A product data processing method, device and equipment

Abstract

The embodiments of this specification provide a product data processing method, device and equipment, which can be used in the financial field or other fields. The method includes determining the target task based on the user's selection of attributes in the task attribute page; obtaining task information corresponding to the target task; when it is determined that the target product is a hook model according to the task information, obtaining indicator data corresponding to the hook model; wherein the hook model is used to calculate the profit and loss of the product in different stress scenarios; wherein the indicator data corresponding to different stress scenarios are different; based on the hook model and the indicator data, determining the result offset of the target product in the specified stress scenario. The embodiments of this specification can solve the problems of incomplete stress testing projects and inflexible measurement between products, and ensure the normal operation of the bank under various pressures.

Description

Technical Field

[0001] The present application relates to the financial field, and in particular to a product data processing method, device and equipment. It should be noted that the product data processing method, device and equipment disclosed in the present application can be used in the financial field, and can also be used in any field other than the financial field, and the application field of the product data processing method, device and equipment disclosed in the present application is not limited. Background Art

[0002] After the financial crisis, in order to enhance the security and stability of the financial system, the United States introduced enhanced prudential standards (EPS). Banks are required to submit qualitative and quantitative information on product stress test results to the Federal Reserve based on the size of their parent banks and institutions in the United States. It can be seen that stress testing of various bank products is becoming increasingly important to ensure that banks can operate normally under various pressures.

[0003] In the prior art, stress testing of various bank products is limited to the analysis of losses. This method cannot comprehensively test the products, and thus cannot ensure that the bank can operate normally under various pressures.

[0004] Therefore, the industry is in urgent need of a technical solution that can solve the above technical problems. Summary of the invention

[0005] The embodiments of this specification provide a product data processing method, device and equipment, which can solve the problems of incomplete stress testing items and inflexible measurement between products, thereby ensuring the normal operation of the bank under various pressures.

[0006] The product data processing method, device and equipment provided in this specification are implemented in the following ways.

[0007] A product data processing method, comprising: determining a target task based on a user's selection of attributes in a task attribute page; the target task indicating the need to calculate an offset of a target product in a specified stress scenario; obtaining task information corresponding to the target task; in the case where it is determined according to the task information that the target product is a hook model, obtaining indicator data corresponding to the hook model; wherein the hook model is used to calculate the profit and loss of a product in different stress scenarios; wherein different stress scenarios correspond to different indicator data; and determining a result offset of the target product in the specified stress scenario based on the hook model and the indicator data.

[0008] A product data processing device comprises: a first determination module, used to determine a target task based on a user's selection of attributes in a task attribute page; the target task indicates that an offset of a target product in a specified stress scenario needs to be calculated; a first acquisition module, used to obtain task information corresponding to the target task; a second acquisition module, used to obtain indicator data corresponding to the hook model when it is determined that the target product is a hook model according to the task information; wherein the hook model is used to calculate the profit and loss of a product in different stress scenarios; wherein the indicator data corresponding to different stress scenarios are different; a second determination module, used to determine the result offset of the target product in the specified stress scenario based on the hook model and the indicator data.

[0009] A product data processing device comprises at least one processor and a memory storing computer executable instructions, wherein when the processor executes the instructions, the steps of any method embodiment in the embodiments of the present specification are implemented.

[0010] A computer-readable storage medium stores computer instructions, which, when executed, implement the steps of any method embodiment in the embodiments of this specification.

[0011] This specification provides a product data processing method, device and equipment. In some embodiments, the target task can be determined based on the user's selection of attributes in the task attribute page; wherein the target task indicates that the offset of the target product in the specified stress scenario needs to be calculated; further, the task information corresponding to the target task can be obtained, and when the target product is judged to be a hook model according to the task information, the indicator data corresponding to the hook model is obtained; wherein the hook model is used to calculate the profit and loss of the product in different stress scenarios, and the indicator data corresponding to different stress scenarios are different; based on the hook model and the indicator data, the result offset of the target product in the specified stress scenario is determined. Since the income and loss measurement under the stress scenario can be carried out for each business type one by one or in batches, the stress test is no longer limited to the analysis of the loss, thereby solving the problems of incomplete stress test items and inability to flexibly carry out measurement between products. Since the PPNR loss and income of each product can be flexibly calculated according to the product tree hierarchical relationship, the PPNR calculation result table of the product dimension can be formed, which can greatly improve the flexible processing capability of the system. The implementation plan provided in this specification can not only solve the problems of incomplete stress testing items and inflexible measurement between products, but also greatly improve the system's flexible processing capabilities and ensure the normal operation of the bank under various pressures. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The drawings described herein are used to provide a further understanding of this specification, constitute a part of this specification, and do not constitute a limitation of this specification. In the drawings:

[0013] Figure 1 It is a flowchart of an embodiment of a product data processing method provided in this specification;

[0014] Figure 2 It is a schematic diagram of an embodiment of grouping and maintaining a PPNR product tree provided in this specification;

[0015] Figure 3 It is a schematic diagram of the module structure of an embodiment of a product data processing device provided in this specification;

[0016] Figure 4 This is a hardware structure block diagram of an embodiment of a product data processing server provided in this specification. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments in this specification, not all of the embodiments. Based on one or more embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the embodiments of this specification.

[0018] The following is an example of a specific application scenario to illustrate the implementation plan of this specification. Specifically, Figure 1 It is a flowchart of an embodiment of a product data processing method provided in this specification. Although this specification provides method operation steps or device structures as shown in the following embodiments or drawings, the method or device may include more or fewer operation steps or module units after partial combination based on routine or no creative labor.

[0019] An implementation scheme provided in this specification can be applied to a client, a server, etc. The client can include a terminal device, such as a smart phone, a tablet computer, etc. The server can include a single computer device, or a server cluster composed of multiple servers, or a server structure of a distributed system, etc.

[0020] It should be noted that the following embodiment description does not limit the technical solutions in other application scenarios that can be extended based on this specification. Figure 1 As shown, in an embodiment of a product data processing method provided in this specification, the method may include the following steps.

[0021] S0: Determine a target task based on the user's selection of attributes in the task attribute page; the target task indicates that the offset of the target product in a specified stress scenario needs to be calculated.

[0022] Among them, the task attribute page may include one or more task attribute boxes. The task attribute box can be used to input or select task attributes. Task attributes may include stress scenario attributes, product attributes, time attributes, etc. In some embodiments, the task attributes may be input by the user through a keyboard, a touch pen, etc., or may be determined by the user by selecting a drop-down menu in the task attribute bar, and this specification does not limit this. The target task can be determined based on the user's selection of attributes in the task attribute page. The target task may indicate that the user needs to calculate the offset of the target product in a specified stress scenario. Among them, the offset may include losses and gains. In some implementation scenarios, the offset corresponding to the product may be called product profit and loss.

[0023] In some embodiments, one or more target tasks may be determined based on the user's selection of attributes in the task attribute page. For example, in some embodiments, based on the user's selection of attributes in the task attribute page, the target task may be determined to be the calculation of the profit and loss of bill discount in a mild stress scenario and the profit and loss of bill rediscount in a moderate and severe stress scenario. Of course, the above is only an exemplary description, and the target tasks are not limited to the above examples. The technical personnel in the relevant field may make other changes under the inspiration of the technical essence of this application, but as long as the functions and effects achieved are the same or similar to those of this application, they should be covered within the scope of protection of this application.

[0024] In some embodiments, a user can send a task calculation request to the server, and then the server displays a task attribute page for the user to select a stress scenario, enter a forecast start date and forecast period, select a product for which calculation needs to be initiated, etc. The server can further determine the target task based on the user's selection of attributes in the task attribute page.

[0025] In some embodiments, before determining the target task based on the user's selection of attributes in the task attribute page, it may include: obtaining macroeconomic indicator data from an indicator database; simulating different stress scenarios based on the macroeconomic indicator data and a preset regression model, and determining indicator data corresponding to different stress scenarios; wherein the different stress scenarios include at least one of the following: baseline, mild, moderate, severe, and extremely severe.

[0026] In some implementation scenarios, the indicator database can be an Oracle database, a MySQL database, etc. The indicator database can include macroeconomic indicator data describing domestic and international economic conditions. In some implementation scenarios, macroeconomic indicator data can be divided into wind economic data and EIU economic data according to the data source. Among them, wind economic data and EIU economic data are two different sources of macroeconomic data in the market, which can be obtained and imported by the business party through other systems.

[0027] In some implementation scenarios, after obtaining macroeconomic indicator data from the indicator database, different stress scenarios can be simulated based on the macroeconomic indicator data and the preset regression model to determine the indicator data corresponding to different stress scenarios. For example, relying on the vector autoregression model and the multivariate linear regression model, accessing macroeconomic indicator data, simulating five stress scenarios such as baseline, mild, moderate, severe, and extremely severe to carry out scenario calculations, and thus determining the indicator data corresponding to different stress scenarios.

[0028] In some embodiments, the index data may include at least one of the following: GDP growth rate / GDP index, year-on-year growth of M2 supply, year-on-year growth of total export value, year-on-year growth of total retail sales of consumer goods, year-on-year growth of completed fixed asset investment, year-on-year growth of average price of commercial housing, consumer price index, producer price index, 3-month treasury bond yield, 10-year treasury bond yield, USD / RMB exchange rate. Of course, the above is only an exemplary description, and the index data is not limited to the above examples. Technical personnel in the relevant field may make other changes under the inspiration of the technical essence of this application, but as long as the functions and effects achieved are the same or similar to those of this application, they should be covered within the scope of protection of this application.

[0029] In some embodiments, the method of determining the target task based on the user's selection of the attributes in the task attribute page may also include: obtaining all stress test products; constructing all stress test products into a product tree; the product tree includes multiple product dimensions, the product dimensions include a top-level directory, a preset number of product directories, and leaf nodes; wherein the leaf nodes include a hook model for the corresponding product; the hook model can be set according to product features; and grouping and maintaining the product tree. The preset number may be 3, 5, etc., which can be set according to the actual scenario, and this specification does not limit this.

[0030] like Figure 2 As shown, Figure 2It is a schematic diagram of an embodiment of grouping and maintaining the PPNR product tree provided in this specification. Among them, PPNR represents net income before provision. In this embodiment, all stress test business products are constructed into a product tree, the product tree is maintained according to the loss and income dimensions, and the hook model function is provided at the leaf node of the product. Among them, S401 is the top-level directory of the product tree, which can be used to display the major product category information (such as interest income, interest expenditure, non-interest income, non-interest expenditure, loan category, interest-bearing assets, deposit category, etc.), S402 is the first-level product directory, which can be used to display the first-level product information (such as bills, etc.), and the user can customize the maintenance of the first-level product information, S403 is the second-level product directory, which can be used to display the second-level product information (such as bill financing, etc.), and the user can customize the maintenance of the second-level product information, S404 is the third-level product directory, which can be used to display the third-level product information (such as bill discount, bill rediscount, etc.), and the user can customize the maintenance of the third-level product information, S405 is the product hook model, at the leaf node of each product, the user can maintain the hook model (also called stress test model) required for the product, such as a balance model or an interest rate model. In this embodiment, the product tree can be divided according to the unified products in the line, and then the third-level products are taken. Of course, in some embodiments, the hook model of the leaf node can be flexibly customized by the business user according to the product characteristics. It should be noted that the model needs to be maintained before it can be hooked to the product, and the product of the hook model can be used to calculate the profit and loss of the product in different stress scenarios. The model can only be hung on the leaf node of the product to participate in the calculation.

[0031] In some embodiments, the linkage model may include a balance model, a consumption model, etc. For example, the linkage model of bill discounting may be a balance model and an interest rate model. Specifically, the formula of the balance model may be expressed as:

[0032] The forecast balance at the time of the bill discount of period T = {[balance of product number of period T = '12'] / [balance of product number of period T-1 = '12']}×[balance at the time of product number of period T-1 = '1500100001']

[0033] Among them, T represents the period, and '12' and '1500100001' represent the product numbers.

[0034] The formula of the interest rate model can be expressed as:

[0035] The interest rate of the bill discount product of period T = [macroeconomic variables of month T] + {[(T-1 month interest rate difference) + (T-2 month interest rate difference) + (T-3 month interest rate difference)] / 3}

[0036] Among them, the macroeconomic variable of month T can be understood as the benchmark interest rate of month T, which is equal to the 6-month SHIBOR. SHIBOR represents the interbank lending rate. The spread of month T-1 can be expressed as (interest income of the month when product number of period T-1 is '1500100001') / (average balance of the month when product number of period T-1 is '1500100001')-(macroeconomic variable of month T-1), and the spread of month T-2 can be expressed as (T- The interest rate spread for T-3 is expressed as (interest income for the month when product number T-2 is ‘1500100001’) / (average balance for the month when product number T-2 is ‘1500100001’)-(macroeconomic variables for T-2). The interest rate spread for T-3 is expressed as (interest income for the month when product number T-3 is ‘1500100001’) / (average balance for the month when product number T-3 is ‘1500100001’)-(macroeconomic variables for T-3).

[0037] Of course, the above is only an exemplary explanation, and the linkage model is not limited to the above example. It can also be a linear regression model: Y(t0) = coefficient 1×variable 1(t0) + coefficient 2×variable 2(t0) + coefficient 3×variable 3(t0) + constant term. Technical personnel in the relevant field may make other changes based on the technical essence of this application, but as long as the functions and effects achieved are the same or similar to those of this application, they should be covered within the scope of protection of this application.

[0038] S2: Acquire task information corresponding to the target task.

[0039] In the embodiment of the present specification, after the target task is determined, task information corresponding to the target task may be obtained.

[0040] In some embodiments, the target task may include a target product, a specified stress scenario, etc., so information corresponding to the target product, information on the specified stress scenario, etc. may be obtained accordingly based on the target task.

[0041] S4: When it is determined that the target product is a hook model according to the task information, obtain indicator data corresponding to the hook model; wherein the hook model is used to calculate the profit and loss of the product in different stress scenarios; wherein the indicator data corresponding to different stress scenarios are different.

[0042] In the embodiment of this specification, after obtaining the task information corresponding to the target task, it can be determined whether the target product is a hook model according to the task information. The hook model can be used to calculate the profit and loss of the product in different stress scenarios.

[0043] Since the model needs to be well maintained before it can be linked to the product, the product linked to the model can be used to calculate the profit and loss of the product under different stress scenarios. The model can only be hung on the leaf node of the product to participate in the calculation.

[0044] In some embodiments, it is possible to verify whether the product selected in the target task is a hook model based on the pressure scenario information, product information, and model information corresponding to the target task. The pressure scenario information can be obtained from other subsystems, and the product information and model information can be obtained from the information maintained by the business user before initiating the calculation.

[0045] In some implementation scenarios, the system will verify whether the model is maintained and the model analysis. For example, if the verification result indicates that the product leaf node is not linked to the model, calculation cannot be made; if the model formula parsing fails or the data acquisition fails during the verification process, calculation cannot be made.

[0046] In the embodiment of this specification, when it is determined that the target product is a hook model, the indicator data corresponding to the hook model can be obtained, wherein the indicator data corresponding to different pressure scenarios are different.

[0047] In some embodiments, when it is determined that the target product is a hook model according to the task information, the method may further include: adding the target task to an asynchronous task queue; correspondingly, obtaining indicator data corresponding to the hook model; and determining the result offset of the target product in the specified stress scenario based on the hook model and the indicator data. In the asynchronous task queue, multiple tasks are calculated asynchronously, which does not require online connection and can improve calculation efficiency.

[0048] In some embodiments, when the target product is not a hook model, it can be prompted that the target product is not a hook model so that the model can be maintained in the product grouping model maintenance function.

[0049] In some implementation scenarios, it is possible to verify whether the product selected in the target task is a hook model based on the scenario information, product information, and model information corresponding to the target task. If so, the target task is added to the asynchronous task queue so that the income and loss of the product in the target task can be predicted in the asynchronous task queue later. If not, it can be prompted that the product in the target task is not a hook model, and then the model can be maintained in the product grouping model maintenance function.

[0050] In some embodiments, after adding the target task to the asynchronous task queue, the indicator data corresponding to the hook model can be obtained. The indicator data may include at least one of the following: GDP growth rate / GDP index, M2 supply year-on-year growth, total export value year-on-year growth, total retail sales of consumer goods year-on-year growth, fixed asset investment completion amount year-on-year growth, average commodity housing price year-on-year growth, consumer price index, producer price index, 3-month treasury bond yield, 10-year treasury bond yield, and USD / RMB exchange rate.

[0051] In some implementation scenarios, after adding the target task to the asynchronous task queue, the asynchronous task module can parse the formula corresponding to the hook model of the task and obtain the corresponding indicator data. For example, if the formula contains a variable for obtaining data, such as "6-month SHIBOR", the corresponding data can be obtained based on the variable.

[0052] In some embodiments, since different stress scenarios correspond to different indicator data, the corresponding indicator data can be obtained according to the selected stress scenario. For example, if the baseline stress scenario is selected, the indicator data corresponding to the baseline stress scenario can be obtained; if the moderate stress scenario is selected, the indicator data corresponding to the moderate stress scenario can be obtained, and so on.

[0053] S6: Based on the hook model and the indicator data, determine the result offset of the target product in the specified stress scenario.

[0054] In the embodiments of this specification, after obtaining the indicator data corresponding to the hook model, the result offset of the target product in the specified stress scenario can be determined based on the hook model and the indicator data. The result offset can include a profit and loss result. The profit and loss result can include a measurement result of gains and losses.

[0055] For example, in some implementation scenarios, after obtaining the indicator data corresponding to the linkage model, the forecast results of each period can be measured cyclically based on the linkage model and indicator data according to the forecast period number in the calculation task set by the business user, and the profit and loss measurement results of the target product in each forecast period under the specified stress scenario can be obtained.

[0056] In some embodiments, after determining the result offset of the target product in the specified stress scenario, the result offset of the target product in the specified stress scenario can also be summarized according to the corresponding product dimension. For example, in some implementation scenarios, after determining the profit and loss result of the target product in the specified stress scenario, the profit and loss result of the target product in the specified stress scenario can also be summarized according to the corresponding product dimension. Table 1 shows the result after summarizing the profit and loss result of the bill discount in the specified stress scenario according to the corresponding product dimension.

[0057] Table 1

[0058]

[0059] In some embodiments, after the results are summarized, the calculation results can be saved to the database in product dimensions. The product dimension refers to various subdivided products in the industry, such as Figure 2 The PPNR product tree lists the first-level product catalog, second-level product catalog, and third-level product catalog.

[0060] In some embodiments, after the calculation results are saved in the database in product dimensions, users' queries and downloads of the task calculation results can also be received.

[0061] In the embodiments of this specification, during the actual PPNR calculation process, users can be supported to flexibly initiate PPNR calculation for a single product combination or multiple product combinations.

[0062] In the embodiments of this specification, by grouping, displaying and storing bank products and linking models to product leaf nodes, it is not only convenient for users to view the hierarchical relationships and model linkage relationships of products in each dimension, but also for the results of PPNR calculation, the PPNR losses and gains of each product and its sub-products can be flexibly summarized according to the product tree hierarchy to form a PPNR calculation result table of the product dimension, thereby greatly improving the flexible processing capabilities of the system.

[0063] In the embodiments of this specification, the stress test calculation tasks can be customized according to user needs, stress tests of different severity levels can be carried out on each product as needed, and the stress test measurement results can be summarized and displayed by product dimension.

[0064] In the embodiments of this specification, under stress scenarios of different severity, linkage models can be introduced for various types of asset and liability business types to carry out profit and loss measurement. Flexible model configuration functions and configuration functions of flexible linkage models for business types can be provided to business users. Revenue and loss measurement under stress scenarios can be carried out for each business type one by one or in batches, thereby solving problems such as incomplete stress testing projects and inability to flexibly carry out measurement between products.

[0065] In the embodiments of this specification, a flexible model configuration function can be provided for users, supporting users to initiate profit and loss forecast calculations based on free product combinations. It can also rely on historical global macroeconomic data to dynamically and forward-lookingly predict the losses and gains of various asset and liability businesses in the next nine quarters for banks under different levels of stress scenarios, so as to ensure that the bank still has sufficient capital to maintain normal operations under various pressures.

[0066] Of course, the above is only an exemplary description, and the embodiments of this specification are not limited to the above examples. Technical personnel in the relevant field may make other changes based on the technical essence of this application. However, as long as the functions and effects achieved are the same or similar to those of this application, they should be included in the scope of protection of this application.

[0067] From the above description, it can be seen that the embodiment of the present application can determine the target task based on the user's selection of the attributes in the task attribute page; wherein, the target task indicates that the offset of the target product in the specified stress scenario needs to be calculated; further, the task information corresponding to the target task can be obtained, and when the target product is judged to be a hook model according to the task information, the indicator data corresponding to the hook model is obtained; wherein, the hook model is used to calculate the profit and loss of the product in different stress scenarios, and the indicator data corresponding to different stress scenarios are different; based on the hook model and the indicator data, the result offset of the target product in the specified stress scenario is determined. Since the income and loss measurement under the stress scenario can be carried out for each business type one by one or in batches, the stress test is no longer limited to the analysis of the loss, thereby solving the problems of incomplete stress test items and inability to flexibly carry out measurement between products. Since the PPNR loss and income of each product can be flexibly calculated according to the product tree hierarchical relationship, a PPNR calculation result table of the product dimension can be formed, thereby greatly improving the system's flexible processing capabilities.

[0068] In this specification, each embodiment of the above method is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. For relevant parts, please refer to the partial description of the method embodiment.

[0069] Based on the product data processing method described above, one or more embodiments of this specification also provide a product data processing device. The device may include a system (including a distributed system), software (application), module, component, server, client, etc. using the method described in the embodiment of this specification and a device combined with necessary implementation hardware. Based on the same innovative concept, the device in one or more embodiments provided in the embodiment of this specification is as described in the following embodiments. Since the implementation scheme and method of the device to solve the problem are similar, the implementation of the specific device in the embodiment of this specification can refer to the implementation of the aforementioned method, and the repetitions will not be repeated. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0070] Specifically, Figure 3 is a schematic diagram of a module structure of an embodiment of a product data processing device provided in this specification, such as Figure 3 As shown, a product data processing device provided in this specification may include: a first determination module 120 , a first acquisition module 122 , a second acquisition module 124 , and a second determination module 126 .

[0071] The first determination module 120 may be used to determine a target task based on a user's selection of an attribute in a task attribute page; the target task indicates that an offset of a target product in a specified stress scenario needs to be calculated;

[0072] A first acquisition module 122 may be used to acquire task information corresponding to the target task;

[0073] The second acquisition module 124 may be used to acquire the indicator data corresponding to the hook model when it is determined according to the task information that the target product is a hook model; wherein the hook model is used to calculate the profit and loss of the product in different stress scenarios; wherein different stress scenarios correspond to different indicator data;

[0074] The second determination module 126 may be configured to determine the result offset of the target product in the specified stress scenario based on the hook model and the indicator data.

[0075] It should be noted that the above-mentioned device may also include other implementation modes according to the description of the method embodiment. The specific implementation mode may refer to the description of the relevant method embodiment, which will not be described one by one here.

[0076] The present specification also provides an embodiment of a product data processing device, comprising a processor and a memory for storing processor executable instructions, wherein the instructions, when executed by the processor, implement the following steps: determining a target task based on a user's selection of attributes in a task attribute page; the target task indicating the need to calculate an offset of a target product in a specified stress scenario; obtaining task information corresponding to the target task; in the case where it is determined according to the task information that the target product is a hook model, obtaining indicator data corresponding to the hook model; wherein the hook model is used to calculate the profit and loss of a product in different stress scenarios; wherein different stress scenarios correspond to different indicator data; and determining a result offset of the target product in the specified stress scenario based on the hook model and the indicator data.

[0077] It should be noted that the above-mentioned device may also include other implementations according to the description of the method or device embodiment. The specific implementation methods can refer to the description of the relevant method embodiments, which will not be described one by one here.

[0078] The method embodiments provided in this specification can be executed in a mobile terminal, a computer terminal, a server or a similar computing device. Taking running on a server as an example, Figure 4 This is a hardware structure block diagram of an embodiment of a product data processing server provided in this specification. The server may be a product data processing device or a product data processing apparatus in the above-mentioned embodiment. Figure 4As shown, the server 10 may include one or more (only one is shown in the figure) processors 100 (the processor 100 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 200 for storing data, and a transmission module 300 for communication functions. A person skilled in the art can understand that Figure 4 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 4 More or fewer components shown in the figure may also include other processing hardware, such as a database or multi-level cache, GPU, or other hardware with Figure 4 Different configurations are shown.

[0079] The memory 200 can be used to store software programs and modules of application software, such as program instructions / modules corresponding to the product data processing method in the embodiment of this specification. The processor 100 executes various functional applications and data processing by running the software programs and modules stored in the memory 200. The memory 200 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 200 may further include a memory remotely arranged relative to the processor 100, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0080] The transmission module 300 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission module 300 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission module 300 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0081] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0082] The methods or devices described in the above embodiments provided in this specification can implement business logic through computer programs and record them on storage media, and the storage media can be read and executed by computers to achieve the effects of the solutions described in the embodiments of this specification. The storage medium may include a physical device for storing information, which is usually to digitize the information and then store it in a medium using electrical, magnetic or optical methods. The storage medium may include: devices that use electrical energy to store information, such as various types of memories, such as RAM, ROM, etc.; devices that use magnetic energy to store information, such as hard disks, floppy disks, magnetic tapes, magnetic core memories, bubble memories, and U disks; devices that use optical methods to store information, such as CDs or DVDs. Of course, there are other types of readable storage media, such as quantum memories, graphene memories, and so on.

[0083] The above-mentioned product data processing method or device embodiment provided in this specification can be implemented by a processor in a computer executing corresponding program instructions, such as using the C++ language of the Windows operating system to implement it on a PC, on a Linux system, or other methods such as using Android or iOS system programming languages ​​to implement it on a smart terminal, as well as processing logic based on a quantum computer, etc.

[0084] It should be noted that the devices, equipment, and systems described in the specification may also include other implementation methods according to the description of the relevant method embodiments. The specific implementation methods can refer to the description of the corresponding method embodiments, which will not be described one by one here.

[0085] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the hardware + program embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0086] For the convenience of description, the above devices are described in various modules according to their functions. Of course, when implementing one or more of the present specification, the functions of some modules can be implemented in the same or more software and / or hardware, and the modules that implement the same function can also be implemented by a combination of multiple sub-modules or sub-units.

[0087] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices, equipment, and systems according to the embodiments of the present invention. It should be understood that it can be implemented by computer program instructions, and these computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the specified function. These computer program instructions can also be stored in a computer-readable memory that can guide the computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, and the instruction device is implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0088] Those skilled in the art will appreciate that one or more embodiments of the present specification may be provided as a method, system or computer program product. Therefore, one or more embodiments of the present specification may be provided in the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware.

[0089] The above is only an example of one or more embodiments of this specification and is not intended to limit one or more embodiments of this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application should be included in the scope of the claims.

Claims

1. A product data processing method, characterized in that: include: Get all stress testing products; All stress testing products are constructed into a product tree; the product tree includes multiple product dimensions, and the product dimensions include a top-level directory, a preset number of product directories, and leaf nodes; wherein the leaf nodes include a hook model of the corresponding product; the hook model can be set according to product features; Performing group maintenance on the product tree; Determine a target task based on a user's selection of a property in a task property page; the target task indicates that an offset of a target product in a specified stress scenario needs to be calculated, and the target product corresponds to a plurality of different stress scenarios; Acquire task information corresponding to the target task; Judging whether the target product is a hook model according to the task information, including: verifying whether the target product is a hook model according to the pressure scenario information, product information, and model information corresponding to the target task; In the case where it is determined according to the task information that the target product is a hook model, indicator data corresponding to the hook model is obtained; wherein the hook model is used to calculate the profit and loss of the product in a plurality of different stress scenarios; wherein the indicator data corresponding to different stress scenarios are different; based on the hook model and the indicator data, the result offset of the target product in the specified stress scenario is determined.

2. The method according to claim 1, characterized in that The task attribute page includes at least the following attributes: stress scenario attributes, product attributes, and time attributes.

3. The method according to claim 1, characterized in that The method of determining the target task based on the user's selection of the attribute in the task attribute page includes: Obtain macroeconomic indicator data from the indicator database; Based on the macroeconomic indicator data and the preset regression model, different stress scenarios are simulated to determine the indicator data corresponding to the different stress scenarios; wherein the different stress scenarios include at least one of the following: baseline, mild, moderate, severe, and extremely severe.

4. The method according to claim 3, characterized in that The indicator data include at least one of the following: GDP growth rate / gross domestic product index, year-on-year growth of M2 supply, year-on-year growth of total export value, year-on-year growth of total retail sales of consumer goods, year-on-year growth of completed fixed asset investment, year-on-year growth of average price of commercial housing, consumer price index, producer price index, 3-month treasury bond yield, 10-year treasury bond yield, and USD / RMB exchange rate.

5. The method according to claim 1, characterized in that The linkage model includes a balance model and a consumption model.

6. The method according to claim 1, characterized in that In the case where it is determined according to the task information that the target product is a hook model, the method further includes: Add the target task to the asynchronous task queue; Accordingly, indicator data corresponding to the hook model is obtained; based on the hook model and the indicator data, the result offset of the target product in the specified stress scenario is determined.

7. The method according to claim 1, characterized in that After determining the result offset of the target product in the specified pressure scenario, the method further includes: The result offsets of the target product in the specified stress scenario are summarized according to the corresponding product dimensions.

8. A product data processing device, characterized in that: include: The first determination module is used to obtain all stress test products; construct all stress test products into a product tree; the product tree includes multiple product dimensions, the product dimensions include a top-level directory, a preset number of product directories, and leaf nodes; wherein the leaf node includes a hook model of the corresponding product; the hook model can be set according to product characteristics; group and maintain the product tree; determine the target task based on the user's selection of attributes in the task attribute page; the target task indicates that the offset of the target product in the specified stress scenario needs to be calculated, and the target product corresponds to multiple different stress scenarios; The first acquisition module is used to acquire task information corresponding to the target task; determine whether the target product is a hook model according to the task information, including: verifying whether the target product is a hook model according to the pressure scenario information, product information, and model information corresponding to the target task; A second acquisition module is used to acquire indicator data corresponding to the hook model when it is determined according to the task information that the target product is a hook model; wherein the hook model is used to calculate the profit and loss of the product in different stress scenarios; wherein different stress scenarios correspond to different indicator data; The second determination module is used to determine the result offset of the target product in the specified stress scenario based on the hook model and the indicator data.

9. A product data processing device, characterized in that: The method comprises at least one processor and a memory storing computer executable instructions, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the instructions.

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

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