Business data processing method and device and server

Abstract

The invention provides a business data processing method, a business data processing device and a server, which can be used in the technical field of finance. Based on the method, before specific implementation, big language model training is utilized in advance to obtain information data which can be based on input multiple data sources and is related to a customer object, and a preset business demand mining model of business demands of the customer object is automatically analyzed and mined. In specific implementation, a server obtains various information data related to candidate customer objects needing to be concerned through a plurality of data sources according to a preset business processing rule at preset time intervals; processing the information data by using a preset business demand mining model, and automatically mining and discovering the business demand of the customer object and the target business suitable for the customer object; according to the method and the device, the business terminal can be automatically created, the corresponding target task is automatically created in time, and then relevant prompts are given to the business terminal, so that the business terminal can efficiently and accurately realize offline business promotion, and a better promotion effect is obtained.

Description

Technical Field

[0001] This specification belongs to the field of Internet technology, and in particular to business data processing methods, devices and servers. Background Art

[0002] Financial transaction institutions (such as banks) often need to arrange business personnel to visit customers offline and promote relevant business products launched by the institution to customers.

[0003] However, based on the existing methods, most of them require business personnel to rely on personal experience to judge customer preferences, and then conduct offline promotion of relevant business products to the customer. During the implementation of the above methods, it is easy to be affected by the subjective factors of the business personnel, resulting in unsatisfactory business promotion results, and may even cause customer disgust.

[0004] To address the above problems, no effective solution has been proposed yet. Summary of the invention

[0005] This specification provides a business data processing method, device and server, which can enable business terminals to efficiently and accurately implement offline business promotion and obtain better promotion effects.

[0006] This specification provides a business data processing method, which is applied to a server of a transaction service platform, including:

[0007] Receive and respond to business promotion attention requests and identify candidate customers who need attention;

[0008] According to the preset business processing rules, at each preset time period, the first type of information data released by the candidate customer objects, the second type of information data released by the transaction service platform, and the third type of information data released by the third party are obtained through multiple data sources;

[0009] combining the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data;

[0010] Using a preset business demand mining model to process the target joint information data, and obtaining a corresponding target processing result; wherein the preset business demand mining model is a model obtained by training based on a large language model;

[0011] According to the target processing results, candidate customers with business needs are identified as target customers, and the target needs of the target customers are determined;

[0012] According to the target demand content, matching candidate businesses are determined from the preset candidate business set as target businesses for target customers;

[0013] Create a target task for offline promotion of the target business to the target customer object; and generate target prompt information corresponding to the target task;

[0014] The target prompt information is sent to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer object offline.

[0015] In one embodiment, the first type of information data published by the candidate customer objects is obtained through multiple data sources, including:

[0016] According to the object identifier of the candidate customer object, query and determine the website, public account, and social account of the candidate customer object;

[0017] According to the website, public account, and social account of the candidate customer object, the information data released by the candidate customer object in the current time period is queried as the first category of information data.

[0018] In one embodiment, the second type of information data released by the transaction service platform is obtained through multiple data sources, including:

[0019] Determining attribute information of the candidate customer object according to the object identifier of the candidate customer object;

[0020] Information data that matches the attribute information of the candidate customer object is screened out from the information data released in the current time period of the transaction service platform and the adjacent valid historical time period as the second category of information data.

[0021] In one embodiment, the third category of information data published by a third party is obtained through multiple data sources, including:

[0022] Determine attribute information of the candidate customer object and object identifiers of associated objects of the candidate customer object according to the object identifier of the candidate customer object;

[0023] According to the attribute information of the candidate customer object, determine the third-party public platform related to the candidate customer object; according to the object identifier of the associated object, determine the website, public account, and social account of the associated object;

[0024] Filter out first branch messages related to candidate customer objects from information data published in the current time period and the adjacent valid historical time period on the third-party public platform; filter out second branch messages related to candidate customer objects from information data published in the current time period on the websites, public accounts, and social accounts of the associated objects;

[0025] The first branch message and the second branch message are combined to obtain corresponding third category information data.

[0026] In one embodiment, after determining the candidate customer object with business needs as the target customer object according to the target processing result, the method further includes:

[0027] According to the target processing results, determine the target demand content of the target customer object;

[0028] According to the target demand content, key information data is screened out from the first category of information data, the second category of information data, and the third category of information data;

[0029] Processing the key information data using a preset semantic extraction model to obtain a key information summary and key content text of the key information data;

[0030] Accordingly, the method further includes:

[0031] The key information summary, key content text, and link address of the key information data are delivered to the business terminal.

[0032] In one embodiment, after sending the target prompt information to the corresponding service terminal, the method further includes:

[0033] Receive target promotion records uploaded by business terminals for offline promotion of target services to target customers, as well as target promotion results;

[0034] According to the target promotion records, the target promotion results are verified to obtain the corresponding target verification results;

[0035] According to the target verification results, when it is determined that the verification has passed, the quality of the offline business promotion of the business terminal for the target customer objects is evaluated according to the target promotion records and target promotion results to obtain the corresponding target evaluation results.

[0036] In one embodiment, after obtaining the corresponding target evaluation result, the method further includes:

[0037] If, according to the target evaluation results, it is determined that the offline business promotion of the business terminal for the target customer object does not meet the preset requirements, and the target promotion result is a promotion failure, detect whether the target customer object and the target business meet the re-promotion conditions;

[0038] When it is determined that the target customer object and the target business meet the re-promotion conditions, a re-promotion task is created to re-promote the target business to the target customer object offline; and attribute information of the business terminal and the target customer object is obtained;

[0039] Using the preset promotion strategy generation model to process the target promotion records, the attribute information of the business terminal, and the attribute information of the target customer object, an improved promotion strategy is determined;

[0040] Sending re-promotion prompt information to the service terminal; wherein the re-promotion prompt information at least carries an improved promotion strategy.

[0041] This specification also provides a business data processing device, which is applied to a server of a transaction service platform, including:

[0042] A receiving module is used to receive and respond to business promotion attention requests and determine candidate customer objects that need attention;

[0043] The acquisition module is used to acquire the first type of information data published by the candidate customer objects, the second type of information data published by the transaction service platform, and the third type of information data published by the third party through multiple data sources at each preset time interval according to the preset business processing rules;

[0044] A combining module, used for combining the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data;

[0045] A processing module, used to process the target joint information data using a preset business demand mining model to obtain a corresponding target processing result; wherein the preset business demand mining model is a model obtained by training based on a large language model;

[0046] The first determination module is used to determine the candidate customer objects with business needs as target customer objects according to the target processing result; and determine the target demand content of the target customer objects;

[0047] The second determination module is used to determine matching candidate services from a preset candidate service set according to target demand content as target services for target customers;

[0048] A creation module is used to create a target task for offline promotion of a target business to a target customer object; and generate target prompt information corresponding to the target task;

[0049] The sending module is used to send the target prompt information to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information and promotes the target business to the target customer object offline.

[0050] The present specification also provides a server, comprising a processor and a memory for storing processor executable instructions, wherein the processor implements relevant steps of the business data processing method when executing the instructions.

[0051] The present specification also provides a computer-readable storage medium on which computer instructions are stored, and the instructions implement the steps of the business data processing method when executed by a processor.

[0052] Based on the business data processing method, device and server provided in this specification, before specific implementation, a preset business demand mining model can be pre-trained using a large language model to obtain information data of customer objects based on multiple data sources, automatically analyzing and mining the business needs of customer objects. During specific implementation, the server can obtain the first type of information data related to the candidate customer objects that need to be concerned, as well as the second type of information data released by the transaction service platform and the third type of information data released by a third party through multiple data sources at intervals of a preset time period according to the preset business processing rules; and combine the information data of the above multiple data sources to obtain target joint information data; then use the preset business demand mining model to process the target joint information data to obtain the corresponding target processing results; according to the target processing results, the candidate customer objects with business needs are determined as target customer objects; and the target demand content of the target customer objects is determined; according to the target demand content, the matching target business is determined from the preset candidate business set; a target task for offline promotion of the target business to the target customer object is created; and target prompt information corresponding to the target task is generated; and the target prompt information is sent to the corresponding business terminal. This can effectively assist business terminals to accurately and automatically discover the business needs of target customers and the target business suitable for the target customers; and automatically create corresponding target tasks in a timely manner, while providing relevant prompts to the corresponding business terminals in a timely manner, so that the business terminals can efficiently and accurately realize offline business promotion and obtain better promotion effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of this specification, the drawings required for use in the embodiments will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 It is a flowchart of a business data processing method provided by an embodiment of this specification;

[0055] Figure 2 It is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example;

[0056] Figure 3 It is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example;

[0057] Figure 4It is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example;

[0058] Figure 5 It is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example;

[0059] Figure 6 It is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example;

[0060] Figure 7 It is a schematic diagram of the structure of a server provided by an embodiment of this specification;

[0061] Figure 8 It is a schematic diagram of the structure of a business data processing device provided by an embodiment of this specification;

[0062] Fig. 9 It is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example. DETAILED DESCRIPTION

[0063] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0064] It should be noted that the user-related information and data involved in the embodiments of this specification are all information and data authorized by the user or fully authorized by relevant parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users or relevant parties to choose to authorize or refuse.

[0065] It should also be noted that in the embodiments of this specification, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0066] See also Figure 1As shown, the embodiment of this specification provides a method for processing business data. The method is specifically applied to the server side. When implemented specifically, the method may include the following contents:

[0067] S101: receiving and responding to a business promotion attention request, and determining candidate customer objects that need attention;

[0068] S102: According to a preset business processing rule, at every preset time period, first-category information data published by candidate customer objects, second-category information data published by the transaction service platform, and third-category information data published by a third party are obtained through multiple data sources;

[0069] S103: combining the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data;

[0070] S104: Processing the target joint information data using a preset business demand mining model to obtain a corresponding target processing result; wherein the preset business demand mining model is a model obtained by training based on a large language model;

[0071] S105: According to the target processing result, the candidate customer objects with business needs are determined as target customer objects; and the target demand content of the target customer objects is determined;

[0072] S106: According to the target demand content, determine matching candidate services from a preset candidate service set as target services for the target customer object;

[0073] S107: Creating a target task for offline promotion of a target business to target customers; and generating target prompt information corresponding to the target task;

[0074] S108: Sending the target prompt information to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer object offline.

[0075] The above-mentioned preset business demand mining model can be specifically understood as an algorithm model that is pre-trained using a large language model and can automatically analyze and mine the business needs of customer objects based on the information of multiple data sources of the input customer objects.

[0076] The above business needs may specifically include: direct business needs, and / or potential business needs. The above direct business needs may specifically be understood as business needs directly expressed by the customer object through information data. The above potential business needs may specifically be understood as business needs implicitly expressed by the customer object through one or more relevant information data, as well as business needs that do not exist in the current time period but are likely to exist in the near future time period.

[0077] The above-mentioned target customer objects can be specifically understood as customer objects that have business needs and are currently suitable for business promotion. The above-mentioned target business can be specifically understood as a product or service that matches the business needs of the target customer objects and is likely to be accepted by the target customer objects. Specifically, for example, the above-mentioned target business can be a financial product or a financial management service, etc. This specification does not limit the specific content and type of the target business.

[0078] Based on the above embodiments, the business terminal can be effectively assisted to automatically and accurately discover the business needs of the target customer objects, as well as the target business suitable for the target customer objects; and the corresponding target tasks can be automatically created in a timely manner, and the business terminal can be given relevant prompts, so that the business terminal can efficiently and accurately realize offline business promotion and obtain better promotion effects. At the same time, it also reduces the workload of business personnel.

[0079] In some embodiments, see Figure 2 As shown, the above-mentioned business data processing method can be specifically applied to the server side. Specifically, the server can specifically include a background server applied to the transaction service platform (for example, XX Bank) side, which can realize data transmission, data processing and other functions. Specifically, the server can be, for example, an electronic device with data calculation, storage and network interaction functions. Alternatively, the server can also be a software program running in the electronic device to provide support for data processing, storage and network interaction. In this embodiment, the number of the servers is not specifically limited. The server can specifically be one server, or several servers, or a server cluster formed by several servers.

[0080] In this embodiment, the business terminal may specifically include a front end applied to the business personnel side of the transaction service platform, which can realize functions such as data collection and data transmission. Specifically, the business terminal may be, for example, an electronic device such as a desktop computer, a tablet computer, a laptop computer, a smart phone, etc. Alternatively, the business terminal may also be a software application that can run on the above electronic devices.

[0081] In specific implementation, the business personnel can log in to the business promotion and attention configuration interface of the transaction service platform through the business terminal. In this interface, the business personnel can select the icon of the customer object that they are responsible for docking and need to pay attention to as the candidate customer object. Correspondingly, the business terminal can respond to the above operation, obtain the object identifier of the selected candidate customer object through the above promotion and attention configuration interface, generate a corresponding business promotion and attention request; and send the business promotion and attention request to the server. Among them, the above business promotion and attention request at least carries the object identifier of the candidate customer object.

[0082] Furthermore, the business personnel can also select the icon of the business they are responsible for as the candidate business in the business promotion attention configuration interface. Accordingly, the above business promotion attention request can also carry the business identifier of the candidate business.

[0083] In specific implementation, the server can respond to the business promotion attention request, determine the candidate customer object that needs to be paid attention to based on the object identifier of the candidate customer object; and further determine multiple data sources that need to be paid attention to for each candidate customer object; and then obtain multiple information data related to the candidate customer object through multiple data sources.

[0084] In some embodiments, the above-mentioned acquisition of the first type of information data published by the candidate customer objects through multiple data sources may include the following contents during specific implementation:

[0085] S1: query and determine the website, public account, and social account of the candidate customer object according to the object identifier of the candidate customer object;

[0086] S2: According to the website, public account, and social account of the candidate customer object, query the information data released by the candidate customer object in the current time period as the first category of information data.

[0087] The first type of information data can be understood as information data released by the candidate customer object. Specifically, the first type of information data can be: public account articles, promotional short videos, externally released plans, status messages, etc.

[0088] It should be noted that the first type of information data listed above is only a schematic illustration. In specific implementation, according to specific application scenarios and processing requirements, the first type of information data may also include information data of other types or contents. This specification does not limit this.

[0089] During specific implementation, the server can automatically track the update dynamics of multiple external media such as websites, public accounts, social accounts, etc. of candidate customer objects; and at every preset time period (for example, every 1 month, etc.), obtain the full amount of information data released by the first candidate customer object in the current time period as the above-mentioned first category of information data.

[0090] Based on the above embodiment, through multiple data sources, the full amount of information data released by the candidate customer objects can be obtained more comprehensively, so that the business needs of the candidate customer objects can be mined more accurately and comprehensively later.

[0091] In some embodiments, the above-mentioned acquisition of the second type of information data released by the transaction service platform through multiple data sources may include the following contents during specific implementation:

[0092] S1: Determine attribute information of the candidate customer object according to the object identifier of the candidate customer object;

[0093] S2: Filter out information data that matches the attribute information of the candidate customer object from the information data released in the current time period of the transaction service platform and the adjacent valid historical time period as the second type of information data.

[0094] The second type of information data can be understood as information data related to candidate customer objects released by the transaction service platform to which the server belongs. The effective historical time period can be the previous time period adjacent to the current time period, or the previous time period and the previous time period adjacent to the current time period.

[0095] The attribute information of the candidate customer object may specifically include static attribute information and / or dynamic attribute information of the candidate customer object.

[0096] In specific implementation, the server can obtain characteristic data of the candidate customer object such as object type, user tag, city, monthly income, etc. as the above-mentioned static attribute information based on the object identifier of the candidate customer object by querying the user database of the platform.

[0097] During specific implementation, the server can also query the platform's user historical business operation records based on the object identifier of the candidate customer object, and obtain the business operation records of the candidate customer object in the most recent historical time period (for example, the last six months); then, based on the business operation records in the most recent historical time period, perform big data analysis to determine the candidate customer object's relatively recent preferred business projects, promotion methods, operating habits and other characteristic data as the above-mentioned dynamic attribute information.

[0098] In specific implementation, the server first determines, based on the static attribute information and / or dynamic attribute information of the candidate customer object, from multiple external information release channels of the transaction service platform, an information release channel that can be reached by the candidate customer object as the target release channel; then, at each preset time period, the server searches the current time period (for example, the current month) and the previous time period adjacent to the current time period (for example, the previous month), for all information data released externally through the target information release channel by the transaction service platform, to find out information data that matches the attribute information of the candidate customer object as the second category of information data.

[0099] Based on the above embodiment, through multiple data sources, information data related to candidate customer objects and released by the transaction service platform can be obtained more comprehensively, so that the business needs of candidate customer objects can be mined more accurately and comprehensively later.

[0100] In some embodiments, see Figure 3 As shown, the third-category information data released by a third party obtained through multiple data sources may include the following contents when implemented specifically:

[0101] S1: Determine attribute information of the candidate customer object and object identifiers of objects associated with the candidate customer object according to the object identifier of the candidate customer object;

[0102] S2: Determine a third-party public platform related to the candidate customer object based on the attribute information of the candidate customer object; determine the website, public account, and social account of the associated object based on the object identifier of the associated object;

[0103] S3: Filter out first branch messages related to candidate customer objects from information data published in the current time period and the adjacent valid historical time period on the third-party public platform; filter out second branch messages related to candidate customer objects from information data published in the current time period on the websites, public accounts, and social accounts of the associated objects;

[0104] S4: Combine the first branch message and the second branch message to obtain corresponding third-category information data.

[0105] The third category of message data may be specifically understood as information data related to the candidate customer objects that is published third party except for the candidate customer objects and the transaction service platform.

[0106] The above-mentioned third parties may specifically include: associated objects that have an associated relationship with the candidate customer object (for example, friends, partners, parent companies, etc. of the candidate customer object) and third-party public platforms (for example, regulatory agencies, service agencies, news media, etc. related to the candidate customer object).

[0107] Correspondingly, the above-mentioned third category of information data may specifically include: first branch messages related to candidate customer objects published by associated objects (for example, text, video, audio, etc. related to candidate customer objects published by associated objects through websites, official accounts, and social accounts), and second branch messages related to candidate customer objects published by third-party public platforms (for example, news, notifications, announcements, reward lists, etc. related to candidate customer objects published by third-party public platforms).

[0108] Before specific implementation, the server can collect in advance the interaction data of each customer object based on the transaction service platform; then, based on the attribute information of each customer object and the interaction data, construct a knowledge graph of customer object relationships based on the transaction service platform.

[0109] In specific implementation, the server can determine the associated objects associated with the candidate customer object by querying the customer object relationship knowledge graph based on the object identifier of the candidate customer object. At the same time, the third-party public platform related to the candidate customer object can also be screened out from the public platforms that the transaction service platform has the authority to query and access based on the attribute information of the candidate customer object. Furthermore, the server can search the current time period and the previous time period adjacent to the current time period for the full amount of information data released by the associated object, as well as the full amount of information data released by the third-party public platform, at each preset time period, and screen out the information data that matches the attribute information of the candidate customer object as the first branch message and the second branch message. The first branch message and the second branch message are then combined to obtain the third type of information data.

[0110] Based on the above embodiment, through multiple data sources, information data published by a third party and related to candidate customer objects can be obtained more comprehensively, so that the business needs of candidate customer objects can be mined more accurately and comprehensively later.

[0111] In some embodiments, more comprehensive and rich target joint information data can be obtained by combining the first category information data, the second category information data, and the third category information data.

[0112] In the specific implementation, it is considered that the third type of information data is not directly released by the candidate customer object, and the actual relevance to the candidate customer object is relatively uncertain, and on the other hand, it is not the data released by the transaction service platform itself, and the reliability of the information data is relatively uncertain. Based on the above considerations, in order to use the information data of different data sources more accurately in the future, when combining the first type of information data, the second type of information data, and the third type of information data, weight labels for the first type of information data, the second type of information data, and the third type of information data can be set respectively, and the corresponding weight coefficients are set in the weight labels; and the first type of information data, the second type of information data, and the third type of information data carrying the weight labels are spliced ​​according to the specified rules to obtain the corresponding target joint information data. Among them, the above weight labels can be determined based on historical data through big data analysis. Specifically, the weight coefficient of the first type of information data is usually greater than the weight coefficient of the second type of information data, and the weight coefficient of the second type of information data is usually greater than the weight coefficient of the third type of information data.

[0113] Furthermore, for the third type of information data, corresponding sub-weight coefficients can be set for the information data provided by the corresponding data source according to the degree of intimacy between the data source of each information data and the candidate customer object, as well as the credit value of the data source itself. Among them, the weight coefficient of the information data obtained by the data source with a higher degree of intimacy with the candidate customer object and a higher credit value is relatively larger.

[0114] In specific implementation, after obtaining the target joint information data, the target joint information data may be preprocessed. Specifically, it may be first detected whether the content of the information data in the target joint information data is empty or invalid data, and the empty information data and invalid information data may be deleted.

[0115] Furthermore, the data type of the information data in the target joint information data can be determined; wherein the data type includes text data (for example, public account articles, news, etc.), video data (for example, promotional short videos, etc.), audio data (for example, voice call clips, etc.), picture data (for example, promotional pictures, etc.), etc.

[0116] According to the data type, the target joint information data is split into a first information data group (corresponding to text data), a second information data group (corresponding to video data), a third information data group (corresponding to audio data), and a fourth information data group (corresponding to picture data).

[0117] For the second information data set, the pre-trained video analysis model is used to perform video content recognition and extraction, and the corresponding content text is combined as the processed second information data set. For the third information data set, the pre-trained speech recognition model is used to perform speech recognition and sorting, and the corresponding content text is combined as the processed third information data set. For the fourth information data set, the pre-trained OCR recognition model is used to perform text character recognition and extraction, and the corresponding content text is combined as the processed fourth information data.

[0118] The first information data group, the processed second information data group, the processed third information data group, and the processed fourth information data group are combined to obtain pre-processed target joint information data.

[0119] In specific implementation, the above-mentioned pre-processed target joint information data can be stored in a corresponding text library for subsequent retrieval and use by a preset business demand mining model.

[0120] In some embodiments, during specific implementation, the above target joint information data (or pre-processed target joint information data) can be input into a preset business demand mining model to analyze and mine the business demand of the candidate customer object. Accordingly, the preset business demand mining model will output multiple possible business demand prediction contents and corresponding probability values ​​as the target processing result based on the input target joint information data through analysis and mining.

[0121] During specific implementation, the server may also combine the above target joint information data with the attribute information of the candidate customer object, and then input them together into a preset business demand mining model to obtain a more accurate target processing result.

[0122] Among them, the above-mentioned preset business demand mining model can specifically be to pre-train a large language model using a large amount of sample data; and adjust the model parameters in a targeted manner according to the output results of the model during training; at the same time, adjust the sample data according to the output results; and then use the adjusted sample data to continue model training on the adjusted model until a preset business demand mining model that meets the requirements is obtained.

[0123] In some embodiments, during specific implementation, the server may first detect whether there is at least one business demand prediction content with a probability value greater than a preset probability threshold according to the target processing result; when it is determined that there is at least one business demand prediction content with a probability value greater than the preset probability threshold, it may be determined that the candidate customer object currently has a business demand; and the candidate customer object may be marked as a target customer object. Further, the business demand prediction content with the largest probability value may be screened out from the multiple business demand prediction contents in the target processing result as the target demand content of the target customer object.

[0124] On the contrary, when it is determined that the probability value of the absence of any business demand forecast content is greater than the preset probability threshold, it can be determined that the candidate customer object currently has no business demand; at this time, prompt information can be generated that the candidate customer object does not need to promote business temporarily.

[0125] In specific implementation, when it is determined that there is at least one business demand forecast content with a probability value greater than a preset probability threshold, and there are multiple business demand forecast contents with the largest probability values ​​in the target processing result, the multiple business demand forecast contents with the largest probability values ​​can be determined as candidate forecast contents. Then, the third category of information data is eliminated from the target joint information data to obtain the target joint information data after elimination; and the preset business demand mining model is used to process the target joint information data after elimination to obtain the corresponding processing result as the auxiliary reference result. From multiple candidate forecast contents, a candidate forecast content that relatively matches the auxiliary reference result is screened out as the target demand content.

[0126] In some embodiments, during specific implementation, the candidate businesses that match the attribute information of the target customer object and have not yet been handled by the target customer object can be screened out from a large number of candidate businesses based on the attribute information of the target customer object and the business handling records of the target customer object; and the above candidate businesses can be combined to construct a preset candidate business set for the target customer object.

[0127] Furthermore, the server can obtain the business introduction texts of the candidate businesses in the preset candidate business set; then based on the corresponding mapping rules, map each candidate business introduction text and target demand content into a corresponding business feature vector and demand feature vector respectively; use each business feature vector and the demand feature vector to calculate the matching degree of the target demand content of each candidate business domain; based on the matching degree, select the candidate business with the highest matching degree from multiple candidate businesses as the target business for the target customer object.

[0128] In some embodiments, the server can automatically create a target task for offline promotion of the target business to the target customer object on the transaction service platform, and send the target task to the management personnel for review. After the management personnel review and determine to execute the target task, the server can further generate target prompt information corresponding to the target task; at the same time, determine the business terminal that matches the target task (for example, the business terminal that is responsible for the target customer object); and then send the target prompt information to the business terminal.

[0129] Accordingly, the business terminal can display the target prompt information to the business personnel. The business personnel can visit the target customer object offline according to the target prompt information, and carry out specific target business promotion for the target customer object.

[0130] In addition, when the manager passes the review, he can also send an assignment instruction about the target task to the server; wherein the assignment instruction can carry the terminal identification of the business terminal assigned by the manager. Accordingly, the server can respond to the assignment instruction and send the target prompt information to the corresponding business terminal.

[0131] In some embodiments, after determining a candidate customer object with business needs as a target customer object according to the target processing result, referring to Figure 4 As shown, when the method is implemented specifically, it may also include the following contents:

[0132] S1: Determine the target demand content of the target customer object based on the target processing results;

[0133] S2: According to the target demand content, select key information data from the first category of information data, the second category of information data, and the third category of information data;

[0134] S3: Process the key information data using a preset semantic extraction model to obtain a key information summary and key content text of the key information data.

[0135] Accordingly, after sending the target prompt information to the corresponding service terminal, the method may further include:

[0136] The key information summary, key content text, and link address of the key information data are delivered to the business terminal.

[0137] In specific implementation, information data with a relatively large correlation with the target demand content (for example, ranked high based on correlation) can be screened out from the first category of information data, the second category of information data, and the third category of information data as key information data. Then, the preset semantic extraction model is used to process the above key information data to obtain the corresponding key information summary and key content text. Furthermore, only the key information summary, key content text, and key information data can be uploaded to the information database of the transaction service platform (for example, Message Square); and the key information summary, key content text, and key information data based on the link address of the information database can be obtained.

[0138] Accordingly, the link address can be added to the target prompt information, and then the target prompt information is sent to the service terminal. The service terminal can display the corresponding link address simultaneously while displaying the target prompt information.

[0139] Before preparing to conduct offline business promotion to target customers, business personnel can click on the corresponding link address to enter the information database, browse and refer to the above-mentioned key information summary, key content text, and the specific content of the key information data, so that they can formulate corresponding promotion strategies in advance, and then conduct offline promotion of the target business to target customers based on the promotion strategy, so as to obtain relatively better promotion effects.

[0140] Furthermore, the server can also construct a user portrait of the target customer object based on the attribute information of the target customer object; then use the user portrait of the target customer object, the target demand content, the introduction text of the target business, and the relevant key information summary and key content text to automatically generate a matching promotion strategy through the corresponding strategy decision model; and provide the promotion strategy to the business terminal so that the business terminal can use the above promotion strategy as a reference to better realize offline business promotion for the target customer object.

[0141] In some embodiments, after the target prompt information is sent to the corresponding service terminal, refer to Figure 5 As shown, when the method is implemented specifically, it may also include the following contents:

[0142] S1: receiving target promotion records of offline target business promotion to target customers and target promotion results uploaded by the business terminal;

[0143] S2: Verify the target promotion results according to the target promotion records to obtain the corresponding target verification results;

[0144] S3: Based on the target verification result, when it is determined that the verification has passed, the quality of the offline business promotion of the business terminal for the target customer object is evaluated according to the target promotion record and the target promotion result to obtain the corresponding target evaluation result.

[0145] During specific implementation, after completing offline promotion of the target business to the target customer object, the business personnel can use the business terminal to upload the target promotion record of offline promotion of the target business to the target customer object, as well as the target promotion results.

[0146] The target promotion record may be data in text form or audio form. The target promotion result may be one of promotion success, promotion failure, and result pending.

[0147] During specific implementation, the server can verify the target promotion results based on the target promotion records by cross-validating the target promotion records with the target promotion results.

[0148] If the target promotion records and target promotion results match each other and can be verified with each other, it can be determined that the received target promotion records and target promotion results are accurate and valid, and then it can be determined that the verification has passed and subsequent quality evaluation can be carried out.

[0149] On the contrary, if the target promotion record and the target promotion result do not match or even contradict each other, it can be determined that at least one of the received target promotion record and the target promotion result is wrong, and then it is determined that the verification has failed. At this time, an error message about retransmitting the target promotion record and the target promotion result can be sent to the service terminal.

[0150] In specific implementation, the server can process the target promotion records and target promotion results according to the preset evaluation rules to evaluate the quality of the offline business promotion behavior of the business terminal for the target customer object and obtain the corresponding target evaluation results. Among them, the preset evaluation rules are determined in advance by clustering the sample promotion records and sample promotion results of the business terminals that meet the requirements and specifications in a large number of different business scenarios.

[0151] Furthermore, matching reward data may be determined based on the target evaluation results, and then the reward data may be distributed to the service terminal.

[0152] In addition, based on the target evaluation results, business terminals with problems in business promotion quality (or not meeting the preset requirements) are identified; and quality prompt information is sent to such business terminals to guide the business terminals to subsequently adjust their business promotion methods and strategies in a targeted manner.

[0153] Based on the above embodiments, the quality evaluation of the offline business promotion behavior of the business terminal for the target customer objects can be automatically and accurately achieved.

[0154] Specifically, when the business terminal obtains the above-mentioned target promotion results, it can also first use the identity private key it holds to encrypt the target promotion results to obtain the ciphertext data of the target promotion results; then add the terminal identification based on the business terminal to the ciphertext data of the target promotion results to generate the identity certificate; at the same time, it will also use the identity private key to encrypt the target promotion record to obtain the ciphertext data of the target promotion record. Then, the ciphertext data of the target promotion results carrying the identity certificate and the ciphertext data of the target promotion record are uploaded to the server together.

[0155] Correspondingly, the server can first detect whether the target promotion result carries an identity credential; and verify the identity credential; when it is determined that the identity credential is true, determine the matching identity public key based on the identity credential; and then use the identity public key to decrypt the ciphertext data of the target promotion result and the ciphertext data of the target promotion record respectively, to obtain the corresponding target promotion record and target promotion result in plain text.

[0156] In some embodiments, after obtaining the corresponding target evaluation result, refer to Figure 6 As shown, when the method is implemented specifically, it may also include the following contents:

[0157] S1: When it is determined based on the target evaluation result that the offline business promotion of the business terminal for the target customer object does not meet the preset requirements and the target promotion result is a promotion failure, detect whether the target customer object and the target business meet the re-promotion conditions;

[0158] S2: When it is determined that the target customer object and the target business meet the re-promotion conditions, a re-promotion task is created to re-promote the target business to the target customer object offline; and attribute information of the business terminal and the target customer object is obtained;

[0159] S3: using a preset promotion strategy generation model to process target promotion records, attribute information of the business terminal, and attribute information of the target customer object, to determine an improved promotion strategy;

[0160] S4: Sending re-promotion prompt information to the service terminal; wherein the re-promotion prompt information at least carries an improved promotion strategy.

[0161] The above-mentioned non-compliance with preset requirements can be specifically understood as the number of behavioral operations that do not comply with preset evaluation rules occurring during offline business promotion for target customers by the business terminal is greater than a preset number threshold (for example, 5 times).

[0162] During specific implementation, it is possible to detect whether the target customer object is an important customer based on its attribute information; at the same time, based on the relevant information of the target business, it is possible to detect whether the target business is a key business of the transaction service platform; when it is determined that the target customer object is an important customer and the target business is a key business, it is determined that the target customer object and the target business meet the re-promotion conditions.

[0163] Furthermore, a pre-trained preset promotion strategy generation model can be used to jointly process the above target promotion records, the attribute information of the service terminal, and the attribute information of the target customer object to generate an improved re-promotion strategy for the target promotion record. The improved re-promotion strategy is then sent to the service terminal via re-promotion prompt information.

[0164] Correspondingly, the business terminal can respond to the re-promotion prompt information, and according to the improved re-promotion strategy, specifically correct and adjust the behavioral operations that did not comply with the preset evaluation rules when conducting offline promotion to the target customer object; and visit the target customer object again, and conduct offline promotion of the target business again to obtain relatively better promotion effects.

[0165] Based on the above embodiments, the loss of important customers can be effectively avoided, and the promotion success rate of key services to important customers can be improved; at the same time, it is also helpful to improve the relevant business capabilities of the business terminal.

[0166] As can be seen from the above, the business data processing method provided by the embodiment of this specification can be pre-trained with a large language model before implementation to obtain a preset business demand mining model that can automatically analyze and mine the business needs of customer objects based on the information data of customer objects from multiple data sources input. During specific implementation, the server can obtain the first type of information data associated with the candidate customer objects that need to be concerned, as well as the second type of information data released by the transaction service platform and the third type of information data released by a third party through multiple data sources at intervals of a preset time period according to the preset business processing rules; and combine the information data of the above multiple data sources to obtain the target joint information data; and then use the preset business demand mining model to process the target joint information data to obtain the corresponding target processing results; according to the target processing results, the candidate customer objects with business needs are determined as target customer objects; and the target demand content of the target customer objects is determined; according to the target demand content, the matching target business is determined from the preset candidate business set; a target task for offline promotion of the target business to the target customer object is created; and a target prompt information corresponding to the target task is generated; and the target prompt information is sent to the corresponding business terminal. This can effectively assist business terminals to accurately and automatically discover the business needs of target customers and the target business suitable for the target customers; and automatically create corresponding target tasks in a timely manner, and provide relevant prompts to the business terminal, so that the business terminal can efficiently and accurately realize offline business promotion and obtain better promotion results.

[0167] This specification embodiment provides a server, referring to Figure 7 The server includes a network communication port 701, a processor 702 and a memory 703, and the above structures are connected through internal cables so that each structure can perform specific data interaction.

[0168] The network communication port 701 may be used to receive a business promotion attention request.

[0169] The processor 702 can be specifically used to respond to a business promotion attention request and determine a candidate customer object that needs attention; according to a preset business processing rule, at each preset time period, obtain the first type of information data released by the candidate customer object, the second type of information data released by the transaction service platform, and the third type of information data released by a third party through multiple data sources; combine the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data; use a preset business demand mining model to process the target joint information data to obtain a corresponding target processing result; wherein the preset business demand mining model is a model obtained by training based on a large language model; according to the target processing result, determine the candidate customer object with business needs as the target customer object; and determine the target demand content of the target customer object; according to the target demand content, determine a matching candidate business from a preset candidate business set as a target business for the target customer object; create a target task for offline promotion of the target business to the target customer object; and generate target prompt information corresponding to the target task; send the target prompt information to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information and promotes the target business to the target customer object offline.

[0170] The memory 703 may be specifically used to store corresponding instruction programs, as well as target joint information data, target demand content and other related data.

[0171] Based on the above method, the relevant structural performance of the server can be effectively utilized, the data processing speed of the electronic device can be improved, and business data processing can be realized efficiently.

[0172] In this embodiment, the network communication port 701 can be a virtual port that is bound to different communication protocols so that different data can be sent or received. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. In addition, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM, CDMA, etc.; it can also be a Wifi chip; it can also be a Bluetooth chip.

[0173] In this embodiment, the processor 702 may be implemented in any appropriate manner. For example, the processor may take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) executable by the (micro)processor, a logic gate, a switch, an application specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, etc. This specification does not limit this.

[0174] In this embodiment, the memory 703 may include multiple levels. In a digital system, anything that can store binary data can be a memory; in an integrated circuit, a circuit with a storage function that has no physical form is also called a memory, such as RAM, FIFO, etc.; in a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0175] The embodiment of the present specification also provides a computer-readable storage medium based on the above-mentioned business data processing method, wherein the computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed, the following are achieved: receiving and responding to a business promotion attention request, and determining a candidate customer object that needs attention; according to a preset business processing rule, at each preset time period, obtaining first-category information data published by the candidate customer object, as well as second-category information data published by the transaction service platform and third-category information data published by a third party through multiple data sources; combining the first-category information data, the second-category information data, and the third-category information data to obtain target joint information data; and using a preset business demand mining model to process the target joint information data. According to the target processing result, the corresponding target processing result is obtained; wherein the preset business demand mining model is a model obtained by training based on the large language model; according to the target processing result, the candidate customer objects with business needs are determined as target customer objects; and the target demand content of the target customer objects is determined; according to the target demand content, matching candidate businesses are determined from the preset candidate business set as the target business for the target customer objects; a target task for offline promotion of the target business to the target customer objects is created; and target prompt information corresponding to the target task is generated; the target prompt information is sent to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer objects offline.

[0176] In this embodiment, the storage medium includes, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a cache, a hard disk (HDD), or a memory card. The memory may be used to store computer program instructions. The network communication unit may be an interface for network connection communication set in accordance with the standard specified by the communication protocol.

[0177] In this embodiment, the functions and effects specifically implemented by the program instructions stored in the computer-readable storage medium can be explained in comparison with other implementations and will not be described in detail here.

[0178] The embodiment of the present specification also provides a computer program product, which at least includes a computer program, and when the computer program is executed by a processor, the following method steps are implemented: receiving and responding to a business promotion attention request, and determining a candidate customer object that needs attention; according to a preset business processing rule, at each preset time period, obtaining a first type of information data released by the candidate customer object, as well as a second type of information data released by the transaction service platform and a third type of information data released by a third party through multiple data sources; combining the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data; using a preset business demand mining model to process the target joint information data, and obtaining a corresponding target processing processing results; wherein the preset business demand mining model is a model obtained by training based on the large language model; according to the target processing results, the candidate customer objects with business needs are determined as target customer objects; and the target demand content of the target customer objects is determined; according to the target demand content, matching candidate businesses are determined from the preset candidate business set as the target business for the target customer objects; a target task for offline promotion of the target business to the target customer objects is created; and target prompt information corresponding to the target task is generated; the target prompt information is sent to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer objects offline.

[0179] See also Figure 8 As shown, the embodiment of this specification also provides a business data processing device, which may specifically include the following structural modules:

[0180] The receiving module 801 may be specifically configured to receive and respond to a business promotion attention request and determine a candidate customer object that needs attention;

[0181] The acquisition module 802 may be specifically configured to acquire the first type of information data published by the candidate customer object, the second type of information data published by the transaction service platform, and the third type of information data published by a third party through multiple data sources at each preset time interval according to a preset business processing rule;

[0182] The combining module 803 may be specifically used to combine the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data;

[0183] The processing module 804 may be specifically used to process the target joint information data using a preset business demand mining model to obtain a corresponding target processing result; wherein the preset business demand mining model is a model obtained by training based on a large language model;

[0184] The first determination module 805 may be specifically used to determine the candidate customer objects with business needs as target customer objects according to the target processing result; and determine the target demand content of the target customer objects;

[0185] The second determination module 806 may be specifically configured to determine matching candidate services from a preset candidate service set according to target demand content as target services for target customers;

[0186] The creation module 807 may be specifically used to create a target task for offline promotion of a target business to a target customer object; and generate target prompt information corresponding to the target task;

[0187] The sending module 808 may be specifically used to send the target prompt information to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer object offline.

[0188] In some embodiments, when the above-mentioned acquisition module 802 is implemented, the first category of information data released by the candidate customer object can be obtained through multiple data sources in the following manner: based on the object identifier of the candidate customer object, query and determine the website, official account, and social account of the candidate customer object; based on the website, official account, and social account of the candidate customer object, query the information data released by the candidate customer object in the current time period as the first category of information data.

[0189] In some embodiments, when the above-mentioned acquisition module 802 is implemented, the second category of information data released by the transaction service platform can be obtained through multiple data sources in the following manner: based on the object identifier of the candidate customer object, the attribute information of the candidate customer object is determined; from the information data released in the current time period of the transaction service platform and the adjacent valid historical time period, the information data that matches the attribute information of the candidate customer object is filtered out as the second category of information data.

[0190] In some embodiments, when the above-mentioned acquisition module 802 is implemented, the third-category information data published by a third party can be obtained through multiple data sources in the following manner: according to the object identifier of the candidate customer object, determine the attribute information of the candidate customer object and the object identifier of the associated object of the candidate customer object; according to the attribute information of the candidate customer object, determine the third-party public platform related to the candidate customer object; according to the object identifier of the associated object, determine the website, official account, and social account of the associated object; filter out the first branch message related to the candidate customer object from the information data published in the current time period of the third-party public platform and the adjacent valid historical time period; filter out the second branch message related to the candidate customer object from the information data published in the current time period on the website, official account, and social account of the associated object; combine the first branch message and the second branch message to obtain the corresponding third-category information data.

[0191] In some embodiments, after candidate customer objects with business needs are determined as target customer objects based on the target processing results, the device, when implemented specifically, can also be used to: determine the target demand content of the target customer object based on the target processing results; filter out key information data from the first category of information data, the second category of information data, and the third category of information data based on the target demand content; and process the key information data using a preset semantic extraction model to obtain a key information summary and key content text of the key information data.

[0192] Correspondingly, after sending the target prompt information to the corresponding business terminal, the device, when implemented, can also be used to: reach the key information summary, key content text, and link address of the key information data to the business terminal.

[0193] In some embodiments, after the target prompt information is sent to the corresponding business terminal, when the device is specifically implemented, it can also be used to: receive the target promotion records of offline target business promotion to target customer objects uploaded by the business terminal, and the target promotion results; verify the target promotion results according to the target promotion records to obtain corresponding target verification results; based on the target verification results, when it is determined that the verification has passed, perform a quality evaluation on the offline business promotion of the business terminal for the target customer objects based on the target promotion records and the target promotion results to obtain corresponding target evaluation results.

[0194] In some embodiments, after obtaining the corresponding target evaluation result, when the device is specifically implemented, it can also be used to: when it is determined based on the target evaluation result that the offline business promotion of the business terminal for the target customer object does not meet the preset requirements and the target promotion result is a promotion failure, detect whether the target customer object and the target business meet the re-promotion conditions; when it is determined that the target customer object and the target business meet the re-promotion conditions, create a re-promotion task for offline re-promoting the target business to the target customer object; and obtain the attribute information of the business terminal and the attribute information of the target customer object; use the preset promotion strategy generation model to process the target promotion record, the attribute information of the business terminal, and the attribute information of the target customer object to determine an improved promotion strategy; send re-promotion prompt information to the business terminal; wherein the re-promotion prompt information carries at least the improved promotion strategy.

[0195] It should be noted that the units, devices or modules described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. For the convenience of description, the above devices are described separately by functions divided into various modules. Of course, when implementing this specification, the functions of each module can be implemented in the same or more software and / or hardware, or the modules that implement the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0196] It can be seen from the above that the business data processing device provided based on the embodiment of this specification can effectively assist the business terminal to accurately and automatically discover the business needs of the target customer object, as well as the target business suitable for the target customer object; and automatically create corresponding target tasks in a timely manner, and provide relevant prompts to the business terminal, so that the business terminal can efficiently and accurately realize offline business promotion and obtain better promotion effects.

[0197] In a specific scenario example, during specific implementation, the business data processing method provided in this specification can be used to implement a bank's news opportunity (e.g., business demand) analysis and customer visits (e.g., customer business promotion) based on a financial big model (e.g., a preset business demand mining model). The specific implementation process can be found in the following content.

[0198] In this scenario example, consider that the full-process AI analysis of the account manager (e.g., business personnel) from business opportunity identification (e.g., exploring business needs), business opportunity analysis to customer visits and post-visit summaries can be implemented by combining the financial big model.

[0199] In this scenario example, see Fig. 9 As shown, the big model can be used to analyze news in a specified direction (for example, third-category information data), and then the financial big model can be called to generate a news summary and business opportunity objects (for example, customer objects) in the news according to the content of the news, and list business opportunity information (for example, business demand content), and then the small model can be combined to perform similarity matching of customer names within the bank, and query business information such as the customer survey report of the customer.

[0200] At the same time, based on the business opportunity objects and business opportunity information generated in the previous step, the administrator can publish business opportunity visit tasks through the business opportunity analysis system in a targeted manner, and the account manager can check the relevant information of the customer through the business opportunity analysis system to prepare better marketing strategies.

[0201] After the visit is completed, the account manager can also describe the visit process (for example, target promotion records) by voice. The system generates the visit content through voice recognition and generates and analyzes the visit record by calling the financial big model. The system also regularly performs AI scoring on the account manager's customer visit content to evaluate the quality of customer visits, so that administrators can systematically assign and manage customer visit tasks to improve efficiency.

[0202] For specific implementation, see Fig. 9 As shown in the figure, after obtaining possible news business opportunity data, the system will regularly store the news and use AI skills to analyze the news for users to browse. At the same time, the business opportunity system can be linked to other management applications to ensure the availability and efficiency of the branch business opportunity visit process.

[0203] For news business opportunity acquisition, news business opportunity analysis and visits, the main data source is the business opportunity news provided by the business department. After the user maintains the news hotspot, the corresponding latest business opportunity news content is saved to the system, and the text content of the article is regularly entered into the database for subsequent system calls and user browsing. Later, the data source can be expanded according to specific business needs. For example, regular article content acquisition from specific websites, searching for existing hot content and keywords through the public interface of commonly used search engines, and obtaining the latest relevant article content.

[0204] News business opportunity analysis is mainly divided into four parts: data maintenance, news square, projects, and enterprise analysis.

[0205] 1) Data maintenance

[0206] On the data maintenance page, users can maintain business opportunity news by themselves. At the same time, users can maintain their own projects and corporate clients in the industry for data analysis by the AI ​​system.

[0207] 2) News Plaza

[0208] Users can view the content of news and business opportunity articles on the News Square page. The business opportunity system calls the big model scheduling platform skills to realize the summary generation of business opportunity news, news description object detection, business opportunity exploration and other functions. Compared with manually browsing business opportunity news to obtain business opportunities, the business opportunity system reduces the amount of reading required for users to obtain business opportunities. Users can quickly obtain business opportunity content by reading summaries and business opportunity exploration information. Users can add and maintain news description objects by themselves, and view the specific content involved in the news description objects in the news.

[0209] Users can click on the news description object, and the system will perform similarity matching based on the news description object, automatically find the corresponding customers in the industry, and display the customer's detailed information in the customer system for users to provide reference.

[0210] At the same time, on the News Square page, the business opportunity system has been linked with the customer visit system and the customer express system. The business opportunity visit administrator can click on the news description object to initiate the customer express business opportunity push of the news description object, publish the visit task and assign it to the customer's maintenance account manager.

[0211] 3) Project / Enterprise Analysis

[0212] Based on the projects / enterprises maintained by the user on the data maintenance page, the system generates a timeline of business opportunity events for the projects / enterprises that the user is following on the project / enterprise analysis page. The user can browse all business opportunity news and related summaries on the timeline as well as historical business opportunity exploration information generated by the AI ​​big model.

[0213] At the same time, users can perform AI summary and analysis on the projects / enterprises they are concerned about under a customized time dimension. Users can view the AI ​​big model under the selected time dimension, including a brief summary of news events within the project / enterprise's cycle, the project / enterprise's funding needs within the cycle, the possible areas of in-depth cooperation between the project / enterprise and the bank, and relevant suggestions for the account manager on the project / enterprise.

[0214] 4) Release of visit tasks

[0215] Users can initiate business opportunity visits to the objects described in the news through the business opportunity system, and push the business opportunity visit tasks to the account managers of the in-bank customers corresponding to the objects.

[0216] After the business opportunity visit task is completed, the visiting account manager can input the progress and results of the visit through voice. The system generates text content in real time based on the input voice, and uses the platform's big model to generate the visit purpose, customer needs, customer business conditions, customer cooperation intentions, bank interbank strategies, and other visit contents of this customer visit task. At the same time, the system performs AI scoring based on the content of this visit for managers to refer to and manage uniformly.

[0217] Through the above scenario examples, it is verified that the business data processing method provided in this manual can better realize business opportunity acquisition, especially for existing customers and potential customers, with higher search condition accuracy and higher crawling efficiency; use AI big models to generate industry-specific analysis and reports: combine existing customer data and financial products to conduct characteristic analysis of customers and generate industry-specific reports; it can also be analyzed through internal self-adjusting big models, combined with special visit tasks, in line with the platform visit needs.

[0218] Although the present specification provides method operation steps as described in the embodiments or flow charts, more or less operation steps may be included based on conventional or non-creative means. The order of steps listed in the embodiments is only one way of executing the order of many steps, and does not represent a unique execution order. When the device or client product in practice is executed, it can be executed in sequence or in parallel according to the method shown in the embodiments or the drawings (for example, a parallel processor or a multi-threaded processing environment, or even a distributed data processing environment). The term "include", "include" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, product or device including a series of elements includes not only those elements, but also includes other elements that are not explicitly listed, or also includes elements inherent to such a process, method, product or device. In the absence of more restrictions, it is not excluded that there are other identical or equivalent elements in the process, method, product or device including the elements. The first, second, etc. words are used to represent the name, and do not represent any particular order.

[0219] Those skilled in the art also know that, in addition to implementing the controller in a purely computer-readable program code, the controller can be made to implement the same function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, such a controller can be considered as a hardware component, and the devices for implementing various functions included therein can also be considered as structures within the hardware component. Or even, the devices for implementing various functions can be considered as both software modules for implementing the method and structures within the hardware component.

[0220] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer-readable storage media including storage devices.

[0221] Through the description of the above embodiments, it can be known that those skilled in the art can clearly understand that the present specification can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present specification can essentially be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a mobile terminal, a server, or a network device, etc.) to execute the methods described in each embodiment of the present specification or some parts of the embodiments.

[0222] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. This specification can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.

[0223] Although the present specification is described through embodiments, those skilled in the art will appreciate that there are many modifications and changes to the present specification without departing from the spirit of the present specification, and it is intended that the appended claims include these modifications and changes without departing from the spirit of the present specification.

Claims

1. A business data processing method, characterized in that: Servers used in the trading service platform include: Receive and respond to business promotion attention requests and identify candidate customers who need attention; According to the preset business processing rules, at each preset time period, the first type of information data released by the candidate customer objects, the second type of information data released by the transaction service platform, and the third type of information data released by the third party are obtained through multiple data sources; combining the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data; Using a preset business demand mining model to process the target joint information data, and obtaining a corresponding target processing result; wherein the preset business demand mining model is a model obtained by training based on a large language model; According to the target processing results, candidate customers with business needs are identified as target customers, and the target needs of the target customers are determined; According to the target demand content, matching candidate businesses are determined from the preset candidate business set as target businesses for target customers; Create a target task for offline promotion of the target business to the target customer object; and generate target prompt information corresponding to the target task; The target prompt information is sent to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer object offline.

2. The method according to claim 1, characterized in that The first type of information data published by the candidate customer objects is obtained through multiple data sources, including: According to the object identifier of the candidate customer object, query and determine the website, public account, and social account of the candidate customer object; According to the website, public account, and social account of the candidate customer object, the information data released by the candidate customer object in the current time period is queried as the first category of information data.

3. The method according to claim 1, characterized in that The second type of information data released by the transaction service platform is obtained through multiple data sources, including: Determining attribute information of the candidate customer object according to the object identifier of the candidate customer object; Information data that matches the attribute information of the candidate customer object is screened out from the information data released in the current time period of the transaction service platform and the adjacent valid historical time period as the second category of information data.

4. The method according to claim 1, characterized in that: Obtain third-party information data published by third parties through multiple data sources, including: Determine attribute information of the candidate customer object and object identifiers of associated objects of the candidate customer object according to the object identifier of the candidate customer object; According to the attribute information of the candidate customer object, determine the third-party public platform related to the candidate customer object; according to the object identifier of the associated object, determine the website, public account, and social account of the associated object; Filter out first branch messages related to candidate customer objects from information data published in the current time period and the adjacent valid historical time period on the third-party public platform; filter out second branch messages related to candidate customer objects from information data published in the current time period on the websites, public accounts, and social accounts of the associated objects; The first branch message and the second branch message are combined to obtain corresponding third category information data.

5. The method according to claim 1, characterized in that After determining the candidate customer objects with business needs as target customer objects according to the target processing result, the method further includes: According to the target processing results, determine the target demand content of the target customer object; According to the target demand content, key information data is screened out from the first category of information data, the second category of information data, and the third category of information data; Processing the key information data using a preset semantic extraction model to obtain a key information summary and key content text of the key information data; Accordingly, the method further includes: The key information summary, key content text, and link address of the key information data are delivered to the business terminal.

6. The method according to claim 1, characterized in that After sending the target prompt information to the corresponding service terminal, the method further includes: Receive target promotion records uploaded by business terminals for offline promotion of target services to target customers, as well as target promotion results; According to the target promotion records, the target promotion results are verified to obtain the corresponding target verification results; According to the target verification results, when it is determined that the verification has passed, the quality of the offline business promotion of the business terminal for the target customer objects is evaluated according to the target promotion records and target promotion results to obtain the corresponding target evaluation results.

7. The method according to claim 6, characterized in that After obtaining the corresponding target evaluation result, the method further includes: If, according to the target evaluation results, it is determined that the offline business promotion of the business terminal for the target customer object does not meet the preset requirements, and the target promotion result is a promotion failure, detect whether the target customer object and the target business meet the re-promotion conditions; When it is determined that the target customer object and the target business meet the re-promotion conditions, a re-promotion task is created to re-promote the target business to the target customer object offline; and attribute information of the business terminal and the target customer object is obtained; Using the preset promotion strategy generation model to process the target promotion records, the attribute information of the business terminal, and the attribute information of the target customer object, an improved promotion strategy is determined; Sending re-promotion prompt information to the service terminal; wherein the re-promotion prompt information at least carries an improved promotion strategy.

8. A business data processing device, characterized in that: Servers used in the trading service platform include: A receiving module is used to receive and respond to business promotion attention requests and determine candidate customer objects that need attention; The acquisition module is used to acquire the first type of information data published by the candidate customer objects, the second type of information data published by the transaction service platform, and the third type of information data published by the third party through multiple data sources at each preset time interval according to the preset business processing rules; A combining module, used for combining the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data; A processing module, used to process the target joint information data using a preset business demand mining model to obtain a corresponding target processing result; wherein the preset business demand mining model is a model obtained by training based on a large language model; The first determination module is used to determine the candidate customer objects with business needs as target customer objects according to the target processing result; and determine the target demand content of the target customer objects; The second determination module is used to determine matching candidate services from a preset candidate service set according to target demand content as target services for target customers; A creation module is used to create a target task for offline promotion of a target business to a target customer object; and generate target prompt information corresponding to the target task; The sending module is used to send the target prompt information to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information and promotes the target business to the target customer object offline.

9. A server, characterized in that: The method comprises a processor and a memory for storing processor-executable instructions, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the instructions.

10. A computer-readable storage medium, characterized in that: Computer instructions are stored thereon, and when the instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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