Method for obtaining risk control compliance result, risk control compliance system, device and medium

Abstract

The invention provides a method for obtaining a risk control compliance result, a risk control compliance system, a device and a medium, the framework of the risk control compliance system comprises a data acquisition layer, an offline batch processing layer and a real-time layer, and the method comprises the following steps: the data acquisition layer acquires product information of a target product through a data acquisition tool; the offline batch processing layer determines section data of an effective risk control compliance rule result according to the product information; and the real-time layer calculates a real-time risk control compliance result at the current moment according to the section data of the risk control compliance rule result and the dynamic data of the target product. According to the method for obtaining the risk control compliance result provided by the embodiment of the invention, the product information is processed through the offline batch processing layer to obtain the section data of the risk control compliance rule result, and the real-time layer connection section data and the dynamic data are combined for processing, so that high-complexity product related information can be processed; and the real-time risk control compliance result of the target product can be rapidly obtained.

Description

Technical Field

[0001] The present application belongs to the field of data processing, and specifically relates to a method for obtaining risk control compliance results, a risk control compliance system, a device and a medium. Background Art

[0002] In the context of the increasing complexity of the global financial market and the continuous escalation of regulatory efforts, building a rigorous and efficient risk control and compliance monitoring system is of decisive significance to the strategic development and stable operation of wealth management companies. In particular, in the model of some wealth management companies adopting a two-tier investment structure, it is necessary to ensure the stable implementation of the top-level investment strategy and accurately grasp the risk context of the underlying assets. In the two-tier investment structure, there is a many-to-many situation in which one product holds multiple asset management plans and multiple products hold one asset management plan. The two-layer many-to-many relationship poses a great challenge to the real-time calculation efficiency of risk control indicators: on the one hand, the investment in the underlying assets of the special account will lead to changes in a large number of product-related risk control and compliance indicators. On the other hand, the subscription and redemption of the special account will also lead to changes in the underlying positions of a large number of products, resulting in an exponential increase in the amount of calculation tasks.

[0003] Therefore, in the investment decision-making process of financial products, a method is needed to obtain the risk control and compliance results of the target product from highly complex product-related information. Summary of the invention

[0004] In response to the problems existing in the above-mentioned prior art, a method for obtaining risk control compliance results, a risk control compliance system, a device and a medium are proposed. By using this method for obtaining risk control compliance results, a risk control compliance system, a device and a medium, the risk control compliance results of the target product can be obtained in highly complex product-related information.

[0005] This application provides the following solution.

[0006] In a first aspect, the present application provides a method for obtaining risk control compliance results, which is applied to a risk control compliance system, wherein the architecture of the risk control compliance system includes a data collection layer, an offline batch processing layer, and a real-time layer, and the method includes:

[0007] The data collection layer collects product information of target products through data collection tools;

[0008] The offline batch processing layer determines the cross-sectional data of the effective risk control compliance rule results based on the product information;

[0009] The real-time layer calculates the real-time risk control compliance results at the current moment based on the cross-sectional data of the risk control compliance rule results and the dynamic data of the target product.

[0010] In some possible embodiments, the real-time layer calculates the real-time risk control compliance results based on the cross-sectional data and the dynamic data of the target product, including:

[0011] The real-time layer calculates the real-time risk control compliance results at the current moment based on the cross-sectional data of the real-time risk control compliance results at the nearby moments and the dynamic data of the target products. The nearby moment is the moment closest to the current moment among the corresponding moments of the historical real-time risk control compliance results.

[0012] In some possible embodiments, the real-time layer calculates the real-time risk control compliance result at the current moment based on the cross-sectional data of the real-time risk control compliance result at the near moment and the dynamic data of the target product, including:

[0013] The real-time layer uses real-time streaming processing to calculate the real-time risk control compliance results at the current moment based on the cross-sectional data of the real-time risk control compliance results at the nearest moment and the dynamic data of the target product.

[0014] In some possible embodiments, the offline batch processing layer determines cross-sectional data of the effective risk control compliance rule results based on the product information, including:

[0015] The offline batch processing layer performs rule calculations based on product information and risk control compliance rule elements to obtain cross-sectional data of the effective risk control compliance rule results. The risk control compliance rule elements include at least one of the rule number, rule name, statistical caliber, statistical range and trigger threshold.

[0016] In some possible embodiments, the offline batch processing layer performs rule calculations based on product information and configured risk control compliance rule elements to obtain cross-sectional data of effective risk control compliance rule results, including:

[0017] The offline batch processing layer parses, cleans or organizes the product information to obtain processed product information;

[0018] The offline batch processing layer performs rule calculations based on the processed product information and risk control compliance rule elements to obtain cross-sectional data of the effective risk control compliance rule results.

[0019] In some possible embodiments, the risk control and compliance system further includes an application layer, and the method further includes:

[0020] The application layer displays risk results for target products based on real-time risk control and compliance results.

[0021] In some possible embodiments, the dynamic data of the target product includes investment decision data or market information data corresponding to the target product.

[0022] In some possible embodiments, the product information of the target product includes at least one of valuation information of the target product, asset management plan valuation information, news information, basic securities information, internal rating information, product attribute information and liquidation information.

[0023] In a second aspect, the present application provides a risk control compliance system, including a data collection layer, an offline batch processing layer, and a real-time layer;

[0024] The data collection layer is used to collect product information of target products through data collection tools;

[0025] The offline batch processing layer is used to determine the cross-sectional data of the effective risk control compliance rule results based on product information;

[0026] The real-time layer is used to calculate the real-time risk control compliance results at the current moment based on the cross-sectional data of the risk control compliance rule results and the dynamic data of the target product.

[0027] In some possible embodiments, the real-time layer is used to calculate the real-time risk control compliance result at the current moment based on the cross-sectional data of the real-time risk control compliance results at the nearby moments and the dynamic data of the target product. The nearby moment is the moment closest to the current moment among the corresponding moments of the historical real-time risk control compliance results.

[0028] In some possible embodiments, the real-time layer is used to calculate the real-time risk control compliance results at the current moment using real-time streaming processing based on the cross-sectional data of the real-time risk control compliance results at the nearest moment and the dynamic data of the target product.

[0029] In some possible embodiments, the offline batch processing layer is used to perform rule calculations based on product information and risk control compliance rule elements to obtain cross-sectional data of effective risk control compliance rule results. The risk control compliance rule elements include at least one of rule number, rule name, statistical caliber, statistical range and trigger threshold.

[0030] In some possible embodiments, the offline batch processing layer is used to parse, clean or organize the product information to obtain processed product information. The offline batch processing layer is also used to perform rule calculations based on the processed product information and risk control compliance rule elements to obtain cross-sectional data of the effective risk control compliance rule results.

[0031] In some possible embodiments, the risk control and compliance system further includes an application layer, and the application layer is used to display risk results for target products based on real-time risk control and compliance results.

[0032] In some possible embodiments, the dynamic data of the target product includes investment decision data or market information data corresponding to the target product.

[0033] In some possible embodiments, the product information of the target product includes at least one of valuation information of the target product, asset management plan valuation information, news information, basic securities information, internal rating information, product attribute information and liquidation information.

[0034] In a third aspect, the present application provides a computer-readable storage medium, which stores a program. When the program is executed by a multi-core processor, the multi-core processor executes the method for obtaining risk control compliance results as described above.

[0035] The method for obtaining risk control compliance results provided in the embodiment of the present application processes product information through an offline batch processing layer to obtain cross-sectional data of risk control compliance rule results, and processes the real-time layered cross-sectional data and dynamic data in combination. It can process highly complex product-related information and obtain real-time risk control compliance results for target products relatively quickly.

[0036] Other advantages of the present application will be explained in more detail with reference to the following description and drawings.

[0037] It should be understood that the above description is only an overview of the technical solution of the present application, so that the technical means of the present application can be more clearly understood and implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically described below by way of example. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The advantages and benefits described herein and other advantages and benefits will be apparent to those skilled in the art by reading the detailed description of the exemplary embodiments below. The accompanying drawings are only used for the purpose of illustrating the exemplary embodiments and are not to be considered as limiting the present application. In the accompanying drawings:

[0039] Figure 1a A schematic diagram of the structure of a hardware operating environment involved in an embodiment of the present application provided in the embodiment of the present application;

[0040] Figure 1b An architecture diagram of a risk control and compliance system provided in an embodiment of the present application;

[0041] Figure 2 A flowchart of a method for obtaining risk control compliance results provided in an embodiment of the present application;

[0042] Figure 3 A schematic diagram of a risk control and compliance system provided in an embodiment of the present application.

[0043] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0044] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0045] In the description of the embodiments of the present application, it should be understood that terms such as "including" or "having" are intended to indicate the presence of disclosed features, numbers, steps, behaviors, components, parts, or a combination thereof in the present specification, and do not exclude the possibility of the presence of one or more other features, numbers, steps, behaviors, components, parts, or a combination thereof.

[0046] Unless otherwise specified, “ / ” means or. For example, A / B can mean A or B. The “and / or” in this article is merely a way to describe the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0047] The terms "first", "second", etc. are used only to distinguish the same or similar technical features for the convenience of description, and should not be understood as indicating or implying the relative importance or quantity of these technical features. Thus, the features defined by "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise specified, the term "plurality" means two or more than two.

[0048] At present, mature risk control systems on the market only identify risks and compliance for some direct investment scenarios of products, but do not cover investment scenarios through asset management plans, and direct investment asset management plans do not conduct underlying asset penetration management, resulting in inaccurate risk compliance identification results in the final system during the investment decision-making process. In the process of investment decision-making, when faced with massive data calculations, the existing mature risk control systems on the market are unable to achieve millisecond-level calculations and second-level feedback on risk compliance identification results.

[0049] It should also be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0050] like Figure 1a As shown, Figure 1a It is a structural diagram of the hardware operating environment involved in the embodiment of the present application.

[0051] It should be noted that Figure 1aThe device for obtaining the risk control compliance result in the embodiment of the present application can be a terminal device such as a PC, a portable computer, etc.

[0052] like Figure 1a As shown, the device for obtaining risk control compliance results may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory, or it may be a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0053] Those skilled in the art will understand that Figure 1a The device structure for obtaining risk control compliance results shown in the figure does not constitute a limitation on the device for obtaining risk control compliance results, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0054] Figure 2 A flowchart of a method for obtaining risk control compliance results provided by this application. In this process, from the perspective of the device, the execution subject can be one or more electronic devices; from the perspective of the program, the execution subject can be the program installed on these electronic devices. In this embodiment, the execution subject of this method can be Figure 1a The device for obtaining risk control compliance results in the illustrated embodiment.

[0055] The method for obtaining the risk control compliance result provided in the embodiment of the present application is applied to the risk control compliance system, such as Figure 1b As shown, the architecture of the risk control and compliance system includes a data collection layer 100, an offline batch processing layer 200, a real-time layer 300, and an application layer 400. Figure 2 As shown, the method for obtaining risk control compliance results provided in the embodiment of the present application includes:

[0056] S201: The data collection layer collects product information of the target product through a data collection tool.

[0057] The target product in the embodiment of the present application may be a financial product or other financial product, which is not limited in the embodiment of the present application. The product information of the target product in the embodiment of the present application may include at least one of the valuation information of the target product, the valuation information of the asset management plan, information information, basic securities information, internal rating information, product attribute information and liquidation information. The data acquisition tool in the embodiment of the present application may be a data acquisition tool such as Sqoop, DataX, Flume, etc., which is not limited in the embodiment of the present application. The data collected by the data acquisition layer in the embodiment of the present application can be stored in a data warehouse.

[0058] S202: The offline batch processing layer determines the cross-sectional data of the effective risk control compliance rule results based on the product information.

[0059] The offline batch processing layer in the embodiment of the present application may be adjacent to the data acquisition layer. The offline batch processing layer in the embodiment of the present application may parse, clean or organize the product information to obtain the processed product information. Specifically, the offline batch processing layer may penetrate and parse the underlying assets of the product information to generate the corresponding asset management plan position information, and the product position information before and after penetration. The offline batch processing layer may also clean, organize, analyze and calculate the product information to ensure the accuracy, uniformity and integrity of the product information.

[0060] The offline batch processing layer in the embodiment of the present application performs rule calculations based on the processed product information to obtain cross-sectional data of the effective risk control compliance rule results. In some embodiments, the embodiment of the present application can define risk control compliance rule elements on the front-end page so that the offline batch processing layer can perform rule calculations based on the processed product information. The risk control compliance rule elements may include one or more of the rule number, rule name, statistical caliber, statistical range, and trigger threshold settings. In actual applications, the offline batch processing layer can use a scheduled task to run batch processing to perform rule calculations based on the processed product information and the risk control compliance rule elements configured on the front-end page to generate cross-sectional data of the risk control compliance rule results. The offline batch processing layer can use the Spark computing engine or the MapReduce computing engine to calculate the cross-sectional data of the configured and effective risk control compliance rule results.

[0061] S203: The real-time layer calculates the real-time risk control compliance result at the current moment based on the cross-sectional data of the risk control compliance rule results and the dynamic data of the target product.

[0062] In an embodiment of the present application, the real-time layer can calculate the real-time risk control compliance result at the current moment based on the cross-sectional data of the real-time risk control compliance result at the near moment and the dynamic data of the target product. The near moment is the moment closest to the current moment among the corresponding moments of the historical real-time risk control compliance results. For example, at time t, the real-time layer can obtain the real-time risk control compliance result corresponding to time t-1, and time t-1 is the near moment of time t. That is, the real-time layer can obtain the real-time risk control compliance result obtained by the last calculation, and the real-time risk control compliance result obtained by the last calculation is the real-time risk control compliance result at the near moment. The dynamic data of the target product can be the dynamic data of the target product corresponding to the time period from the near moment to the current moment. As an example, the dynamic data of the target product includes investment decision data or market information data corresponding to the target product.

[0063] In some possible embodiments, the real-time layer can calculate the real-time risk control compliance results at the current moment based on the cross-sectional data of the real-time risk control compliance results at the near moment and the dynamic data of the target product using a real-time streaming processing method. The streaming processing method includes a Kafka real-time streaming processing method, a Flink real-time streaming processing method, or other types of stream processing methods, which are not limited in the embodiments of the present application. The real-time layer can calculate the real-time risk control compliance results at the current moment based on the cross-sectional data of the real-time risk control compliance results at the near moment and the dynamic data of the target product. It should be noted that this continuously iterative calculation method can reduce the amount of calculation for each calculation of the real-time risk control compliance results, so that it can process highly complex product-related information and obtain the real-time risk control compliance results of the target product relatively quickly.

[0064] In some possible embodiments, the risk control compliance system provided in the embodiments of the present application also includes an application layer. The method for obtaining risk control compliance results provided in the embodiments of the present application also includes that the application layer displays risk results for the target product based on the real-time risk control compliance results. It should be noted that the application layer in the embodiments of the present application can provide an intuitive user interface, allowing users to query risk compliance rule results, maintain risk control compliance rule elements, etc., and can also implement user authority management to ensure that only authorized users can access sensitive data and maintain risk control compliance rule element information. The embodiments of the present application are not limited here.

[0065] In summary, the method for obtaining risk control compliance results provided in the embodiment of the present application processes product information through an offline batch processing layer to obtain cross-sectional data of risk control compliance rule results, and iteratively processes the cross-sectional data and dynamic data in combination through a real-time layer. It can process highly complex product-related information, adapt to a variety of investment decision-making scenarios, and can relatively quickly obtain real-time risk control compliance results for target products. The technical solution of the present application meets real-time requirements through a big data stream-batch integrated solution, using distributed, high-concurrency, multi-stream parallel, multi-level caching and other methods. The technical solution of the present application improves the accuracy of risk compliance identification results in the investment decision-making process by improving data processing efficiency, covering a large number of direct investments, and identifying risk rules in investment scenarios through asset management plans.

[0066] In the description of this specification, the description with reference to the terms "some possible embodiments", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application, and the above terms do not necessarily represent the same embodiment or example. Moreover, the described specific features, structures, materials or characteristics may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0067] About the method flow chart of the present application embodiment, some operations are described as different steps performed in a certain order. Such flow chart belongs to illustrative and non-restrictive. Some steps described in this article can be grouped together and performed in a single operation, or some steps can be divided into multiple sub-steps and can be performed in an order different from that shown in this article. Each step shown in the flow chart can be realized in any way by any circuit structure and / or tangible mechanism (for example, by software, hardware (for example, the logical function realized by processor or chip) etc. running on computer equipment and / or any combination thereof).

[0068] Those skilled in the art will appreciate that, in the method described in the above specific implementation, the writing order of each step does not mean a strict execution order, and the specific execution order of each step should be determined by its function and possible internal logic.

[0069] According to the method for obtaining risk control compliance results provided in the above embodiments, an embodiment of the present application also provides a risk control compliance system.

[0070] like Figure 3As shown, the risk control and compliance system provided in the embodiment of the present application includes a data collection layer 100, an offline batch processing layer 200 and a real-time layer 300.

[0071] The data collection layer 100 is used to collect product information of target products through data collection tools;

[0072] The offline batch processing layer 200 is used to determine the cross-sectional data of the effective risk control compliance rule results according to the product information;

[0073] The real-time layer 300 is used to calculate the real-time risk control compliance results at the current moment based on the cross-sectional data of the risk control compliance rule results and the dynamic data of the target product.

[0074] As a possible implementation method, the real-time layer is used to calculate the real-time risk control compliance result at the current moment based on the cross-sectional data of the real-time risk control compliance results at the nearby moments and the dynamic data of the target products. The nearby moment is the moment closest to the current moment among the corresponding moments of the historical real-time risk control compliance results.

[0075] As a possible implementation method, the real-time layer is used to calculate the real-time risk control compliance results at the current moment using real-time streaming processing based on the cross-sectional data of the real-time risk control compliance results at the nearest moment and the dynamic data of the target product.

[0076] As a possible implementation method, the offline batch processing layer is used to perform rule calculations based on product information and risk control compliance rule elements to obtain cross-sectional data of effective risk control compliance rule results. The risk control compliance rule elements include at least one of rule number, rule name, statistical caliber, statistical range and trigger threshold.

[0077] As a possible implementation method, the offline batch processing layer is used to parse, clean or organize product information to obtain processed product information. The offline batch processing layer is also used to perform rule calculations based on the processed product information and risk control compliance rule elements to obtain cross-sectional data of the effective risk control compliance rule results.

[0078] As a possible implementation method, the risk control and compliance system also includes an application layer, which is used to display risk results for target products based on real-time risk control and compliance results.

[0079] As a possible implementation method, the dynamic data of the target product includes investment decision data or market information data corresponding to the target product.

[0080] As a possible implementation method, the product information of the target product includes at least one of valuation information of the target product, asset management plan valuation information, news information, basic securities information, internal rating information, product attribute information and liquidation information.

[0081] It should be noted that the risk control and compliance system in the embodiment of the present application can implement the various processes of the embodiment of the aforementioned method and achieve the same effects and functions, which will not be repeated here.

[0082] According to some embodiments of the present application, a device for obtaining a risk control compliance result according to an embodiment of the present application is provided, for executing Figure 2 The method for obtaining risk control compliance results shown, the device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor so that the at least one processor can execute the method described in the above embodiment.

[0083] According to some embodiments of the present application, a non-volatile computer storage medium is provided for a method of obtaining risk control compliance results, on which computer executable instructions are stored, and the computer executable instructions are configured to execute, when executed by a processor: the method described in the above embodiments.

[0084] Computer-readable media include permanent and non-permanent, removable and non-removable media, and information storage can be achieved by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer-readable storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory, read-only memory, electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. In addition, although the operations of the method of the present application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. In addition, some steps can be omitted, multiple steps can be combined into one step, and / or one step can be decomposed into multiple sub-steps.

[0085] Although the spirit and principle of the present application have been described above with reference to several specific embodiments, it should be understood that the present application is not limited to the disclosed specific embodiments, and the division of various aspects does not mean that the features in these aspects cannot be combined. The present application is intended to cover various modifications and equivalent arrangements included in the spirit and scope of the attached claims.

Claims

1. A method for obtaining risk control compliance results, characterized in that: The method is applied to a risk control and compliance system, the architecture of which includes a data collection layer, an offline batch processing layer, and a real-time layer. The method includes: The data collection layer collects product information of the target product through a data collection tool; The offline batch processing layer determines cross-sectional data of the effective risk control compliance rule results according to the product information; The real-time layer calculates the real-time risk control compliance result at the current moment based on the cross-sectional data of the risk control compliance rule results and the dynamic data of the target product.

2. The method according to claim 1, characterized in that The real-time layer calculates the real-time risk control compliance results according to the cross-sectional data and the dynamic data of the target product, including: The real-time layer calculates the real-time risk control compliance result at the current moment based on the cross-sectional data of the real-time risk control compliance result at the nearby moment and the dynamic data of the target product. The nearby moment is the moment closest to the current moment among the corresponding moments of the historical real-time risk control compliance results.

3. The method according to claim 2, characterized in that The real-time layer calculates the real-time risk control compliance result at the current moment based on the cross-sectional data of the real-time risk control compliance result at the near moment and the dynamic data of the target product, including: The real-time layer calculates the real-time risk control compliance results at the current moment using real-time streaming processing based on the cross-sectional data of the real-time risk control compliance results at the nearby moments and the dynamic data of the target product.

4. The method according to claim 1, characterized in that: The offline batch processing layer determines cross-sectional data of the effective risk control compliance rule results according to the product information, including: The offline batch processing layer performs rule calculations based on product information and risk control compliance rule elements to obtain cross-sectional data of effective risk control compliance rule results. The risk control compliance rule elements include at least one of rule number, rule name, statistical caliber, statistical range and trigger threshold.

5. The method according to claim 4, characterized in that The offline batch processing layer performs rule calculations based on product information and configured risk control compliance rule elements to obtain cross-sectional data of effective risk control compliance rule results, including: The offline batch processing layer parses, cleans or organizes the product information to obtain processed product information; The offline batch processing layer performs rule calculations based on the processed product information and risk control compliance rule elements to obtain cross-sectional data of the effective risk control compliance rule results.

6. The method according to claim 1, characterized in that The risk control and compliance system further includes an application layer, and the method further includes: The application layer displays risk results for the target product according to the real-time risk control compliance results.

7. The method according to claim 1, characterized in that The dynamic data of the target product includes investment decision data or market information data corresponding to the target product.

8. The method according to any one of claims 1 to 7, characterized in that: The product information of the target product includes at least one of the valuation information of the target product, asset management plan valuation information, news information, basic securities information, internal rating information, product attribute information and liquidation information.

9. A risk control and compliance system, characterized in that: Includes data collection layer, offline batch processing layer and real-time layer; The data collection layer is used to collect product information of target products through data collection tools; The offline batch processing layer is used to determine cross-sectional data of the effective risk control compliance rule results according to the product information; The real-time layer is used to calculate the real-time risk control compliance results at the current moment based on the cross-sectional data of the risk control compliance rule results and the dynamic data of the target product.

10. A computer-readable storage medium storing a program, wherein when the program is executed by a multi-core processor, the multi-core processor executes the method according to any one of claims 1 to 8.

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