Risk-weighted asset system testing method, device, equipment and readable storage medium

Abstract

The present invention provides a risk-weighted asset system testing method, device, equipment and readable storage medium, which relates to the technical field of risk-weighted asset systems, including obtaining each debt item, relevant information of each debt item and the operation rules of the reconstructed system; establishing a single-account measurement mathematical model and a batch comparison test mathematical model, combining the single-account measurement part with the batch comparison test part, the single-account measurement verifies the accuracy of the calculation of the reconstructed system to reduce unnecessary consumption of server resources, while the batch comparison test focuses on the comparison between the reconstruction and the pre-reconstruction, and on the basis of the single-account measurement, the correctness of the system risk-weighted asset calculation rules is guaranteed, and on this basis, the batch comparison test is carried out, and this test method ensures that the final risk-weighted asset measurement results of the new and old systems only have errors within an acceptable range.

Description

Technical Field

[0001] The present invention relates to the technical field of risk-weighted asset systems, and in particular to a risk-weighted asset system testing method, device, equipment and readable storage medium. Background Art

[0002] There is no targeted solution for the risk-weighted asset measurement system, especially the data testing method for the reconstructed risk-weighted asset measurement system, in the current banking system. Since the calculation results of the system before and after the reconstruction are kept consistent, the risk-weighted asset measurement system itself has a huge amount of data, which requires a lot of manpower and server resources. Summary of the invention

[0003] The purpose of the present invention is to provide a risk-weighted asset system testing method, device, equipment and readable storage medium to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0004] In a first aspect, the present application provides a risk-weighted asset system testing method, comprising: obtaining first information, the first information including database data, the database data including each debt and related information of each debt, the related information including first risk information and first detailed information; obtaining second information, the second information including the operation rules of the reconstructed system; establishing a single measurement mathematical model based on the second information, the first information being used as input information of the single measurement mathematical model; solving the single measurement model to obtain third information, the third information including the verification result of the first risk information corresponding to each debt; establishing a batch comparison test mathematical model based on the first information and the third information; solving the batch comparison test mathematical model to obtain fourth information, the fourth information including the verification result of the first information, the verification result of the first information including the verification result of the first detailed information of each debt; outputting the fourth information.

[0005] Furthermore, the single-item calculation mathematical model is established based on the second information, and the first information is used as the input information of the single-item calculation mathematical model, including: establishing a risk-weighted asset mathematical model based on the second information, and using the first detailed information as the input information of the risk-weighted asset mathematical model; solving the risk-weighted asset mathematical model to obtain fifth information, and the fifth information is the second risk information corresponding to each debt item calculated by the calculation rules of the reconstructed system; establishing a first judgment model with the fifth information and the first risk information; solving the first judgment model to obtain a verification result of the first risk-weighted asset, and the first risk information verification result includes but is not limited to pass and fail; obtaining the verification result of the first risk-weighted asset.

[0006] Furthermore, the establishment of a batch comparison test mathematical model based on the first information and the third information includes: if the verification result of the first risk information is failure, outputting sixth information, and the sixth information is that the calculation rules of the reconstructed system do not meet the requirements; if the result of the verification of the first risk information is pass, establishing a debt batch comparison test mathematical model based on the first information and the third information, solving the debt batch comparison test mathematical model, and obtaining the calculation result of the debt batch comparison test mathematical model.

[0007] Furthermore, the establishment of a mathematical model for batch comparison testing of debts based on the first information and the third information includes: obtaining seventh information, the seventh information including difference tolerance, summary indicators and summary dimensions; establishing a multi-dimensional comparison mathematical model based on the first information, the third information and the seventh information; solving the multi-dimensional comparison mathematical model, the output result of the multi-dimensional comparison mathematical model including the verification result of the first detailed information of each debt; and obtaining the calculation result of the multi-dimensional comparison mathematical model.

[0008] Furthermore, the multi-dimensional comparison mathematical model is established based on the first information, the third information and the seventh information, including: establishing a summary comparison table based on the summary index and the summary dimension, the third information includes the second detailed information of each debt item, the second detailed information is calculated by a single measurement mathematical model, and the difference between the first detailed information and the second detailed information of each debt item is calculated under the same summary index and summary dimension; establishing a second judgment model based on the difference and the difference tolerance, the output result of the second judgment model includes the verification result of the first detailed information; solving the second judgment model; obtaining the calculation result of the second judgment model and the summary comparison table.

[0009] Furthermore, the second judgment model is established based on the difference and the difference tolerance, including: if the difference is within the difference tolerance range, outputting the verification result of the first detailed information; if the difference is within the difference tolerance range, outputting the verification result of the first detailed information, the first detailed information corresponding to the debt, and the second detailed information.

[0010] In the second aspect, the present application also provides a risk-weighted asset system testing device, comprising a first data acquisition module, a second information acquisition module and a single calculation module: the first data acquisition module is used to acquire first information, the first information includes database data, the database data includes each debt item and related information of the each debt item, the related information includes first risk information and first detailed information; the second information acquisition module is used to acquire second information, the second information includes the operation rules of the reconstructed system; the single calculation module is used to establish a single calculation mathematical model according to the second information, the first information is used as the input information of the single calculation mathematical model, and the single calculation model is solved to obtain third information, the third information includes the verification result of the first risk information corresponding to each debt item; the batch comparison test module is used to establish a batch comparison test mathematical model according to the first information and the third information, solve the batch comparison test mathematical model to obtain fourth information, the fourth information includes the verification result of the first information, the verification result of the first information includes the verification result of the first detailed information of each debt item, and output the fourth information; the output module is used to output the fourth information.

[0011] Furthermore, the single calculation module includes: a risk-weighted asset calculation module, which is used to establish a risk-weighted asset mathematical model based on the second information, use the first detailed information as the input information of the risk-weighted asset mathematical model, and solve the risk-weighted asset mathematical model to obtain fifth information, wherein the fifth information is the second risk information corresponding to each debt item calculated by the calculation rules of the reconstructed system; a first judgment module, which is used to establish a first judgment model with the fifth information and the first risk information, solve the first judgment model to obtain a verification result of the first risk-weighted asset, wherein the verification result of the first risk information includes but is not limited to pass and fail, and obtain the verification result of the first risk-weighted asset.

[0012] Furthermore, the batch comparison test module includes: a second judgment module, used to determine if the verification result of the first risk information is failed, then output sixth information, the sixth information being that the calculation rules of the reconstructed system do not meet the requirements; a third judgment module, used to determine if the verification result of the first risk information is passed, then establish a debt batch comparison test mathematical model based on the first information and the third information; solve the debt batch comparison test mathematical model to obtain the calculation result of the debt batch comparison test mathematical model.

[0013] Furthermore, the third judgment module includes: a third data acquisition module, used to obtain the seventh information, the seventh information includes difference tolerance, summary indicators and summary dimensions; a multi-dimensional comparison module, used to establish a multi-dimensional comparison mathematical model based on the first information, the third information and the seventh information, and solve the multi-dimensional comparison mathematical model, the output result of the multi-dimensional comparison mathematical model includes the verification result of the first detailed information of each debt item, and obtains the calculation result of the multi-dimensional comparison mathematical model.

[0014] Furthermore, the multi-dimensional comparison module includes: a detailed difference comparison module, which is used to establish a summary comparison table according to the summary index and the summary dimension, the third information includes the second detailed information of each debt item, the second detailed information is calculated by a single measurement mathematical model, and the difference between the first detailed information and the second detailed information of each debt item is calculated under the same summary index and summary dimension; a fourth judgment module, which is used to establish a second judgment model according to the difference and the difference tolerance, the output result of the second judgment model includes the verification result of the first detailed information, the second judgment model is solved, and the calculation result of the second judgment model and the summary comparison table are obtained.

[0015] Furthermore, the fourth judgment module includes: a first sub-logic module, used to determine if the difference is within the difference tolerance range, and then output the verification result of the first detailed information; a second sub-logic module, used to determine if the difference is within the difference tolerance range, and then output the verification result of the first detailed information, the first detailed information corresponding to the debt, and the second detailed information.

[0016] In a third aspect, the present application also provides a risk-weighted asset system testing device, including:

[0017] Memory for storing computer programs;

[0018] A processor is used to implement the steps of risk-weighted asset system testing when executing the computer program.

[0019] In a fourth aspect, the present application further provides a readable storage medium, characterized in that a computer program is stored on the readable storage medium, and the computer program implements the steps of the risk-weighted asset system testing method when executed by a processor.

[0020] The beneficial effects of the present invention are:

[0021] 1. By combining the single calculation part with the batch comparison test part of the invention, the single calculation verifies the accuracy of the calculation of the system after reconstruction and reduces the consumption of unnecessary server resources, while the batch comparison test focuses on the comparison between before and after reconstruction. On the basis of the single calculation, the correctness of the system risk-weighted asset calculation rules is guaranteed, and the batch comparison test is carried out on this basis. Through this test method, it is ensured that the final risk-weighted asset measurement results of the system before reconstruction and the system after reconstruction have only an error within an acceptable range;

[0022] 2. This application adopts a multi-subject and first-level institution comparison method in batch comparison testing, realizes latitude and multi-level testing, reduces some unnecessary data comparison content, improves overall testing efficiency, and solves the problem that a large amount of server resources and human resources are consumed in the data testing scheme of the reconstructed risk-weighted asset system;

[0023] 3. This application adopts a multi-subject and first-level institution comparison method in batch comparison testing, uses multi-dimensional and multi-level testing, and outputs the part where the relevant problems are located. While improving data accuracy, it will not affect the overall operation process due to partial errors.

[0024] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 This is a flow chart of the risk-weighted asset system testing method described in the present invention;

[0027] Figure 2 It is a schematic diagram of the structure of the risk-weighted asset system testing device described in an embodiment of the present invention;

[0028] Figure 3 Schematic diagram of the structure of a single test module in an embodiment of the present invention;

[0029] Figure 4 This is a schematic diagram of the structure of the batch comparison module described in an embodiment of the present invention:

[0030] Figure 5 This is a schematic diagram of the structure of the third judgment module described in an embodiment of the present invention:

[0031] Figure 6 This is a schematic diagram of the structure of the multi-dimensional comparison module described in an embodiment of the present invention:

[0032] Figure 7 This is a schematic diagram of the structure of the fourth judgment module described in an embodiment of the present invention:

[0033] Figure 8 2 is a schematic diagram of the structure of the risk-weighted asset system testing equipment described in an embodiment of the present invention.

[0034] Markings in the figure: 1. First data acquisition module; 2. Second information acquisition module; 3. Single measurement module; 31. Risk-weighted asset calculation module; 32. First judgment module; 4. Batch comparison test module; 41. Second judgment module; 42. Third judgment module; 421. Third data acquisition module; 422. Multi-dimensional comparison module; 4221. Detailed difference comparison module; 4222. Fourth judgment module; 5. Output module; 6. First sub-logic module; 7. Second sub-logic module. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0036] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0037] This embodiment provides a risk-weighted asset system testing method, see Figure 1 The method includes step S100, step S200, step S300, step S400 and step S500:

[0038] S100. Acquire first information, where the first information includes database data, and the database data includes each debt item and related information of each debt item, and the related information includes first risk information and first detailed information.

[0039] It should be noted that in S100, the first detailed information includes but is not limited to basic information such as debt number, subject, core product number, risk exposure type code, on- and off-balance sheet identification, etc., while the first risk information includes but is not limited to information such as mitigation coverage risk exposure, mitigation uncovered risk exposure, and risk-weighted assets. The above-mentioned relevant information is all known data calculated by the system before reconstruction.

[0040] S200, obtaining second information, where the second information includes the first detailed information;

[0041] It is understandable that the operation rules in this step include but are not limited to the operation rules configured according to the basic information fields obtained in S100, wherein the operation rules are used to calculate the mitigation coverage risk exposure, the mitigation uncovered risk exposure, and the final risk-weighted assets of the debt item according to the information such as the internal and external identification of the table, whether the mitigation identification is qualified, and the mitigation weight. The specific operation rules of the reconstructed system are not the focus of this application, so the specific operation rules will not be repeated.

[0042] S300, establishing a single-transaction calculation mathematical model according to the second information, using the first information as input information of the single-transaction calculation mathematical model, solving the single-transaction calculation model to obtain third information, the third information including a verification result of the first risk information corresponding to each debt item;

[0043] Among them, the main purpose of S300 is to verify whether the operation rules of the reconstructed system are correct, and to preliminarily obtain information on whether the calculation logic of the reconstructed system is consistent with the required risk-weighted asset measurement logic. This method can obtain a preliminary judgment with less resource consumption in view of the large amount of data in the risk-weighted asset measurement system, and the information obtained in this step can also be further used, so that the results of resource consumption can still be used, and because the coupling between the preliminary processing and the actual calculation is not high, this logic can also be used for the reconstruction of other risk-weighted asset measurement systems, and has universality. Specifically, in step S300, a single-measurement mathematical model is established according to the second information, and the first information is used as the input information of the single-measurement mathematical model, including steps S310 and S320, as follows:

[0044] S310, establishing a risk-weighted asset mathematical model according to the second information, using the fifth information as input information of the risk-weighted asset mathematical model, solving the risk-weighted asset mathematical model to obtain the fifth information, where the fifth information is the second risk information corresponding to each debt item calculated by the calculation rule of the reconstructed system;

[0045] It can be understood that in this step, the second information is used to configure the operation rules to calculate each debt item, and the first detailed information including but not limited to the debt item number, account, core product number, risk exposure type code, internal and external identification, etc. are input into the risk-weighted asset mathematical model. The risk-weighted asset mathematical model calculates the mitigation coverage risk exposure, mitigation uncovered risk exposure and the final risk-weighted assets of the debt item based on the internal and external identification, whether the mitigation is qualified, and the mitigation weight. In this step, the Excel program can be used to establish the risk-weighted asset mathematical model to reduce the development cost of developers.

[0046] S320. Establish a first judgment model with the fifth information and the first risk information, solve the first judgment model to obtain a verification result of the first risk-weighted asset, the verification result of the first risk information includes but is not limited to pass and fail, and obtain the verification result of the first risk-weighted asset.

[0047] It can be understood that in this step, the first risk information of each debt item in the system before reconstruction, i.e., the mitigation coverage risk exposure, mitigation uncovered risk exposure, and risk-weighted assets, can be compared with the calculated data results of the system after reconstruction. If there is no difference, it means that the calculation results are consistent when the basic information is the same. This means that the risk-weighted asset calculation rules in the reconstructed system are correct. If there is a difference, the logic of the risk-weighted asset calculation rules in the reconstructed system can be corrected with less resource consumption. If there is a difference, it can be corrected as soon as possible to reduce unnecessary resource consumption.

[0048] S400. A batch comparison test mathematical model is established based on the first information and the third information, and the batch comparison test mathematical model is solved to obtain fourth information, wherein the fourth information includes a verification result of the first information, and the verification result of the first information includes a verification result of the first detailed information of each debt item.

[0049] It can be understood that this step is performed after completing a single measurement test. After completing a single measurement test, it can be basically guaranteed that the system operation rules after reconstruction are consistent with the required risk-weighted asset measurement logic. The next step is to conduct a comparative test between the system after reconstruction and the system before reconstruction. Since there are many debt items involved in the calculation of risk-weighted assets, the total amount of data from the two systems is nearly 8 million. If every relevant information of each debt item is compared, the comparison will be time-consuming, inefficient, and labor-intensive, and there are various disadvantages. Because the present application adopts multi-dimensional batch measurement, it reduces the test volume and resource consumption without reducing the test results. Specifically, in this step S400, a batch comparison test mathematical model is established according to the first information and the third information, including step S410 and step S420;

[0050] S410, if the verification result of the first risk information is not passed, output sixth information, the sixth information is that the calculation rule of the reconstructed system does not meet the requirements, otherwise execute S420;

[0051] It can be understood that this step is to verify the result of a single measurement. Of course, for those skilled in the art, this step can be placed between steps S300 and S400. No specific limitation is made in this application.

[0052] S420. If the result of the first risk information verification is passed, a mathematical model for the debt batch comparison test is established based on the first information and the third information, the mathematical model for the debt batch comparison test is solved, and the calculation result of the mathematical model for the debt batch comparison test is obtained.

[0053] It can be understood that this step starts the comparison test on the data, wherein in step S420, a mathematical model for batch comparison test of debt items is established according to the first information and the third information, including step S421 and step S422.

[0054] S421. Acquire seventh information, where the seventh information includes difference tolerance, summary index, and summary dimension;

[0055] It can be understood that in this step, the indicators that need to be compared and summarized are obtained, including but not limited to asset balance, risk asset balance, assessment capital balance, assessment capital RMB balance, mitigation amount, and impairment reserve balance. There are also dimensions that need to be summarized, including but not limited to business cash, funding cash and other items and first-level institutions. The difference tolerance can be selected according to the standards of different banks. In this application, the interval [-1%, 1%] is taken as an example.

[0056] S422. Establish a multi-dimensional comparison mathematical model based on the first information, the third information and the seventh information, and solve the multi-dimensional comparison mathematical model. The output result of the multi-dimensional comparison mathematical model includes the verification result of the first detailed information of each debt item, and obtains the calculation result of the multi-dimensional comparison mathematical model.

[0057] It should be noted that in this application, SQL scripts are written and executed to extract data according to the determined summary indicators and dimensions, and SQL statements are used to summarize the first detailed information and the second detailed information by subject. The summary indicators include but are not limited to: asset balance, risk asset balance, assessment capital balance, assessment capital RMB balance, mitigation amount, impairment reserve balance total field, and the subjects are sorted from small to large during the summary. In step S422, a multi-dimensional comparison mathematical model is established based on the first information, the third information and the seventh information, including steps S4221, S4222, S4223 and S4224.

[0058] S4221. A summary comparison table is established according to the summary index and summary dimension. The third information includes the second detailed information of each debt item, wherein the second detailed information is calculated by a single-item measurement mathematical model, and the difference between the first detailed information and the second detailed information of each debt item is calculated under the same summary index and summary dimension.

[0059] It can be understood that in this step, the first detailed information and the second detailed information are obtained and compared one by one in order in the summary comparison table, and the summary items in the summary comparison table include but are not limited to: asset balance, risk asset balance, assessment capital balance, assessment capital RMB balance, mitigation amount, impairment reserve balance, etc., and the items are sorted from small to large when summarizing. The formula: difference = value calculated by the operation rules of the system before reconstruction - value calculated by the operation rules of the system after reconstruction; difference ratio = difference / value calculated by the operation rules of the system before reconstruction is used to calculate the two indicators of difference and difference ratio.

[0060] S4222. Establish a second judgment model according to the difference and the difference tolerance, and the output result of the second judgment model includes the verification result of the first detailed information;

[0061] It is understandable that this step is to find out the accounts whose risk-weighted asset difference ratio exceeds the difference tolerance. The purpose of this is to eliminate the accounts that exceed the difference tolerance, so as to facilitate the analysis and investigation of the data with large differences in the later stage and find out the reasons for the differences. Specifically, first analyze the difference accounts based on the difference amount and difference ratio of the asset balance, the mitigation amount and the total impairment provision. Check whether it is caused by these factors.

[0062] If the final result of risk-weighted assets differs due to differences in asset balances, mitigation amounts, and the total of impairment reserves, investigate whether the difference under the subject is reasonable. If not, call up the first detailed information and the second detailed information under the subject to find out the specific difference value. If the difference is not caused by the above factors, call up the first detailed information and the second detailed information of the subject, and analyze the cause of the difference and whether the difference is reasonable through detailed comparison. The test based on the first-level institution is consistent with the test based on the subject. Through analysis in two dimensions, many different data can be found, and they can be located one by one to find out the problems, ensure the accuracy of the final data quality, and further improve the final use effect of this application.

[0063] S4223, solving the second judgment model;

[0064] S4224. Obtain the calculation results of the second judgment model and a summary comparison table.

[0065] Among them, in step S4222, a second judgment model is established according to the difference and the difference tolerance, including the following steps:

[0066] If the difference is within the tolerance range, the verification result of the first detailed information is output;

[0067] If the difference is within the tolerance range, the verification result of the first detailed information, the first detailed information corresponding to the debt and the second detailed information are output.

[0068] It can be understood that in this step, the verification result of the first detailed information includes but is not limited to test passed and test passed.

[0069] S500: Output fourth information.

[0070] Embodiment 2:

[0071] Corresponding to the above method embodiment, this embodiment further provides a risk-weighted asset system testing device. The risk-weighted asset system testing device described below and the risk-weighted asset system testing method described above can be referenced to each other.

[0072] like Figures 2 to 7 As shown, a risk-weighted asset system testing device includes a first data acquisition module 1, a second information acquisition module 2, a single transaction calculation module 3 and a batch comparison test module 4.

[0073] The first data acquisition module 1 is used to acquire first information, the first information includes database data, the database data includes each debt item and related information of each debt item, and the related information includes first risk information and first detailed information.

[0074] The second information acquisition module 2 is used to acquire second information, where the second information includes the operation rules of the reconstructed system.

[0075] The single-transaction calculation module 3 is used to establish a single-transaction calculation mathematical model based on the second information, and the first information is used as the input information of the single-transaction calculation mathematical model. The single-transaction calculation model is solved to obtain the third information, and the third information includes the verification result of the first risk information corresponding to each debt item.

[0076] The single-transaction calculation module 3 includes a risk-weighted asset calculation module 31 and a first judgment module 32:

[0077] The risk-weighted asset calculation module 31 is used to establish a risk-weighted asset mathematical model based on the second information, using the first detailed information as input information of the risk-weighted asset mathematical model; solving the risk-weighted asset mathematical model to obtain fifth information, the fifth information being the second risk information corresponding to each debt item calculated by the calculation rules of the reconstructed system.

[0078] The first judgment module 32 is used to establish a first judgment model based on the fifth information and the first risk information; solve the first judgment model to obtain a verification result of the first risk-weighted asset, and the first risk information verification result includes but is not limited to pass and fail; obtain the verification result of the first risk-weighted asset.

[0079] The batch comparison test module 4 is used to establish a batch comparison test mathematical model based on the first information and the third information, solve the batch comparison test mathematical model to obtain the fourth information, the fourth information includes the verification result of the first information, the verification result of the first information includes the verification result of the first detailed information of each debt item, and output the fourth information.

[0080] Furthermore, the batch comparison test module 4 includes a second judgment module 41 and a third judgment module 42 .

[0081] The second judgment module 41 is used to judge that if the verification result of the first risk information is not passed, then output the sixth information, the sixth information is that the calculation rule of the reconstructed system does not meet the requirements;

[0082] The third judgment module 42 is used to determine if the result of the first risk information verification is passed, then establish a debt batch comparison test mathematical model based on the first information and the third information; solve the debt batch comparison test mathematical model to obtain the calculation result of the debt batch comparison test mathematical model.

[0083] The third judgment module 42 includes a third data acquisition module 421 and a multi-dimensional comparison module 422 .

[0084] The third data acquisition module 421 is used to acquire seventh information, where the seventh information includes difference tolerance, summary index and summary dimension;

[0085] The multi-dimensional comparison module 422 is used to establish a multi-dimensional comparison mathematical model based on the first information, the third information and the seventh information, and solve the multi-dimensional comparison mathematical model. The output result of the multi-dimensional comparison mathematical model includes the verification result of the first detailed information of each debt item, and obtains the calculation result of the multi-dimensional comparison mathematical model.

[0086] The multi-dimensional comparison module 422 includes a detailed difference comparison module 4221 and a fourth judgment module 4222 .

[0087] The detail difference comparison module 4221 is used to establish a summary comparison table according to the summary index and summary dimension, wherein the third information includes the second detail information of each debt item, the second detail information is calculated by the single-item measurement mathematical model, and the difference between the first detail information and the second detail information of each debt item is calculated under the same summary index and summary dimension;

[0088] The fourth judgment module 4222 is used to establish a second judgment model according to the difference and the difference tolerance, the output result of the second judgment model includes the verification result of the first detailed information, solve the second judgment model, and obtain the calculation result of the second judgment model and the summary comparison table.

[0089] The fourth determination module 4222 includes a first sub-logic module 6 and a second sub-logic module 7 .

[0090] Specifically, the first sub-logic module 6 is used to determine if the difference is within the difference tolerance range, and then output the verification result of the first detailed information.

[0091] The second sub-logic module 7 is used to determine if the difference is within the difference tolerance range, and then output the verification result of the first detailed information, the first detailed information corresponding to the debt item, and the second detailed information.

[0092] It should be noted that, regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0093] Embodiment 3:

[0094] Corresponding to the above method embodiment, a risk-weighted asset system testing device is also provided in this embodiment. The risk-weighted asset system testing device described below and the risk-weighted asset system testing method described above can refer to each other.

[0095] Figure 8 FIG. 8 is a block diagram of a risk-weighted asset system testing device 800 according to an exemplary embodiment. Figure 8As shown, the video surveillance object analysis device 800 may include: a processor 801 and a memory 802. The video surveillance object analysis device 800 may also include one or more of a multimedia component 803, an input / output (I / O) interface 804, and a communication component 805.

[0096] The processor 801 is used to control the overall operation of the video surveillance object analysis device 800 to complete all or part of the steps in the above-mentioned video surveillance object analysis method. The memory 402 is used to store various types of data to support the operation of the video surveillance object analysis device 800. For example, these data may include instructions for any application or method operating on the video surveillance object analysis device 800, as well as application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 802 or sent via the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules can be keyboards, mice, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the video surveillance object analysis device 800 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 805 can include: Wi-Fi module, Bluetooth module, NFC module.

[0097] In an exemplary embodiment, the video surveillance object analysis device 800 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned video surveillance object analysis method.

[0098] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned video surveillance object analysis method are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 802 including program instructions, and the above-mentioned program instructions can be executed by the processor 801 of the video surveillance object analysis device 800 to complete the above-mentioned video surveillance object analysis method.

[0099] Embodiment 4:

[0100] Corresponding to the above method embodiment, a readable storage medium is also provided in this embodiment. The readable storage medium described below and the risk-weighted asset system testing method described above can refer to each other.

[0101] A readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the risk-weighted asset system testing method of the above method embodiment.

[0102] The readable storage medium may specifically be a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or other readable storage medium that can store program codes.

[0103] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0104] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A risk-weighted asset system testing method, characterized in that: include: Acquire first information, wherein the first information includes database data, the database data includes each debt item and related information of each debt item, and the related information includes first risk information and first detailed information; Acquiring second information, wherein the second information includes an operation rule of the reconstructed system; Establishing a single-transaction calculation mathematical model according to the second information, wherein the first information serves as input information of the single-transaction calculation mathematical model; Solving the single-debt estimation model to obtain third information, wherein the third information includes a verification result of the first risk information corresponding to each debt item; Establishing a batch comparison test mathematical model according to the first information and the third information; Solving the batch comparison test mathematical model to obtain fourth information, the fourth information including the verification result of the first information, the verification result of the first information including the verification result of the first detailed information of each debt item; The fourth information is output.

2. The risk-weighted asset system testing method according to claim 1, characterized in that: The single-transaction calculation mathematical model is established according to the second information, wherein the first information is used as input information of the single-transaction calculation mathematical model, including: Establishing a risk-weighted asset mathematical model according to the second information, and using the first detailed information as input information of the risk-weighted asset mathematical model; Solving the risk-weighted asset mathematical model to obtain fifth information, wherein the fifth information is the second risk information corresponding to each debt item calculated by the calculation rule of the reconstructed system; Establishing a first judgment model using the fifth information and the first risk information; Solving the first judgment model to obtain a verification result of the first risk-weighted asset, where the first risk information verification result includes but is not limited to pass and fail; A verification result of the first risk-weighted asset is obtained.

3. The risk-weighted asset system testing method according to claim 1, characterized in that: The step of establishing a batch comparison test mathematical model according to the first information and the third information includes: If the verification result of the first risk information is failure, outputting sixth information, wherein the sixth information is that the calculation rule of the reconstructed system does not meet the requirements; If the result of the verification of the first risk information is passed, a mathematical model for batch comparison test of debts is established based on the first information and the third information, the mathematical model for batch comparison test of debts is solved, and the calculation result of the mathematical model for batch comparison test of debts is obtained.

4. The risk-weighted asset system testing method according to claim 3, characterized in that: The step of establishing a debt batch comparison test mathematical model based on the first information and the third information includes: Acquiring seventh information, wherein the seventh information includes a difference tolerance, a summary index, and a summary dimension; Establishing a multi-dimensional comparison mathematical model according to the first information, the third information and the seventh information; Solving the multi-dimensional comparison mathematical model, wherein the output result of the multi-dimensional comparison mathematical model includes the verification result of the first detailed information of each debt item; Obtain calculation results of the multi-dimensional comparison mathematical model.

5. The risk-weighted asset system testing method according to claim 4, characterized in that: The establishing of a multi-dimensional comparison mathematical model according to the first information, the third information and the seventh information includes: A summary comparison table is established according to the summary index and the summary dimension, wherein the third information includes the second detailed information of each debt item, the second detailed information is calculated by a single-item measurement mathematical model, and the difference between the first detailed information and the second detailed information of each debt item is calculated under the same summary index and summary dimension; Establishing a second judgment model according to the difference and the difference tolerance, wherein the output result of the second judgment model includes a verification result of the first detailed information; Solving the second judgment model; Obtain the calculation results of the second judgment model and a summary comparison table.

6. The risk-weighted asset system testing method according to claim 5, characterized in that: The establishing of a second judgment model according to the difference and the difference tolerance comprises: If the difference is within the difference tolerance range, outputting the verification result of the first detailed information; If the difference is within the difference tolerance range, the verification result of the first detailed information, the first detailed information corresponding to the debt, and the second detailed information are output.

7. A risk-weighted asset system testing device, characterized in that: include: A first data acquisition module, used to acquire first information, wherein the first information includes database data, the database data includes each debt item and related information of each debt item, and the related information includes first risk information and first detailed information; A second information acquisition module, used to acquire second information, wherein the second information includes an operation rule of the reconstructed system; a single-transaction calculation module, configured to establish a single-transaction calculation mathematical model according to the second information, wherein the first information is used as input information of the single-transaction calculation mathematical model, and the single-transaction calculation model is solved to obtain third information, wherein the third information includes a verification result of the first risk information corresponding to each debt item; a batch comparison test module, configured to establish a batch comparison test mathematical model according to the first information and the third information, solve the batch comparison test mathematical model to obtain fourth information, wherein the fourth information includes a verification result of the first information, the verification result of the first information includes a verification result of the first detailed information of each debt item, and output the fourth information; The output module is used to output fourth information.

8. The risk-weighted asset system testing device according to claim 7, characterized in that: The single-bill calculation module comprises: a risk-weighted asset calculation module, configured to establish a risk-weighted asset mathematical model according to the second information, use the first detailed information as input information of the risk-weighted asset mathematical model, solve the risk-weighted asset mathematical model to obtain fifth information, wherein the fifth information is the second risk information corresponding to each debt item calculated by the calculation rules of the reconstructed system; A first judgment module is used to establish a first judgment model with the fifth information and the first risk information, and solve the first judgment model to obtain a verification result of the first risk-weighted asset. The verification result of the first risk information includes but is not limited to pass and fail, and the verification result of the first risk-weighted asset is obtained.

9. The risk-weighted asset system testing device according to claim 7, characterized in that: The batch comparison test module includes: A second judgment module is used to judge that if the verification result of the first risk information is not passed, then output sixth information, the sixth information being that the calculation rule of the reconstructed system does not meet the requirements; The third judgment module is used to determine if the result of the verification of the first risk information is passed, then establish a debt batch comparison test mathematical model based on the first information and the third information; solve the debt batch comparison test mathematical model to obtain the calculation result of the debt batch comparison test mathematical model.

10. The risk-weighted asset system testing device according to claim 9, characterized in that: The third judgment module includes: A third data acquisition module, used to acquire seventh information, where the seventh information includes difference tolerance, summary index and summary dimension; A multi-dimensional comparison module is used to establish a multi-dimensional comparison mathematical model based on the first information, the third information and the seventh information, and solve the multi-dimensional comparison mathematical model. The output result of the multi-dimensional comparison mathematical model includes the verification result of the first detailed information of each debt item, and obtains the calculation result of the multi-dimensional comparison mathematical model.

11. The risk-weighted asset system testing device according to claim 10, characterized in that: The multi-dimensional comparison module includes: A detail difference comparison module is used to establish a summary comparison table according to the summary index and the summary dimension, wherein the third information includes the second detail information of each debt item, the second detail information is calculated by a single-item measurement mathematical model, and the difference between the first detail information and the second detail information of each debt item is calculated under the same summary index and summary dimension; The fourth judgment module is used to establish a second judgment model according to the difference and the difference tolerance, the output result of the second judgment model includes the verification result of the first detailed information, solve the second judgment model, and obtain the calculation result of the second judgment model and the summary comparison table.

12. The risk-weighted asset system testing device according to claim 11, characterized in that: The fourth judgment module includes: A first sub-logic module is configured to output a verification result of the first detailed information if the difference is within the difference tolerance range; The second sub-logic module is used to determine if the difference is within the difference tolerance range, and then output the verification result of the first detailed information, the first detailed information corresponding to the debt, and the second detailed information.

13. A risk-weighted asset system testing device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of risk-weighted asset system testing as claimed in any one of claims 1 to 6 when executing the computer program.

14. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the risk-weighted asset system testing method according to any one of claims 1 to 6 are implemented.

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