Risk analysis method and system for financial data

Abstract

The invention relates to the technical field of financial risk analysis, in particular to a risk analysis method and system for financial data. Comprising the following steps: S1, collecting internal financial data of internal enterprises, and performing related enterprise list identification according to the internal financial data; s2, performing external financial data collection and external enterprise information collection according to the related enterprise list, and screening the internal financial data in combination with the related enterprise list to obtain related financial data corresponding to each external enterprise; by dynamically calculating a risk compression resistance residual value and monitoring the overall risk openness of the enterprise in real time, if the amount of a single risk transaction exceeds the residual compression resistance value, the risk level is automatically improved to the highest, the transaction is frozen, and the management layer needs to perform approval personally, so that the facture of an enterprise fund chain and the improvement of the overall risk tolerance caused by a single high-risk transaction are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of financial risk analysis, and in particular to a risk analysis method and system for financial data. Background Art

[0002] Financial management is a management activity that organizes, plans, directs, and controls the movement of funds within a company. It aims to achieve a company's financial goals through effective fund management and investment decisions. Traditional financial management methods are unable to effectively identify and manage financial risks, especially when dealing with large amounts of financial data, high processing speeds, and complex data analysis. Traditional financial management methods often rely on manual processing, which is not only inefficient but also prone to errors, making it impossible to promptly identify and address potential financial risks.

[0003] However, most existing technologies are limited to internal enterprise data scenarios and lack the integrated analysis of external related information. In actual applications, the financial risks of enterprises not only come from internal transaction records, but are also closely related to external factors such as the credit status of partners and changes in the industry environment. For example, relying solely on internal data may not be able to identify in advance the performance risks of external enterprises caused by industrial and commercial changes, legal proceedings or industry policy adjustments, which can easily lead to data blind spots, causing risk assessment results to deviate from the actual situation and causing high-risk risks to the enterprise's finances. Therefore, a risk analysis method and system for financial data are proposed. Summary of the Invention

[0004] The object of the present invention is to provide a risk analysis method and system for financial data to solve the problems raised in the above background technology.

[0005] To solve the above technical problems, one of the objectives of the present invention is to provide a risk analysis method for financial data, comprising the following steps:

[0006] S1. Collect internal financial data of internal enterprises and identify the list of relevant enterprises based on the internal financial data;

[0007] S2. Collect external financial data and external enterprise information based on the list of relevant enterprises, and simultaneously screen the internal financial data in combination with the list of relevant enterprises to obtain the relevant financial data corresponding to each external enterprise;

[0008] S3. Conduct basic financial amount flow analysis based on external financial data combined with external enterprise information, intercept relevant financial data for valid time periods, and then dynamically adjust the basic financial amounts based on valid relevant financial data;

[0009] S4. Based on the adjusted basic financial amounts and internal financial data, set differentials for different risk levels. Simultaneously, combine the new internal financial data corresponding to each external enterprise with the basic financial amounts to determine risk, and conduct a review based on the determination results.

[0010] S5. Perform dynamic risk stress tolerance residual value analysis based on internal financial data, compare the risk stress tolerance residual value with the newly verified internal financial data, and determine the highest risk for the new internal financial data based on the comparison results.

[0011] As a further improvement of this technical solution, S1 collects financial data through the financial software of the enterprise's financial end, and uses the collected financial data as internal financial data. At the same time, it identifies related corporate cooperation based on the internal financial data, obtains related companies that have cooperation with internal companies, and summarizes them as a list of related companies.

[0012] As a further improvement of the present technical solution, S1 and S2 regard enterprises that need to undergo risk analysis as internal enterprises, and regard enterprises that have financial expenditure correlation with internal enterprises as external enterprises.

[0013] As a further improvement of this technical solution, the steps of S2 are as follows:

[0014] S2.1. Collect external financial data and external enterprise information based on the list of relevant enterprises, and obtain the external financial data and external enterprise information corresponding to each external enterprise in the list of relevant enterprises;

[0015] Download the financial statements submitted by external companies every quarter as external financial data;

[0016] Obtain basic information of external enterprises as external enterprise information;

[0017] S2.2. Screen the internal financial data in conjunction with the list of related companies to obtain the relevant financial data corresponding to each external company.

[0018] As a further improvement of this technical solution, the steps of S3 are as follows:

[0019] S3.1. Evaluate the economic status of external enterprises based on external financial data and obtain the economic status score of the enterprises;

[0020] Conduct basic economic evaluation of external enterprises based on external enterprise information to obtain the basic economic score of the enterprise;

[0021] By comprehensively analyzing the economic status score of the enterprise and the basic economic score, the basic financial amount corresponding to the expenditure is matched to each external enterprise based on the analysis results;

[0022] S3.2. Set a valid period, intercept relevant financial data based on the obtained valid period, and then use the relevant financial data intercepted based on the valid period as the valid relevant financial data;

[0023] S3.3. Dynamically adjust the basic financial amount in combination with valid relevant financial data.

[0024] As a further improvement of this technical solution, the S3.3 further includes the following steps:

[0025] S3.3.1. Evaluate the payment settlement efficiency based on valid relevant financial data and obtain a settlement efficiency score;

[0026] S3.3.2. Evaluate the frequency of business cooperation based on valid relevant financial data and obtain a cooperation frequency score;

[0027] S3.3.3. Evaluate the amount of valid relevant financial data and obtain a numerical score for the amount;

[0028] S3.3.4. The settlement efficiency score, cooperation frequency score, and amount score are combined with the basic financial amount for adjustment. The higher the score, the greater the upward adjustment amount of the basic financial amount. Conversely, the lower the score, the smaller the upward adjustment amount of the basic financial amount.

[0029] As a further improvement of this technical solution, the steps of S4 are as follows:

[0030] S4.1. Combine the adjusted basic financial amounts of each external enterprise with internal financial data to conduct risk level analysis. Each risk level is assigned a corresponding difference between the basic financial amount and the adjusted basic financial amount.

[0031] S4.2. Obtain new internal financial data generated in real time and perform risk assessment based on the new internal financial data combined with the corresponding external enterprise's basic financial amounts. If the amount of the new internal financial data exceeds the basic financial amount, calculate the difference between the excess amount and each risk level to determine the risk level of the new internal financial data. Upload the new financial data with the risk level to the management terminal for review.

[0032] When the amount of the new internal financial data is less than the basic financial amount, it is determined that there is no risk level and the company's financial department will conduct a normal review.

[0033] As a further improvement of this technical solution, the steps of S5 are as follows:

[0034] S5.1. Perform dynamic risk resilience residual value analysis based on internal financial data. Obtain the risk resilience residual value based on the risk results. Then, extract new internal financial data with risk levels and compare it with the risk resilience residual value.

[0035] S5.2. When the amount of new internal financial data with a risk rating is greater than the remaining risk tolerance value, the risk rating of the new internal financial data will be adjusted to the highest level and then reviewed by management;

[0036] S5.3. When the amount of new internal financial data with a risk level is less than the remaining risk tolerance value, the original risk level shall be maintained.

[0037] A second object of the present invention is to provide a risk analysis system for financial data, comprising any one of the above-mentioned risk analysis methods for financial data, including a data screening module, a risk determination module, and a risk adjustment module;

[0038] The data screening module is used to collect internal financial data of internal enterprises, identify a list of related enterprises based on the internal financial data, collect external financial data and external enterprise information based on the list of related enterprises, and screen the internal financial data in combination with the list of related enterprises to obtain relevant financial data corresponding to each external enterprise;

[0039] The risk assessment module is used to analyze the flow of basic financial amounts based on external financial data combined with external enterprise information, intercept relevant financial data for valid time periods, and then dynamically adjust the basic financial amounts in combination with valid relevant financial data. Based on the adjusted basic financial amounts and combined with internal financial data, the module sets differentials for different risk levels. At the same time, the module combines the new internal financial data corresponding to each external enterprise with the basic financial amounts to conduct risk assessment, and conducts a review based on the assessment results.

[0040] The risk adjustment module is used to perform dynamic risk stress resistance residual value analysis based on internal financial data, compare the risk stress resistance residual value with the reviewed new internal financial data, and determine the highest risk for the new internal financial data based on the comparison results.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] 1. A risk analysis method and system for financial data. This system automatically collects internal financial data through financial software and combines it with external data such as industrial and commercial data, credit information, and industry reports to build a three-dimensional portrait of internal transactions and external credit. This avoids risk blind spots caused by relying solely on internal data and enables an upgrade from transaction amount monitoring to comprehensive enterprise risk assessment.

[0043] 2. A risk analysis method and system for financial data. This system dynamically calculates the residual risk tolerance value to monitor the company's overall risk exposure in real time. If the amount of a single risky transaction exceeds the residual tolerance value, the risk level is automatically raised to the highest level and the transaction is frozen, requiring personal approval from management. This prevents a single high-risk transaction from causing a break in the company's capital chain and improves overall risk tolerance. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is the overall flow chart of the present invention;

[0045] Figure 2 A flowchart of the process of obtaining relevant financial data corresponding to each external enterprise for the present invention;

[0046] Figure 3 A flowchart of the present invention for dynamically adjusting the basic financial amount in combination with valid relevant financial data;

[0047] Figure 4 A flowchart of the present invention for performing different risk level analyses;

[0048] Figure 5 This is a flowchart of the present invention for extracting new internal financial data with risk levels and comparing them with the risk stress residual value. DETAILED DESCRIPTION

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0050] like Figure 1-Figure 5 As shown, one of the objectives of the present invention is to provide a risk analysis method for financial data, comprising the following steps:

[0051] S1. Collect internal financial data of internal enterprises and identify the list of relevant enterprises based on the internal financial data;

[0052] S1 collects financial data through the financial software on the enterprise's financial side, and uses the collected financial data as internal financial data. At the same time, it identifies related corporate cooperation based on the internal financial data, obtains related companies that have cooperation with internal companies, and summarizes them as a list of related companies.

[0053] S1 and S2 treat enterprises that require risk analysis as internal enterprises and those that have financial expenditure-related relationships with internal enterprises as external enterprises.

[0054] S2. Collect external financial data and external enterprise information based on the list of relevant enterprises, and simultaneously screen the internal financial data in combination with the list of relevant enterprises to obtain the relevant financial data corresponding to each external enterprise;

[0055] The steps of S2 are as follows:

[0056] S2.1. Collect external financial data and external enterprise information based on the list of relevant enterprises, and obtain the external financial data and external enterprise information corresponding to each external enterprise in the list of relevant enterprises;

[0057] Download the financial statements submitted by external companies every quarter as external financial data;

[0058] Identify the channels for obtaining quarterly financial statements from external companies, such as official company websites, stock exchange websites (for listed companies), and professional financial data platforms. Follow the list of relevant companies and download each external company's quarterly financial statement from the data source in turn. Then, perform preliminary processing on the downloaded financial statements, such as extracting key data items (assets, liabilities, revenue, profits, etc.) and standardizing the data format.

[0059] Obtain basic information of external enterprises as external enterprise information;

[0060] Determine the basic information of external enterprises that need to be collected, including the company's registered address, legal representative, registered capital, business scope, establishment time, equity structure, etc., and obtain relevant information through channels such as the website of the industrial and commercial administrative department, the corporate credit information disclosure system, and the website of the industry association. Then, integrate the various types of collected information to establish a basic information file for each external enterprise.

[0061] S2.2. Screen the internal financial data in conjunction with the list of related companies to obtain the relevant financial data corresponding to each external company.

[0062] Match the names of the counterparty companies in the internal financial data with the list of relevant companies, filter out the financial data of companies whose counterparties are on the list of relevant companies from the internal financial data, classify the filtered financial data according to external companies, and obtain the relevant financial data corresponding to each external company.

[0063] S3. Conduct basic financial amount flow analysis based on external financial data combined with external enterprise information, intercept relevant financial data for valid time periods, and then dynamically adjust the basic financial amounts based on valid relevant financial data;

[0064] The steps for S3 are as follows:

[0065] S3.1. Evaluate the economic status of external enterprises based on external financial data and obtain the economic status score of the enterprises;

[0066] Conduct basic economic evaluation of external enterprises based on external enterprise information to obtain the basic economic score of the enterprise;

[0067] By comprehensively analyzing the company's economic status score and basic economic score, the basic financial amount corresponding to the expenditure is matched to each external company based on the analysis results. The specific steps are as follows:

[0068] Economic status assessment and scoring: Extract key financial indicators from external financial data, such as total assets, total liabilities, and owner's equity in the balance sheet; operating income and net profit in the income statement; and cash flow from operating activities in the cash flow statement. Because different financial indicators have different dimensions and value ranges, they need to be standardized to facilitate subsequent comprehensive calculations. Then, based on the importance of each financial indicator to the company's economic status, determine the weight of each indicator. Multiply the standardized indicator value by the corresponding weight, and then sum it to obtain the company's economic status score. The formula is as follows:

[0069]

[0070] Among them, S e is the economic status score of the enterprise, k is the number of financial indicators, w j is the indicator weight, z j is the jth financial indicator of the enterprise;

[0071] Basic Economic Assessment and Scoring: Extract information related to basic economic conditions from external corporate data, such as the company's industry position, market share, technological strength, management team quality, and policy environment. Then, develop scoring criteria for each basic economic factor. For example, industry position can be divided into three levels: leading, medium, and lagging, each with a corresponding score. Based on the company's performance on each basic economic factor, a score is assigned according to the scoring criteria. The scores for each factor are then added together to obtain the company's basic economic score.

[0072] Comprehensive analysis and matching of basic financial amounts: The economic status score and basic economic score are weighted averaged according to certain weights to obtain the comprehensive score of the enterprise. Different intervals are divided according to the range of the comprehensive score. Each interval corresponds to a different basic financial amount level. The basic financial amount is matched to the enterprise according to the interval in which the comprehensive score falls. The formula is as follows:

[0073] Sp=weSe+wbSb;

[0074] Among them, S p is the comprehensive score of the enterprise, w e is the economic status score weight, w b is the basic economic score weight, Sb Provide basic economic scores for enterprises, and e +w=1.

[0075] S3.2. Set the effective period, intercept the relevant financial data according to the obtained effective period, and then use the relevant financial data intercepted according to the effective period as the effective relevant financial data. The specific steps are as follows:

[0076] Determine the target analysis period: clearly define the time range for analysis (e.g., the past year, the past three years), or set a base period based on the business cycle (e.g., quarterly, annual);

[0077] Screening for valid data periods: Eliminate time periods where the data missing rate exceeds a threshold (e.g., 20%), identify periods with abnormal data fluctuations (e.g., sudden large-value transactions, unusual fluctuations in financial indicators), and determine whether they are valid business cycles. Also, consider the industry characteristics of external companies (e.g., seasonal industries) and retain periods with active collaboration with internal companies.

[0078] Extracting valid and relevant financial data: Based on the above filtering criteria, extract a continuous, complete time period that complies with business logic from the raw data as the valid time period. Transaction records matching this time period are then extracted from the internal financial data to generate valid and relevant financial data.

[0079] S3.3. Dynamically adjust the basic financial amount in combination with valid relevant financial data.

[0080] S3.3 also includes the following steps:

[0081] S3.3.1. Evaluate the payment settlement efficiency based on valid relevant financial data and obtain a settlement efficiency score;

[0082] Extract transaction dates and payment cycles (e.g., the number of days from invoice issuance to payment receipt) from valid relevant financial data, and set scoring criteria based on the length of the payment cycle (e.g., using the industry average as a benchmark);

[0083] S3.3.2. Evaluate the frequency of business cooperation based on valid relevant financial data and obtain a cooperation frequency score;

[0084] Count the number of transactions or cooperation frequency within the effective period (e.g., monthly / quarterly transactions), and divide the scoring levels into high, medium, and low frequency levels according to the transaction frequency range;

[0085] S3.3.3. Evaluate the amount of valid relevant financial data and obtain a numerical score for the amount;

[0086] Calculate the average single transaction amount and the proportion of cumulative transaction amount (as a proportion of total internal corporate expenditure) within the effective period, and set the scoring level based on the amount or proportion.

[0087] Assign weights to the three scoring items (e.g., settlement efficiency 40%, cooperation frequency 30%, and amount 30%);

[0088] S3.3.4. The settlement efficiency score, cooperation frequency score, and amount score are combined with the basic financial amount to make adjustments. The higher the score, the greater the upward adjustment amount of the basic financial amount. Conversely, the lower the score, the smaller the upward adjustment amount of the basic financial amount. The formula is as follows:

[0089] Zth=w1×Jv+w2×hz+w3×Je;

[0090] Among them, Z th For the comprehensive score, J v is the settlement efficiency score, h z Score the frequency of collaboration, J e is the numerical score of the amount, w1, w2, and w3 are the corresponding weights respectively;

[0091]

[0092] Among them, G t G is the adjustment amount. c is the basic financial amount, α is the adjustment coefficient;

[0093] The higher the score, the greater the coefficient, which is set according to the enterprise's risk preference (0.1-0.3).

[0094] S4. Based on the adjusted basic financial amounts and internal financial data, set differentials for different risk levels. Simultaneously, combine the new internal financial data corresponding to each external enterprise with the basic financial amounts to determine risk, and conduct a review based on the determination results.

[0095] The steps for S4 are as follows:

[0096] S4.1. Combine the adjusted basic financial amounts of each external enterprise with internal financial data to conduct risk level analysis. Each risk level is assigned a corresponding difference between the basic financial amount and the adjusted basic financial amount.

[0097] Based on the company's risk management strategy and historical data, risks are divided into different levels, such as low risk, medium risk, and high risk. For each risk level, a corresponding amount difference from the basic financial amount is set. For example, the low risk level exceeds the basic financial amount by a certain percentage (such as 5%), the medium risk level exceeds by a certain percentage (such as 10%), and the high risk level exceeds by a certain percentage (such as 15%).

[0098] S4.2. Obtain new internal financial data generated in real time (new internal financial data generated by transactions with external companies, including transaction amounts, transaction times, and other information, is obtained in real time from the company's financial system). Risk assessment is performed based on this new internal financial data combined with the corresponding external company's basic financial amounts. If the amount of the new internal financial data exceeds the basic financial amount, the excess amount is combined with the difference between each risk level to determine the risk level of the new internal financial data. The new financial data with the risk level is then uploaded to the management terminal for review.

[0099] When the amount of the new internal financial data is less than the basic financial amount, it is determined that there is no risk level and the company's financial department will conduct a normal review.

[0100] S5. Perform dynamic risk stress tolerance residual value analysis based on internal financial data, compare the risk stress tolerance residual value with the newly verified internal financial data, and determine the highest risk for the new internal financial data based on the comparison results.

[0101] The steps for S5 are as follows:

[0102] S5.1. Perform dynamic risk resilience residual value analysis based on internal financial data. Obtain the risk resilience residual value based on the risk results. Then, extract new internal financial data with risk levels and compare it with the risk resilience residual value.

[0103] S5.2. When the amount of new internal financial data with a risk rating is greater than the remaining risk tolerance value, the risk rating of the new internal financial data will be adjusted to the highest level and then reviewed by management;

[0104] S5.3. When the amount of new internal financial data with a risk level is less than the remaining risk tolerance value, the original risk level is maintained. The specific steps are as follows:

[0105] Define the remaining risk tolerance value: the maximum risk exposure that a company can bear within a certain period of time. This value is calculated based on core financial indicators such as net assets and cash flow. Data such as total assets, total liabilities, net cash flow from operating activities, and existing risk exposure are extracted from internal financial data. The remaining tolerable risk limit is dynamically calculated using a risk quantification model.

[0106] Comparison of monetary values and residual stress tolerance: New internal financial data with risk levels (such as low, medium, and high) are screened from the risk assessment results, and the monetary values involved are extracted. The monetary values of the risk data are then compared with the dynamically calculated residual stress tolerance value to determine whether the risk exceeds the company's overall risk tolerance.

[0107] Risk level adjustment and review: If the amount is greater than the remaining risk tolerance, the risk level will be forcibly raised to the highest level and submitted to management for review;

[0108] If the amount is less than or equal to the remaining risk tolerance, the original risk level will be maintained and the review will be conducted according to the normal process. The formula is as follows:

[0109] Gk=C×β-Gr

[0110] Among them, G k is the residual value of risk resistance, C is the net assets, β is the risk tolerance ratio, G r It is the existing risk exposure (the total amount of unsettled risk transactions that have occurred).

[0111] A second object of the present invention is to provide a risk analysis system for financial data, comprising any one of the above-mentioned risk analysis methods for financial data, including a data screening module, a risk determination module, and a risk adjustment module;

[0112] The data screening module is used to collect the internal financial data of internal enterprises, identify the relevant enterprise list based on the internal financial data, collect external financial data and external enterprise information based on the relevant enterprise list, and screen the internal financial data in combination with the relevant enterprise list to obtain the relevant financial data corresponding to each external enterprise;

[0113] The risk assessment module is used to analyze the flow of basic financial amounts based on external financial data combined with external enterprise information, intercept relevant financial data for valid time periods, and then dynamically adjust the basic financial amounts based on valid relevant financial data. Based on the adjusted basic financial amounts and internal financial data, the module sets differentials for different risk levels. At the same time, the new internal financial data corresponding to each external enterprise is combined with the basic financial amounts to conduct risk assessments, and the assessment results are reviewed.

[0114] The risk adjustment module is used to perform dynamic risk stress residual value analysis based on internal financial data, compare the risk stress residual value with the newly verified internal financial data, and determine the highest risk for the new internal financial data based on the comparison results.

[0115] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and improvements may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and improvements fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A risk analysis method for financial data, characterized by: The steps include: S1. Collect internal financial data of internal enterprises and identify the list of relevant enterprises based on the internal financial data; S2. Collect external financial data and external enterprise information based on the list of relevant enterprises, and simultaneously screen the internal financial data in combination with the list of relevant enterprises to obtain the relevant financial data corresponding to each external enterprise; S3. Conduct basic financial amount flow analysis based on external financial data combined with external enterprise information, intercept relevant financial data for valid time periods, and then dynamically adjust the basic financial amounts based on valid relevant financial data; S4. Based on the adjusted basic financial amounts and internal financial data, set differentials for different risk levels. Simultaneously, combine the new internal financial data corresponding to each external enterprise with the basic financial amounts to determine risk, and conduct a review based on the determination results. S5. Perform dynamic risk stress tolerance residual value analysis based on internal financial data, compare the risk stress tolerance residual value with the newly verified internal financial data, and determine the highest risk for the new internal financial data based on the comparison results.

2. A risk analysis method for financial data according to claim 1, characterized in that: The S1 collects financial data through the financial software of the enterprise's financial end, and uses the collected financial data as internal financial data. At the same time, it identifies related corporate cooperation based on the internal financial data, obtains related companies that have cooperation with internal companies, and summarizes them as a list of related companies.

3. The risk analysis method for financial data according to claim 1, characterized in that: The S1 and S2 are based on the principle that enterprises that need to undergo risk analysis are regarded as internal enterprises, and enterprises that have financial expenditure correlation with internal enterprises are regarded as external enterprises.

4. The risk analysis method for financial data according to claim 1, characterized in that: The steps of S2 are as follows: S2.

1. Collect external financial data and external enterprise information based on the list of relevant enterprises, and obtain the external financial data and external enterprise information corresponding to each external enterprise in the list of relevant enterprises; Download the financial statements submitted by external companies every quarter as external financial data; Obtain basic information of external enterprises as external enterprise information; S2.

2. Screen the internal financial data in conjunction with the list of related companies to obtain the relevant financial data corresponding to each external company.

5. The risk analysis method for financial data according to claim 1, characterized in that: The steps of S3 are as follows: S3.

1. Evaluate the economic status of external enterprises based on external financial data and obtain the economic status score of the enterprises; Conduct basic economic evaluation of external enterprises based on external enterprise information to obtain the basic economic score of the enterprise; By comprehensively analyzing the economic status score of the enterprise and the basic economic score, the basic financial amount corresponding to the expenditure is matched to each external enterprise based on the analysis results; S3.

2. Set a valid period, intercept relevant financial data based on the obtained valid period, and then use the relevant financial data intercepted based on the valid period as the valid relevant financial data; S3.

3. Dynamically adjust the basic financial amount in combination with valid relevant financial data.

6. The risk analysis method for financial data according to claim 1, characterized in that: The S3.3 further includes the following steps: S3.3.

1. Evaluate the payment settlement efficiency based on valid relevant financial data and obtain a settlement efficiency score; S3.3.

2. Evaluate the frequency of business cooperation based on valid relevant financial data and obtain a cooperation frequency score; S3.3.

3. Evaluate the amount of valid relevant financial data and obtain a numerical score for the amount; S3.3.

4. The settlement efficiency score, cooperation frequency score, and amount score are combined with the basic financial amount for adjustment. The higher the score, the greater the upward adjustment amount of the basic financial amount. Conversely, the lower the score, the smaller the upward adjustment amount of the basic financial amount.

7. The risk analysis method for financial data according to claim 1, characterized in that: The steps of S4 are as follows: S4.

1. Combine the adjusted basic financial amounts of each external enterprise with internal financial data to conduct risk level analysis. Each risk level is assigned a corresponding difference between the basic financial amount and the adjusted basic financial amount. S4.

2. Obtain new internal financial data generated in real time and perform risk assessment based on the new internal financial data combined with the corresponding external enterprise's basic financial amounts. If the amount of the new internal financial data exceeds the basic financial amount, calculate the difference between the excess amount and each risk level to determine the risk level of the new internal financial data. Upload the new financial data with the risk level to the management terminal for review. When the amount of the new internal financial data is less than the basic financial amount, it is determined that there is no risk level and the company's financial department will conduct a normal review.

8. The risk analysis method for financial data according to claim 1, characterized in that: The steps of S5 are as follows: S5.

1. Perform dynamic risk resilience residual value analysis based on internal financial data. Obtain the risk resilience residual value based on the risk results. Then, extract new internal financial data with risk levels and compare it with the risk resilience residual value. S5.

2. When the amount of new internal financial data with a risk rating is greater than the remaining risk tolerance value, the risk rating of the new internal financial data will be adjusted to the highest level and then reviewed by management; S5.

3. When the amount of new internal financial data with a risk level is less than the remaining risk tolerance value, the original risk level shall be maintained.

9. A risk analysis system for financial data, configured to implement the risk analysis method for financial data according to any one of claims 1 to 8, characterized in that: Including data screening module, risk determination module and risk adjustment module; The data screening module is used to collect internal financial data of internal enterprises, identify a list of related enterprises based on the internal financial data, collect external financial data and external enterprise information based on the list of related enterprises, and screen the internal financial data in combination with the list of related enterprises to obtain relevant financial data corresponding to each external enterprise; The risk assessment module is used to analyze the flow of basic financial amounts based on external financial data combined with external enterprise information, intercept relevant financial data for valid time periods, and then dynamically adjust the basic financial amounts in combination with valid relevant financial data. Based on the adjusted basic financial amounts and combined with internal financial data, the module sets differentials for different risk levels. At the same time, the module combines the new internal financial data corresponding to each external enterprise with the basic financial amounts to conduct risk assessment, and conducts a review based on the assessment results. The risk adjustment module is used to perform dynamic risk stress resistance residual value analysis based on internal financial data, compare the risk stress resistance residual value with the reviewed new internal financial data, and determine the highest risk for the new internal financial data based on the comparison results.

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