Data processing method and device based on business and financial data conversion

Abstract

The invention relates to the technical field of data processing, and discloses a data processing method and device based on business and financial data conversion, and the method comprises the steps: obtaining intermediate data corresponding to first data of a plurality of business systems; determining second data based on the intermediate data and a preset business and financial data conversion rule; and based on the intermediate data and the second data, determining a risk value of a risk assessment object associated with the target business. According to the technical scheme, the business data of different formats in the multiple business systems are automatically converted into the effective financial data, the management cost of business and financial conversion is reduced, meanwhile, the financial data and the business data are jointly used as the basis of risk evaluation, and the reliability of the risk evaluation result is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a data processing method and device based on business and financial data conversion. Background Art

[0002] In the business of providing property protection services to users, it is generally possible to conduct a risk assessment of the reliability of the property protection service itself based on the detailed information within the business, so as to adjust the content of the property protection service based on the results of the risk assessment and better serve the users.

[0003] However, the information involved in the business is actually only the front-end information involved in the entire property protection service. In other words, the information involved in the business can only reflect the performance of the property protection service in the business dimension, but does not involve the performance of the property protection service in other aspects such as finance. Therefore, the result of risk assessment of property protection services based only on business information is relatively one-sided and inaccurate.

[0004] Therefore, how to comprehensively and accurately conduct risk assessment of property protection services has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The present invention provides a data processing method and device based on business-finance data conversion to solve the technical problem in the related art that risk assessment of property protection services is performed only based on business information, resulting in insufficient accuracy of risk assessment results.

[0006] In a first aspect, a data processing method based on business and financial data conversion is provided, comprising:

[0007] Acquire intermediate data corresponding to first data of multiple business systems, wherein the first data is used to reflect the performance of target businesses in the multiple business systems in the business dimension, and the intermediate data is a conversion result after the first data is converted from a current format to a target format, and the target format is a specified data format for a business-finance data conversion function;

[0008] Determine second data based on the intermediate data and preset business-finance data conversion rules, wherein the second data is used to reflect the performance of the target business to which the first data belongs in the financial dimension;

[0009] Based on the intermediate data and the second data, a risk value of a risk assessment object associated with the target business is determined, wherein the risk assessment object includes the property protection service provided by the target business, the seller, executor and protection object of the property protection service.

[0010] In one embodiment of the present application, optionally, the acquiring intermediate data corresponding to the first data of the plurality of business systems includes:

[0011] The intermediate data corresponding to the first data in the multiple business systems is obtained by connecting to a unified data upload interface of the multiple business systems, wherein the multiple business systems are used to convert the first data in a current format into the intermediate data in a target format based on a preset mapping rule.

[0012] In one embodiment of the present application, optionally, the acquiring intermediate data corresponding to the first data of the plurality of business systems includes:

[0013] Acquire first data of the multiple business systems;

[0014] Based on a preset mapping rule, the first data in a current format is converted into the intermediate data in a target format, wherein the preset mapping rule is used to reflect the association relationship between the current format and the target format.

[0015] In one embodiment of the present application, optionally, determining the second data based on the intermediate data and a preset business and financial data conversion rule includes:

[0016] For each data feature in the intermediate data, determining the type of financial data to which the data feature can be applied;

[0017] other necessary features other than the data features required to obtain the financial data type;

[0018] Based on the data feature, the other necessary features and a predetermined data calculation rule corresponding to the financial data type, a portion of the second data corresponding to the data feature is determined.

[0019] In one embodiment of the present application, optionally, the method further includes:

[0020] For each of the data feature and the other necessary features, obtaining a weight corresponding to the feature;

[0021] Based on the weights, determining weighted values ​​of the features;

[0022] Determining whether the weighted value of each of the data features and the other necessary features is within a corresponding preset confidence range;

[0023] When the judgment result is yes, setting a security identifier for the second data;

[0024] When the judgment result is no, a risk indicator is set for the second data.

[0025] In one embodiment of the present application, optionally, obtaining the weight corresponding to the feature includes:

[0026] Determine a first proportion of third data in historical data related to the business-finance data conversion function, wherein the third data is security data with a manually set security identifier;

[0027] Determine a second proportion of fourth data in the historical data whose characteristic is within a preset safety characteristic value range;

[0028] Based on the first proportion and the second proportion, a weight corresponding to the feature is determined.

[0029] In one embodiment of the present application, optionally, determining the weight corresponding to the feature based on the first proportion and the second proportion includes:

[0030] The square root of the product of the first proportion and the second proportion is set as the weight corresponding to the feature.

[0031] In one embodiment of the present application, optionally, determining the risk value of the risk assessment object associated with the target business based on the intermediate data and the second data includes:

[0032] Based on the intermediate data and the second data, construct a covariance matrix, wherein the element in the mth row and the nth column in the covariance matrix is ​​the covariance of the eigenvalue of the mth data feature and the eigenvalue of the nth data feature in the intermediate data and the second data;

[0033] Selecting elements greater than or equal to a preset covariance threshold in the covariance matrix and forming an enhanced feature sequence in descending order;

[0034] Obtaining the initial risk value and the risk correction coefficient of the enhanced feature sequence, wherein the initial risk value is the weighted average value of each element in the enhanced feature sequence, and the risk correction coefficient is the standard deviation of the enhanced feature sequence;

[0035] Based on the initial risk value and the risk correction coefficient, a risk value of a risk assessment object associated with the target business is determined.

[0036] In a second aspect, a data processing device based on business and financial data conversion is provided, comprising:

[0037] An intermediate data acquisition unit, used to acquire intermediate data corresponding to first data of multiple business systems, wherein the first data is used to reflect the performance of target businesses in the multiple business systems in the business dimension, and the intermediate data is a conversion result after the first data is converted from a current format to a target format, and the target format is a specified data format for a business-finance data conversion function;

[0038] A business-finance data conversion unit, configured to determine second data based on the intermediate data and a preset business-finance data conversion rule, wherein the second data is used to reflect the performance of the target business to which the first data belongs in a financial dimension;

[0039] A risk assessment unit is used to determine the risk value of the risk assessment object associated with the target business based on the intermediate data and the second data, wherein the risk assessment object includes the property protection service provided by the target business, the seller, executor and protection object of the property protection service.

[0040] In one embodiment of the present application, optionally, the intermediate data acquisition unit includes:

[0041] A first processing unit is used to obtain intermediate data corresponding to the first data in the multiple business systems by connecting to a unified data upload interface of the multiple business systems, wherein the multiple business systems are used to convert the first data in a current format into the intermediate data in a target format based on a preset mapping rule.

[0042] In one embodiment of the present application, optionally, the intermediate data acquisition unit includes:

[0043] The second processing unit is used to obtain the first data of the multiple business systems, and convert the first data in a current format into the intermediate data in a target format based on a preset mapping rule, wherein the preset mapping rule is used to reflect the association between the current format and the target format.

[0044] In one embodiment of the present application, optionally, the business-finance data conversion unit is used to: for each data feature in the intermediate data, determine the type of financial data that the data feature can participate in; obtain other necessary features other than the data feature required for the financial data type; and determine the corresponding part of the data feature in the second data based on the data feature, the other necessary features and the predetermined data calculation rules corresponding to the financial data type.

[0045] In one embodiment of the present application, optionally, the device further includes:

[0046] A weight acquisition unit, used for acquiring a weight corresponding to each of the data feature and the other necessary features;

[0047] A weighted value calculation unit, used to determine the weighted value of the feature based on the weight;

[0048] A label assignment unit is used to determine whether the weighted value of each of the data features and the other necessary features is within a corresponding preset confidence range, wherein when the judgment result is yes, a security mark is set for the second data, and when the judgment result is no, a risk mark is set for the second data.

[0049] In one embodiment of the present application, optionally, the weight acquisition unit is used to: determine a first proportion of third data in historical data related to a business and financial data conversion function, wherein the third data is security data with a manually set security identifier; determine a second proportion of fourth data in the historical data whose characteristics are within a preset security characteristic value range; and determine the weight corresponding to the characteristic based on the first proportion and the second proportion.

[0050] In one embodiment of the present application, optionally, the weight acquisition unit is used to: set the square root of the product of the first proportion and the second proportion as the weight corresponding to the feature.

[0051] In one embodiment of the present application, optionally, the risk assessment unit includes:

[0052] A matrix construction unit, configured to construct a covariance matrix based on the intermediate data and the second data, wherein the element in the mth row and the nth column of the covariance matrix is ​​the covariance of the eigenvalue of the mth data feature and the eigenvalue of the nth data feature in the intermediate data and the second data;

[0053] An enhanced feature sequence extraction unit is used to select elements greater than or equal to a preset covariance threshold in the covariance matrix and form an enhanced feature sequence in descending order;

[0054] A parameter acquisition unit, used to acquire the initial risk value and the risk correction coefficient of the enhanced feature sequence, wherein the initial risk value is the weighted average value of each element in the enhanced feature sequence, and the risk correction coefficient is the standard deviation of the enhanced feature sequence;

[0055] The risk value calculation unit is used to determine the risk value of the risk assessment object associated with the target business based on the initial risk value and the risk correction coefficient.

[0056] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned intelligent question and answer processing method when executing the computer program.

[0057] In a fourth aspect, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned intelligent question and answer processing method are implemented.

[0058] The above technical solution aims to solve the technical problem that the risk assessment results of property protection services are not accurate enough because the risk assessment is only based on business information in the related technology. By automatically converting the business data of multiple business systems into financial data, when conducting risk assessment on the risk assessment object, financial data and business data can be used together as the basis for risk assessment, thereby improving the reliability of risk assessment results and avoiding the problem of inaccurate assessment results caused by relying solely on business data for risk assessment. Of course, in this process, by automatically converting business data of different formats in multiple business systems into valid financial data, the management cost of business-finance conversion is also reduced, and the overall efficiency of business and financial work involved in property protection services is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0060] Figure 1 A flow chart of a data processing method based on business and financial data conversion according to an embodiment of the present application is shown;

[0061] Figure 2 A flowchart of business and financial data conversion according to an embodiment of the present application is shown;

[0062] Figure 3 A flow chart showing a method for calculating a risk value according to an embodiment of the present application is shown;

[0063] Figure 4 is a schematic diagram of a structure of a computer device in one embodiment of the present invention;

[0064] Figure 5 It is another structural schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] Figure 1 A flow chart of a data processing method based on business and financial data conversion according to an embodiment of the present application is shown.

[0067] like Figure 1 As shown, according to an embodiment of the present application, a data processing method based on business and financial data conversion includes:

[0068] Step 102: Acquire intermediate data corresponding to first data of multiple business systems.

[0069] The business system refers to a system that can provide property protection services and perform tasks such as customization, issuance and maintenance of property protection services. The property protection services here refer to insurance services related to the property security of users, including but not limited to property loss insurance, liability insurance, credit insurance, guarantee insurance, etc.

[0070] The first data is used to reflect the performance of the target business in the multiple business systems in the business dimension, including but not limited to one or more of insurance type information, basic policy information, co-insurance information, basic batch information, self-service card activation information and liability information.

[0071] The intermediate data is the conversion result of the first data from the current format to the target format, the current format is the original format of the first data, and the target format is the specified data format for the business and financial data conversion function.

[0072] In actual scenarios, the data formats in different business systems are different. For example, in the business system (insurance system) used to customize and sell property protection services, data in JSON format is used, in the business system (underwriting system) used to verify whether the seller and the insured person of the property protection service are valid, data in XML format is used, and in the business system (underwriting system) used to provide property protection services, data in CSV format is used. For another example, the specified data format of the business-finance data conversion function can be set to Excel, so the intermediate data in Excel format corresponding to the data in each business system can be obtained as the basis for business-finance data conversion and subsequent risk assessment and other processing. In other words, the intermediate data is the first data in each business system that can be used for the effective expression of the business-finance data conversion function.

[0073] In one possible design, intermediate data corresponding to the first data in the multiple business systems is obtained by connecting to a unified data upload interface of the multiple business systems, wherein the multiple business systems are used to convert the first data in a current format into the intermediate data in a target format based on preset mapping rules.

[0074] That is to say, different business systems can be connected to the management platform via the same interface, which is the unified data upload interface, and is used to transmit intermediate data in the target format, while the conversion of the first data into the intermediate data in the target format is completed by the business system itself, so as to save the resources of the management platform. At this point, each business system can actively upload the intermediate data obtained by its own first data conversion to the management platform through the unified data upload interface, and can also respond to the data upload instruction transmitted by the unified data upload interface and then upload the intermediate data obtained by its own first data conversion to the management platform.

[0075] Optionally, the management platform described herein is a system such as a financial system, an actuarial system or a reinsurance system that needs to call both financial data and business data.

[0076] Optionally, the management platform may also be a higher-level management system for managing multiple business systems, financial systems, actuarial systems, reinsurance systems, etc.

[0077] In another possible design, the management platform may obtain the first data of the multiple business systems, and then convert the first data in the current format into the intermediate data in the target format based on a preset mapping rule, wherein the preset mapping rule is used to reflect the association between the current format and the target format. In other words, the management platform may also directly obtain the first data of the multiple business systems, and then convert the first data in multiple different formats into the intermediate data in the target format for subsequent processing.

[0078] Step 104, determining the second data based on the intermediate data and the preset business and financial data conversion rules.

[0079] The information involved in the business is actually only the front-end information involved in the entire property protection service. In other words, the information involved in the business can only reflect the performance of the property protection service in the business dimension, but does not involve the performance of the property protection service in other aspects such as finance. Therefore, the result of risk assessment of property protection services based only on business information is rather one-sided and inaccurate.

[0080] On this basis, after obtaining the information related to the intermediate data business, the financial data associated with the target business, that is, the second data, can be obtained through business-financial data conversion as a reference condition for another dimension of risk assessment of property protection services.

[0081] Specifically, the preset business-finance data conversion rules can be reasonably set based on the actual financial data statistical needs and risk assessment needs. On this basis, the preset business-finance data conversion rules can be used to convert all intermediate data related to the target business from different business systems into second data, which is used to reflect the performance of the target business to which the first data belongs in the financial dimension. In a narrow sense, it can be understood that the second data is financial data converted from business data.

[0082] For each business system, intermediate data after its data is converted into the target format can be obtained and used in the process of business-financial data conversion without the need to customize business-financial data conversion rules unique to each business system. This reduces the configuration work involved in data conversion between multiple business systems and financial systems, and can avoid affecting the management efficiency of property protection services due to different data formats provided by different business systems.

[0083] In one possible design, reference Figure 2 The business and financial data conversion method described in step 104 is shown in the following steps.

[0084] Step 1042: for each data feature in the intermediate data, determine the type of financial data to which the data feature can be applied.

[0085] Intermediate data includes, but is not limited to, one or more of the following: insurance type information, basic policy information, co-insurance information, basic batch information, self-service card activation information, and liability information. Each of these information contains lower-level information. For example, if the basic policy information further includes the policy number and batch revision number, these lower-level information can be converted into feature values ​​through coding, and the feature values ​​reflect the data characteristics of the information.

[0086] Furthermore, the financial data type represents an accounting subject. For the business-finance conversion process, data features such as the policy number and the revision number will be mapped to the corresponding accounting subject as parameters for calculating financial data under the accounting subject. Various parameters are finally summarized into various financial statements. Thus, the financial data type that the data feature can participate in is determined, that is, which accounting subject calculation will use the data feature.

[0087] Step 1044, obtaining other necessary features other than the data features required for the financial data type.

[0088] For individual financial data related to this data feature, the calculation basis includes this data feature as well as other necessary features. For example, for the data feature of insurance premium rate in property damage insurance, in the financial data, when calculating the underwriting probability of users who have insured property damage insurance, other necessary features that need to be adjusted include: the number of times the user has insured property damage insurance in the historical period, the number of times underwriting occurred among these times, the number of times other users with the same user profile as the user have insured property damage insurance in the same historical period, and the number of times underwriting occurred, etc.

[0089] Step 1046: Determine the portion of the second data corresponding to the data feature based on the data feature, the other necessary features, and a predetermined data calculation rule corresponding to the financial data type.

[0090] At this point, the data features and the other necessary features are processed according to the predetermined data calculation rules corresponding to the financial data type to obtain the final required financial data.

[0091] Therefore, the performance of the target business in the financial dimension can be accurately inferred based on the performance of the target business in the business dimension, so that the performance of the target business in the financial dimension, that is, the second data, can be added as a new basis for risk assessment.

[0092] It is important to know that in the process of enterprise operation, different departments often use different systems to manage data. For example, the business department uses the business system to perform the customization, issuance and maintenance of property protection services, and the financial department uses the financial system to manage the financial information involved in the customization, issuance and maintenance of property protection services. Under this data management model of separation of business and finance, the formats of business data and financial data are inconsistent. Even if the business data is imported into the financial system, manual participation in data conversion and management is still required, which increases the management cost of the enterprise and affects the accuracy of the data and the reliability of the decisions made based on the data.

[0093] In this regard, related technologies have proposed that business data can be converted into financial data in a financial system. Specifically, for different business systems, a set of data conversion logic needs to be set up in different financial systems. However, this technical solution can only customize business-finance data conversion rules for different companies' diverse business systems and financial systems, which is time-consuming and labor-intensive and not universally applicable. The business-finance conversion method provided in this application can automatically convert business data in the target format into financial data, which not only reduces the cost of business-finance data conversion, improves the overall management and control efficiency of property insurance, but also provides an effective basis for subsequent risk assessments.

[0094] Step 106: Determine a risk value of a risk assessment object associated with the target business based on the intermediate data and the second data.

[0095] Ultimately, the intermediate data reflecting the performance of the target business in multiple business systems and the second data reflecting the performance of the target business in the financial dimension are used together as the basis for risk assessment of the risk assessment object, thereby improving the comprehensiveness of the risk assessment.

[0096] Among them, the risk assessment objects include the property protection services provided by the target business, the sellers, executors and protection objects of the property protection services.

[0097] In a possible design, the risk assessment object includes the property protection service provided by the target business. Accordingly, the first data is information related to the service content and service quality of the property protection service in multiple business systems, and the second data is the service cost information and service income information of the property protection service in the financial dimension. Therefore, the level of the risk value represents the level of the property protection service.

[0098] In another possible design, the risk assessment object includes the seller of the property protection service. Accordingly, the first data is the sales data of the property protection service sold to the current user in multiple business systems, and the second data includes: the service cost information, service income information, the seller's remuneration ratio and sales level in the financial dimension of the property protection service, so that the risk value represents the sales ability of the seller.

[0099] In another possible design, the risk assessment object includes the executor of the property protection service. Accordingly, the first data is the information such as the premium payment time and premium payment amount involved in the underwriting process of the property protection service for the current user in multiple business systems, and the second data includes: the insurance premium rate in the contract, the insurance premium rate corresponding to the actual premium, etc. Therefore, the level of the risk value represents the rationality of the underwriting process and results of the executor.

[0100] In another possible design, the risk assessment object includes the protected object of the property protection service. The protected object is the current user mentioned above. Accordingly, the first data is the underwriting information of the property protection service of the current user in multiple business systems and the underwriting information of the historical protection service of the current user. The second data includes: the comprehensive insurance premium rate of the current user in the category of property protection, etc. Therefore, the level of risk value represents the possibility of reasonable insurance for the protected object. In other words, it can reflect whether the protected object has the possibility of insurance fraud.

[0101] Of course, the above embodiments only list various examples of the first data and the second data. In actual scenarios, the first data and the second data may be information associated with various aspects of the property protection service, and are not limited to the situations given in the above examples.

[0102] Reference Figure 3 As shown, the specific method of determining the risk value of the risk assessment object associated with the target business in step 106 includes:

[0103] Step 1062: construct a covariance matrix based on the intermediate data and the second data.

[0104] Among them, the elements in the mth row and nth column of the covariance matrix are the covariance of the eigenvalues ​​of the mth data feature and the eigenvalues ​​of the nth data feature in the intermediate data and the second data. It can be said that it reflects the correlation between the mth data feature and the nth data feature in the business data and the financial data, that is, the correlation between the two data features that have an impact on the risk value of the risk assessment object.

[0105] Step 1064, selecting elements greater than or equal to a preset covariance threshold in the covariance matrix, and composing an enhanced feature sequence in descending order.

[0106] The preset covariance threshold refers to the lowest value of the covariance when two data features are correlated. If an element in the covariance matrix is ​​greater than or equal to the preset covariance threshold, it means that the two data features corresponding to the element have sufficient correlation. The higher the value of the element, the higher the level of impact on the reliability of the risk assessment object when the two interact with each other.

[0107] Step 1066, obtaining the initial risk value and risk correction coefficient of the enhanced feature sequence, wherein the initial risk value is the weighted average of each element in the enhanced feature sequence, and the risk correction coefficient is the standard deviation of the enhanced feature sequence.

[0108] Step 1068: Determine the risk value of the risk assessment object associated with the target business based on the initial risk value and the risk correction coefficient.

[0109] Specifically, the initial risk value of the enhanced feature sequence reflects the average impact of each group of data features with sufficient correlation on the reliability of the risk assessment object, and the risk correction coefficient of the enhanced feature sequence reflects the distribution law of each group of data features with sufficient correlation. The risk value obtained by combining the two can effectively reflect the reliability of the risk assessment object in the target business under the comprehensive effect of each group of data features.

[0110] The above technical solution, by automatically converting business data of multiple business systems into financial data, can use both financial data and business data as the basis for risk assessment when conducting risk assessment on risk assessment objects, thereby improving the reliability of risk assessment results and avoiding the problem of inaccurate assessment results caused by relying solely on business data for risk assessment. Of course, in this process, by automatically converting business data of different formats in multiple business systems into valid financial data, the management cost of business-finance conversion is also reduced, and the overall efficiency of business and financial work involved in property protection services is improved.

[0111] On the basis of any of the above embodiments, after the intermediate data is converted into the corresponding second data, for each data feature in the intermediate data, and each feature of other necessary features under the financial data type corresponding to each data feature, first, the weight corresponding to the feature can be obtained, and based on the weight, the weighted value of the feature can be determined. The weighted value of the feature can more realistically reflect the degree of influence of the feature on the security of the second data than the weight of the feature itself.

[0112] Among them, the method of obtaining the weight corresponding to the feature specifically includes: determining a first proportion of third data in the historical data related to the business and financial data conversion function, wherein the third data is security data with a manually set security mark; determining a second proportion of fourth data in the historical data whose feature is within a preset security feature value range; based on the first proportion and the second proportion, determining the weight corresponding to the feature. The first proportion reflects the proportion of security data in the historical data, that is, the security performance level of the historical data with this feature, the fourth data reflects the proportion of data in the historical data with this feature and the feature showing sufficient security, and the weight obtained based on the first proportion and the second proportion reflects the degree of influence of the feature on the security of the second data. Optionally, the square root of the product of the first proportion and the second proportion is set as the weight corresponding to the feature.

[0113] Next, determine whether the weighted value of each of the data features and the other necessary features is within the corresponding preset confidence range, which is a reasonable range for the weighted value of a single feature when the second data has sufficient security.

[0114] Therefore, when the judgment result is yes, that is, the weighted value of each of the data features and the other necessary features is within the corresponding preset confidence range, it can be determined that the second data has sufficient security. At this time, a security flag can be set for the second data.

[0115] On the contrary, if the weighted values ​​of the data features and each of the other necessary features are not all within the corresponding preset confidence range, it means that the content security corresponding to the features whose weighted values ​​are not within the preset confidence range in the second data is insufficient, and it can be determined that the overall security of the second data is insufficient. At this time, a risk indicator can be set for the second data.

[0116] Ultimately, the risk identifier or security identifier can be added to the second data as a separate data feature. In this way, in the process of determining the risk value of the risk assessment object associated with the target business based on the intermediate data and the second data, the security of the second data itself can be used as a necessary data feature and added to the basis for evaluation, thereby further improving the accuracy of risk assessment of the risk assessment object.

[0117] The embodiment of the present application further provides a data processing device based on business and financial data conversion, comprising:

[0118] An intermediate data acquisition unit, used to acquire intermediate data corresponding to first data of multiple business systems, wherein the first data is used to reflect the performance of target businesses in the multiple business systems in the business dimension, and the intermediate data is a conversion result after the first data is converted from a current format to a target format, and the target format is a specified data format for a business-finance data conversion function;

[0119] A business-finance data conversion unit, configured to determine second data based on the intermediate data and a preset business-finance data conversion rule, wherein the second data is used to reflect the performance of the target business to which the first data belongs in a financial dimension;

[0120] A risk assessment unit is used to determine the risk value of the risk assessment object associated with the target business based on the intermediate data and the second data, wherein the risk assessment object includes the property protection service provided by the target business, the seller, executor and protection object of the property protection service.

[0121] In one embodiment of the present application, optionally, the intermediate data acquisition unit includes:

[0122] A first processing unit is used to obtain intermediate data corresponding to the first data in the multiple business systems by connecting to a unified data upload interface of the multiple business systems, wherein the multiple business systems are used to convert the first data in a current format into the intermediate data in a target format based on a preset mapping rule.

[0123] In one embodiment of the present application, optionally, the intermediate data acquisition unit includes:

[0124] The second processing unit is used to obtain the first data of the multiple business systems, and convert the first data in a current format into the intermediate data in a target format based on a preset mapping rule, wherein the preset mapping rule is used to reflect the association between the current format and the target format.

[0125] In one embodiment of the present application, optionally, the business-finance data conversion unit is used to: for each data feature in the intermediate data, determine the type of financial data that the data feature can participate in; obtain other necessary features other than the data feature required for the financial data type; and determine the corresponding part of the data feature in the second data based on the data feature, the other necessary features and the predetermined data calculation rules corresponding to the financial data type.

[0126] In one embodiment of the present application, optionally, the device further includes:

[0127] A weight acquisition unit, used for acquiring a weight corresponding to each of the data feature and the other necessary features;

[0128] A weighted value calculation unit, used to determine the weighted value of the feature based on the weight;

[0129] A label assignment unit is used to determine whether the weighted value of each of the data features and the other necessary features is within a corresponding preset confidence range, wherein when the judgment result is yes, a security mark is set for the second data, and when the judgment result is no, a risk mark is set for the second data.

[0130] In one embodiment of the present application, optionally, the weight acquisition unit is used to: determine a first proportion of third data in historical data related to a business and financial data conversion function, wherein the third data is security data with a manually set security identifier; determine a second proportion of fourth data in the historical data whose characteristics are within a preset security characteristic value range; and determine the weight corresponding to the characteristic based on the first proportion and the second proportion.

[0131] In one embodiment of the present application, optionally, the weight acquisition unit is used to: set the square root of the product of the first proportion and the second proportion as the weight corresponding to the feature.

[0132] In one embodiment of the present application, optionally, the risk assessment unit includes:

[0133] A matrix construction unit, configured to construct a covariance matrix based on the intermediate data and the second data, wherein the element in the mth row and the nth column of the covariance matrix is ​​the covariance of the eigenvalue of the mth data feature and the eigenvalue of the nth data feature in the intermediate data and the second data;

[0134] An enhanced feature sequence extraction unit is used to select elements greater than or equal to a preset covariance threshold in the covariance matrix and form an enhanced feature sequence in descending order;

[0135] A parameter acquisition unit, used to acquire the initial risk value and the risk correction coefficient of the enhanced feature sequence, wherein the initial risk value is the weighted average value of each element in the enhanced feature sequence, and the risk correction coefficient is the standard deviation of the enhanced feature sequence;

[0136] The risk value calculation unit is used to determine the risk value of the risk assessment object associated with the target business based on the initial risk value and the risk correction coefficient.

[0137] The device uses any one of the solutions described in the above embodiments, and therefore has all the above technical effects, which will not be repeated here.

[0138] In addition, in one embodiment, the present application provides a computer device, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client via a network connection. When the computer program is executed by the processor, the method described in any of the above embodiments can be implemented.

[0139] In one embodiment, the present application further provides a computer device, which may be a client, and its internal structure diagram may be as follows: Figure 5As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, the method described in any of the above embodiments can be implemented.

[0140] Any of the above-mentioned computer devices in the embodiments of the present application may exist in various forms, including but not limited to:

[0141] (1) Mobile communication devices: These devices are characterized by their mobile communication functions and their main purpose is to provide voice and data communications. These terminals include: smart phones (such as iPhone), multimedia phones, functional phones, and low-end phones.

[0142] (2) Ultra-mobile personal computer devices: These devices fall into the category of personal computers, have computing and processing capabilities, and generally also have mobile Internet access features. These terminals include: PDA, MID and UMPC devices, such as iPad.

[0143] (3) Portable entertainment devices: These devices can display and play multimedia content. They include audio and video players (such as iPods), handheld game consoles, e-books, as well as smart toys, wearable devices, and portable car navigation devices.

[0144] (4) Server: A device that provides computing services. The server consists of a processor, hard disk, memory, system bus, etc. The server is similar to a general computer architecture, but because it needs to provide highly reliable services, it has higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0145] (5) Other electronic devices with data interaction functions.

[0146] In addition, an embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to perform the following steps:

[0147] Acquire intermediate data corresponding to first data of multiple business systems, wherein the first data is used to reflect the performance of target businesses in the multiple business systems in the business dimension, and the intermediate data is a conversion result after the first data is converted from a current format to a target format, and the target format is a specified data format for a business-finance data conversion function;

[0148] Determine second data based on the intermediate data and preset business-finance data conversion rules, wherein the second data is used to reflect the performance of the target business to which the first data belongs in the financial dimension;

[0149] Based on the intermediate data and the second data, a risk value of a risk assessment object associated with the target business is determined, wherein the risk assessment object includes the property protection service provided by the target business, the seller, executor and protection object of the property protection service.

[0150] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant description in the aforementioned method embodiment. In order to avoid repetition, they will not be described one by one here.

[0151] The above describes in detail the technical solution of the present application in conjunction with the accompanying drawings. The technical solution of the present application, by automatically converting the business data of multiple business systems into financial data, can use both financial data and business data as the basis for risk assessment when conducting risk assessment on risk assessment objects, thereby improving the reliability of risk assessment results and avoiding the problem of inaccurate assessment results caused by relying solely on business data for risk assessment. Of course, in this process, by automatically converting business data of different formats in multiple business systems into valid financial data, the management cost of business-finance conversion is also reduced, and the overall efficiency of business and financial work involved in property protection services is improved.

[0152] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0153] It should be understood that, although the terms first, second, etc. may be used to describe data in the embodiments of the present application, these data should not be limited to these terms. These terms are only used to distinguish data from each other. For example, without departing from the scope of the embodiments of the present application, the first data may also be referred to as the second data, and similarly, the second data may also be referred to as the first data.

[0154] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0155] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0156] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0157] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A data processing method based on business and financial data conversion, characterized in that: include: Acquire intermediate data corresponding to first data of multiple business systems, wherein the first data is used to reflect the performance of target businesses in the multiple business systems in the business dimension, and the intermediate data is a conversion result after the first data is converted from a current format to a target format, and the target format is a specified data format for a business-finance data conversion function; Determine second data based on the intermediate data and preset business-finance data conversion rules, wherein the second data is used to reflect the performance of the target business to which the first data belongs in the financial dimension; Based on the intermediate data and the second data, a risk value of a risk assessment object associated with the target business is determined, wherein the risk assessment object includes the property protection service provided by the target business, the seller, executor and protection object of the property protection service.

2. The method according to claim 1, characterized in that The obtaining of intermediate data corresponding to the first data of the plurality of business systems includes: Acquiring intermediate data corresponding to the first data in the multiple business systems by connecting to a unified data upload interface of the multiple business systems, wherein the multiple business systems are used to convert the first data in a current format into the intermediate data in a target format based on a preset mapping rule; or Acquire first data of the multiple business systems; Based on a preset mapping rule, the first data in a current format is converted into the intermediate data in a target format, wherein the preset mapping rule is used to reflect the association relationship between the current format and the target format.

3. The method according to claim 1 or 2, characterized in that The determining of the second data based on the intermediate data and the preset business and financial data conversion rule includes: For each data feature in the intermediate data, determining the type of financial data to which the data feature can be applied; other necessary features other than the data features required to obtain the financial data type; Based on the data feature, the other necessary features and a predetermined data calculation rule corresponding to the financial data type, a portion of the second data corresponding to the data feature is determined.

4. The method according to claim 3, characterized in that Also includes: For each of the data feature and the other necessary features, obtaining a weight corresponding to the feature; Based on the weights, determining weighted values ​​of the features; Determining whether the weighted value of each of the data features and the other necessary features is within a corresponding preset confidence range; When the judgment result is yes, setting a security identifier for the second data, and adding the security identifier to the data feature of the second data; When the judgment result is no, a risk identifier is set for the second data, and the risk identifier is added to the data feature of the second data.

5. The method according to claim 4, characterized in that The obtaining the weight corresponding to the feature includes: Determine a first proportion of third data in historical data related to the business-finance data conversion function, wherein the third data is security data with a manually set security identifier; Determine a second proportion of fourth data in the historical data whose characteristic is within a preset safety characteristic value range; Based on the first proportion and the second proportion, a weight corresponding to the feature is determined.

6. The method according to claim 5, characterized in that The determining, based on the first proportion and the second proportion, a weight corresponding to the feature includes: The square root of the product of the first proportion and the second proportion is set as the weight corresponding to the feature.

7. The method according to claim 3, characterized in that The determining, based on the intermediate data and the second data, a risk value of a risk assessment object associated with the target business includes: Based on the intermediate data and the second data, construct a covariance matrix, wherein the element in the mth row and the nth column in the covariance matrix is ​​the covariance of the eigenvalue of the mth data feature and the eigenvalue of the nth data feature in the intermediate data and the second data; Selecting elements greater than or equal to a preset covariance threshold in the covariance matrix and forming an enhanced feature sequence in descending order; Obtaining the initial risk value and the risk correction coefficient of the enhanced feature sequence, wherein the initial risk value is the weighted average value of each element in the enhanced feature sequence, and the risk correction coefficient is the standard deviation of the enhanced feature sequence; Based on the initial risk value and the risk correction coefficient, a risk value of a risk assessment object associated with the target business is determined.

8. A data processing device based on business and financial data conversion, characterized in that: include: An intermediate data acquisition unit, used to acquire intermediate data corresponding to first data of multiple business systems, wherein the first data is used to reflect the performance of target businesses in the multiple business systems in the business dimension, and the intermediate data is a conversion result after the first data is converted from a current format to a target format, and the target format is a specified data format for a business-finance data conversion function; A business-finance data conversion unit, configured to determine second data based on the intermediate data and a preset business-finance data conversion rule, wherein the second data is used to reflect the performance of the target business to which the first data belongs in a financial dimension; A risk assessment unit is used to determine the risk value of the risk assessment object associated with the target business based on the intermediate data and the second data, wherein the risk assessment object includes the property protection service provided by the target business, the seller, executor and protection object of the property protection service.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

Images