Financial risk management method and system based on artificial intelligence

Abstract

The invention is suitable for the field of financial risk management, and provides a financial risk management method and system based on artificial intelligence, and the system comprises a policy collection and analysis module, an industry evaluation simulation module, an industry trend development analysis module, and a financial risk comprehensive analysis module. The system can evaluate the response of the industry indexes when different policy parameters change through sensitivity analysis, and simulates the industry development result in the policy change process. The simulation analysis can help predict the growth, periodicity and potential risk of the industry.

Description

Technical Field

[0001] The present invention belongs to the field of financial risk management, and in particular, relates to a financial risk management method and system based on artificial intelligence. Background Art

[0002] The field of financial risk management refers to the use of a series of strategies, tools and techniques to identify, evaluate, monitor and control various risks that may arise from financial activities in order to ensure the safety of funds of financial institutions and investors and maintain the stability and healthy development of financial markets. The core goal of financial risk management is to reduce the negative impact of risks on the financial status and operations of financial institutions while optimizing the balance between risk and return.

[0003] Traditional methods may lack systematic and quantitative analysis, and sensitivity analysis usually requires a lot of manual calculations and model building, which is inefficient. In addition, traditional risk assessment methods are usually periodic and cannot reflect the dynamic changes of the market and policies in real time, resulting in delayed risk warning and response measures. Summary of the invention

[0004] The purpose of the present invention is to provide a financial risk management method based on artificial intelligence, aiming to solve the technical problems existing in the prior art identified in the background technology.

[0005] The present invention is implemented in this way: a financial risk management method based on artificial intelligence, the method comprising:

[0006] Identify the industry type of the transaction object and collect policy announcements related to the industry type. Extract and analyze fiscal policies and industry regulatory policies from the policy announcements, identify the policy purpose and affected entities, and determine the policy change trend by comparing the differences before and after the policy changes.

[0007] Collect economic indicator data of the industry and use it to evaluate the overall health and market structure of the industry, judge the industry's growth, cyclicality and potential risks, evaluate the industry's social impact, establish a development simulation model, and use sensitivity analysis to evaluate the response of industry indicators to changes in different policy parameters, and obtain industry development results during policy changes;

[0008] Predict industry development trends, and based on industry development trends, evaluate the impact of industry changes on social development and the direction of impact, and predict the direction of policy adjustments for industry development;

[0009] Comprehensively assess the potential impact of policy changes on the industry and the direction of policy adjustments for industry development, and assess the policy risks of the industry in which the transaction counterparty is located.

[0010] As a further solution of the present invention, the identification of policy objectives, affected entities and expected impacts, and determination of policy change trends by comparing the differences before and after the policy changes, specifically include:

[0011] Obtain the industry type information of the transaction object, and set keyword filters accordingly, identify policy announcements matching the industry type from policy channels, and extract relevant content of fiscal policy and industry regulatory policy;

[0012] Parse policy documents through text analysis to clarify the purpose and expected goals of the policy, and identify the relationship between the affected entities explicitly mentioned in the policy and the industry types of the transaction objects;

[0013] Collect historical data and changes in market indicators before and after policy changes, analyze the development trajectory of policies, and identify the long-term trends and cyclical characteristics of policy changes.

[0014] As a further solution of the present invention, the overall health status and market structure of the industry are evaluated, the growth, cyclicality and potential risks of the industry are judged, the social influence of the industry is evaluated, a development simulation model is established, and the response of industry indicators to changes in different policy parameters is evaluated through sensitivity analysis, specifically including:

[0015] Obtain economic indicator data of the industry, evaluate the financial health status and market competition level of the industry, and evaluate the growth rate and future development trend of the industry based on the changes in economic indicator data;

[0016] Analyze the market share of the industry and, based on the industry type, analyze the social influence of the transaction object;

[0017] Build a development simulation model, substitute the current economic indicator data of the industry and the current policy announcements that match the industry type into the model, combine the long-term trend and cyclical characteristics of policy changes, and simulate the industry development results during the policy development process.

[0018] As a further solution of the present invention, the prediction of industry development trends, and based on the industry development trends, the evaluation of the impact of industry changes on social development and the direction of impact, and the prediction of the policy adjustment direction for industry development specifically include:

[0019] Analyze historical industry data and predict industry indicators for several future time periods;

[0020] Combined with industry development trends, analyze the impact of industry development on social development;

[0021] Analyze the adjustment direction and intensity of government policies under similar historical scenarios, and predict policy trends based on the current policy environment and industry status.

[0022] As a further solution of the present invention, the policy risk of the industry in which the transaction object is located is evaluated, specifically including:

[0023] Comprehensively consider the potential impact of policy changes on the industry and the direction of policy adjustments for industry development, and identify risk factors related to the industry type of the transaction object;

[0024] Based on risk factors, assess the development risk of the transaction object.

[0025] Another object of the present invention is to provide a financial risk management system based on artificial intelligence, the system comprising:

[0026] The policy collection and analysis module is used to identify the industry type of the transaction object and collect policy announcements related to the industry type. It extracts and analyzes fiscal policies and industry regulatory policies from the policy announcements, identifies the policy purpose and affected entities, and determines the policy change trend by comparing the differences before and after the policy changes.

[0027] The industry assessment simulation module is used to collect economic indicator data of the industry, and use it to evaluate the overall health status and market structure of the industry, judge the growth, cyclicality and potential risks of the industry, evaluate the social impact of the industry, establish a development simulation model, and evaluate the response of industry indicators to changes in different policy parameters through sensitivity analysis to obtain the industry development results during the policy change process;

[0028] The industry trend development analysis module is used to predict industry development trends, and based on industry development trends, evaluate the impact of industry changes on social development and the direction of impact, and predict the direction of policy adjustments for industry development;

[0029] The comprehensive financial risk analysis module is used to comprehensively consider the potential impact of policy changes on the industry and the direction of policy adjustments for industry development, and to assess the policy risks of the industry in which the transaction object is located.

[0030] As a further solution of the present invention, the policy collection and analysis module includes:

[0031] The industry identification unit is used to obtain the industry type information of the transaction object and set keyword filters accordingly to identify policy announcements matching the industry type from policy channels and extract relevant content of fiscal policies and industry regulatory policies;

[0032] The policy analysis and association unit is used to analyze policy documents through text analysis, clarify the purpose and expected goals of the policy, and identify the association between the affected entities explicitly mentioned in the policy and the industry types of the transaction objects;

[0033] The data trend analysis and identification unit is used to collect historical data and changes in market indicators before and after policy changes, analyze the development trajectory of policies, and identify the long-term trends and cyclical characteristics of policy changes.

[0034] As a further solution of the present invention, the industry assessment simulation module includes:

[0035] The economic indicator evaluation unit is used to obtain the economic indicator data of the industry, evaluate the financial health status and market competition level of the industry, and evaluate the growth rate and future development trend of the industry based on the changes in economic indicator data;

[0036] The influence analysis unit is used to analyze the market share of the industry and, based on the industry type, analyze the social influence of the transaction object;

[0037] The industry development simulation unit is used to build a development simulation model. It substitutes the current economic indicator data of the industry and the current policy announcements that match the industry type into the model, and combines the long-term trend and cyclical characteristics of policy changes to simulate the industry development results during the policy development process.

[0038] As a further solution of the present invention, the industry trend development analysis module includes:

[0039] The future indicator prediction unit is used to analyze the industry's historical data and predict the industry indicators within a certain period of time in the future;

[0040] Impact assessment unit, used to analyze the impact of industry development on social development in combination with industry development trends;

[0041] The policy trend prediction unit is used to analyze the adjustment direction and intensity of government policies under similar historical scenarios, and predict the policy direction based on the current policy environment and industry status.

[0042] As a further solution of the present invention, the financial risk comprehensive analysis module includes:

[0043] The policy impact factor identification unit is used to comprehensively consider the potential impact of policy changes on the industry and the policy adjustment direction for industry development, and identify risk factors related to the industry type of the transaction object;

[0044] The transaction object development risk assessment unit is used to assess the development risk of the transaction object based on risk factors.

[0045] The beneficial effects of the present invention are:

[0046] The system can evaluate the response of industry indicators to changes in different policy parameters through sensitivity analysis, and simulate the industry development results during policy changes. This simulation analysis can help predict the growth, cyclicality and potential risks of the industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A flowchart of a financial risk management method based on artificial intelligence provided by an embodiment of the present invention;

[0048] Figure 2 A flow chart of determining a policy change trend by comparing the difference before and after the policy change provided by an embodiment of the present invention;

[0049] Figure 3 A flowchart of an embodiment of the present invention for evaluating the response of industry indicators to changes in different policy parameters through sensitivity analysis to obtain industry development results during policy changes;

[0050] Figure 4 A flowchart for evaluating the impact of industry changes on social development and the direction of impact, and predicting the direction of policy adjustments for industry development, provided by an embodiment of the present invention;

[0051] Figure 5 A flowchart for evaluating the policy risk of the industry in which the transaction object is located provided by an embodiment of the present invention;

[0052] Figure 6 A structural block diagram of an artificial intelligence-based financial risk management system provided by an embodiment of the present invention;

[0053] Figure 7 A structural block diagram of a policy collection and analysis module provided by an embodiment of the present invention;

[0054] Figure 8 A structural block diagram of an industry assessment simulation module provided by an embodiment of the present invention;

[0055] Fig. 9 A structural block diagram of an industry trend development analysis module provided by an embodiment of the present invention;

[0056] Fig.10 This is a structural block diagram of the financial risk comprehensive analysis module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0059] Figure 1 A flowchart of a financial risk management method based on artificial intelligence provided by an embodiment of the present invention, a financial risk management method based on artificial intelligence, the method comprising:

[0060] S100, identify the industry type of the transaction object, and collect policy announcements related to the industry type, extract and analyze fiscal policies and industry regulatory policies from the policy announcements, identify the policy purpose and affected entities, and determine the policy change trend by comparing the differences before and after the policy changes;

[0061] This step obtains the industry type information of the transaction object and sets keyword filters accordingly, including industry-specific terms, relevant policy keywords, etc., to filter out policy announcements that match the industry type of the transaction object. The advantage of this step is that it can accurately match policy announcements related to the industry type of the transaction object, avoid interference from irrelevant information, and improve the accuracy and efficiency of policy identification.

[0062] Collect policy announcements from multiple policy release channels (such as official government websites, industry associations, policy databases, etc.), and identify policy announcements that match the industry type of the transaction object through the set keyword filters. Use natural language processing (NLP) technology to perform text analysis on policy documents, extract content related to fiscal policies and industry regulatory policies, and clarify the purpose and expected goals of policy formulation. The advantage of this step is that it uses automated text analysis technology to quickly extract key policy content and affected entities, saving the time and cost of manual analysis and improving the accuracy of analysis.

[0063] Through text mining technology, we identify the affected entities explicitly mentioned in the policy and analyze the relationship between these entities and the industry types of the transaction objects. At the same time, we collect historical data and relevant market indicators before and after the policy changes, such as industry growth rate, investment data, market share, etc. By comparing the differences before and after the policy changes, we analyze the development trajectory of the policy and identify the long-term trends and cyclical characteristics of the policy changes. The advantage of this step is that it comprehensively evaluates the impact of policy changes on the industry, identifies the long-term trends and cyclical characteristics of policy changes, and provides important data support for subsequent industry development simulation and risk assessment.

[0064] By analyzing the policy development trajectory, we can dynamically identify the trend of policy changes, provide forward-looking guidance for the response strategies of industries and enterprises in the policy environment, and help enterprises better adapt to changes in the policy environment. At the same time, based on the analysis of historical data and market indicators, we can provide empirical support for policy impact assessment, enhance the scientificity and credibility of the assessment results, and provide a solid data foundation for corporate decision-making.

[0065] like Figure 2 As shown, the policy objectives, affected entities and expected impacts are identified, and the policy change trend is determined by comparing the differences before and after the policy changes, including:

[0066] S110, obtaining industry type information of the transaction object, and setting keyword filters accordingly, identifying policy announcements matching the industry type from policy channels, and extracting relevant content of fiscal policies and industry regulatory policies;

[0067] S120, parse policy documents through text analysis to clarify the purpose and expected goals of the policy, and identify the relationship between the affected entities explicitly mentioned in the policy and the industry types of the transaction objects;

[0068] S130, collect historical data and market indicator changes before and after policy changes, analyze the development trajectory of policies, and identify the long-term trends and cyclical characteristics of policy changes.

[0069] S200, collects economic indicator data of the industry, and uses it to evaluate the overall health and market structure of the industry, judge the industry's growth, cyclicality and potential risks, evaluate the industry's social impact, establish a development simulation model, and use sensitivity analysis to evaluate the response of industry indicators to changes in different policy parameters, and obtain the industry development results during the policy change process;

[0070] This step evaluates the financial health of the industry by obtaining economic indicator data of the industry, such as revenue growth rate, profit margin, debt-to-asset ratio, etc. At the same time, the changing trends of these indicators are analyzed to evaluate the growth rate and future development trends of the industry. The advantage of this step is that it objectively evaluates the financial status and growth potential of the industry through quantitative analysis, providing data support for subsequent industry risk assessment.

[0071] Analyze the industry's market share to understand the industry's competitive position in the overall market. Combined with the industry type, further analyze the social influence of the transaction object, including the industry's contribution to employment, taxation, technological innovation, etc. The advantage of this step is that it comprehensively evaluates the industry's market competitiveness and social influence, providing a more comprehensive perspective for industry risk assessment.

[0072] We will also build a development simulation model, and substitute the current economic indicator data of the industry and the current policy announcements that match the industry type into the model. Combined with the long-term trend and cyclical characteristics of policy changes, we will simulate the industry development results during the policy development process. Through sensitivity analysis, we will evaluate the response of industry indicators when different policy parameters change, and predict the specific impact of policy changes on industry development. The advantage of this step is that through simulation analysis, we can predict the potential impact of policy changes on the industry and provide forward-looking decision support for risk management.

[0073] like Figure 3 As shown, the overall health status and market structure of the industry are evaluated, the growth, cyclicality and potential risks of the industry are judged, the social impact of the industry is evaluated, a development simulation model is established, and the response of industry indicators to changes in different policy parameters is evaluated through sensitivity analysis, including:

[0074] S210, obtain the economic indicator data of the industry, evaluate the financial health status and market competition level of the industry, and evaluate the growth rate and future development trend of the industry based on the changes in the economic indicator data;

[0075] S220, analyze the market share of the industry and, based on the industry type, analyze the social influence of the transaction object;

[0076] S230, build a development simulation model, substitute the current economic indicator data of the industry and the current policy announcements that match the industry type into the model, combine the long-term trend and cyclical characteristics of policy changes, and simulate the industry development results during the policy development process.

[0077] S300, predicts industry development trends, and based on industry development trends, evaluates the impact of industry changes on social development and the direction of impact, and predicts the direction of policy adjustments for industry development;

[0078] This step analyzes the industry's historical data, including but not limited to sales data, market share, technological progress, etc., and uses statistical methods such as time series analysis and regression analysis to predict industry indicators for several future time periods. The advantage of this step is that through in-depth analysis of historical data, it can provide scientific predictions for the future development of the industry and provide data support for risk management.

[0079] Combined with industry development trends, analyze the impact of industry growth, technological innovation, market expansion and other factors on social development. Evaluate the industry's contribution to employment, economic growth, environmental protection and other aspects, as well as the social problems and challenges it may bring. The advantage of this step is that it comprehensively evaluates the social impact of the industry and provides a more comprehensive perspective for policy making and risk management.

[0080] Analyze the direction and intensity of government policy adjustments under similar historical scenarios, and predict the direction of future policies in combination with the current policy environment, industry status, and social needs. By comparing historical data with current conditions, identify the laws and trends of policy adjustments, and provide forward-looking guidance for policy risk assessment. The advantage of this step is that by drawing on historical experience, it is possible to more accurately predict future policy changes and provide strategic support for risk management.

[0081] like Figure 4 As shown, the forecast of industry development trends, and based on the industry development trends, the impact of industry changes on social development and the direction of impact are evaluated, and the direction of policy adjustments for industry development are predicted, including:

[0082] S310, analyze industry historical data and predict industry indicators in several future time periods;

[0083] S320, combined with industry development trends, analyze the impact of industry development on social development;

[0084] S330, analyze the adjustment direction and intensity of government policies under similar historical scenarios, and predict policy trends based on the current policy environment and industry status.

[0085] S400, comprehensively considers the potential impact of policy changes on the industry and the direction of policy adjustments for industry development, and assesses the policy risks of the industry in which the transaction object is located.

[0086] This step will combine the analysis results of the previous steps to comprehensively sort out the potential impact of policy changes on the industry, including the specific impact of fiscal policies and industry regulatory policies on the financial health, market structure and social influence of the industry. The advantage of this step is that it can systematically integrate the results of previous analyses, comprehensively evaluate the multi-level impact of policy changes on the industry, and provide a comprehensive information basis for risk assessment.

[0087] Based on industry development trends and social impact assessments, combined with the laws of policy adjustments under similar historical scenarios, we predict the possible direction of future policy adjustments. Through a comprehensive analysis of policy change trends and industry development effects, we identify the possible paths and strengths of future policy adjustments. The advantage of this step is that through forward-looking predictions, we can identify possible policy change paths in advance and provide early warning information for risk management.

[0088] Combined with the potential impact of policy changes and the direction of future policy adjustments, identify risk factors related to the industry type of the transaction object. These risk factors may include policy uncertainty, market fluctuations, technological changes, social opinions, etc. Through quantitative and qualitative analysis of different risk factors, clarify their specific impact on the transaction object. The advantage of this step is that it can comprehensively identify multi-dimensional risk factors related to the industry and provide detailed information support for the risk assessment of the transaction object.

[0089] Based on the identified risk factors, a risk assessment model is used to assess the development risks of the transaction object under different policy environments. This includes financial risk, market risk, compliance risk, and reputation risk. By simulating the development path of the transaction object under different scenarios, the risk exposure of the transaction object under different policy environments is quantitatively assessed. The advantage of this step is that through quantitative analysis, the specific risks of the transaction object can be objectively assessed, providing a scientific basis for decision-making.

[0090] like Figure 5 As shown in the figure, the policy risks of the industry in which the transaction object is located include:

[0091] S410, comprehensively consider the potential impact of policy changes on the industry and the policy adjustment direction for industry development, and identify the risk factors related to the industry type of the transaction object;

[0092] S420, based on risk factors, assess the development risk of the transaction object.

[0093] Figure 6 A structural block diagram of an artificial intelligence-based financial risk management system provided by an embodiment of the present invention, the artificial intelligence-based financial risk management system, the system comprising:

[0094] The policy collection and analysis module 100 is used to identify the industry type of the transaction object, collect policy announcements related to the industry type, extract and analyze fiscal policies and industry regulatory policies from the policy announcements, identify policy purposes and affected entities, and determine the policy change trend by comparing the differences before and after the policy changes;

[0095] The industry assessment simulation module 200 is used to collect economic indicator data of the industry, and evaluate the overall health status and market structure of the industry based on it, judge the growth, cyclicality and potential risks of the industry, evaluate the social influence of the industry, establish a development simulation model, evaluate the response of industry indicators to changes in different policy parameters through sensitivity analysis, and obtain the industry development results during the policy change process;

[0096] The industry trend development analysis module 300 is used to predict the industry development trend, and based on the industry development trend, evaluate the impact of industry changes on social development and the direction of impact, and predict the direction of policy adjustments for industry development;

[0097] The financial risk comprehensive analysis module 400 is used to comprehensively consider the potential impact of policy changes on the industry and the direction of policy adjustments for industry development, and to evaluate the policy risks of the industry in which the transaction object is located.

[0098] Figure 7 This is a structural block diagram of a policy collection and analysis module provided in an embodiment of the present invention, wherein the policy collection and analysis module includes:

[0099] The industry identification unit 110 is used to obtain the industry type information of the transaction object, and set a keyword filter accordingly, identify the policy announcements matching the industry type from the policy channel, and extract the relevant contents of the fiscal policy and industry supervision policy;

[0100] A policy analysis and association unit 120 is used to analyze the policy document through text analysis, clarify the purpose and expected goals of the policy, and identify the association between the affected entities explicitly mentioned in the policy and the industry types of the transaction objects;

[0101] The data trend analysis and identification unit 130 is used to collect historical data and market indicator changes before and after policy changes, analyze the development trajectory of the policy, and identify the long-term trends and cyclical characteristics of policy changes.

[0102] Figure 8 A structural block diagram of an industry assessment simulation module provided in an embodiment of the present invention, wherein the industry assessment simulation module includes:

[0103] The economic indicator evaluation unit 210 is used to obtain the economic indicator data of the industry, evaluate the financial health status and market competition level of the industry, and evaluate the growth rate and future development trend of the industry based on the changes in the economic indicator data;

[0104] The influence analysis unit 220 is used to analyze the market share of the industry and analyze the social influence of the transaction object in combination with the industry type;

[0105] The industry development simulation unit 230 is used to build a development simulation model, substitute the current economic indicator data of the industry and the current policy announcements matching the industry type into the model, and combine the long-term trend and cyclical characteristics of policy changes to simulate the industry development results during the policy development process.

[0106] Fig. 9 A structural block diagram of an industry trend development analysis module provided in an embodiment of the present invention, wherein the industry trend development analysis module includes:

[0107] A future indicator prediction unit 310 is used to analyze industry historical data and predict industry indicators within a certain period of time in the future;

[0108] The impact assessment unit 320 is used to analyze the impact of industry development on social development in combination with industry development trends;

[0109] The policy trend prediction unit 330 is used to analyze the adjustment direction and strength of government policies under similar historical scenarios, and predict the policy trend in combination with the current policy environment and industry status.

[0110] Fig.10 This is a structural block diagram of a financial risk comprehensive analysis module provided in an embodiment of the present invention, wherein the financial risk comprehensive analysis module includes:

[0111] The policy influencing factor identification unit 410 is used to comprehensively consider the potential impact of policy changes on the industry and the policy adjustment direction for industry development, and identify risk factors related to the industry type of the transaction object;

[0112] The transaction object development risk assessment unit 420 is used to assess the development risk of the transaction object based on risk factors.

[0113] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have strict order restrictions, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0114] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0115] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0116] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0117] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A financial risk management method based on artificial intelligence, characterized in that: The method comprises: Identify the industry type of the transaction object and collect policy announcements related to the industry type. Extract and analyze fiscal policies and industry regulatory policies from the policy announcements, identify the policy purpose and affected entities, and determine the policy change trend by comparing the differences before and after the policy changes. Collect economic indicator data of the industry and use it to evaluate the overall health and market structure of the industry, judge the industry's growth, cyclicality and potential risks, evaluate the industry's social impact, establish a development simulation model, and use sensitivity analysis to evaluate the response of industry indicators to changes in different policy parameters, and obtain industry development results during policy changes; Predict industry development trends, and based on industry development trends, evaluate the impact of industry changes on social development and the direction of impact, and predict the direction of policy adjustments for industry development; Comprehensively assess the potential impact of policy changes on the industry and the direction of policy adjustments for industry development, and assess the policy risks of the industry in which the transaction counterparty is located.

2. The method according to claim 1, characterized in that The policy objectives, affected entities and expected impacts are identified, and the policy change trend is determined by comparing the differences before and after the policy changes, including: Obtain the industry type information of the transaction object, and set keyword filters accordingly, identify policy announcements matching the industry type from policy channels, and extract relevant content of fiscal policy and industry regulatory policy; Parse policy documents through text analysis to clarify the purpose and expected goals of the policy, and identify the relationship between the affected entities explicitly mentioned in the policy and the industry types of the transaction objects; Collect historical data and changes in market indicators before and after policy changes, analyze the development trajectory of policies, and identify the long-term trends and cyclical characteristics of policy changes.

3. The method according to claim 2, characterized in that The above mentioned assessment of the overall health status and market structure of the industry, the evaluation of the industry's growth, cyclicality and potential risks, the assessment of the industry's social impact, the establishment of a development simulation model, and the evaluation of the response of industry indicators to changes in different policy parameters through sensitivity analysis include: Obtain economic indicator data of the industry, evaluate the financial health status and market competition level of the industry, and evaluate the growth rate and future development trend of the industry based on the changes in economic indicator data; Analyze the market share of the industry and, based on the industry type, analyze the social influence of the transaction object; Build a development simulation model, substitute the current economic indicator data of the industry and the current policy announcements that match the industry type into the model, combine the long-term trend and cyclical characteristics of policy changes, and simulate the industry development results during the policy development process.

4. The method according to claim 3, characterized in that The aforementioned prediction of industry development trends, and based on the industry development trends, the assessment of the impact of industry changes on social development and the direction of impact, and the prediction of the direction of policy adjustments for industry development, specifically include: Analyze historical industry data and predict industry indicators for several future time periods; Combined with industry development trends, analyze the impact of industry development on social development; Analyze the adjustment direction and intensity of government policies under similar historical scenarios, and predict policy trends based on the current policy environment and industry status.

5. The method according to claim 4, characterized in that The policy risks of the industry in which the transaction object is located include: Comprehensively consider the potential impact of policy changes on the industry and the direction of policy adjustments for industry development, and identify risk factors related to the industry type of the transaction object; Based on risk factors, assess the development risk of the transaction object.

6. Financial risk management system based on artificial intelligence, characterized by: The system comprises: The policy collection and analysis module is used to identify the industry type of the transaction object and collect policy announcements related to the industry type. It extracts and analyzes fiscal policies and industry regulatory policies from the policy announcements, identifies the policy purpose and affected entities, and determines the policy change trend by comparing the differences before and after the policy changes. The industry assessment simulation module is used to collect economic indicator data of the industry, and use it to evaluate the overall health status and market structure of the industry, judge the growth, cyclicality and potential risks of the industry, evaluate the social impact of the industry, establish a development simulation model, and evaluate the response of industry indicators to changes in different policy parameters through sensitivity analysis to obtain the industry development results during the policy change process; The industry trend development analysis module is used to predict industry development trends, and based on industry development trends, evaluate the impact of industry changes on social development and the direction of impact, and predict the direction of policy adjustments for industry development; The comprehensive financial risk analysis module is used to comprehensively consider the potential impact of policy changes on the industry and the direction of policy adjustments for industry development, and to assess the policy risks of the industry in which the transaction object is located.

7. The system according to claim 6, characterized in that The policy collection and parsing module includes: The industry identification unit is used to obtain the industry type information of the transaction object and set keyword filters accordingly to identify policy announcements matching the industry type from policy channels and extract relevant content of fiscal policies and industry regulatory policies; The policy analysis and association unit is used to analyze policy documents through text analysis, clarify the purpose and expected goals of the policy, and identify the association between the affected entities explicitly mentioned in the policy and the industry types of the transaction objects; The data trend analysis and identification unit is used to collect historical data and changes in market indicators before and after policy changes, analyze the development trajectory of policies, and identify the long-term trends and cyclical characteristics of policy changes.

8. The system according to claim 7, characterized in that The industry assessment simulation module includes: The economic indicator evaluation unit is used to obtain the economic indicator data of the industry, evaluate the financial health status and market competition level of the industry, and evaluate the growth rate and future development trend of the industry based on the changes in economic indicator data; The influence analysis unit is used to analyze the market share of the industry and, based on the industry type, analyze the social influence of the transaction object; The industry development simulation unit is used to build a development simulation model. It substitutes the current economic indicator data of the industry and the current policy announcements that match the industry type into the model, and combines the long-term trend and cyclical characteristics of policy changes to simulate the industry development results during the policy development process.

9. The system according to claim 8, characterized in that The industry trend development analysis module includes: The future indicator prediction unit is used to analyze the industry's historical data and predict the industry indicators within a certain period of time in the future; Impact assessment unit, used to analyze the impact of industry development on social development in combination with industry development trends; The policy trend prediction unit is used to analyze the adjustment direction and intensity of government policies under similar historical scenarios, and predict the policy direction based on the current policy environment and industry status.

10. The system according to claim 9, characterized in that The financial risk comprehensive analysis module includes: The policy impact factor identification unit is used to comprehensively consider the potential impact of policy changes on the industry and the policy adjustment direction for industry development, and identify risk factors related to the industry type of the transaction object; The transaction object development risk assessment unit is used to assess the development risk of the transaction object based on risk factors.

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