Financial risk control method and device, equipment and storage medium

Abstract

The invention relates to a financial risk control method and device, equipment and a storage medium. The financial risk control method comprises the steps of obtaining risk data of a set investment type in a financial investment field; performing risk classification and risk grading processing on the risk data to obtain a risk classification grading result; generating a risk early warning report according to the risk classification grading result and a set risk index so as to carry out risk control based on the risk early warning report; wherein the set risk index is used for quantifying and representing the risk bearing capability and / or investment demand of the investor. According to the method provided by the invention, the accuracy of risk control is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer technology, and in particular to a financial risk control method, device, equipment and storage medium. BACKGROUND

[0002] The existing risk control technology mostly depends on traditional rule engines or simple statistical models, and is difficult to cope with complex and changeable financial environment, and has problems such as risk identification lag, rough classification, and untimely early warning, resulting in low risk control precision. SUMMARY

[0003] In order to solve the above technical problems, the present application provides a financial risk control method, device, equipment and storage medium.

[0004] In a first aspect, the present application provides a financial risk control method, comprising:

[0005] obtaining risk data of a set investment type in the field of financial investment;

[0006] performing risk classification and risk grading processing on the risk data to obtain a risk classification and grading result;

[0007] generating a risk warning report according to the risk classification and grading result and a set risk indicator, so as to perform risk control based on the risk warning report; wherein the set risk indicator is used to quantify and represent the risk bearing capacity and / or investment demand of the investor.

[0008] Optionally, the set investment type includes a fund investment project and / or a local investment project; wherein the risk data of the fund investment project includes data of at least one category of honor dynamics, financing dynamics, business dynamics and talent dynamics; and the risk data of the local investment project includes data of at least one category of scientific and technological achievements, business development, patent achievements and cooperation information.

[0009] Optionally, the risk classification and grading processing on the risk data to obtain the risk classification and grading result comprises:

[0010] extracting at least one set risk category corresponding risk information from the risk data, wherein the set risk category is divided into a plurality of risk subcategories;

[0011] comprehensively analyzing the risk identifiers of the plurality of risk subcategories in the risk information to determine the risk level of the set risk category, wherein the risk identifier is used to represent the risk degree of the risk subcategory;

[0012] wherein the risk classification and grading result includes the set risk category and the risk level of the set risk category.

[0013] Optionally, the risk identifiers of multiple risk subcategories in the comprehensive analysis risk information are analyzed to determine the risk level of the set risk category, including:

[0014] The risk identifier of each risk subcategory is determined to correspond to the set risk level;

[0015] The multiple set risk levels of multiple risk subcategories and the set weight of each risk subcategory are comprehensively analyzed to determine the risk level of the set risk category.

[0016] Optionally, the set risk category is judicial risk, operational risk, regulatory risk, public opinion risk, business risk, or related risk; wherein the judicial risk is used to assess the judicial risk level of the enterprise; the operational risk is used to assess the operational risk level of the enterprise; the regulatory risk is used to assess the regulatory risk level of the enterprise; the public opinion risk is used to assess the public opinion risk level of the enterprise; the business risk is used to assess the operational stability and legal compliance of the enterprise; and the related risk is used to assess the risk level of the related entity of the enterprise.

[0017] Optionally, according to the risk classification and grading result and the set risk indicator, a risk warning report is generated, including:

[0018] According to the risk classification and grading result and the set risk indicator, a risk warning is performed through a financial data model;

[0019] According to the risk warning, a risk warning report is generated through a large language model, wherein the risk warning report includes risk processing suggestions.

[0020] Optionally, risk data of the set investment type in the financial investment field is obtained, including:

[0021] The risk content is determined by performing risk analysis on the risk file of the set investment type in the financial investment field tracked in real time;

[0022] According to the risk content in the risk file, risk data of different levels and different categories is constructed, and the risk data is arranged in a structured form.

[0023] In a second aspect, the embodiments of the present disclosure provide a financial risk control device, including:

[0024] The acquisition unit is configured to obtain risk data of a set investment type in a financial investment field;

[0025] The risk classification and grading unit is configured to perform risk classification and risk grading processing on the risk data to obtain a risk classification and grading result;

[0026] The report generation unit is configured to generate a risk warning report according to the risk classification grading result and a set risk index, so as to control the risk based on the risk warning report; wherein the set risk index is used to quantify and represent the risk bearing capacity and / or investment demand of the investor.

[0027] In a third aspect, the embodiments of the present disclosure provide an electronic device, comprising:

[0028] a memory;

[0029] a processor; and

[0030] a computer program;

[0031] The computer program is stored in the memory and is configured to be executed by the processor to implement the method of the first aspect as described above.

[0032] In a fourth aspect, the embodiments of the present disclosure provide a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the method of the first aspect as described above.

[0033] The financial risk control method provided by the present disclosure comprises: obtaining risk data of a set investment type in a financial investment field; performing risk classification and risk grading processing on the risk data through a large language model to obtain a risk classification grading result; generating a risk warning report according to the risk classification grading result and a set risk index, so as to control the risk based on the risk warning report; wherein the set risk index is used to quantify and represent the risk bearing capacity and / or investment demand of the investor, thereby improving the accuracy of risk control. BRIEF DESCRIPTION OF DRAWINGS

[0034] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present disclosure and, together with the specification, serve to explain the principles of the present disclosure.

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0036] Figure 1 A flowchart of a financial risk control method provided by the embodiments of the present disclosure;

[0037] Figure 2 A flowchart of another financial risk control method provided by the embodiments of the present disclosure;

[0038] Figure 3A structural schematic diagram of a financial risk control device provided by an embodiment of the present disclosure is shown in the figure.

[0039] Figure 4 A structural schematic diagram of an electronic device provided by an embodiment of the present disclosure is shown in the figure. DETAILED DESCRIPTION

[0040] In order to more clearly understand the above-mentioned purposes, features and advantages of the present disclosure, the solutions of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0041] In the following description, many specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure can also be implemented in other ways different from those described herein; obviously, the embodiments in the description are only some of the embodiments of the present disclosure, not all the embodiments.

[0042] To solve the above technical problems, the present embodiment provides a financial risk control method, which integrates multi-source data such as judicial, operation, supervision, public opinion, business and associated risks, builds a comprehensive risk identification model, and realizes dynamic monitoring and intelligent early warning of enterprise risks. This method improves the comprehensiveness and accuracy of risk prediction, helps to take control measures in advance, reduces potential losses, and enhances the enterprise's ability to resist risks. One or more of the following embodiments are described in detail.

[0043] The financial risk control method provided by the present embodiment can be applied to the financial risk control scene. The method can be executed by a financial risk control device, which can be realized by software and / or hardware, and the device can be integrated in an electronic device. The electronic device can include but is not limited to mobile terminals such as smart phones, notebook computers, digital broadcast receivers, personal digital assistants (PDA), tablet computers (Tablet PC), PMP (portable multimedia player), vehicle terminal (such as vehicle navigation terminal), wearable devices, and fixed terminals such as digital television, desktop computer, smart home device, etc.

[0044] Figure 1 A flowchart of a financial risk control method provided by an embodiment of the present disclosure is shown in the figure, which specifically includes the following steps as shown in the figure. Figure 1

[0045] S101, acquiring risk data of a set investment type in a financial investment field.

[0046] ​It is understood that the investment type is determined according to at least one of the investment objectives, risk preferences, asset properties, market environment, etc. of the investor, wherein the investment type includes at least one investment project, or the investor directly selects at least one investment project under the investment type, such as stocks, bonds, funds, etc. A comprehensive monitoring and tracking mechanism is constructed for at least one investment project under the investment type, and at least one investment project is dynamically tracked in the financial investment field to obtain risk data. The risk data helps the investor or investor to understand various aspects of the enterprise, thereby providing appropriate guidance and risk management.

[0047] The investment type includes fund investment projects and / or in-house investment projects; the risk data of the fund investment project includes at least one of honor dynamics, financing dynamics, business dynamics, and talent dynamics; the risk data of the in-house investment project includes at least one of scientific and technological achievements, business development, patent achievements, and cooperation information.

[0048] It is understood that the investment type includes at least one investment project type, including fund investment projects and in-house investment projects. The fund investment project generally refers to the investment activities of various investment funds (such as stock funds, bond funds, money market funds, and private equity funds) established by fund management companies or investment management institutions, and the in-house investment project refers to the investment activities directly conducted by the enterprise headquarters or parent company, which is often to support the long-term development strategy of the company. Subsequently, a comprehensive monitoring and tracking mechanism is constructed for the fund investment project, and the risk data of the fund investment project includes at least one of honor dynamics, financing dynamics, business dynamics, and talent dynamics, and other possible categories are not limited. A comprehensive monitoring and tracking mechanism is constructed for the capital holding in-house investment project, and the risk data of the in-house investment project includes at least one of scientific and technological achievements, business development, patent achievements, and cooperation information. The management project key tracking and monitoring function can also be provided for the projects responsible by the investment manager or the risk control personnel. At the same time, it also supports to collect any fund dynamics and project dynamics to a self-defined theme directory, and to follow up the key attention dynamics.

[0049] Optionally, the risk data of the investment type in the financial investment field is obtained, which can be realized by the following steps:

[0050] The risk analysis is performed on the risk file of the investment type in the financial investment field tracked in real time to determine the risk content; different levels and different categories of risk data are constructed according to the risk content in the risk file, and the risk data is arranged in a structured form.

[0051] Understandably, through the financial vertical field large model, the various risk files or risk data of at least one investment project tracked in real time are analyzed, for example, public opinion risk files, financial risk files, etc. Then, the risk content in the risk files or risk data is processed into different levels and different types of risk data, and further arranged into formatted risk data, wherein the formatted risk data includes keywords and corresponding description data, for example, the keyword is a risk event, and the description data is related data of negative events such as financial fraud, large shareholder reduction, and industry policy tightening. This kind of structured risk data is used to classify and track risks dynamically, so that the risk data can be clearly and accurately presented to the user.

[0052] S102, risk classification and risk grading processing of risk data is performed to obtain risk classification and grading results.

[0053] Understandably, on the basis of the above S101, the risk classification and grading processing can be performed by a large language model, wherein the large language model can be a vertical large model in the financial field. Based on the dynamic risk data tracked in real time, the large language model is used to perform risk classification and grading processing on the risk data to obtain risk classification and grading results, wherein the risk classification and grading results include risk categories and risk levels of the risk categories.

[0054] Among them, the risk categories are set as judicial risk, operational risk, regulatory risk, public opinion risk, business risk or associated risk; wherein the judicial risk is used to assess the judicial risk level of the enterprise; the operational risk is used to assess the operational risk level of the enterprise; the regulatory risk is used to assess the regulatory risk level of the enterprise; the public opinion risk is used to assess the public opinion risk level of the enterprise; the business risk is used to assess the operational stability and legal compliance of the enterprise; and the associated risk is used to assess the risk level of the related entity of the enterprise.

[0055] Understandably, the financial risk label system constructed includes multiple set risk categories and possible set risk levels of each set risk category. The large language model classifies and grades the risk data under the financial risk label system to obtain risk classification and grading results. Among them, the multiple set risk categories include judicial risk, operational risk, regulatory risk, public opinion risk, business risk and / or associated risk, and the set risk level is three levels of high, medium and low, or specific numerical values within the range of 0-1. Understandably, setting multiple set risk categories can perform risk assessment in multiple dimensions.

[0056] Understandably, judicial risk involves the risk of legal litigation or legal disputes that the enterprise may face, including but not limited to contract breach, intellectual property disputes, labor disputes, etc., used to assess the level of judicial risk of the enterprise. Operational risk involves market demand changes, cost fluctuations, supply chain disruptions, and other risks, used to assess the uncertainties related to the daily operation of the enterprise. Regulatory risk is used to assess the enterprise's situation in regulatory compliance, including government regulatory strength, regulatory compliance, etc. Public opinion risk mainly refers to the influence of public opinion and media on the image and brand reputation of the enterprise. It can be understood by monitoring social media, news reports and other public channels to understand the public's view of the enterprise. Business risk refers to the problems of the enterprise in registration, annual inspection, tax declaration, etc. It also includes the uncertainties brought by shareholder structure, capital changes, etc. It mainly focuses on the situation of the enterprise in business registration, credit record, etc. Related risk refers to the risk caused by the transactions or relationships between the enterprise and its parent company, subsidiary or other related companies, used to assess the reasonableness, transparency of related transactions and whether there is interest transfer.

[0057] Optionally, the risk data is classified and graded to obtain a risk classification and grading result, which can be realized by the following steps:

[0058] At least one risk information corresponding to a set risk category is extracted from the risk data, wherein the set risk category is divided into a plurality of risk subcategories; the risk identifiers of the plurality of risk subcategories in the risk information are comprehensively analyzed to determine the risk level of the set risk category, wherein the risk identifier is used to represent the risk degree of the risk subcategory; wherein the risk classification and grading result includes the set risk category and the risk level of the set risk category.

[0059] Understandably, the risk information corresponding to each set risk category is extracted from the risk data, for example, the risk information corresponding to the operational risk is the operation report information related to the enterprise, the risk information corresponding to the public opinion risk is the public opinion information related to the enterprise, and the risk information corresponding to the related risk is the risk information of the enterprise related entity, including shareholders, branch agencies, etc.

[0060] It can be understood that each risk category is divided into multiple risk subcategories. The risk subcategories can be understood as specific risk problems under the risk category, or secondary risk categories of the risk category. Specifically, the multiple risk subcategories under the judicial risk include at least one of court announcements, judicial documents, high risk levels, court session announcements, high consumption restrictions, persons subject to execution, persons subject to execution for loss of trust, administrative penalties, case filing information, bankruptcy restructuring, judicial auctions, final cases, litigation disputes, equity freezing, service announcements, and pre-litigation mediation. The multiple risk subcategories under the operating risk include at least one of revocation, equity hypothecation, movable property mortgage, security price fluctuations, guarantee information, stock price crashes, revocation, migration, management changes, delisting, suspension, difficult capital turnover, equity pledge, sale of assets, termination of listing, business suspension, asset anomalies, land mortgage, intellectual property hypothecation, asset restructuring obstacles, and merger and acquisition restructuring obstacles. The multiple risk subcategories under the regulatory risk include at least one of serious violations of the law, inability to contact through registered residence or business location, failure to publicize annual reports within a specified period, registration violations, fines, concealment of true information in publicized information, violations of registration management, other illegal activities, invoice violations, failure to publicize enterprise information as required, advertising violations, issuance of inquiry letters, long-term suspension of business operations, issuance of false advertisements, administrative violations, product quality violations, illegal land occupation, unfair competition, fire safety administrative penalties, violations of price management regulations, environmental violations, tax violations, warnings, construction without approval, air pollution, infringement of registered trademarks, false advertising, and at least one of the following: stock reduction, performance loss, illegal activities, infringement, fines, rights protection, illegal activities of senior management, warnings, claims, investigations, performance decline, layoffs, inability of senior management to perform their duties, bribery, sudden events, contract disputes, orders to correct, suicide, sudden bankruptcy, production accidents, disclosure problems, suspension of production, misappropriation of funds, bankruptcy liquidation, and high-level investigations. The multiple risk subcategories under the business risk include at least one of changes in key personnel, changes in business scope, changes in legal representatives, changes in shareholders, changes in registered capital, changes in enterprise addresses, changes in enterprise types, changes in enterprise business periods, changes in enterprise names, and changes in foreign investment. The multiple risk subcategories under the associated risk include at least one of management changes in associated entities, equity pledge, orders to correct, administrative penalties, illegal activities, orders to correct, illegal activities, administrative penalties, orders to correct, illegal activities, and the like.

[0061] Understandably, for each set risk category, the risk identification of each risk subcategory is comprehensively analyzed to determine the risk level of the set risk category, wherein the risk information includes the risk identification or the risk identification can be parsed based on the risk information, and the risk identification is used to represent the risk degree of the risk subcategory, which can be the number, frequency or quantitative value of the occurrence of the risk subcategory, for example, the quantitative value of the specific change of the business scope change risk subcategory under the business risk is 2, and the number of the production accident risk subcategory under the public opinion risk is 2, that is, 2 production accidents have occurred. The risk classification and grading result includes the set risk category and the risk level of the set risk category, and can also include the specific risk identification of the risk subcategory divided under the set risk category, for example, in the form of "production accident (2)", indicating that 2 production accidents have occurred, so as to more intuitively and more detailedly represent the risk level, and also provide the interpretability of the risk level.

[0062] Optionally, the risk identification of a plurality of risk subcategories in the risk information is comprehensively analyzed to determine the risk level of the set risk category, that is, the determination of the risk level of the set risk category can be realized by the following steps:

[0063] The risk identification of each risk subcategory corresponds to a set risk level, and the plurality of set risk levels of the plurality of risk subcategories and the set weight of each risk subcategory are comprehensively analyzed to determine the risk level of the set risk category.

[0064] Understandably, for each risk subcategory, the risk level is set according to its severity, that is, each risk subcategory is scored or rated according to quantitative or qualitative standards. One possible case is to set the risk level with 1-5, 1 being the lowest and 5 being the highest, for example, the risk identification of the exchange rate fluctuation risk is 15%, and the set risk level is set to 3. Different risk subcategories have different effects on the overall risk category, and the weight of the risk subcategory can be set according to the demand, and the weight range can be 0-1. Subsequently, the weighted average method or other models (such as score card, matrix method) can be used to calculate the score of the overall risk category as the risk level of the set risk category.

[0065] S103, generating a risk warning report according to the risk classification and grading result and the set risk indicator, so as to control the risk based on the risk warning report.

[0066] The set risk indicator is used to quantify and represent the risk bearing capacity and / or investment demand of the investor.

[0067] Understandably, on the basis of S102, the financial field vertical model is used to perform real-time analysis on the classified risk data (such as market risk, credit risk, and liquidity risk) and key quantitative indicators (such as volatility, maximum drawdown, leverage ratio, and default probability) to generate a structured risk warning report and push it to the relevant department in the first time, thereby realizing the automation and timeliness of risk identification. Meanwhile, the model can also generate targeted risk mitigation suggestions based on historical disposal cases, regulatory policies, and financial engineering methods. The set risk indicator refers to a set of key indicators artificially set or selected to measure, monitor, and warn investment risks under a specific investment strategy or risk management framework. The quantitative and characterization of the risk indicators represent the risk-bearing capacity and / or actual investment demand of investors. For example, the set risk indicator is set for investors with low risk appetite (such as conservative or stable type). Different risk indicators correspond to different risk indicators, and the risk indicator refers to the risk monitoring parameter.

[0068] Optionally, according to the risk classification and grading results and the set risk indicator, a risk warning report is generated, which can be realized through the following steps:

[0069] The financial data model is used to perform risk warning based on the risk classification and grading results and the set risk indicator. The large language model is used to generate a risk warning report based on the risk warning, wherein the risk warning report includes risk handling suggestions.

[0070] Understandably, the financial data model can be understood as a financial mathematical model. Different set risk indicators correspond to different financial mathematical models, and the financial data model can be pre-trained. The financial data model is used to perform risk warning based on the risk classification and grading results and the set risk indicator, and the financial field large language model is used to write a high-quality risk report, so that when a risk occurs, the risk can be automatically diverted and warned according to the risk warning report, thereby realizing timely and accurate risk warning. The model can also generate accurate risk handling suggestions for the risk control department to refer to. Specifically, the risk warning report can be sent to the member responsible for receiving the warning information of the project team, and the project team is prompted to take corresponding measures for processing.

[0071] The financial risk control method provided by the embodiments of the present disclosure realizes clear and accurate presentation of risk information by organizing and dynamically tracking risks through structured data. The large model is used to automatically process risk data, complete intelligent classification and grading of risks, and combine them with quantitative indicators to generate high-quality risk reports, thereby realizing timely and accurate risk warning. Relying on the financial field large model, targeted risk response suggestions are further generated to assist the risk control department in making efficient decisions and improve the automation and intelligence level of risk control.

[0072] On the basis of the above embodiments,Figure 2 Another flowchart of a financial risk control method provided by an embodiment of the present disclosure is shown in FIG. 6, which includes the following steps:

[0073] 1) performing dynamic tracking on fund investment projects and local investment projects to obtain risk data; 2) performing risk classification and grading on the risk data by a vertical large model in the financial field to obtain multiple risk categories and risk levels of each risk category, wherein the risk categories include judicial risk, operational risk, public opinion risk, business risk, and correlation risk, and the risk levels include high, medium, and low; 3) performing risk early warning according to specific quantitative indicators and the risk classification and grading results by a financial mathematical model; 4) writing a high-quality risk report by a large language model in the financial field and pushing the report to a risk control department.

[0074] It can be understood that the specific implementation of steps 1) to 4) is described in the above embodiments, which will not be repeated here.

[0075] Figure 3 A structure diagram of a financial risk control device provided by an embodiment of the present disclosure is shown in FIG. 7. The financial risk control device provided by the embodiment of the present disclosure can execute the processing flow provided by the financial risk control method embodiment. As shown in FIG. 7, the financial risk control device 300 includes: Figure 3

[0076] The acquisition unit 301 is configured to acquire risk data of a set investment type in the financial investment field.

[0077] The risk classification and grading unit 302 is configured to perform risk classification and risk grading on the risk data by a pre-trained model to obtain a risk classification and grading result.

[0078] The report generation unit 303 is configured to generate a risk early warning report according to the risk classification and grading result and a set risk indicator, so as to perform risk control based on the risk early warning report; wherein the set risk indicator is used to quantify and represent the risk bearing capacity and / or investment demand of an investor.

[0079] The set investment type includes fund investment projects and / or local investment projects; the risk data of the fund investment projects includes at least one of honor dynamics, financing dynamics, business dynamics, and talent dynamics; and the risk data of the local investment projects includes at least one of scientific and technological achievements, business development, patent achievements, and cooperation information.

[0080] Optionally, the risk classification and grading unit 302 is configured to:

[0081] extract risk information corresponding to at least one set risk category from the risk data, wherein the set risk category is divided into multiple risk subcategories.

[0082] ​The risk identifiers of the plurality of risk subcategories in the comprehensive risk information are analyzed to determine a risk level of the set risk category, wherein the risk identifier is used to represent a risk degree of the risk subcategory.

[0083] The risk classification and grading result includes the set risk category and the risk level of the set risk category.

[0084] Optionally, the risk classification and grading unit 302 is configured to:

[0085] determine the set risk level corresponding to the risk identifier of each risk subcategory;

[0086] The plurality of set risk levels of the plurality of risk subcategories and the set weight of each risk subcategory are comprehensively analyzed to determine the risk level of the set risk category.

[0087] The set risk category is judicial risk, operating risk, regulatory risk, public opinion risk, business risk, or correlation risk; the judicial risk is used to assess the judicial risk level of the enterprise; the operating risk is used to assess the operating risk level of the enterprise; the regulatory risk is used to assess the regulatory risk level of the enterprise; the public opinion risk is used to assess the public opinion risk level of the enterprise; the business risk is used to assess the operating stability and legal compliance of the enterprise; and the correlation risk is used to assess the risk level of the related entity of the enterprise.

[0088] Optionally, the report generation unit 303 is configured to:

[0089] perform risk warning according to the risk classification and grading result and the set risk indicator through the financial data model;

[0090] generate a risk warning report according to the risk warning through the large language model, wherein the risk warning report includes risk processing suggestions.

[0091] Optionally, the acquisition unit 301 is configured to:

[0092] perform risk analysis on the risk file of the set investment type in the financial investment field tracked in real time to determine the risk content;

[0093] construct risk data of different levels and different categories according to the risk content in the risk file, and arrange the risk data into a structured form.

[0094] Figure 3 The financial risk control device of the illustrated embodiment can be used to execute the technical solutions of the above-mentioned method embodiments, and the implementation principles and technical effects are similar, which will not be described here.

[0095] Figure 4 The structural schematic diagram of the electronic device provided by the embodiment of the present disclosure is provided. The following will be specifically referred to Figure 4, which shows a schematic structural diagram of an electronic device 400 suitable for implementing the embodiments of the present disclosure. The electronic device 400 in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), wearable electronic devices, and the like, as well as fixed terminals such as digital TVs, desktop computers, smart home devices, and the like. Figure 4 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0096] like Figure 4 As shown, electronic device 400 may include a processing device 401 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes to implement the financial risk control method of the embodiment described in the present disclosure according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage device 408 into a random access memory (RAM) 403. Various programs and data required for the operation of electronic device 400 are also stored in RAM 403. Processing device 401, ROM 402, and RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to bus 404.

[0097] Typically, the following devices may be connected to the I / O interface 405: an input device 406 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 408 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 409. The communication device 409 may allow the electronic device 400 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 4 The electronic device 400 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0098] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for executing the methods illustrated by the flowcharts, thereby implementing the financial risk control method as described above. In such embodiments, the computer program can be downloaded and installed from the network by the communication device 409, or installed from the storage device 408, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the methods of embodiments of the present disclosure are performed.

[0099] It should be noted that the computer-readable medium described above in the present disclosure can be a computer-readable signal medium or a computer-readable storage medium or any combination thereof. The computer-readable storage medium may, for example, be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination thereof. More specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, the computer-readable signal medium can include a data signal propagated in a baseband or as a carrier wave in a propagated data signal, in which the computer-readable program code is carried. Such a propagated data signal can take many forms, including but not limited to, an electromagnetic signal, an optical signal, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium that is not a computer-readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained in the computer-readable medium can be transmitted by any suitable medium, including but not limited to, wire, cable, RF (radio frequency), or the like, or any suitable combination thereof.

[0100] In some embodiments, the client, server, or other computing machines can communicate using any known or later developed form of computer-readable media, including but not limited to wireless media, wire-based media, optical-based media, and the like. In some embodiments, the client, server, or other computing machines can communicate using any current or later developed network protocol, such as the HyperText Transfer Protocol (HTTP), and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet, and the like, as well as any current or later developed network.

[0101] The computer-readable medium described above can be included in the electronic device described above; alternatively, the computer-readable medium can exist as a standalone entity.

[0102] Optionally, when the one or more programs are executed by the electronic device, the electronic device can further execute other steps described in the above embodiments.

[0103] Computer program code for carrying out operations of the present disclosure can be written in any one or combination of one or more programming languages, including an object-oriented programming language such as Java, Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network ("LAN") or a wide area network ("WAN"), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0104] The computer program product of the first aspect can include one or more non-transitory computer-readable media storing instructions that, when executed, cause one or more processors to perform the operations of the first aspect. The computer program product of the first aspect can include a non-transitory computer-readable medium storing code that, when executed, causes a computer to perform operations for the first aspect.

[0105] The units described in the embodiments of the present disclosure can be implemented by software, or by hardware, or by a combination of software and hardware. In some cases, the names of the units do not constitute a limitation on the units themselves.

[0106] The functions described in this document can be implemented in part or in whole using one or more hardware logic components. For example, and without limitation, illustrative types of hardware logic components that can be used include Field-programmable Gate Arrays (FPGAs), Program-specific Integrated Circuits (ASICs), Program-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), etc.

[0107] In the context of the present disclosure, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium will include one or more lines of electrical connections, portable computer disks, hard disk drives, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0108] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or gateway that includes a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also includes elements that are inherent to such process, method, article or gateway. In the absence of further restrictions, the elements defined by the sentence "including a..." do not exclude the presence of other identical elements in the process, method, article or gateway that includes the elements.

[0109] The foregoing description is intended only to provide specific embodiments of the present disclosure, intended to enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the embodiments described herein, but rather to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

Claims

1. A financial risk control method, characterized in that: include: Obtain risk data for a given investment type in the financial investment field; Performing risk classification and risk grading processing on the risk data to obtain risk classification and grading results; A risk warning report is generated based on the risk classification and grading results and the set risk indicators, so that risk control can be carried out based on the risk warning report; wherein the set risk indicators are used to quantify and characterize investors' risk-bearing capacity and / or investment needs.

2. The method according to claim 1, characterized in that The set investment types include fund investment projects and / or headquarters investment projects; wherein, the risk data of the fund investment projects include at least one category of data including honor dynamics, financing dynamics, business dynamics and talent dynamics; the risk data of the headquarters investment projects include at least one category of data including scientific and technological achievements, business development, patent achievements and cooperation information.

3. The method according to claim 1, characterized in that The risk classification and risk grading processing of the risk data to obtain the risk classification and grading results includes: Extracting risk information corresponding to at least one set risk category from the risk data, wherein the set risk category is divided into a plurality of risk subcategories; Comprehensively analyzing the risk identifiers of the multiple risk subcategories in the risk information to determine the risk level of the set risk category, wherein the risk identifier is used to represent the risk degree of the risk subcategory; The risk classification and grading result includes the set risk category and the risk level of the set risk category.

4. The method according to claim 3, characterized in that The comprehensively analyzing the risk identifiers of the multiple risk subcategories in the risk information to determine the risk level of the set risk category includes: Determine the set risk level corresponding to the risk indicator of each risk subcategory; The multiple set risk levels of the multiple risk subcategories and the set weight of each risk subcategory are comprehensively analyzed to determine the risk level of the set risk category.

5. The method according to claim 3, characterized in that The set risk categories are judicial risk, operational risk, regulatory risk, public opinion risk, industrial and commercial risk or related risk; among them, the judicial risk is used to assess the judicial risk level of the enterprise; the operational risk is used to assess the operational risk level of the enterprise; the regulatory risk is used to assess the regulatory risk level of the enterprise; the public opinion risk is used to assess the public opinion risk level of the enterprise; the industrial and commercial risk is used to assess the operational stability and legal compliance of the enterprise; and the related risk is used to assess the risk level of the enterprise's related entities.

6. The method according to claim 1, characterized in that Generating a risk warning report based on the risk classification and grading results and the set risk indicators includes: Conduct risk warnings based on the risk classification and grading results and set risk indicators through financial data models; A risk warning report is generated based on the risk warning using a large language model, wherein the risk warning report includes risk handling suggestions.

7. The method according to claim 1, characterized in that The step of obtaining risk data of a set investment type in the financial investment field includes: Conduct risk analysis on risk documents of set investment types in the financial investment field that are tracked in real time to determine the risk content; According to the risk content in the risk document, risk data of different levels and categories are constructed, and the risk data are organized into a structured form.

8. A financial risk control device, characterized in that: include: An acquisition unit, used to acquire risk data of a set investment type in the financial investment field; A risk classification and grading unit is used to perform risk classification and risk grading processing on the risk data to obtain a risk classification and grading result; A report generation unit is used to generate a risk warning report based on the risk classification and grading results and set risk indicators, so as to perform risk control based on the risk warning report; wherein the set risk indicators are used to quantify and characterize investors' risk-bearing capacity and / or investment needs.

9. An electronic device, characterized in that: include: Memory; processor; as well as computer programs; The computer program is stored in the memory and is configured to be executed by the processor to implement the financial risk control method according to any one of claims 1 to 7.

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

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