Business data processing method, apparatus, device, and medium

Abstract

The embodiment of the application provides a kind of service data processing method, device, equipment and medium, the method includes: according to source service data set, obtain the target management object set for managing service object;The target service object that each service management object in target management object set is managed is obtained, and according to the virtual asset period increment corresponding to target service object, generating increment curve;According to target service object, increment curve and each service management object respectively corresponding management statistics information, each service management object respectively in M evaluation dimensions is obtained on evaluation index;According to increment curve, each service management object respectively corresponding stability evaluation value is obtained, and the industry weight corresponding to target service object is obtained;According to stability evaluation value, industry weight and target service object, each service management object respectively corresponding N class label is determined.Using the embodiment of the application, the screening efficiency and accuracy of service object can be improved.

Description

Technical Field

[0001] This application relates to the field of Internet technology, and in particular to a business data processing method, apparatus, device, and medium. Background Technology

[0002] With the development of data informatization, the volume of data is growing rapidly, and big data is showing a trend of diversification and decentralization. In an environment with large-scale business objects, most business objects are redundant for users, who are only interested in certain business objects. Therefore, filtering out effective business objects for users has become a daily requirement.

[0003] In existing technologies, within platforms used to process business objects, tags can be manually added sequentially to all business objects on the platform based on information such as the management object corresponding to the business object, the business object's duration, and the business object's category. This allows users to select business objects of interest based on these manually added tags. However, due to the large number of business objects on the platform, manually adding tags is time-consuming. Furthermore, manually added tags are subjective and may not accurately reflect the business objects themselves. The business objects filtered through these manual tags may not be of interest to the user, resulting in inaccurate filtering results. Users then need to perform multiple filters to find the business objects they are interested in, leading to extremely low filtering efficiency. Summary of the Invention

[0004] This application provides a business data processing method, apparatus, device, and medium that can improve the efficiency and accuracy of filtering business objects.

[0005] One embodiment of this application provides a business data processing method, including:

[0006] Obtain the source business data set, and based on the source business data set, obtain the target management object set used to manage business objects;

[0007] Obtain the target business objects managed by each business management object in the target management object set, and generate an increment curve corresponding to each business management object based on the periodic increment of the virtual assets corresponding to the target business object;

[0008] Based on the target business object, the incremental curve, and the management statistics corresponding to each business management object, obtain the evaluation indicators for each business management object on M evaluation dimensions; the evaluation indicators corresponding to the M evaluation dimensions are used to filter the management object display list from the set of target management objects, where M is a positive integer greater than 1;

[0009] Based on the incremental curve, obtain the stability assessment value corresponding to each business management object, and obtain the industry weight corresponding to the target business object;

[0010] Based on the stability assessment value, industry weight, and target business object, determine the N types of tags corresponding to each business management object; the N types of tags are used to filter the business management objects in the management object display list, where N is a positive integer.

[0011] One embodiment of this application provides a business data processing apparatus, including:

[0012] The collection acquisition module is used to acquire the source business data collection and, based on the source business data collection, acquire the target management object collection used to manage business objects.

[0013] The curve generation module is used to obtain the target business objects managed by each business management object in the target management object set, and generate an incremental curve corresponding to each business management object based on the virtual asset periodic increment corresponding to the target business object.

[0014] The indicator acquisition module is used to obtain the evaluation indicators of each business management object on M evaluation dimensions based on the target business object, the incremental curve, and the management statistics corresponding to each business management object. The evaluation indicators corresponding to the M evaluation dimensions are used to filter the management object display list from the set of target management objects, where M is a positive integer greater than 1.

[0015] The weight acquisition module is used to obtain the stability assessment value corresponding to each business management object based on the incremental curve, and to obtain the industry weight corresponding to the target business object.

[0016] The tag determination module is used to determine N types of tags for each business management object based on the stability assessment value, industry weight, and target business object. The N types of tags are used to filter the business management objects in the management object display list, where N is a positive integer.

[0017] The collection acquisition module includes:

[0018] The business type determination unit is used to obtain the source business data set from the source database and determine the target business type based on the business category to which the business objects contained in the source business data set belong.

[0019] The management object acquisition unit is used to obtain an initial management object set based on the management object information corresponding to the business objects contained in the source business data set; each initial management object in the initial management object set is unique.

[0020] The index percentage determination unit is used to obtain the first total number of business objects managed by each initial management object, and to obtain the second total number of business objects with target business types managed by each initial management object, and to determine the ratio between the second total number and the first total number as the quantity percentage;

[0021] The management object selection unit is used to identify the initial management objects whose quantity ratio is greater than the ratio threshold in the initial management object set as business management objects, and add the business management objects to the target management object set.

[0022] The target management object set includes business management object i, and the number of target business objects managed by business management object i is K, where K is a positive integer and i is a positive integer less than or equal to the number of business management objects contained in the target management object set.

[0023] The curve generation module includes:

[0024] The asset cycle increment acquisition unit is used to acquire the virtual asset cycle increment of the K target business objects managed by business management object i in multiple first time periods.

[0025] The object period increment determination unit is used to determine the average value of the virtual asset period increment of K target business objects in each first time period as the management object period increment corresponding to business management object i.

[0026] The incremental curve generation unit is used to generate the incremental curve corresponding to business management object i based on the periodic increment of the management object i in multiple first time periods.

[0027] Among them, the M evaluation dimensions include management scale dimension, risk dimension, and attention dimension;

[0028] The metrics acquisition module includes:

[0029] The first indicator acquisition unit is used to acquire the evaluation indicators of each business management object in the dimension of management scale based on the virtual asset scale of the target business object.

[0030] The second indicator acquisition unit is used to obtain the volatility, maximum drawdown and Sharpe ratio corresponding to each business management object according to the incremental curve, and to perform a weighted summation of the volatility, maximum drawdown and Sharpe ratio to obtain the assessment indicators of each business management object in the risk dimension.

[0031] The data statistics unit is used to obtain the number of newly held objects and information statistics corresponding to the target business object, as well as the number of searches corresponding to each business management object.

[0032] The third indicator acquisition unit is used to determine the number of newly acquired objects, the number of information statistics, and the number of searches as management statistics information, and to obtain the evaluation indicators of each business management object in the dimension of attention based on the management statistics information.

[0033] The first indicator acquisition unit includes:

[0034] The sorting subunit is used to sort the business management objects in the target management object set according to the virtual asset scale of the target business object, and obtain the object sorting result of the target management object set;

[0035] The scale assessment value determination sub-unit is used to obtain the first scale assessment value corresponding to each business management object based on the object sorting result, and to determine the second scale assessment value corresponding to each business management object based on the number of business management objects corresponding to the target business object.

[0036] The weighted summation subunit is used to perform a weighted summation operation on the first scale evaluation value and the second scale evaluation value to obtain the evaluation index of each business management object in the management scale dimension.

[0037] The weight acquisition module includes:

[0038] The ranking evaluation value acquisition unit is used to acquire one or more ranking evaluation values ​​corresponding to each business management object based on the periodic increment of the management object contained in one or more second time periods of the incremental curve.

[0039] The stability assessment value acquisition unit is used to obtain the sorting standard deviation and sorting mean corresponding to one or more sorting assessment values, and to obtain the stability assessment value corresponding to each business management object based on the sorting standard deviation and sorting mean.

[0040] The business weight accumulation unit is used to obtain the industry set associated with the source business data set, obtain the business weight corresponding to the target business object, and accumulate the business weights under each industry in the industry set to obtain the industry weight of the target business object under each industry.

[0041] The target management object set includes business management object i, the number of target business objects managed by business management object i is K, and the N types of labels include key business object labels, management style labels and stability labels. K is a positive integer, and i is a positive integer less than or equal to the number of business management objects contained in the target management object set.

[0042] The label determination module includes:

[0043] The stability tag addition unit is used to add a stability tag to business management object i if the stability assessment value corresponding to business management object i is less than or equal to the stability threshold.

[0044] The object evaluation value acquisition unit is used to acquire the term information, virtual asset scale and honor information of the K target business objects managed by business management object i, and to acquire the object evaluation value of the K target business objects based on the term information, virtual asset scale and honor information.

[0045] The key business object tag addition unit is used to add a key business object tag to the target business object with the highest object evaluation value among K target business objects;

[0046] The average industry weight determination unit is used to determine the average industry weight of business management object i in each industry based on the industry weight corresponding to each of the K target business objects.

[0047] The style weight acquisition unit is used to accumulate the industry weights under the style type of each industry in the industry set to obtain the style weights of K target business objects under the style type.

[0048] The management style label determination unit is used to determine the average style weight corresponding to business management object i based on the style weight corresponding to each of the K target business objects, and to determine the management style label corresponding to business management object i based on the average industry weight and the average style weight.

[0049] One aspect of this application provides a computer device, including a memory and a processor. The memory is connected to the processor, the memory is used to store a computer program, and the processor is used to call the computer program so that the computer device executes the method provided in one aspect of this application.

[0050] One aspect of this application provides a computer-readable storage medium storing a computer program adapted to be loaded and executed by a processor, so that a computer device having a processor performs the method provided in one aspect of this application.

[0051] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method provided in the above aspect.

[0052] This application embodiment can obtain a source business data set, obtain a target management object set for managing business objects based on the source business data set, obtain the target business objects managed by each business management object in the target management object set, generate an incremental curve corresponding to each business management object based on the virtual asset periodic increment corresponding to the target business object, obtain evaluation indicators for each business management object on M evaluation dimensions based on the target business object, the incremental curve, and the management statistics corresponding to each business management object, and use the evaluation indicators corresponding to the M evaluation dimensions to filter the management object display list from the target management object set, where M is a positive integer greater than 1; then, based on the incremental curve, obtain the stability evaluation value corresponding to each business management object, obtain the industry weight corresponding to the target business object, and then, based on the stability evaluation value, industry weight, and target business object, determine N types of tags corresponding to each business management object, which are used to filter the business management objects in the management object display list, where N is a positive integer. As can be seen, by using the virtual asset cycle increment of the target business objects managed by the business management object, an incremental curve corresponding to each business management object can be generated. Then, based on the target business object, the incremental curve, and management statistics, the evaluation indicators of each business management object on M evaluation dimensions can be determined. At the same time, tags can be added to each business management object based on stability evaluation value, industry weight, and target business object. Through evaluation indicators on different evaluation dimensions and multiple tags, a quantitative and qualitative screening process for business management objects can be realized, thereby improving the screening accuracy of business objects. By mapping between business management objects and business objects, appropriate business objects can be selected, thereby improving the screening efficiency of business objects. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a schematic diagram of a network architecture provided in an embodiment of this application;

[0055] Figure 2 This is a flowchart illustrating a business data processing method provided in an embodiment of this application;

[0056] Figure 3 This is a schematic diagram of an incremental curve provided in an embodiment of this application;

[0057] Figure 4 This is a flowchart illustrating a business data processing method according to an embodiment of this application;

[0058] Figure 5 This is a schematic diagram of a fund manager screening process provided in an embodiment of this application;

[0059] Figure 6 This is a schematic diagram of a fund manager screening interface provided in an embodiment of this application;

[0060] Figure 7 This is a schematic diagram of the structure of a business data processing device provided in an embodiment of this application;

[0061] Figure 8 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0062] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0063] Please see Figure 1 , Figure 1 Figure 1 is a schematic diagram of a network architecture provided in an embodiment of this application. As shown in Figure 1, the network architecture may include a server 10d and a user terminal cluster. The user terminal cluster may include one or more user terminals; the number of user terminals is not limited here. Figure 1 As shown, the user terminal cluster can specifically include user terminal 10a, user terminal 10b, and user terminal 10c. Server 10d can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. User terminals 10a, 10b, and 10c can all include: smartphones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices (such as smartwatches and smart bracelets), and smart TVs, etc. Figure 1As shown, user terminal 10a, user terminal 10b, and user terminal 10c can each connect to server 10d via a network, so that each user terminal can interact with server 10d through the network connection.

[0064] Taking user terminal 10a in a user terminal cluster as an example, user terminal 10a can integrate a business client. Each business object contained in the business client can correspond to one or more business management objects. When a user wants to select a business object that meets their needs in the business client, it is essentially selecting a suitable business management object. Through evaluation indicators on multiple evaluation dimensions (these evaluation indicators can be calculated by the backend server of the business client, which can be the aforementioned server 10d), one or more business management objects that meet the user's needs can be filtered out. At the same time, by calculating different evaluation indicators, multiple types of information tags corresponding to the business management objects can be generated. These multiple types of information tags can further filter the final business management object from one or more business management objects, and then the desired business object can be selected from the one or more business objects managed by the business management object. The aforementioned business client can refer to a client used to process business objects, which may include, but are not limited to, financial products (e.g., fund products, stock products), application software, music products, video products, etc. The business management object can refer to a user used to manage the business object. When the business object is a fund product, the business management object can be a fund manager; when the business object is a music product, the business management object can be a singer; when the business object is a video product, the business management object can be a director, etc.

[0065] Please see Figure 2 , Figure 2 This is a flowchart illustrating a business data processing method according to an embodiment of this application. It can be understood that this business data processing method can be executed by a computer device, which can be a user terminal (e.g., the one described above). Figure 1 The user terminal 10a in the corresponding embodiment, or a server (e.g., the one described above). Figure 1 The server 10d in the corresponding embodiment can be a system consisting of a user terminal and a server, or a computer program application (including program code); no specific limitation is made here. Figure 2 As shown, this business data processing method may include the following steps:

[0066] Step S101: Obtain the source business data set, and obtain the target management object set for managing business objects based on the source business data set.

[0067] Specifically, the computer device can periodically retrieve a source business data set from the Juyuan database. This source business data set may include information such as the business category corresponding to the business object, the management object information corresponding to the business object, and the performance of the business object. The Juyuan database can be configured with at least one type of interface, such as an Oracle (a relational database management system) interface or a SQL Server (a relational database management system) interface. The computer device calls the corresponding interface using the programming language it employs to retrieve the source business data set from the Juyuan database. The Juyuan database can be updated based on the business data of the business objects published in real time. The aforementioned source business data set originating from the Juyuan database is merely a specific example in this application embodiment. The source business data set may also originate from other databases, such as the backend database in the business client. This application does not limit the source of the source business data set.

[0068] Computer equipment can determine the initial management object corresponding to each business object in the source business data set based on the management object information contained in the source business data set, and obtain a target management object set based on the initial management object corresponding to each business object. The initial management objects contained in the target management object set can be called business management objects. For example, the computer equipment can combine the initial management objects corresponding to each business object into a target management object set; or, by counting the number of business objects managed by each initial management object, sorting all initial management objects according to the number of business objects, and taking the top a (a is a positive integer, such as a can take the value 1, 2, ...) initial management objects into a target management object set; or, classifying the initial management objects, combining the initial management objects of a certain business type into a target management object set; and so on. This application does not specifically limit the type and number of business management objects in the target management object set.

[0069] Step S102: Obtain the target business objects managed by each business management object in the target management object set, and generate the increment curve corresponding to each business management object according to the virtual asset period increment corresponding to the target business object.

[0070] Specifically, for each business management object included in the target management object set, the target business objects it manages can be obtained; each business management object can manage one or more business objects, and the one or more business objects managed by a business management object can have different business types or the same business type; a business management object can manage business objects independently, or a business object can be jointly managed by two or more business management objects; the target business object can be all the business objects managed by the business management object (i.e., one or more business objects managed by the business management object can include business objects managed independently by the business management object, as well as business objects jointly managed with other business management objects), or it can be a portion of the business objects managed by the business management object. For example, based on the business types of one or more business objects managed by a business management object, one or more business objects can be divided into different groups. Business objects in a group can have the same business type, and thus, business objects in a group with a certain business type can be identified as the target business objects corresponding to that business management object; or, business objects in two or more groups can be identified as the target business objects corresponding to that business management object; or, when the business type of a group is the same as the business type of the business management object, the business objects in that group can be identified as the target business objects corresponding to that business management object. This application can obtain the target business objects managed by the business management object according to actual needs, and this application does not specifically limit the type of target business objects.

[0071] Furthermore, the computer equipment can acquire the virtual asset cycle increment corresponding to the target business object. Based on the virtual asset cycle increment, an increment curve (also known as a business management object career curve) can be generated for each business management object. Different target business objects have different performance characteristics. The performance of the target business objects managed by the business management object can be used to reflect the management capability of the business management object. The performance of the business management object can be presented in the form of an increment curve. The increment curve here is generated by connecting the virtual asset cycle increments of the target business object in multiple time periods. The virtual asset cycle increment here can refer to the virtual asset increment of the target business object in a single time period. The virtual asset cycle increment can include, but is not limited to, the target business object's rate of return, click-through rate, playback rate, download rate, viewership rate, etc. The time period here can be called the first time period, which can be one day, one week, etc. This application does not limit the specific duration of the first time period. A business management object can manage one or more target business objects. When a business management object manages only one target business object, an increment curve corresponding to the business management object can be generated based on the virtual asset cycle increment of the target business object in multiple first time periods. When a business management object manages multiple target business objects, the average value (which can be called the increment average value) of the virtual asset cycle increment of multiple target business objects in a single first time period can be obtained to get the cycle increment of the business management object in a single first time period (which can also be called the managed object cycle increment). Then, based on the managed object cycle increment of the business management object in multiple first time periods, an increment curve corresponding to the business management object can be generated.

[0072] Optionally, assume that the target management object set includes business management object i, i.e., any business management object in the target management object set, and the number of target business objects managed by business management object i is K, where K is a positive integer, such as K can take the value 1, 2, ..., and i can be a positive integer less than or equal to the number of business management objects included in the target management object set; the computer device can obtain the K target business objects managed by business management object i, obtain the virtual asset cycle increment of each of the K target business objects in multiple first time periods, and determine the average increment of the virtual asset cycle increment of the K target business objects in each first time period as the management object cycle increment corresponding to business management object i; based on the management object cycle increment of business management object i in multiple first time periods, an increment curve corresponding to business management object i is generated. If business management object i leaves its post in the first time period, i.e., business management object i cancels management of at least one of the K target business objects in the first time period, then the virtual asset cycle increment of the at least one target business object canceled by business management object i in the first time period is 0. It should be noted that for each business management object in the target management object set, the above operations can be used to generate an incremental curve corresponding to each business management object. One business management object can correspond to one incremental curve or multiple incremental curves. For example, by calculating the average of the virtual asset periodic increments corresponding to K target business objects, an incremental curve corresponding to business management object i can be generated, in which case business management object i corresponds to one incremental curve. Alternatively, by connecting the virtual asset periodic increments of each target business object within multiple first time periods, an incremental curve can be generated corresponding to each target business object, in which case business management object i can correspond to K incremental curves. Alternatively, target business objects of the same business type can generate one incremental curve; when K target business objects correspond to 2 business types, business management object i can correspond to 2 incremental curves. This application does not impose any limitations on this.

[0073] Please see Figure 3 , Figure 3 This is a schematic diagram of an incremental curve provided in an embodiment of this application. For example... Figure 3As shown below, taking a fund investment scenario as an example, the generation process of the incremental curve is described. In the fund investment scenario, the business management object in the target management object set can be fund manager A, and the target business object managed by the business management object can be the target fund product managed by fund manager A (e.g., an equity fund). The virtual asset period increment corresponding to the target business object can be the daily return of the target fund product, and the first time period here can be 1 day. The computer equipment can obtain the average daily return of all target fund products managed by fund manager A during his employment period (February 2018 to June 2021) (i.e., the average incremental return). By obtaining the average daily return of fund manager A, a return series for fund manager A is obtained. By connecting the average returns in this return series, the incremental curve corresponding to fund manager A (also known as the fund manager career curve) is obtained. At this time, the incremental curve can be regarded as the performance of fund manager A.

[0074] Optionally, to more intuitively illustrate the performance of fund manager A, the average daily return of all funds (including the target fund) within the same business type can be obtained. This average return can be called the peer average. By connecting the daily peer averages, a peer incremental curve can be generated. This peer incremental curve can be used to represent the average performance within the business type to which the target fund belongs. Figure 3 As shown, the business client can display the incremental curve 20a corresponding to fund manager A, and the incremental curve 20b of similar funds associated with fund manager A. Incremental curve 20a reflects fund manager A's performance trend over the past 6 months, while incremental curve 20b reflects the performance trend of similar funds within the same business type over the past 6 months. Users can also view the performance trends of incremental curve 20a and incremental curve 20b over the past year, 3 years, 5 years, and since their appointment. Optionally, when fund manager A leaves their position within a certain period, their daily return during that period can be determined to be 0, and this can also be treated as 0 when calculating the average return of similar funds.

[0075] Step S103: Based on the target business object, the incremental curve, and the management statistics information corresponding to each business management object, obtain the evaluation indicators for each business management object on M evaluation dimensions; The evaluation indicators corresponding to the M evaluation dimensions are used to filter the management object display list from the target management object set, where M is a positive integer greater than 1.

[0076] Specifically, for each business management object in the target management object set, the corresponding evaluation indicators can be calculated from M evaluation dimensions. M can be a positive integer greater than 1, such as M can take the value 2, 3, ... The M evaluation dimensions here can include, but are not limited to, one or more of the following dimensions: management scale, long-term incremental (such as long-term returns), short-term incremental (such as short-term returns), risk, management years, awards, attention (popularity), comprehensive evaluation, etc. By calculating the evaluation indicators on the above M evaluation dimensions, the business management objects in the target management object set are screened. For example, when the M evaluation dimensions include four dimensions: management scale, long-term incremental growth, short-term incremental growth, and comprehensive evaluation, we can calculate evaluation indicator 1 for each business management object in the management scale dimension, evaluation indicator 2 in the long-term incremental growth dimension, and evaluation indicator 3 in the short-term incremental growth dimension. Then, we can calculate evaluation indicator 4 in the comprehensive evaluation dimension based on evaluation indicator 1, evaluation indicator 2, and evaluation indicator 3. When the M evaluation dimensions include three dimensions: risk, management years, and awards, we can calculate evaluation indicator 5 for each business management object in the risk dimension, evaluation indicator 6 in the management years dimension, evaluation indicator 7 in the awards dimension, and so on.

[0077] Regarding the aforementioned management scale dimension, the computer equipment can obtain the virtual asset scale of the target business object. Based on the virtual asset scale, the evaluation index of each business management object in the management scale dimension can be calculated. The evaluation index in this application can be considered as the specific evaluation value obtained through calculation. For example, if the target business object is a fund product, and each person spends 100 yuan to purchase the fund product, and the number of people who purchase the fund product is 100, then the virtual asset scale of the target business object can be determined to be 10,000.

[0078] Regarding the aforementioned long-term and short-term incremental dimensions, computer equipment can obtain the cumulative increment of the business management object over different time periods based on the incremental curve, such as the cumulative increment over the past five years (e.g., cumulative revenue), the cumulative increment over the past three years, the cumulative increment over the past two years, and the cumulative increment over the past year. By assigning weights to these cumulative increments, evaluation indicators for the business management object in the long-term incremental dimension and the short-term incremental dimension can be calculated. For example, weights can be assigned to the cumulative increments over the past five years, the past three years, and the past year to calculate the evaluation indicators for the business management object in the long-term incremental dimension; similarly, weights can be assigned to the cumulative increments over the past two years and the past year to calculate the evaluation indicators for the business management object in the short-term incremental dimension.

[0079] Regarding the aforementioned risk dimensions, computer equipment can also calculate assessment indicators for the business management object in terms of risk based on the incremental curve. For example, the computer equipment can calculate the volatility, maximum drawdown, and Sharpe ratio corresponding to the business management object based on the incremental curve. By assigning weights to volatility, maximum drawdown, and Sharpe ratio, the assessment indicators for the business management object in terms of risk are calculated. Volatility can be considered an economic phenomenon, referring to the degree of fluctuation in virtual asset prices (e.g., financial asset prices). It measures the uncertainty of virtual asset cyclical increments (e.g., asset returns) and can be used to reflect the risk level of virtual assets (e.g., financial assets). The higher the volatility, the more drastic the fluctuations in virtual asset prices (financial asset prices), and the stronger the uncertainty of virtual asset cyclical increments (asset returns). The lower the volatility, the smoother the fluctuations in virtual asset prices (financial asset prices), and the stronger the certainty of virtual asset cyclical increments (asset returns). Maximum drawdown is an important indicator for measuring the risk of the target business object. It can be understood as the maximum possible loss, and its value is the maximum decline from any high point to the subsequent low point on the incremental curve within a selected time period. The Sharpe ratio, also known as the Sharpe index, is a standardized indicator for evaluating the performance of business targets. Simply put, the Sharpe ratio can be understood as the excess return obtained above the risk-free rate for every unit of risk undertaken. The higher the Sharpe ratio, the higher the excess return obtained for a certain level of risk. Conversely, if the Sharpe ratio is very small or even negative, it indicates that the excess return obtained for a certain level of risk is small or non-existent.

[0080] Regarding the aforementioned management tenure, awards, and attention dimensions, the computer equipment can obtain management statistics for each business management object. This statistics may include the management tenure of the business management object, the number and types of awards received, and the level of attention received. For example, when the target business object is a fund product, the aforementioned management tenure could be the investment tenure of the fund manager (business management object). Evaluation indicators for the business management object in the management tenure dimension can be calculated using the management tenure. Furthermore, by assigning weights to information such as the number of award types and the number of awards, evaluation indicators for the business management object in the awards dimension can be calculated. Finally, evaluation indicators for the business management object in the attention dimension can be calculated based on the level of attention received.

[0081] Optionally, regarding the aforementioned comprehensive evaluation dimensions, when the M evaluation dimensions include the aforementioned 8 evaluation dimensions, the computer equipment can assign weights to the aforementioned 7 evaluation indicators, and calculate the evaluation indicators (also called comprehensive evaluation indicators) of the business management objects in the comprehensive dimensions through weighted summation. The evaluation indicators in the aforementioned M evaluation dimensions can be used to filter the list of management objects from the target management object set. All evaluation indicators in the M evaluation dimensions can be calculated using formulas, meaning that the target management object set can be quantitatively filtered through evaluation indicators. For example, when the management scale dimension among the M evaluation dimensions is used as a filtering condition for the target management object set, the objects can be sorted according to the evaluation indicators of each business management object in the target management object set in the management scale dimension, and a list of management objects can be selected from the target management object set based on the sorting results. The number of business management objects included in this list is less than or equal to the number of business management objects included in the target management object set. Similarly, when the risk dimension among the M evaluation dimensions is used as a filtering condition for the target management object set, the objects can be sorted according to the evaluation indicators of each business management object in the target management object set in the risk dimension, and a list of management objects can be selected from the target management object set based on the sorting results, and so on.

[0082] Step S104: Obtain the stability assessment value corresponding to each business management object based on the incremental curve, and obtain the industry weight corresponding to the target business object.

[0083] Specifically, computer equipment can obtain the stability assessment value corresponding to each business management object based on the incremental curve corresponding to that object. This stability assessment value can be determined by the performance stability of each time period on the incremental curve. For example, computer equipment can calculate the performance stability of the current year (the year in which the current system time is located) and the most recent three calendar years (a calendar year can be a time period) using the incremental curve, and then determine the stability assessment value corresponding to the business management object based on the calculated performance stability. Alternatively, computer equipment can calculate the performance stability of the current year and the most recent five calendar years using the incremental curve, and then determine the stability assessment value corresponding to the business management object based on the calculated performance stability. The performance stability of each calendar year can be reflected by the mean and standard deviation. It should be noted that determining the stability assessment value based on the performance stability of the most recent three calendar years or the performance stability of the most recent five calendar years are examples in the embodiments of this application. The stability assessment value involved in this application can also be determined based on the business stability of any other year, such as the business stability of the current year and the most recent four calendar years, the performance stability of a specified calendar year (e.g., 2015-2018), etc. This application does not limit the years and number of calendar years involved in the stability assessment value.

[0084] Optionally, for each business management object in the target management object set, management style can be analyzed based on the target business objects it manages. The computer equipment can obtain the business weight corresponding to each business object, which can be understood as the proportion of each business object in market value; for example, when the business object is a fund product, the business weight can refer to the proportion of its stock holding market value to its net asset value. An industry set associated with the aforementioned original business data set can be obtained. Each business object can have a certain weight in one or more industries within the industry set, meaning a target business object can correspond to one or more industries. For each target business object managed by a business management object, its industry weight in each industry can be calculated. The industry weight can be the result of summing the business weights of each target business object within that industry; alternatively, the industry weight can also be the result of summing the business weights of each target business object within that industry and then performing further processing (such as normalization, logarithmic processing).

[0085] It should be noted that the aforementioned industry set can be a conventional industry classification strategy in the field, or it can be a pre-set industry classification strategy by the business client. This industry set may include, but is not limited to, industries such as: chemicals, automobiles, machinery, non-ferrous metals, building materials, mining, steel, banking, non-bank financial institutions, real estate, electronics, computers, electrical equipment, media, military industry, telecommunications, food and beverage, home appliances, agriculture, forestry, animal husbandry and fishery, textiles and apparel, light manufacturing, commerce and trade, leisure services, pharmaceuticals, public utilities, construction and decoration, and transportation. For the target business objects managed by the business management objects in the target management object set, the industry weight of each target business object in the industry set can be obtained. When the business weight of a target business object in a certain industry (e.g., chemicals) is 0, it can be determined that the industry weight of the target business object in that industry is 0. In other words, when the industry set includes B (B is a positive integer, such as B can be 28) industries, the industry weights of each target business object managed by the business management object can be calculated.

[0086] Step S105: Based on the stability assessment value, industry weight, and target business object, determine the N-type labels corresponding to each business management object; the N-type labels are used to filter the business management objects in the management object display list, where N is a positive integer.

[0087] Specifically, for each business management object in the target management object set, N types of information tags (i.e., N-type tags) can be generated for the business management object. N can be a positive integer, such as 1, 2, ... The N-type tags here can include, but are not limited to, one or more of the following tags: business management object type, key business object (also known as representative work), management style, incremental curve, stability, etc. By generating N-type tags for business management objects, these tags can help users quickly understand the business management objects and select those that meet their needs. Specifically, the business management object type can refer to the business type corresponding to the business management object, and the business management object type tag can be determined by the business type of the target business object managed by that business management object; the key business object tag can be determined by the virtual asset scale, awards received, and the management years of the business management object; the management style tag can be determined by the industry weight corresponding to the target business object; and the stability tag can be determined by the aforementioned stability assessment value. After generating N types of tags for each business management object in the target management object set, the N types of tags can be used to filter the business management objects in the management object display list. In this way, users can select the business objects that meet their needs from all the business objects managed by the selected business management object.

[0088] In this embodiment, an incremental curve corresponding to each business management object can be generated by the virtual asset periodic increment of the target business object managed by the business management object. Then, based on the target business object, the incremental curve, and management statistics, the evaluation indicators of each business management object on M evaluation dimensions can be determined. At the same time, tags can be added to each business management object based on stability evaluation value, industry weight, and target business object. Through evaluation indicators on different evaluation dimensions and multiple tags, a quantitative and qualitative screening process for business management objects can be realized, thereby improving the screening accuracy of business objects. By mapping between business management objects and business objects, suitable business objects can be selected, thereby improving the screening efficiency of business objects.

[0089] Please see Figure 4 , Figure 4 This is a flowchart illustrating a business data processing method according to an embodiment of this application. It can be understood that this business data processing method can be executed by a computer device, which can be a user terminal (e.g., the one described above). Figure 1 The user terminal 10a in the corresponding embodiment, or a server (e.g., the one described above). Figure 1 The server 10d in the corresponding embodiment can be a system consisting of a user terminal and a server, or a computer program application (including program code); no specific limitation is made here. Figure 4 As shown, this business data processing method may include the following steps:

[0090] Step S201: Obtain the source business data set from the source database; determine the target business type based on the business category to which the business objects contained in the source business data set belong; and obtain the initial management object set based on the management object information corresponding to the business objects contained in the source business data set.

[0091] Specifically, computer devices can retrieve source business data sets from the source database by calling interfaces (e.g., Oracle interfaces, SQL Server interfaces, etc.). They can then obtain the business categories to which the business objects contained in the source business data set belong. These business categories can include multiple hierarchical categories (e.g., first-level, second-level, third-level, and fourth-level categories). Based on the business category to which the business object belongs, a target business type can be defined, which can be called a business management object type. For example, business type conditions can be preset. When the business category corresponding to a business object meets the business type conditions, it can be determined that the business category of the business object belongs to the aforementioned target business type. It should be noted that the number of target business types in this application can be one or more. When there is only one target business type, business type conditions associated with that target business type can be preset; when there are multiple target business types, business type conditions associated with each target business type can be preset separately.

[0092] Optionally, the computer device can obtain management object information corresponding to the business objects contained in the source business data set. Based on this management object information, an initial management object set can be obtained. This initial management object set may include a list of unique management objects in the entire market. The management object information may include the initial management object corresponding to the business object, the management period of the initial management object for that business object, and other information. For example, suppose the source business data set includes business object 1, business object 2, business object 3, business object 4, business object 5, and business object 6; the initial management object managing the aforementioned business object 1 can be the initial management object 1, that is, business object 1 corresponds to initial management object 1, business object 2 corresponds to initial management object 2, business object 3 corresponds to initial management object 3, business object 4 corresponds to initial management object 4, business object 5 corresponds to initial management object 5, and business object 6 corresponds to initial management object 6. Then, the initial management objects 1, 2, 3, 4, 5, and 6 can be combined into an initial management object set.

[0093] Step S202: Obtain the first total number of business objects managed by each initial management object, and obtain the second total number of business objects with target business type managed by each initial management object. Determine the ratio between the second total number and the first total number as the quantity percentage.

[0094] Specifically, the computer device can obtain the first total number of business objects managed by each initial management object in the initial management object set, that is, obtain the first total number of business objects managed by each initial management object. It can also obtain the second total number of business objects of the target business type managed by each initial management object, and determine the ratio between the second total number and the first total number as the quantity percentage. For example, for any initial management object in the initial management object set (e.g., initial management object a, where a is a positive integer less than or equal to the number of initial management objects in the initial management object set), if the number of business objects managed by initial management object a is 6 (the aforementioned first total number), and 3 out of the 6 business objects (the aforementioned second total number) belong to the target business type, then the quantity percentage corresponding to initial management object a can be determined to be 1 / 2.

[0095] Step S203: In the initial management object set, identify the initial management objects whose quantity ratio is greater than the ratio threshold as business management objects, and add the business management objects to the target management object set.

[0096] Specifically, when the proportion of initial managed object 'a' in the initial managed object set exceeds a certain threshold, initial managed object 'a' can be added to the target managed object set as a business managed object. This threshold can be a pre-set value less than 1 and can be set according to actual needs. In other words, among all initial managed objects in the initial managed object set, those with a proportion exceeding the threshold can be identified as business managed objects and added to the target managed object set.

[0097] Step S204: Obtain the target business objects managed by each business management object in the target management object set, and generate the increment curve corresponding to each business management object based on the virtual asset period increment corresponding to the target business object.

[0098] The specific implementation process of step S204 can be found in the above. Figure 2 Step S103 in the corresponding embodiment will not be described again here.

[0099] Step S205: Based on the virtual asset scale of the target business object, obtain the evaluation indicators for each business management object in the management scale dimension.

[0100] Specifically, the computer equipment can sort the business management objects in the target management object set according to the virtual asset scale of the target business object, and obtain the object sorting result of the target management object set; based on the object sorting result, obtain the first scale evaluation value corresponding to each business management object, and then determine the second scale evaluation value corresponding to each business management object according to the number of business management objects corresponding to the target business object; by performing a weighted summation operation on the first scale evaluation value and the second scale evaluation value, obtain the evaluation index of each business management object in the management scale dimension.

[0101] Specifically, when a business management object i (any business management object in the target management object set) manages one target business object, the virtual asset size of that target business object is the virtual asset size managed by business management object i. When a business management object i manages multiple target business objects, the total size obtained by summing the virtual asset sizes corresponding to the multiple target business objects can be used as the virtual asset size managed by business management object i. Assume the number of business management objects contained in the target management object set is D, meaning the target management object set includes D... There are D business management objects, where D can be a positive integer, such as 1, 2, ... The computer device can sort the virtual asset scale managed by the D business management objects in the target management object set in descending order to obtain the sorted D business management objects (i.e., the object sorting result of the target management object set); Based on the ranking of the business management object in the sorted D business management objects, the ranking percentile value of the business management object is calculated (for ease of description, the ranking percentile value here is referred to as the first ranking percentile value). The first ranking percentile value can be used as the first scale evaluation value corresponding to the business management object. The first ranking percentile value can be defined as follows: When the ranking of business management object i (i is a positive integer less than or equal to D) in the target management object set is the t-th (t is a positive integer less than or equal to D) in the sorted D business management objects, the first ranking percentile value corresponding to business management object i can be calculated as: (t-1) / (D-1). The higher the ranking of the business management object, the smaller the first ranking percentile value. It should be noted that the definition of the first ranking percentile value mentioned above is only an example in the embodiments of this application, and it can also be presented in other forms, such as t / D. This application does not limit the definition form of the first ranking percentile value; the descriptions such as "first" and "second" in the embodiments of this application do not have specific semantic information, that is, the terms such as "second ranking percentile value" and "third ranking percentile value" mentioned below have the same calculation method, which will not be repeated hereafter.

[0102] When business management object i in the target management object set has independently managed target business objects, it indicates that the number of business management objects corresponding to the target business object is 1, and the independent management object score of business management object i can be determined as the first value (for example, the first value can be 1); when business management object i does not have independently managed target business objects, it indicates that the target business objects managed by business management object i are all jointly managed with other business management objects, that is, the number of business management objects corresponding to the target business objects is greater than or equal to 2, and the independent management object score of business management object i can be determined as the second value (for example, the second value can be 0). The independent management object score here can be used as the second scale evaluation value corresponding to the business management object. Furthermore, the computer device can obtain the first weight corresponding to the first ranking percentile and the second weight corresponding to the score of the independent managed object. The first ranking percentile is multiplied by the first weight, and then the independent managed object score is multiplied by the second weight to obtain the total score of business managed object i. After calculating the total scores for each of the D business managed objects in the target managed object set, they can be sorted from largest to smallest to obtain a sorted set of D business managed objects. Based on the ranking of each business managed object among the sorted D business managed objects, the second ranking percentile for each business managed object can be calculated again, and this second ranking percentile is used as an evaluation indicator for the business managed object in the management scale dimension. The first and second weights can be pre-configured values, such as the first weight being set to 80% and the second weight to 20%. This application does not limit the specific values ​​of the first and second weights.

[0103] Optionally, when the management scale dimension is used as a filtering condition for the target management object set, the objects can be sorted from smallest to largest according to the evaluation indicators on the management scale dimension, and a management object display list for display in the business client can be selected from the sorted D business management objects. For example, the top 10 business management objects can be selected from the sorted D business management objects as the management object display list; or, business management objects with evaluation indicators lower than the score threshold can be selected from the sorted D business management objects as the management object display list. It should be noted that when the evaluation indicators of business management objects on M evaluation dimensions are all ranking percentile values, the target management object set can be filtered by sorting the ranking percentile values ​​from smallest to largest.

[0104] Step S206: Obtain the volatility, maximum drawdown, and Sharpe ratio corresponding to each business management object based on the incremental curve. Perform a weighted summation of the volatility, maximum drawdown, and Sharpe ratio to obtain the assessment indicators of each business management object in terms of risk dimension.

[0105] Specifically, when screening business management objects in the target management object set, the risk of the business management objects can also be considered to select robust ones. Computer equipment can calculate the volatility, maximum drawdown, and Sharpe ratio for each of the D business management objects in the target management object set based on their respective incremental curves. Lower volatility and maximum drawdown are better; that is, lower values ​​result in a higher ranking and a lower percentile. A higher Sharpe ratio is better; that is, a higher Sharpe ratio results in a higher ranking and a lower percentile.

[0106] Specifically, for business management object i in the target management object set, the volatility over different time periods can be calculated based on the incremental curve corresponding to business management object i. Then, the volatility over different time periods can be weighted and summed to obtain the final volatility corresponding to business management object i. The volatility over the aforementioned different time periods can include at least two of the following: volatility over the past five years, volatility over the past four years, volatility over the past three years, volatility over the past two years, volatility over the past year, etc. For ease of description, the following description uses volatility over the past five years, volatility over the past three years, and volatility over the past year as examples. In the specific process of calculating the final volatility corresponding to the business management object, the computer device can obtain the third weight corresponding to the volatility over the past five years, the fourth weight corresponding to the volatility over the past three years, and the fifth weight corresponding to the volatility over the past year. The volatility over the past five years is multiplied by the third weight, plus the volatility over the past three years multiplied by the fourth weight, plus the volatility over the past year multiplied by the fifth weight to obtain the final volatility corresponding to business management object i. The third, fourth, and fifth weights mentioned above can be pre-configured values, such as the third weight being set to 50%, the fourth weight to 30%, and the fifth weight to 20%. This application does not limit the specific values ​​of the third, fourth, and fifth weights.

[0107] Furthermore, after calculating the final volatility corresponding to each of the D business management objects in the target management object set, the computer equipment can sort the D business management objects in ascending order of final volatility, and calculate the rank percentile value (which can be called the third rank percentile value) of each business management object on the volatility indicator based on the ranking of each business management object. It can be understood that when calculating the final volatility corresponding to a business management object, it can be calculated by directly weighting and summing the volatility over the past five years, the past three years, and the past year, or it can be calculated by weighting and summing the rank percentile values ​​of volatility over different time periods.

[0108] Based on a similar processing procedure to that for volatility, the fourth percentile of each business management object in terms of maximum drawdown and the fifth percentile of each business management object in terms of Sharpe ratio can be calculated. Then, the sixth weight corresponding to the third percentile, the seventh weight corresponding to the fourth percentile, and the eighth weight corresponding to the fifth percentile can be obtained. These weights are multiplied and summed, and the weighted sums are reordered in ascending order to calculate the percentile values, which serve as the risk score for each business management object. This risk score can be used as an assessment indicator for the business management object in terms of risk. The sixth, seventh, and eighth weights can be pre-configured values, such as 1 / 3 for each. This application does not limit the specific values ​​of the sixth, seventh, and eighth weights. When risk dimension is used as a filtering condition for the set of target management objects, they can be sorted from smallest to largest according to the evaluation indicators on the risk dimension, and the management object display list to be displayed in the business client can be selected from the sorted D business management objects.

[0109] Step S207: Obtain the number of newly held objects and information statistics corresponding to the target business object, as well as the number of searches corresponding to each business management object; determine the number of newly held objects, information statistics and search counts as management statistics information, and obtain the evaluation indicators of each business management object in the attention dimension based on the management statistics information.

[0110] Specifically, the computer device can obtain management statistics for each business management object in the target management object set. These statistics may include the number of newly acquired users, information statistics, and search counts for each target business object. The number of newly acquired users can refer to the difference in the number of users acquired over two consecutive time periods, such as a quarter or a month. For example, the device can obtain the number of users acquired by all target business objects managed by a business management object in the most recent two quarters, sum the number of users acquired by all target business objects for each quarter, and use the difference in the number of users acquired by the same business management object over the most recent two quarters as the number of newly acquired users. A positive number indicates that the number of users acquired by the business management object increased over the two consecutive time periods; a negative number indicates that the number of users acquired by the business management object decreased over the two consecutive time periods; and a zero number indicates that the number of users acquired by the business management object remained unchanged over the two consecutive time periods. Information statistics can refer to the number of times a business management object is mentioned in different news articles, plus the number of times the target business objects managed by that business management object are mentioned. Search counts can refer to the number of times the business management object and its managed target business objects are searched in the business client.

[0111] The computer device can use the number of newly added holding objects, the number of information statistics, and the number of searches as indicators to sort the D business management objects in the target management object set from largest to smallest according to the single indicator, and calculate the ranking percentile value corresponding to the single indicator. By multiplying and adding the ranking percentile values ​​corresponding to each indicator, the total ranking score corresponding to each business management object is obtained. The ranking objects are then sorted in ascending order of total ranking score and the ranking percentile value is calculated to obtain the popularity score corresponding to each business management object. The popularity score here can be used as an evaluation indicator of the business management object in the dimension of attention.

[0112] Optionally, the management statistics may also include the number of people who have favorited and purchased the target business object. The number of people who have favorited and purchased can also be used as indicators. The number of people who have favorited can refer to the number of times a user adds the target business object managed by the business management object to the self-selected database in the business client; the number of people who have purchased can refer to the number of times a user purchases the target business object managed by the business management object in the business client. The computer device can obtain the ranking percentile value of the business management object for the metric of the number of favorites and the ranking percentile value of the business management object for the metric of the number of purchases. Then, the ranking percentile values ​​of each indicator can be multiplied and added together to obtain the total ranking score for each business management object. The ranking percentile values ​​are then calculated and sorted in ascending order of the total ranking score to obtain the popularity score for each business management object. This popularity score can be used as an evaluation indicator for the business management object in terms of attention. It is understood that the weights corresponding to each indicator can be pre-configured according to actual needs. For example, the weights corresponding to the number of newly held objects, the number of information statistics, the number of searches, the number of favorites, and the number of purchases can all be set to 20%. This application does not limit this. When the focus dimension is used as a filtering condition for the target management object set, the objects can be sorted from smallest to largest according to the evaluation indicators on the focus dimension, and the management object display list for display in the business client can be selected from the sorted D business management objects.

[0113] Optionally, the M evaluation dimensions used to screen business management objects can also include dimensions such as long-term incremental growth, short-term incremental growth, management years, awards received, and comprehensive evaluation. For the long-term incremental growth dimension, the computer equipment can calculate the cumulative incremental growth of each business management object over different time periods based on its incremental curve. The cumulative incremental growth within a single time period can be used as an indicator. This allows for the sorting of the D business management objects by their cumulative incremental growth within a single time period from largest to smallest, and the calculation of the rank percentile for each business management object's cumulative incremental growth within that single time period. For example, the cumulative increment over different time periods can include the cumulative increment over the past five years, the cumulative increment over the past three years, and the cumulative increment over the past year. These increments can then be sorted in descending order of the cumulative increment over the past five years, the past three years, and the past year, and the ranking percentiles can be calculated. These ranking percentiles are multiplied by their corresponding weights and then summed to obtain the total increment scores for each of the D business management objects. The total increment scores are then sorted in ascending order, and the final ranking percentile is calculated. This final ranking percentile can serve as an evaluation indicator for the business management objects in the longer-term increment dimension. It should be noted that the weights corresponding to the cumulative increments over the past five years, the past three years, and the past year can be pre-configured according to actual needs. For example, the weight of the cumulative increment over the past five years can be set to 60%, the weight of the cumulative increment over the past three years can be set to 30%, and the weight of the cumulative increment over the past year can be set to 10%. This application does not impose any limitations on this.

[0114] For the short-term incremental dimension, the cumulative increment within the time period involved in calculating the evaluation indicators for the short-term incremental dimension is different from the cumulative increment within the time period involved in calculating the evaluation indicators for the long-term incremental dimension. For example, the cumulative increment within the time period involved in the short-term incremental dimension can include the cumulative increment of the most recent two years and the cumulative increment of the most recent year. The weights corresponding to the cumulative increment of the most recent two years and the cumulative increment of the most recent year can be set to 50%. The calculation process of the evaluation indicators for the short-term incremental dimension is the same as that of the evaluation indicators for the long-term incremental dimension, and will not be repeated here.

[0115] Regarding the management tenure dimension, the management tenure of the D business management objects can be sorted in descending order, and the ranking percentile value can be calculated based on the ranking of the business management objects. This ranking percentile value can be used as an evaluation indicator for the business management objects in the management tenure dimension.

[0116] Regarding the award-winning aspect, the computer device can obtain information such as the number of award types and the number of awards received by each business management object. It can sort the D business management objects by the number of award types in descending order and calculate the rank percentile value based on each object's ranking. Simultaneously, it can also sort the D business management objects by the number of awards received in descending order and calculate the rank percentile value based on each object's ranking. Multiplying these two rank percentile values ​​by their corresponding weights and then summing them yields the total award score for each of the D business management objects. The total award scores are then sorted in ascending order, and the final rank percentile value is calculated. This final rank percentile value can serve as an evaluation indicator for the business management object in terms of award-winning performance. It should be noted that the weights corresponding to the number of award types and the number of awards received can be pre-configured according to actual needs. For example, the weight of the number of award types can be set to 30%, and the weight of the number of awards received can be set to 70%. This application does not impose any limitations on this.

[0117] For the comprehensive evaluation dimensions, the computer equipment can assign weights to the evaluation indicators of the above six evaluation dimensions (which can be the evaluation indicators of the other evaluation dimensions excluding the short-term incremental dimension from the above seven evaluation dimensions). By multiplying the evaluation indicators of the six evaluation dimensions by their corresponding weights and then adding them together, the comprehensive total score corresponding to each business management object can be obtained. The total score of the awards is sorted in ascending order, and the final ranking percentile value is calculated. Here, the final ranking percentile value can be used as the evaluation indicator of the business management object in the comprehensive evaluation dimensions. It should be noted that the weights corresponding to the evaluation indicators of the above six evaluation dimensions can be pre-configured according to actual needs. For example, the weight of the management scale dimension can be set to 10%, the weight of the long-term incremental dimension can be set to 40%, the weight of the risk dimension can be set to 20%, the weight of the management years dimension can be set to 10%, the weight of the award status dimension can be set to 10%, and the weight of the attention dimension can be set to 10%. This application does not limit this. It is understandable that the evaluation dimensions used to screen business management objects may include other evaluation dimensions besides the eight listed above, such as team evaluation, etc. This application does not limit this.

[0118] Step S208: Based on the periodic increment of the managed objects contained in the incremental curve within one or more second time periods, obtain one or more sorting evaluation values ​​corresponding to each business management object; obtain the sorting standard deviation and sorting average value corresponding to the one or more sorting evaluation values; and obtain the stability evaluation value corresponding to each business management object based on the sorting standard deviation and sorting average value.

[0119] Specifically, the computer equipment can calculate the periodic increment of each business management object within one or more second time periods based on the incremental curve. These second time periods can be calendar years, semi-annual periods, etc. By sorting the periodic increments of the management objects within a single second time period in descending order and calculating the rank percentile values, the rank percentile values ​​(i.e., one or more ranking evaluation values) for each second time period are obtained. Then, the average (i.e., the ranking average) and standard deviation (i.e., the ranking standard deviation) of each rank percentile value can be calculated. The standard deviation and average are then sorted in ascending order. The ranking of each business management object based on the standard deviation is added to its ranking based on the average, yielding the total value for each business management object. These total values ​​are then sorted in ascending order, and the rank percentile value is calculated based on the ranking of the business management object. This rank percentile value can be used as the stability evaluation value for the corresponding business management object. For example, the aforementioned one or more second time periods can include the periodic increments of the management objects for the current and the last five calendar years; or, the aforementioned one or more second time periods can include the periodic increments of the management objects for the current and the last three calendar years.

[0120] Step S209: Obtain the industry set associated with the source business data set, obtain the business weight corresponding to the target business object, and accumulate the business weights under each industry in the industry set to obtain the industry weight of the target business object under each industry.

[0121] Specifically, the computer device can acquire an industry set associated with the source business data set. This industry set may include one or more industries. After acquiring the business weight corresponding to the target business object, for each industry in the industry set, the business weights of the target business objects within that industry can be accumulated to obtain the industry weight of the target business object in each industry. In other words, the industry weight in this embodiment is calculated for each target business object managed by the business management object.

[0122] Step S210: If the stability assessment value corresponding to business management object i is less than or equal to the stability threshold, then add a stability label to business management object i.

[0123] Specifically, if the stability assessment value of business management object i in the target management object set is less than or equal to the stability threshold (which can be preset according to actual needs), a stability label can be added to business management object i.

[0124] Step S211: Obtain the term information, virtual asset scale, and honor information corresponding to the K target business objects managed by business management object i. Based on the term information, virtual asset scale, and honor information, obtain the object evaluation value corresponding to the K target business objects. Among the K target business objects, add a key business object tag to the target business object corresponding to the highest object evaluation value.

[0125] Specifically, the computer device can obtain three indicators corresponding to all target business objects (e.g., K target business objects) managed by business management object i: term information (tenure), virtual asset scale, and honor information. The three indicators corresponding to the K target business objects are sorted in descending order, and the ranking percentile value is calculated based on the ranking. Then, the ranking percentile value of the three indicators is multiplied by the corresponding weight and added together to serve as the object evaluation value for each of the K target business objects. Among the K target business objects, a key business object label is added to the target business object corresponding to the highest object evaluation value. The key business object label here is the key business object label of business management object i.

[0126] Step S212: Based on the industry weight corresponding to each of the K target business objects, determine the average industry weight of business management object i under each industry; based on the style type to which each industry in the industry set belongs, sum up the industry weights under the style type to obtain the style weights of the K target business objects under the style type.

[0127] Specifically, after obtaining the industry weight of each target business object in each industry, the computer equipment can determine the average industry weight of business management object i in any industry within the aforementioned industry set by taking the average of the industry weights of the K target business objects managed by business management object i in that industry. For a single business management object, an average industry weight can be calculated for each industry. For example, if the K target business objects managed by business management object i include target business object 1, target business object 2, and target business object 3, and target business object 1 has an industry weight of 5% in the electronics industry, target business object 2 has an industry weight of 1% in the electronics industry, and target business object 3 has an industry weight of 2% in the electronics industry, then the average industry weight of business management object i in the electronics industry can be determined as (5% + 1% + 2%) / 3. Similarly, for all other industries in the industry set except for the electronics industry, the average industry weight of business management object i in each industry can be obtained by following the aforementioned operation.

[0128] Optionally, the computer device can also acquire multiple different style types, each of which can include one or more industries. Each industry within a style type can be predefined. For example, all industries included in the industry set can be categorized into multiple style types, which may include cyclical style, financial / real estate style, growth style, consumer style, stable style, etc. The industries included in the industry set in the current example can be found above. Figure 2 Step S104 in the corresponding embodiment will not be repeated here; cyclical styles can include industries such as chemicals, automobiles, machinery, non-ferrous metals, building materials, mining, and steel; financial and real estate styles can include industries such as banking, non-bank financial institutions, and real estate; growth styles can include industries such as electronics, computers, electrical equipment, media, military, and communications; consumer styles can include industries such as food and beverage, home appliances, agriculture, forestry, animal husbandry and fishery, textiles and apparel, light manufacturing, commerce and trade, leisure services, and pharmaceuticals; stable styles can include industries such as public utilities, construction and decoration, and transportation.

[0129] Specifically, for any one of the K target business objects managed by business management object i, the style weight of that target business object under each style type can be obtained by summing its industry weights in each style type. For example, if target business object 1 has an industry weight of 10% in the electronics industry, 9% in the computer industry, 8% in the electrical equipment industry, 7% in the media industry, 6% in the military industry, and 5% in the communications industry, then the style weight of target business object 1 under the growth style can be determined as: 10% + 9% + 8% + 7% + 6% + 5% = 45%.

[0130] Step S213: Determine the average style weight corresponding to business management object i based on the style weight corresponding to each of the K target business objects, and determine the management style label corresponding to business management object i based on the average industry weight and the average style weight.

[0131] Specifically, after obtaining the style weights of each target business object under various style types, the computer device can determine the average style weight of business management object i under any style type by taking the average of the style weights of the K target business objects managed by business management object i under that style type. For a single business management object, an average style weight can be calculated for each style type. For example, if the K target business objects managed by business management object i include target business object 1, target business object 2, and target business object 3, and target business object 1 has a style weight of 5% under the growth style, target business object 2 has a style weight of 3% under the growth style, and target business object 3 has a style weight of 4% under the growth style, then the average style weight of business management object i under the growth style can be determined as (5% + 3% + 4%) / 3. Similarly, for all style types other than the growth style, the average style weight of business management object i under each style type can be obtained by following the aforementioned operation.

[0132] Furthermore, the computer equipment can determine the management style label corresponding to business management object i based on the average industry weight and average style weight. The management style label can include, but is not limited to, style labels, industry labels, and balance labels. The computer equipment can use style types with an average style weight greater than a style weight threshold (which can be preset, e.g., 30%) as the style label for business management object i. For example, if the average style weight of business management object i in the growth style is greater than the preset style weight threshold, the growth style can be considered the primary style for this business management object, and a growth style label can be added to business management object i. Similarly, the computer equipment can use industries with an average industry weight greater than an industry weight threshold (which can be preset, e.g., 20%) as the industry label for business management object i. For example, if the average industry weight of business management object i in the electronics industry is greater than the preset industry weight threshold, the electronics industry can be considered the primary industry for this business management object, and an electronics industry label can be added to business management object i. If the average style weight of business management object i under each style type is less than or equal to the style weight threshold, and the average industry weight of business management object i under each industry is less than or equal to the industry weight threshold, then it means that business management object i has neither an industry label nor an industry label. The coefficient of variation of the average style weight of business management object i under each style type can be calculated (for example, this coefficient of variation can be the standard deviation or mean of each average style weight). The smaller the coefficient of variation, the more balanced the style of business management object i. Alternatively, the coefficient of variation of the average industry weight of business management object i under each industry can be calculated. The smaller the coefficient of variation, the more balanced the industry of business management object i. When the coefficient of variation is less than a preset threshold, it indicates that business management object i is biased towards balance, and a balanced label can be added to business management object i.

[0133] In this embodiment, an incremental curve corresponding to each business management object can be generated based on the virtual asset periodic increment of the target business object managed by the business management object. Then, based on the target business object, the incremental curve, and management statistics, evaluation indicators for each business management object on M evaluation dimensions can be determined. At the same time, tags can be added to each business management object based on stability evaluation value, industry weight, and target business object. Through evaluation indicators on different evaluation dimensions and multiple tags, a quantitative and qualitative screening process for business management objects can be realized, thereby improving the screening accuracy of business objects. By mapping between business management objects and business objects, suitable business objects can be selected, thereby improving the screening efficiency of business objects. By converting the evaluation indicators on different evaluation dimensions into ranking percentile values ​​and using ranking percentile values ​​in a unified format to screen business management objects, the uniformity across different evaluation dimensions can be enhanced, further improving the screening efficiency of business objects.

[0134] Optionally, when the business data processing method proposed in this application is applied in a wealth management and investment scenario, the business management object can be a fund manager, and the target business object can be a fund product. (See attached diagram.) Figure 5 -Appendix Figure 6 The fund manager selection process is described in detail.

[0135] Please see Figure 5 , Figure 5 This is a schematic diagram of a fund manager screening process provided in an embodiment of this application. For example... Figure 5 As shown, the process of screening fund managers and extracting fund manager tags can be achieved through the following steps S1-S9:

[0136] Step S1: Obtain the latest daily fund data from the Juyuan database.

[0137] Specifically, for all publicly offered fund products in the market (hereinafter referred to as "fund products"), the latest daily fund data (i.e., the source business data set) can be obtained from the Juyuan database. In other words, once the daily fund data in the Juyuan database is updated, the latest daily fund data can be obtained from the Juyuan database by calling the interface. At this time, "daily" can be considered as the aforementioned first time period.

[0138] Step S2: Classify the fund products.

[0139] Specifically, the Juyuan database provides secondary, tertiary, and quaternary classifications for each fund product's investment type. Here, investment type can be considered a business category, and secondary, tertiary, and quaternary classifications can be considered multiple levels of categories. Actively managed equity funds (i.e., target business type) can be defined as including the following categories: 1. When the secondary classification is equity, the tertiary classification must be standard equity or enhanced index equity; 2. When the secondary classification is mixed, the tertiary classification can be equity-biased, or types II, III, and IV of flexible allocation funds. Passively managed equity funds can be defined as those containing only index equity. Actively managed and passively managed equity funds can be collectively referred to as equity-biased funds.

[0140] Among them, bond-oriented funds can be defined as including the following categories: 1. When the secondary classification is bond type, the tertiary classification must be pure bond type, convertible bond type, or ordinary bond type; 2. When the secondary classification is mixed type, the tertiary classification can be bond-oriented, capital-protected type, or type I of flexible allocation type. Funds with a primary classification of money market are defined as money market funds.

[0141] Based on the above definitions, all fund products in the market can be divided into equity-oriented, bond-oriented, and money market funds. Equity-oriented funds can be further subdivided into actively managed equity funds and passively managed equity funds. Based on the fund manager information (i.e., the information on the managed assets) of the fund products, a unique list of fund managers (i.e., the initial set of managed assets) is obtained across the entire market.

[0142] Step S3: Classify fund managers.

[0143] Specifically, after obtaining the list of fund managers and the classification results of fund products across the entire market, information about the fund managers can be compiled, which may include:

[0144] 1. The total number of funds managed by the fund manager (i.e., the first total number) and the total size (i.e., the sum of the virtual asset size of all funds managed by the fund manager);

[0145] 2. The number of actively managed equity funds managed by the fund manager (i.e., the second total number) and size (i.e., the virtual asset size of the target business objects); the proportion of the number of actively managed equity funds to the total number of fund products (referred to as the number percentage, or quantity percentage); the proportion of the size of actively managed equity funds to the total size of fund products (referred to as the size percentage); the number of passively managed equity funds managed by the fund manager and size; the proportion of the number of passively managed equity funds and size; the number of bond funds managed by the fund manager and size; the proportion of the number of bond funds and size; and the number of money market funds managed by the fund manager and size.

[0146] 3. Fund managers can be classified according to the following rules: If the number of actively managed equity funds managed by a fund manager accounts for more than 50% (the percentage threshold), the fund manager is identified as an actively managed equity fund manager; if the number of passively managed equity funds managed by a fund manager accounts for more than 50%, the fund manager is identified as a passively managed equity fund manager; if the number of bond funds managed by a fund manager accounts for more than 50%, the fund manager is identified as a bond fund manager; if the number of money market funds managed by a fund manager accounts for more than 50%, the fund manager is identified as a money market fund manager; if a fund manager does not belong to any of the above four categories, the fund manager is identified as a mixed fund manager.

[0147] 4. Does the fund manager have independently managed actively managed equity funds, meaning does he / she have any fund products where he / she is the sole fund manager? Generally speaking, excellent fund managers have their own independently managed fund products, while new fund managers with insufficient experience may co-manage with others.

[0148] Step S4: Mapping fund managers to fund products.

[0149] Specifically, after obtaining the fund manager classification results, subsequent operations can be performed according to the fund manager's category. For ease of description, the following will use actively managed equity fund managers as an example, that is, actively managed equity fund managers are selected from the list of fund managers in the entire market to form the aforementioned target management object set. Since each actively managed equity fund manager may manage multiple actively managed equity funds, and the performance of each actively managed equity fund is different, it is necessary to map the performance curves of multiple actively managed equity funds onto the fund manager to reflect the fund manager's average level (also known as the fund manager's career curve, i.e., the aforementioned incremental curve); this fund manager's career curve can be used to calculate the fund manager's returns, risks, and other indicators.

[0150] A fund manager's career curve can be defined as a curve generated daily by averaging the daily returns (i.e., the increment of the virtual asset cycle) of all actively managed equity funds under their management throughout their career. Optionally, if a fund manager leaves their position during the period, the daily return for the gap period is 0, and the average return of similar funds is also treated as 0. The fund manager's career curve is obtained by connecting the daily returns of each fund manager, as described above. Figure 3 The incremental curve 20a in the corresponding embodiment.

[0151] It's important to note that the fund manager career curve calculation only applies to actively managed equity, bond, and money market fund managers, excluding passively managed equity and mixed-asset fund managers. Passively managed equity funds passively track indices and their performance is unrelated to the fund manager's investment capabilities. Mixed-asset fund managers may manage multiple investment types without a primary focus, making it impossible to create a single career curve. To calculate a mixed-asset fund manager's career curve, all managed funds must be individually analyzed according to the aforementioned categories (actively managed equity, bond, and money market). Therefore, a mixed-asset fund manager may have one or more career curves. When calculating a fund manager's career curve, you can use fund products that match the fund manager's type. For example, if the fund manager is actively managed equity, you can select all actively managed equity funds under their management to calculate the career curve; if the fund manager is bond-oriented, you can select all bond-oriented funds under their management to calculate the career curve.

[0152] Step S5: Evaluate fund managers from multiple dimensions. The top L fund managers for each evaluation dimension are displayed on the fund manager module of the business client.

[0153] Specifically, computer equipment can screen fund managers from multiple evaluation dimensions. The following is a detailed description of the fund manager screening process, using eight dimensions as an example: assets under management, long-term returns (i.e., long-term incremental returns), short-term returns (i.e., short-term incremental returns), risk, investment tenure (i.e., management tenure), awards, popularity (i.e., attention), and comprehensive evaluation. In the fund manager module of the business client, the above-mentioned multiple evaluation dimensions can be presented directly, or other concepts that are more of a focus for users can be used to present these multiple evaluation dimensions. For example, the scale of management dimension can be presented as "top-tier in scale", the long-term return dimension can be presented as "best-performing", the short-term return dimension can be presented as "industry rising star", the risk dimension can be presented as "stable and balanced", the investment years dimension can be presented as "veteran investment researcher", the awards dimension can be presented as "award-winning expert", the popularity dimension can be presented as "most popular", and the comprehensive evaluation dimension can be presented as "comprehensive best choice", etc. This application does not limit the way multiple evaluation dimensions are presented in the business client.

[0154] Optionally, the assets under management (AUM) dimension refers to evaluating fund managers based on their size, selecting the top L (i.e., the top L funds, where L can be a positive integer) fund managers to display on the fund manager module of the business client. The fund manager information referenced for the AUM dimension is shown in Table 1 below:

[0155] Table 1

[0156]

[0157] In Table 1, the specific indicators refer to the specific fund manager information referenced for that evaluation dimension, and the values ​​in parentheses represent the weights corresponding to the specific fund manager information. It should be noted that in this embodiment, the values ​​in parentheses in the tables corresponding to each evaluation dimension have the same meaning; they all represent the weights corresponding to the respective indicators (specific fund manager information). The values ​​in parentheses are merely examples. Given that the sum of the weights of the indicators referenced for each evaluation dimension is 1, other weight allocation methods may exist. For example, in Table 1 above, the weight allocation for "the size of the managed actively managed equity funds" can be 70%, and the weight for "whether there are independently managed actively managed equity funds" can be 30%, etc. This application does not limit the weight allocation for each evaluation dimension, and will not elaborate further thereafter.

[0158] Regarding the aforementioned assets under management (AUM) dimension, all actively managed equity fund managers (hereinafter referred to as fund managers for ease of description) can be calculated as follows: ① Based on the AUM of the actively managed equity funds managed by each fund manager, they are ranked from largest to smallest. The ranking percentile value (i.e., the aforementioned first AUM assessment value, or the aforementioned first ranking percentile value) is calculated for each fund manager according to the ranking. This ranking percentile value can be defined as follows: Assuming a fund manager's ranking is t and the total number of fund managers is D, then the ranking percentile value can be: (t-1) / (D-1). ② For fund managers with independently managed actively managed equity funds, their independent management target score can be determined to be 1 (i.e., the first value); for fund managers without independently managed actively managed equity funds, their independent management target score can be determined to be 0 (i.e., the second value). The independent management target score here can be considered the second AUM assessment value. ③ The fund manager's total score is calculated by multiplying the ranking percentile value obtained in step ① by 80% (i.e., the first weight), and then adding the score of the independent managed objects obtained in step ② by multiplying by 20% (i.e., the second weight). The fund managers are then ranked in descending order of this total score. ④ The ranking percentile value is calculated based on the ranking in step ③, serving as the final score for the assets under management (AUM) dimension, i.e., the evaluation indicator for the fund manager in this dimension. ⑤ When this AUM dimension is used as a criterion for selecting fund managers, the top L fund managers can be displayed on the results page of the business client.

[0159] Optionally, the long-term return dimension refers to evaluating fund managers from the perspective of their long-term cumulative returns, in order to select the top-performing fund managers to be displayed in the fund manager module of the business client. The fund manager information referenced for the long-term return dimension is shown in Table 2 below:

[0160] Table 2

[0161]

[0162] The specific indicators in Table 2 refer to the information of specific fund managers referenced for long-term returns, namely, the cumulative returns over the past five years (i.e., the cumulative increase over the past five years), the cumulative returns over the past three years, and the cumulative returns over the past year. The calculation method for fund managers in the long-term return dimension is similar to that for the aforementioned assets under management dimension. The three indicators are sorted in descending order, and the ranking percentile values ​​for each indicator are calculated. Then, the ranking percentile values ​​for each indicator are multiplied by their corresponding weights and summed to obtain the fund manager's total long-term return score (i.e., the aforementioned total gain score). Subsequently, the total long-term return scores are sorted in ascending order, and the final ranking percentile value is calculated, which is the evaluation indicator for the fund manager in the long-term return dimension. When this long-term return dimension is used as a criterion for selecting fund managers, the top L fund managers can be displayed on the results page of the business client.

[0163] Optionally, the short-term return dimension refers to evaluating fund managers from the perspective of their short-term cumulative returns to select the top-performing fund managers to be displayed in the fund manager module of the business client. The fund manager information referenced for the short-term return dimension is shown in Table 3 below:

[0164] Table 3

[0165]

[0166]

[0167] The specific indicators in Table 3 refer to the information of specific fund managers referenced for short-term returns, namely, the cumulative return over the past two years (i.e., the cumulative increase over the past two years) and the cumulative return over the past year. The calculation method for fund managers in the short-term return dimension is similar to that for the long-term return dimension. The two indicators are sorted in descending order, and their respective percentile values ​​are calculated. Then, the percentile values ​​for each of the three indicators are multiplied by their corresponding weights and summed to obtain the fund manager's total short-term return score. Subsequently, the total short-term return scores are sorted in ascending order, and the final percentile value is calculated, which is the fund manager's evaluation indicator in the short-term return dimension. When this short-term return dimension is used as a criterion for selecting fund managers, the top L fund managers can be displayed on the results page of the business client.

[0168] Optionally, the purpose of the risk dimension can be based on a longer-term return perspective, taking into account the risk of fund managers to identify those with excellent and stable performance. The fund manager information referenced for the risk dimension is shown in Table 4 below:

[0169] Table 4

[0170]

[0171]

[0172] The calculation method for fund managers' risk dimension is similar to that of the aforementioned assessment dimensions. However, it's important to note that lower volatility and maximum drawdown are better; smaller values ​​result in a higher ranking and a lower percentile. Conversely, a higher Sharpe ratio is better; a higher Sharpe ratio results in a higher ranking and a lower percentile. The volatility, maximum drawdown, and Sharpe ratio can be extracted for different time periods as shown in Table 4 above, and the ranking percentile for each time period can be calculated. Then, these three indicators can be weighted according to the weights in Table 4 (each indicator has a weight of 1 / 3) and summed with the corresponding ranking percentile. The sums are then reordered in ascending order of weighted sum value, and the ranking percentile is calculated as the fund manager's risk score, i.e., the fund manager's risk assessment indicator.

[0173] Furthermore, based on the cumulative percentile value corresponding to the cumulative returns of fund managers over the past three years, fund managers with a cumulative percentile value of less than 30% can be identified. Based on the risk scores of fund managers with a cumulative percentile value of less than 30%, the top L fund managers can be displayed on the results page of the business client.

[0174] Optionally, the investment tenure dimension only considers one indicator: the fund manager's investment tenure. Funds are sorted from longest to shortest based on this investment tenure, and then the percentile value is calculated as the final score for this dimension, which is the evaluation indicator for the fund manager in this area. When this investment tenure dimension is used as a criterion for selecting fund managers, the top L fund managers can be displayed on the results page of the business client. The fund manager information referenced for the investment tenure dimension is shown in Table 5 below:

[0175] Table 5

[0176] concept Evaluation Dimensions Specific indicators / weights Veteran investment researcher Investment period Investment period (100%)

[0177] Optionally, this award-winning dimension can refer to two indicators: the number of award types and the number of awards received by the fund manager. These two indicators can be sorted in descending order, and the ranking percentile values ​​for each indicator can be calculated. These percentile values ​​are then multiplied by their corresponding weights and summed. The weighted sums are then sorted in ascending order, and the ranking percentile values ​​are used as the evaluation indicator for the fund manager's award-winning dimension. When this award-winning dimension is used as a criterion for selecting fund managers, the top L fund managers can be displayed on the results page of the business client. It is better for both the number of award types and the number of awards to be higher. The fund manager information referenced for the award-winning dimension is shown in Table 6 below.

[0178] Table 6

[0179]

[0180] Optionally, the popularity dimension can refer to five indicators: the number of new fund managers added to their portfolios in the past quarter (i.e., the number of new holdings), the number of searches (i.e., the number of searches), the number of fund managers added to their watchlists (i.e., the number of favorites), the number of fund managers purchased, and the news popularity (i.e., the number of news statistics). Higher values ​​for these five indicators are better. The five indicators are sorted in descending order, and their corresponding percentile values ​​are calculated. Then, each percentile value is multiplied by its corresponding weight (20%) as shown in Table 7, and the sums are calculated. The weighted sums are then sorted in ascending order, and the resulting percentile values ​​are used as the evaluation indicator for the fund manager's popularity. When this popularity dimension is used as a criterion for selecting fund managers, the top L fund managers can be displayed on the results page of the business client. The specific fund manager information referenced for the popularity dimension is shown in Table 7 below.

[0181] Table 7

[0182]

[0183]

[0184] Optionally, a comprehensive evaluation can be conducted to select fund managers based on the six evaluation dimensions mentioned above: assets under management, long-term returns, risk, investment tenure, awards, and popularity. The weights corresponding to these six evaluation dimensions are shown in Table 8 below.

[0185] Table 8

[0186]

[0187] As shown in Table 8 above, the six evaluation dimensions can be sorted and their percentile values ​​calculated. The percentile values ​​of each dimension are then multiplied by their corresponding weights and summed. The weighted sum is then used to sort the results and calculate the percentile values ​​again, which serve as the evaluation indicators for the comprehensive evaluation dimensions. When this comprehensive evaluation dimension is used as a criterion for selecting fund managers, the top L fund managers can be displayed on the results page of the business client.

[0188] In this embodiment, fund manager types can be defined more accurately, and the active investment capabilities of fund managers can be evaluated more effectively and objectively. Simultaneously, the performance of multiple fund products can be synthesized into the average performance of a fund manager, completing the mapping from fund products to fund managers and helping users understand the average investment level of fund managers. By calculating evaluation indicators on different evaluation dimensions daily, the different needs of different users can be better met, and it is also easier for users to understand, providing a reference for their investments.

[0189] Step S6: Generate representative works based on multiple fund product attributes.

[0190] Specifically, based on the fund manager's type, we can obtain the fund products of the same type managed by each fund manager. When the fund manager is a generalist, we can obtain all the fund products managed by that fund manager. If the fund manager is an actively managed equity fund manager, we can obtain the actively managed equity fund products managed by that fund manager, and obtain three key indicators for each actively managed equity fund product: the tenure of the actively managed equity fund product (term information), the size of the actively managed equity fund product (i.e., virtual asset size), and the number of awards received by the actively managed equity fund product (i.e., honors information).

[0191] The three indicators are sorted in descending order, and the ranking percentile is calculated based on the ranking. The ranking percentile of each indicator is then multiplied by its corresponding weight and summed to obtain the fund evaluation value (i.e., the aforementioned object evaluation value) for each actively managed equity fund. The fund evaluation values ​​are then sorted in ascending order, and the actively managed equity fund ranked first can be considered the fund manager's representative work, and a representative work label (i.e., a key business object label) is added to that actively managed equity fund. The weights corresponding to the three indicators can be the same.

[0192] Step S7: Multiple fund products periodically report their holdings to generate fund manager investment qualifications.

[0193] Specifically, for actively managed equity fund managers, their investment styles can be analyzed. Computer equipment can obtain the latest periodic reports of each actively managed equity fund managed by the fund manager, including the stock holdings, the corresponding Shenwan Level 1 industries (which can include 28 industries, forming an industry set), and the percentage of the fund's net asset value based on the market value of the stock holdings. After obtaining the stock weights (i.e., business weights) for each actively managed equity fund, the industry weights of each fund under each industry can be calculated. These industry weights can be the sum of the stock weights under that industry. Furthermore, based on the Shenwan Level 1 industries included in the multi-dimensional fundamental styles (i.e., various style types), the style weights of each actively managed equity fund under each fundamental style (each style type) can be further calculated. These style weights can be the sum of the industry weights included in each fundamental style. The Shenwan Level 1 industries included in multi-dimensional fundamental styles (e.g., five fundamental styles) can be found above. Figure 4 Step S212 in the corresponding embodiment will not be described again here.

[0194] After obtaining the industry weights and style weights for each actively managed equity fund, the average industry weight and average style weight for the fund manager can be further calculated. The average industry weight can be the average of the industry weights of all actively managed equity funds managed by the fund manager for each of the 28 industries mentioned above. The average style weight can be the average of the style weights of all actively managed equity funds managed by the fund manager for each of the five fundamental style dimensions. Computer equipment can then add an investment style tag to the fund manager based on the average industry weights and average style weights for each fundamental style dimension. The process of adding an investment style tag to the fund manager can be found above. Figure 4 Step S213 in the corresponding embodiment will not be described again here.

[0195] Step S8: Calculate the ranking of similar funds based on career curves, and calculate the stability of fund manager rankings.

[0196] Specifically, computer equipment can calculate the percentile ranking of a fund manager's performance for each calendar year (i.e., the aforementioned second time period) on their career curve. For example, it can calculate the performance stability of the current year and the most recent three calendar years (referred to as "three years + stability"), and the performance stability of the current year and the most recent five calendar years (referred to as "five years + stability"). The performance stability of the current year is only calculated if the current date is greater than June 30th; it is not calculated if the current date is less than or equal to June 30th. The calculation method for "three years + stability" or "five years + stability" can be expressed as follows: calculate the performance of each calendar year on the fund manager's career curve, and calculate the fund manager's percentile ranking among all comparable fund managers. After obtaining the ranking percentile values ​​for each calendar year, the standard deviation (i.e., the aforementioned ranking standard deviation) and mean (i.e., the aforementioned ranking mean) of the ranking percentile values ​​for each calendar year can be calculated. The mean and standard deviation are then sorted in ascending order, and a weighted sum is calculated using a 50%:50% weighting (i.e., both the mean and standard deviation have a 50% weight). The weighted sum is then sorted in ascending order, and the ranking percentile values ​​are calculated. If a fund manager's career curve, excluding the current year, is less than 3 years, then both the "3-year + stability" and "5-year + stability" ratings for that fund manager can be set to NA. If a fund manager's career curve, excluding the current year, is less than 5 years, then the "5-year + stability" rating for that fund manager can be set to NA. Here, both "3-year + stability" and "5-year + stability" can be referred to as stability assessment values.

[0197] For example, the "five-year+ stability" of fund manager A can be expressed as follows: If the current date is 20210710 (greater than 20210630, meaning half of the current year has passed), then the ranking percentile of the fund manager's career curve within the current year can be calculated as X0. Then, the ranking percentile of the most recent 5 calendar years (2016-2020) can be calculated. Assuming the ranking percentile for 2016 is X1, for 2017 it is X2, for 2018 it is X3, for 2019 it is X4, and for 2020 it is X5, then the standard deviation Q = std(X) and the mean P = mean(X) of the sequence [X0, X1, X2, X3, X4, X5] can be calculated. If there are H fund managers over a five-year period, then the standard deviation and mean of each of the H fund managers are sorted in ascending order. The ranking of the mean P can be denoted as Rank_P, and the ranking of the standard deviation Q can be denoted as Rank_Q. The total value is obtained by calculating Rank_P + Rank_Q. This total value is then sorted in ascending order. If fund manager A ranks t among the H fund managers, the final "five-year + stability" can be calculated as (t-1) / (H-1), and a smaller value is better. Similarly, the "three-year + stability" for fund manager A can be calculated in the same way as the "five-year + stability" calculation. Optionally, the computer equipment can pre-set a threshold Y. When the "three-year + stability" or "five-year + stability" is less than or equal to the threshold Y, a stability label can be added to fund manager A.

[0198] Please see Figure 6 , Figure 6 This is a schematic diagram of a fund manager selection interface provided in an embodiment of this application. For example... Figure 6The currently displayed interface is the homepage 30a of the business client. This homepage 30a may include a fund manager module, which displays the top-ranked fund managers selected by the business client's backend service based on eight evaluation dimensions. These eight evaluation dimensions can be comprehensive evaluation, evaluation dimension 1, evaluation dimension 2, evaluation dimension 3, evaluation dimension 4, evaluation dimension 5, evaluation dimension 6, and evaluation dimension 7. When a user selects a different evaluation dimension, homepage 30a displays a list of fund managers calculated based on that dimension (such as the aforementioned top L fund managers). The fund manager lists corresponding to different evaluation dimensions are updated daily. For example, if a user selects evaluation dimension 1, homepage 30a will display a list of fund managers filtered based on evaluation dimension 1, which may include fund manager A and fund manager B, etc. The fund managers listed on homepage 30a can display information such as their investment style tag 30b, assets under management, annualized average return, and the fund products they manage. Optionally, a stability label can be added for the fund manager on the homepage 30a. For example, the stability label for fund manager A is stability label 1.

[0199] Furthermore, when a user selects a specific fund manager (e.g., Fund Manager A), they can access the fund details page 30c. This page 30c can include Fund Manager A's personal profile, career trajectory 30d, and the fund products they manage. Users can also tag representative funds managed by Fund Manager A, such as Fund A, and add a representative work tag 30e (i.e., a key business object tag) to Fund A. In the business client, users can then select fund products managed by fund managers of interest for investment.

[0200] Optionally, fund manager investment style and ranking stability can be directly displayed as tags on the homepage 30a of the business client; while tags such as fund representative works and fund manager career curve can be displayed on the fund details page 30c. Of course, all tags of a fund manager can be displayed on the homepage 30a, or all can be displayed on the fund details page 30c. This application does not limit the display position of fund manager tags.

[0201] In this embodiment, indicators such as the fund manager's representative works, investment style, and ranking stability are dynamically and continuously calculated to form tags. These tags are then displayed in the business client, which can help users understand fund managers more intuitively, provide users with reference, and improve the efficiency of fund manager selection.

[0202] Optionally, when the business data processing method proposed in this application is applied to a music screening scenario, the business management object can be a singer, and the target business object can be a musical work. The computer device can acquire a music data set containing the latest musical works (i.e., the source business data set), and can classify the musical works in the music data set, such as classifying them into pop music, classical music, hip-hop music, etc.; based on the singer information corresponding to the musical works contained in the music data set, it can obtain a list of all singers in the music platform (e.g., a platform application, also known as a business client); and classify the singers in the singer list according to the type of musical works sung by each singer in the singer list to obtain the singer's category, such as pop singer, classical singer, hip-hop singer, etc.

[0203] Furthermore, all singers of the pop singer type can be grouped into a target singer set (i.e., a target management object set). The pop music works performed by each pop singer (i.e., a business management object) in the target singer set (i.e., the aforementioned target business objects) are obtained. Based on the virtual asset cycle increment corresponding to the pop music works (e.g., the number of plays, clicks, and revenue per unit time in multiple first-time periods), an increment curve is generated for each pop singer. Based on the number of pop music works performed by each pop singer, the increment curve, and the music performance information corresponding to each pop singer, evaluation indicators for each pop singer across multiple evaluation dimensions are obtained. The evaluation indicators corresponding to M evaluation dimensions are used to filter the singer display list from the target singer set, where M is a positive integer greater than 1. Then, based on the increment curve, a stability evaluation value corresponding to each pop singer can be obtained, along with the industry weight corresponding to each pop music work. Here, the industry weight can refer to the weight of each pop music work within its respective genre. Finally, based on the stability evaluation value, industry weight, and pop music works, N types of tags corresponding to each pop singer can be determined. These N types of tags are used to filter the pop music works in the singer display list. In other words, multiple evaluation dimensions can be used to filter the list of singers to be displayed on the music platform from the target singer set. Then, based on the N types of tags for each popular singer, the list of popular singers of interest can be further selected, and the music works of interest sung by the selected popular singers can be selected for playback.

[0204] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of a business data processing device provided in an embodiment of this application. Figure 7As shown, the business data device 1 may include: a set acquisition module 11, a curve generation module 12, an indicator acquisition module 13, a weight acquisition module 14, and a label determination module 15;

[0205] The collection acquisition module 11 is used to acquire the source business data set and, based on the source business data set, acquire the target management object set used to manage business objects.

[0206] The curve generation module 12 is used to obtain the target business objects managed by each business management object in the target management object set, and generate an incremental curve corresponding to each business management object based on the virtual asset periodic increment corresponding to the target business object.

[0207] The indicator acquisition module 13 is used to obtain the evaluation indicators of each business management object on M evaluation dimensions based on the target business object, the incremental curve and the management statistics information corresponding to each business management object; the evaluation indicators corresponding to the M evaluation dimensions are used to filter the management object display list from the target management object set, where M is a positive integer greater than 1;

[0208] The weight acquisition module 14 is used to obtain the stability assessment value corresponding to each business management object according to the incremental curve, and to obtain the industry weight corresponding to the target business object.

[0209] The tag determination module 15 is used to determine N types of tags corresponding to each business management object based on the stability assessment value, industry weight, and target business object; the N types of tags are used to filter the business management objects in the management object display list, where N is a positive integer.

[0210] The specific implementation functions of the set acquisition module 11, curve generation module 12, indicator acquisition module 13, weight acquisition module 14, and label determination module 15 can be found above. Figure 2 Steps S101-S105 in the corresponding embodiments will not be described again here.

[0211] In one or more embodiments, the collection acquisition module 11 may include: a business type determination unit 111, a management object acquisition unit 112, an index ratio determination unit 113, and a management object selection unit 114.

[0212] The business type determination unit 111 is used to obtain the source business data set from the source database and determine the target business type according to the business category to which the business objects contained in the source business data set belong.

[0213] The management object acquisition unit 112 is used to acquire an initial management object set based on the management object information corresponding to the business objects contained in the source business data set; each initial management object in the initial management object set is unique.

[0214] The index percentage determination unit 113 is used to obtain the first total number of business objects managed by each initial management object, and to obtain the second total number of business objects with target business types managed by each initial management object, and to determine the ratio between the second total number and the first total number as the quantity percentage.

[0215] The management object selection unit 114 is used to identify the initial management objects whose quantity ratio is greater than the ratio threshold in the initial management object set as business management objects and add the business management objects to the target management object set.

[0216] The specific implementation functions of the business type determination unit 111, the management object acquisition unit 112, the index percentage determination unit 113, and the management object selection unit 114 can be found above. Figure 4 Steps S201-S203 in the corresponding embodiments will not be described again here.

[0217] In one or more embodiments, the target management object set includes business management object i, and the number of target business objects managed by business management object i is K, where K is a positive integer and i is a positive integer less than or equal to the number of business management objects contained in the target management object set;

[0218] The curve generation module 12 may include: an asset cycle increment acquisition unit 121, an object cycle increment determination unit 122, and an increment curve generation unit 123;

[0219] The asset cycle increment acquisition unit 121 is used to acquire the virtual asset cycle increment of the K target business objects managed by the business management object i in multiple first time periods.

[0220] The object period increment determination unit 122 is used to determine the average increment of the virtual asset period increment of K target business objects in each first time period as the management object period increment corresponding to business management object i.

[0221] The incremental curve generation unit 123 is used to generate an incremental curve corresponding to the business management object i based on the management object period increment of the business management object i in multiple first time periods.

[0222] The specific implementation functions of the asset cycle increment acquisition unit 121, the object cycle increment determination unit 122, and the increment curve generation unit 123 can be found above. Figure 2 Step S102 in the corresponding embodiment will not be described again here.

[0223] In one or more embodiments, the M evaluation dimensions include management scale dimension, risk dimension, and attention dimension;

[0224] The indicator acquisition module 13 may include: a first indicator acquisition unit 131, a second indicator acquisition unit 132, a data statistics unit 133, and a third indicator acquisition unit 134;

[0225] The first indicator acquisition unit 131 is used to acquire the evaluation indicators of each business management object in the management scale dimension based on the virtual asset scale of the target business object.

[0226] The second indicator acquisition unit 132 is used to obtain the volatility, maximum drawdown and Sharpe ratio corresponding to each business management object according to the incremental curve, and to perform a weighted summation of the volatility, maximum drawdown and Sharpe ratio to obtain the assessment indicators of each business management object in the risk dimension.

[0227] The data statistics unit 133 is used to obtain the number of newly held objects and information statistics corresponding to the target business object, as well as the number of searches corresponding to each business management object.

[0228] The third indicator acquisition unit 134 is used to determine the number of newly acquired objects, the number of information statistics, and the number of searches as management statistics information, and to obtain the evaluation indicators of each business management object in the dimension of attention based on the management statistics information.

[0229] The specific implementation functions of the first indicator acquisition unit 131, the second indicator acquisition unit 132, the data statistics unit 133, and the third indicator acquisition unit 134 can be found above. Figure 4 Steps S205-S207 in the corresponding embodiments will not be described again here.

[0230] In one or more embodiments, the first indicator acquisition unit 131 may include: a sorting subunit 1311, a scale evaluation value determination subunit 1312, and a weighted summation subunit 131;

[0231] The sorting subunit 1311 is used to sort the business management objects in the target management object set according to the virtual asset scale of the target business object, and obtain the object sorting result of the target management object set;

[0232] The scale assessment value determination subunit 1312 is used to obtain the first scale assessment value corresponding to each business management object according to the object sorting result, and to determine the second scale assessment value corresponding to each business management object according to the number of business management objects corresponding to the target business object.

[0233] The weighted summation subunit 1313 is used to perform a weighted summation operation on the first scale evaluation value and the second scale evaluation value to obtain the evaluation index of each business management object in the management scale dimension.

[0234] The specific implementation functions of the sorting subunit 1311, the scale evaluation value determination subunit 1312, and the weighted summation subunit 131 can be found in the above description. Figure 4 Step S205 in the corresponding embodiment will not be described again here.

[0235] In one or more embodiments, the weight acquisition module 14 may include: a sorting evaluation value acquisition unit 141, a stability evaluation value acquisition unit 142, and a business weight accumulation unit 143;

[0236] The sorting evaluation value acquisition unit 141 is used to acquire one or more sorting evaluation values ​​corresponding to each business management object based on the periodic increment of the management object contained in one or more second time periods of the incremental curve.

[0237] The stability assessment value acquisition unit 142 is used to acquire the sorting standard deviation and sorting mean corresponding to one or more sorting assessment values, and to acquire the stability assessment value corresponding to each business management object based on the sorting standard deviation and sorting mean.

[0238] The business weight accumulation unit 143 is used to obtain the industry set associated with the source business data set, obtain the business weight corresponding to the target business object, accumulate the business weight under each industry in the industry set, and obtain the industry weight of the target business object under each industry.

[0239] The specific implementation functions of the sorting evaluation value acquisition unit 141, the stability evaluation value acquisition unit 142, and the business weight accumulation unit 143 can be found above. Figure 4 Steps S208-S209 in the corresponding embodiments will not be described again here.

[0240] In one or more embodiments, the target management object set includes business management object i, the number of target business objects managed by business management object i is K, and the N types of tags include key business object tags, management style tags and stability tags, where K is a positive integer and i is a positive integer less than or equal to the number of business management objects contained in the target management object set.

[0241] The tag determination module 15 may include: a stability tag addition unit 151, an object evaluation value acquisition unit 152, a key business object tag addition unit 153, an average industry weight determination unit 154, and a style weight acquisition unit 155.

[0242] The stability label adding unit 151 is used to add a stability label to the business management object i if the stability evaluation value corresponding to the business management object i is less than or equal to the stability threshold.

[0243] The object evaluation value acquisition unit 152 is used to acquire the term information, virtual asset scale and honor information of the K target business objects managed by the business management object i, and to acquire the object evaluation value of the K target business objects based on the term information, virtual asset scale and honor information.

[0244] The key business object tag adding unit 153 is used to add a key business object tag to the target business object with the largest object evaluation value among K target business objects;

[0245] The average industry weight determination unit 154 is used to determine the average industry weight of business management object i in each industry based on the industry weight corresponding to each of the K target business objects.

[0246] The style weight acquisition unit 155 is used to accumulate the industry weights under the style type for each industry in the industry set, and obtain the style weights of K target business objects under the style type.

[0247] The management style label determination unit 156 is used to determine the average style weight corresponding to business management object i based on the style weight corresponding to each of the K target business objects, and to determine the management style label corresponding to business management object i based on the average industry weight and the average style weight.

[0248] The specific implementation functions of the stability tag addition unit 151, the object evaluation value acquisition unit 152, the key business object tag addition unit 153, the average industry weight determination unit 154, and the style weight acquisition unit 155 can be found above. Figure 4 Steps S210-S213 in the corresponding embodiments will not be described again here.

[0249] In this embodiment, an incremental curve corresponding to each business management object can be generated based on the virtual asset periodic increment of the target business object managed by the business management object. Then, based on the target business object, the incremental curve, and management statistics, evaluation indicators for each business management object on M evaluation dimensions can be determined. At the same time, tags can be added to each business management object based on stability evaluation value, industry weight, and target business object. Through evaluation indicators on different evaluation dimensions and multiple tags, a quantitative and qualitative screening process for business management objects can be realized. Furthermore, by mapping between business management objects and business objects, suitable business objects can be selected, which can improve the screening efficiency of business objects. By converting the evaluation indicators on different evaluation dimensions into ranking percentile values ​​and using ranking percentile values ​​in a unified format to screen business management objects, the uniformity across different evaluation dimensions can be enhanced, further improving the screening efficiency of business objects.

[0250] Further, please see Figure 8 , Figure 8 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Figure 8 As shown, the computer device 1000 can be a user terminal, for example, the one described above. Figure 1 The user terminal 10a in the corresponding embodiment can also be a server, for example, as described above. Figure 1 The server 10d in the corresponding embodiment will not be limited here. For ease of understanding, this application takes a computer device as a user terminal as an example. The computer device 1000 may include: a processor 1001, a network interface 1004, and a memory 1005. In addition, the computer device 1000 may also include: a user interface 1003, and at least one communication bus 1002. The communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a Wi-Fi interface). The memory 1004 may be a high-speed RAM memory or a non-volatile memory, such as at least one disk storage device. The memory 1005 may optionally be at least one storage device located remotely from the aforementioned processor 1001. Figure 8 As shown, the memory 1005, which is a computer-readable storage medium, may include an operating system, a network communication module, a user interface module, and a device control application.

[0251] The network interface 1004 in the computer device 1000 can also provide network communication functions, and the optional user interface 1003 can also include a display screen and a keyboard. In the computer device 1000 shown in Figure 8, the network interface 1004 provides network communication functions; the user interface 1003 is mainly used to provide an input interface for the user; and the processor 1001 can be used to call the device control application stored in the memory 1005 to achieve:

[0252] Obtain the source business data set, and based on the source business data set, obtain the target management object set used to manage business objects;

[0253] Obtain the target business objects managed by each business management object in the target management object set, and generate an increment curve corresponding to each business management object based on the periodic increment of the virtual assets corresponding to the target business object;

[0254] Based on the target business object, the incremental curve, and the management statistics corresponding to each business management object, obtain the evaluation indicators for each business management object on M evaluation dimensions; the evaluation indicators corresponding to the M evaluation dimensions are used to filter the management object display list from the set of target management objects, where M is a positive integer greater than 1;

[0255] Based on the incremental curve, obtain the stability assessment value corresponding to each business management object, and obtain the industry weight corresponding to the target business object;

[0256] Based on the stability assessment value, industry weight, and target business object, determine the N types of tags corresponding to each business management object; the N types of tags are used to filter the business management objects in the management object display list, where N is a positive integer.

[0257] It should be understood that the computer device 1000 described in the embodiments of this application can execute the foregoing text. Figure 2 Figure 4- Figure 5 The description of the business data processing method in any corresponding embodiment can also be executed as described above. Figure 7 The description of the business data processing device 1 in the corresponding embodiments will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated here.

[0258] Furthermore, it should be noted that this application embodiment also provides a computer-readable storage medium, which stores a computer program executed by the aforementioned business data processing device 1. The computer program includes program instructions, and when the processor executes the program instructions, it can execute the aforementioned... Figure 2 , Figures 4-5The description of the business data processing method in any corresponding embodiment is already provided and will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated. For technical details not disclosed in the computer-readable storage medium embodiments involved in this application, please refer to the description of the method embodiments of this application. As an example, program instructions can be deployed and executed on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network. These multiple computing devices distributed across multiple locations and interconnected via a communication network can constitute a blockchain system.

[0259] Furthermore, it should be noted that this application also provides a computer program product or computer program, which may include computer instructions, which may be stored in a computer-readable storage medium. The processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor may execute the computer instructions, causing the computer device to perform the aforementioned actions. Figure 2 , Figures 4-5 The description of the business data processing method in any corresponding embodiment is already provided, and therefore will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated. For technical details not disclosed in the computer program products or computer program embodiments involved in this application, please refer to the description of the method embodiments of this application.

[0260] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0261] The steps in the method of this application embodiment can be adjusted, combined, or deleted according to actual needs.

[0262] The modules in the device of this application embodiment can be merged, divided, and deleted according to actual needs.

[0263] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0264] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. A business data processing method, characterized in that, The method is performed by a computer device and includes: Every so often, the API is called to retrieve a set of source business data from the source database, and a set of target management objects for managing business objects is obtained based on the source business data set. Obtain the target business object managed by each business management object in the target management object set, and generate an increment curve corresponding to each business management object based on the virtual asset period increment corresponding to the target business object; Based on the target business object, the incremental curve, and the management statistics corresponding to each business management object, the evaluation indicators for each business management object on M evaluation dimensions are obtained; the evaluation indicators corresponding to the M evaluation dimensions are used to filter the management object display list from the target management object set, where M is a positive integer greater than 1; Based on the incremental curve corresponding to each business management object, the periodic increment of the management object within one or more second time periods is used to obtain the stability assessment value corresponding to each business management object, and the industry weight corresponding to the target business object is obtained. Based on the stability assessment value, the industry weight, and the target business object, N types of tags are determined for each business management object; the N types of tags are used to filter the business management objects in the management object display list, where N is a positive integer. When a user selects one of the M evaluation dimensions displayed in the business client, the business client displays a list of management objects corresponding to the evaluation dimensions selected by the selection operation, and N types of labels for each business management object in the list of management objects.

2. The method according to claim 1, characterized in that, The step of obtaining the target management object set for managing business objects based on the source business data set includes: The target business type is determined based on the business category to which the business objects contained in the source business data set belong; Based on the management object information corresponding to the business objects contained in the source business data set, an initial management object set is obtained; each initial management object in the initial management object set is unique. Obtain the first total number of business objects managed by each initial management object, and obtain the second total number of business objects with the target business type managed by each initial management object, and determine the ratio between the second total number and the first total number as the quantity percentage; In the initial set of managed objects, the initial managed objects whose quantity ratio is greater than the ratio threshold are identified as business managed objects, and the business managed objects are added to the target set of managed objects.

3. The method according to claim 1, characterized in that, The target management object set includes business management object i, and the number of target business objects managed by business management object i is K, where K is a positive integer and i is a positive integer less than or equal to the number of business management objects contained in the target management object set; The step of obtaining the target business objects managed by each business management object in the target management object set, and generating an increment curve corresponding to each business management object based on the virtual asset periodic increment corresponding to the target business object, includes: Obtain the K target business objects managed by the business management object i, and obtain the virtual asset periodic increment of the K target business objects in multiple first time periods; The average increment of the virtual asset cycle increment of the K target business objects in each first time period is determined as the cycle increment of the management object corresponding to the business management object i. Based on the management object cycle increment of the business management object i within the multiple first time periods, an incremental curve corresponding to the business management object i is generated.

4. The method according to claim 1, characterized in that, The M evaluation dimensions include management scale, risk, and attention level. The step of obtaining evaluation indicators for each business management object across M evaluation dimensions based on the target business object, the incremental curve, and the management statistics corresponding to each business management object includes: Based on the virtual asset scale of the target business object, obtain the evaluation indicators for each business management object in the management scale dimension; Based on the incremental curve, the volatility, maximum drawdown, and Sharpe ratio corresponding to each business management object are obtained. The volatility, maximum drawdown, and Sharpe ratio are weighted and summed to obtain the evaluation index of each business management object on the risk dimension. Obtain the number of newly added holding objects and information statistics corresponding to the target business object, and obtain the number of searches corresponding to each business management object; The number of newly added holding objects, the number of information statistics, and the number of searches are determined as the management statistics information. Based on the management statistics information, the evaluation indicators of each business management object on the attention dimension are obtained.

5. The method according to claim 4, characterized in that, The step of obtaining the evaluation indicators for each business management object on the management scale dimension based on the virtual asset scale of the target business object includes: Based on the virtual asset scale of the target business object, the business management objects in the target management object set are sorted to obtain the object sorting result of the target management object set; Based on the object sorting result, obtain the first scale evaluation value corresponding to each business management object, and determine the second scale evaluation value corresponding to each business management object based on the number of business management objects corresponding to the target business object. The first scale evaluation value and the second scale evaluation value are weighted and summed to obtain the evaluation index of each business management object on the management scale dimension.

6. The method according to claim 1, characterized in that, The step of obtaining a stability assessment value for each business management object based on the incremental curve corresponding to each business management object within one or more second time periods, and obtaining the industry weight corresponding to the target business object, includes: Based on the incremental curve corresponding to each business management object, and the periodic increment of the management object included in one or more second time periods, obtain one or more ranking evaluation values ​​corresponding to each business management object. Obtain the sorting standard deviation and sorting mean corresponding to the one or more sorting evaluation values, and obtain the stability evaluation value corresponding to each business management object based on the sorting standard deviation and the sorting mean; Obtain the industry set associated with the source business data set, obtain the business weight corresponding to the target business object, and accumulate the business weights under each industry in the industry set to obtain the industry weight of the target business object under each industry.

7. The method according to claim 6, characterized in that, The target management object set includes business management object i, and the number of target business objects managed by business management object i is K. The N types of tags include key business object tags, management style tags, and stability tags, where K is a positive integer and i is a positive integer less than or equal to the number of business management objects contained in the target management object set. The step of determining N types of tags corresponding to each business management object based on the stability assessment value, the industry weight, and the target business object includes: If the stability assessment value corresponding to the business management object i is less than or equal to the stability threshold, then a stability label is added to the business management object i. Obtain the term information, virtual asset scale, and honor information corresponding to the K target business objects managed by the business management object i, and obtain the object evaluation value corresponding to the K target business objects based on the term information, the virtual asset scale, and the honor information. Among the K target business objects, add a key business object tag to the target business object corresponding to the highest object evaluation value; Based on the industry weight corresponding to each of the K target business objects, determine the average industry weight of the business management object i in each industry; Based on the style type of each industry in the industry set, the industry weights under the style type are accumulated to obtain the style weights of the K target business objects under the style type. Based on the style weight corresponding to each of the K target business objects, the average style weight corresponding to the business management object i is determined, and based on the average industry weight and the average style weight, the management style label corresponding to the business management object i is determined.

8. A business data processing device, characterized in that, include: The collection acquisition module is used to periodically call the interface to retrieve the source business data collection from the source database, and then retrieve the target management object collection for managing business objects based on the source business data collection. The curve generation module is used to obtain the target business objects managed by each business management object in the target management object set, and generate an incremental curve corresponding to each business management object based on the virtual asset periodic increment corresponding to the target business object; The indicator acquisition module is used to acquire the evaluation indicators of each business management object on M evaluation dimensions based on the target business object, the incremental curve, and the management statistics information corresponding to each business management object; the evaluation indicators corresponding to the M evaluation dimensions are used to filter the management object display list from the target management object set, where M is a positive integer greater than 1; The weight acquisition module is used to obtain the stability assessment value corresponding to each business management object based on the incremental curve corresponding to each business management object and the periodic increment of the management object within one or more second time periods, and to obtain the industry weight corresponding to the target business object. The tag determination module is used to determine N types of tags corresponding to each business management object based on the stability assessment value, the industry weight, and the target business object; The N types of tags are used to filter the business management objects in the management object display list, where N is a positive integer; The tag determination module is also used to, when receiving a user's selection operation for the M evaluation dimensions displayed in the business client, display a list of management objects corresponding to the evaluation dimensions determined by the selection operation, and N types of tags for each business management object in the list of management objects.

9. A computer device, characterized in that, Including memory and processor; The memory is connected to the processor, the memory is used to store computer programs, and the processor is used to invoke the computer programs so that the computer device performs the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded and executed by a processor to cause a computer device having the processor to perform the method of any one of claims 1-7.

11. A computer program product, characterized in that, The computer program product includes computer instructions that, when executed by a processor, implement the method described in any one of claims 1-7.

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