Method and system for trust market risk monitoring and early warning

Abstract

The invention discloses a trust market risk monitoring and early warning method and system. The method comprises the steps of 1, data acquisition; step 2, constructing financial risk early warning measures; step 3, implementing an early warning monitoring means; 4, implementing a responsibility system; 5, a responsibility mutual supervision system of all function management departments is established; 6, evaluating punishment measures and extra-large financial risk credit investigation systems; according to the method, the credible big data platform is adopted to collect the underlying risk index data of the multi-business-state financial institutions, and the data differences and the operating business states of the financial institutions such as banks, securities, trust and the like are integrated, so that the data security is ensured, and the risk data marts are established in a classified manner according to the business modes, the operating characteristics and the contained risk categories of the business states. The management cockpit adopts top thinking to quickly, timely and visually display the overall operation condition and risk condition of each commercial financial institution.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to a method and system for monitoring and early warning of trust market risks. Background Art

[0002] The formation of modern trusts marks the transition from civil trusts with natural persons as trustees to commercial trusts with legal persons as trustees. Trust activities undertaken for the purpose of profit by trustees make trusts a commercial act and trust business an important part of financial services. When trusts become a commercial act, especially when their special institutional advantages become an important part of the financial industry, the sum of demand and supply of trust services forms the trust market; it can also be said that the field where the trust service industry realizes its value is the trust market. The trust market, together with the capital market, money market, and insurance market, constitutes the modern financial market.

[0003] Among them, the Chinese patent with application number "CN202310854501.5" discloses "a risk monitoring and early warning method for collateral management in the banking industry", which records "the present invention discloses a risk monitoring and early warning method for collateral management in the banking industry, which relates to the technical field of collateral management. The risk monitoring and early warning method and device for collateral management in the banking industry include the following operating steps: S1, collateral perception; S2, sensing end type selection; S3, safety judgment; S4, risk warning and S5, multi-platform access. The risk monitoring and early warning method and device for collateral management in the banking industry, when deriving risk hazards, the environmental data of the future time period used will be combined with the electrical data, structural data, and endurance data in this time period for derivation, and then based on the derived possible risk hazards, the results will be transmitted to the monitoring platform for early warning, and the corresponding risk hazard treatment plan will be pushed, thereby obtaining a relatively accurate prediction of risk hazards based on the predicted data derivation to achieve early warning so that the staff can prevent and handle them in time, thereby reducing losses; However, the prospecting method in the above patent document still has the following defects: 1) The traditional trust market business generally requires early warning of financial market trust risks, because trust is essentially linked to various financial funds and items, and provides financial services that anticipate rising or falling losses. However, once the economy is involved, it is easy for some trust services to be under-regulated, which can easily lead to unwarranted losses of financial assets, or untimely financial warnings during the regulatory stage, resulting in capital losses or disappearances; 2) The funds in the traditional financial trust market generally need to be analyzed for large-scale trusts that are experiencing capital losses or the corresponding trust market. The common problem is that a specific part of the funds is not accurate enough in subsequent monitoring, which can easily lead to the inability to confirm the fund information. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for monitoring and early warning of trust market risks to solve the problems raised by the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: A method for monitoring and early warning of trust market risks: Step 1: obtaining the data source of funds in initial circulation; Step 2: constructing risk early warning technology; Step 3: Means of determining trust market risks; Step 4: Elimination techniques after risks occur; Step 5: Countermeasures for trust risk monitoring and early warning; Step 6: Means of improving early warning.

[0006] As a preferred solution of the present invention: Step 1 is specifically as follows: Point 1: The relationship between the financial currency pool of the buyer's market and the seller's market of the trust market and the ownership of the trust bond option bond; It is clear that there is a balance between the capital pool and the pool of bonds gathered, and the specific exchange rate relationship is linked to trust monitoring; Compare the review of the Ponzi scheme with the amount of funds owned by each owner; Point 2: The big data platform obtains the capital operation data of financial enterprises and verifies the contractual connection between the data and the data platform; Compare the inflow of international funds with the rise and fall of various trust markets; The relationship between the outflow of corporate financial capital loans and the circular comparison data of the existing trust market capital pool, and its rationality; (1) Identify the source of funds: Determine the source and outflow areas of funds, obtain the underlying financial data and the subsequent fund flow, pre-process the underlying data of financial institutions, and compare the data combing during the period with the negotiation contracts of the underlying data fund pool and the bond selling and redemption companies; (2) Early warning of the coordination status of the financial trust market and data monitoring and reading in the early warning method of the later plan. In addition, the quantitative analysis of the financial currency pool in the plan data, the acquisition of specific funds and the further acquisition and analysis of the corresponding treatment of residual funds of the trust fund; (3) Monitoring and early warning management of corresponding trust risks: sorting out and monitoring the specific risks of the corresponding amount of funds; (4) Constructing a data mart based on the trust market; The data include the specific debts of the sellers in the trust market and the balance of the residual fund pool, as well as the difference in the flow direction of the debts and residual funds in the plan; (5) Monitoring and early warning of specific financial market risks and corresponding data risk input; (6) Feedback on the balance in specific corresponding plans and the diameter flow of funds in specific markets.

[0007] Point 3: Classification of fund data: After preprocessing, save the original data, and then aggregate and process the data to form a data indicator layer. Classify the indicator data according to capital, operating, credit risk, liquidity risk and market risk to form a financial risk data mart; After establishing the classification, collect early warnings of market risks involved by enterprises; Set risk appetite and limit indicators, and determine the classification of fund data during the statement stage based on the risk appetite statement of the financial institution; Point 4: It is used to monitor whether the indicators exceed the threshold and then issue risk warning; Determine whether specific monitoring data indicators are reasonable, and the analysis of risk warning monitoring technology obtains corresponding data analysis; Based on the corresponding data trusts, there are: through manual in-depth real-time retrieval: determine the overview, capital situation, equity situation, operating situation, credit risk situation, liquidity and market risk situation, as well as early warning analysis to display financial capital and risk information.

[0008] As a preferred solution of the present invention: Step 2 is specifically as follows: Point 1: Start from the macro perspective: Observe the overview data: From the perspective of the total score, first focus on displaying the capital and risk-return situation of the financial institution as a whole, as well as the operating conditions, and determine.

[0009] Equity structure: Equity data provides insight into the equity structure of financial institutions, information on the top ten shareholders and basic information on directors.

[0010] Capital situation: capital data is used to display capital analysis, as well as the various returns and risks of capital.

[0011] Business performance: Business performance shows the financial indicators of financial institutions such as assets, income, and profits, as well as the comparison of business capabilities in the industry; Credit risk situation: Display the total amount of loans of financial institutions, non-performing assets, impairment provision balance and other credit risk situations, as well as the concentration risk situation of enterprises; Specific credit risk warning is based on the analysis of each data to display financial capital and risk information, based on the technical solution in the technology to determine the internal financial component data capital and risk return situation, as well as the operating conditions, according to the specific credit analysis and specific funds linked to the two data integration solutions to determine the specific data analysis of financial capital quantity and capital trend; Point 2: Early warning, analysis of data trust market archives, deadline determination, and evaluation and judgment based on corresponding capital information assets and data; Point 3: Using market and liquidity risk: showing the VaR value of market risk of financial institutions and the annual profit and loss of trading books, as well as the 30-day liquidity gap, and highlighting the information relationship between the VAR data of market risk of financial institutions and the loss or profit of trading books; Set up a data margin fund pool; In the storage of trust data and subsequent reserve funds, it is ensured that when an early warning is issued, the reserve funds can be promptly withdrawn to fill the gap, ensuring the stability of the market and making data analysis more accurate to avoid decoupling from actual financial data; Risk warnings and specific warning types use warning analysis: According to the warning threshold set in the first step, the warning information of various preference and limit indicators is displayed. After the threshold is determined, when the risk threshold is triggered, a warning is issued in time, and the determined data can be analyzed more reasonably.

[0012] As a preferred solution of the present invention: Step three specifically comprises: according to the warning threshold set in Step 1, displaying warning information of various preference and limit indicators; Determine the data and specific data information generated by the trust market, combine the early warning threshold data analysis, based on the trust market risk, as a classification, summarize the problems generated by the trust risk, and determine the occurrence of the corresponding risk after summarization; Point 2: Use the trust market’s risk access accordingly, and independently obtain data based on trust market risks according to trust risk exposure; A technique for investigating the trust market, analyzing the structured data, and building a data model; Analyze information problems in the trust market and plan strategies for corresponding solutions; Minimize the impact, determine the risk report and solution; Sudden data anomalies require timely identification of the cause of the problem and timely correction of the data presented in the trust market stage; Based on the risk warning and analysis of the corresponding data, use the specific warning coordination plan and channels to determine the specific factors that cause risks to the specific market and the funds, or call on the reserve funds in the fund pool to make up for the loss and recover the funds after recovery.

[0013] As a preferred solution of the present invention, step 4 is specifically as follows: Step 3, early warning signal handling. According to the early warning information generated in step 2, the early warning information is issued according to the corresponding early warning agency, and after the early warning agency handles the early warning information, it is reported, fed back and tracked until the early warning signal is lifted.

[0014] Step 4: Automatically generate a risk assessment report. (1) Create a risk assessment report template. The system has a built-in risk assessment report template function. You can create a risk assessment report template for the corresponding institution based on the type of financial institution. Financial institutions include banks, securities, trusts, etc. (2) Generate a report with one click. Select the template created in the first step and select the data date. According to the data date, the current risk data will be automatically collected and filled into the risk report to generate the first version of the risk assessment report. (3) Add qualitative analysis. Based on the data generated in the risk assessment report, edit the qualitative analysis content online. (4) Generate a risk assessment report. After editing, you can view the risk assessment report through preview and provide a download function.

[0015] As a preferred solution of the present invention: Step 5 is specifically as follows: Point 1: Implementing the repair and responsibility after the cause of the risk; Determine the remediation after the corresponding risks are generated, and fill the gaps as assets of the enterprises and individuals who need to bear them in the form of specific accountability information; Point 2: Ensure the data gains and losses before and after data repair, as well as the analysis and blocking of specific data; Verify the company's own operating conditions, implement asset filing for financial formats, build a cockpit, determine various data files, and manual information; During this period, data information coordination and supplementation were combined with: specific data analysis, and the subsequent implementation of information acquisition methods to make up for specific loopholes.

[0016] As a preferred solution of the present invention: Step 6 specifically includes: based on the improvement of the specific early warning method, based on the data analysis in the specific early warning detection scheme, and the information filing channel after the later data is written and the early warning disclosure on the data analysis; Improve the punishment measures after early warning, based on the behavior of financial crimes, to achieve information communication and networking in the cockpit, and to ensure asset implementation and business implementation mechanisms for financial fraud and trust behavior; Coordinate the summarization and sorting of various types of data, integrate the detection of information risks, obtain information and expand the specific information monitoring, and coordinate the conversion of information mismatch problems; Step 2: Determine the data update of the guidance data and the specific data connected to the cockpit; The storage method is determined as follows: after the summarized and sorted information is determined, it is stored in a server with networking function, and a redundant backup plan is activated to ensure the security of the data.

[0017] A system for monitoring and early warning of trust market risks, comprising any one of the above-mentioned methods for monitoring and early warning of trust market risks, It includes cockpit building module, data storage module and alarm module for coordinating early warning; The cockpit construction module includes a display module for implementing data display, an output module for data call-out and printing, and a data transmission module for constructing corresponding data images; The display module and the data transmission module are bidirectionally arranged, and the output module and the data transmission module are bidirectionally arranged.

[0018] As a preferred solution of the present invention: the data storage module is respectively composed of: a storage server module, a redundant storage hard disk module, a bandwidth network module and an analysis module for data interaction; The storage server module and the data storage module are bidirectionally arranged, the redundant storage hard disk module and the bandwidth network module are unidirectionally arranged, and the analysis module and the external redundant storage hard disk module are unidirectionally controlled.

[0019] As a preferred solution of the present invention: the alarm module is respectively composed of: a preset trigger module, a decision module, an option module for built-in programs, and a problem troubleshooting module; The preset trigger module and the alarm module are bidirectionally arranged, the decision module and the preset trigger module are bidirectionally arranged, the option module and the decision module are bidirectionally arranged, and the problem troubleshooting module and the option module are bidirectionally arranged.

[0020] Compared with the prior art, the present invention has the following beneficial effects: 1) Through the evaluation of the initial source of funds and subsequent review, the risk monitoring and early warning means in the plan utilizes the diameter monitoring within the currency pool of the trust market to ensure that the trust funds have a process-based and specific monitoring purpose when they are entrusted to large financial institutions as agents. The monitoring and early warning management and risk sorting functions adopted ensure that the invested trust funds are given a more comprehensive early warning at the stage of large-scale dispersion; 2) The diameter source address and capital flow direction are used to determine the source and direction of the underlying financial data, determine whether the relationship between the capital and bond pools is balanced in the later stage, and use capital classification to determine whether the financial attributes of the funds are consistent with the nature of the trust. While ensuring the healthy development of finance, data risk input is used to discover the financial problems caused by various reasons in the past and make timely corrections; 3) Use a cockpit with IoT attributes to sort out relatively accurate and effective financial market risk data from various complex data. This data can be changes in the seller's financial reservoir, as well as strong monitoring of later data. Use various liquidity in the correction plan to monitor abnormal losses caused by operating problems or external environment. In the event of large-scale losses caused by corruption, timely classify them into operating, credit risk, liquidity risk and market risk to form a financial risk data mart. After establishing the classification, collect market risk warnings involved in the enterprise, BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of the steps of the present invention; Figure 2 It is a schematic diagram of the module structure of the present invention.

[0022] In the figure: 1. Cockpit construction module; 11. Display module; 12. Output module; 13. Data transmission module; 2. Data storage module; 21. Storage server module; 22. Redundant storage hard disk module; 23. Bandwidth network module; 24. Analysis module; 3. Alarm module; 31. Trigger module; 32. Decision module; 33. Option module; 34. Troubleshooting module. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0024] See also Figure 1 - Figure 2 ,The present invention provides a technical solution: a method for monitoring and early warning of trust market risks. In this embodiment: Step 1: obtaining the data source of funds in initial circulation; Point 1: The relationship between the financial currency pool in the buyer's market and the seller's market of the trust market and the ownership of trust bond options bonds; It is clear that there is a balance between the capital pool and the pool of bonds gathered, and the specific exchange rate relationship is linked to trust monitoring; Compare the review of the Ponzi scheme with the amount of funds owned by each owner; Point 2: The big data platform obtains the capital operation data of financial enterprises and verifies the contractual connection between the data and the data platform; Compare the inflow of international funds with the rise and fall of various trust markets; The relationship between the outflow of corporate financial capital loans and the circular comparison data of the existing trust market capital pool, and its rationality; (1) Identify the source of funds: Determine the source and outflow areas of funds, obtain the underlying financial data and the subsequent fund flow, pre-process the underlying data of financial institutions, and compare the data combing during the period with the negotiation contracts of the underlying data fund pool and the bond selling and redemption companies; (2) Early warning of the coordination status of the financial trust market and data monitoring and reading in the early warning method of the later plan. In addition, the quantitative analysis of the financial currency pool in the plan data, the acquisition of specific funds and the further acquisition and analysis of the corresponding treatment of residual funds of the trust fund; (3) Monitoring and early warning management of corresponding trust risks: sorting out and monitoring the specific risks of the corresponding amount of funds; (4) Constructing a data mart based on the trust market; The data include the specific debts of the sellers in the trust market and the balance of the residual fund pool, as well as the difference in the flow direction of the debts and residual funds in the plan; (5) Monitoring and early warning of specific financial market risks and corresponding data risk input; (6) Feedback on the balance in specific corresponding plans and the diameter flow of funds in specific markets.

[0025] Point 3: Classification of fund data: After preprocessing, save the original data, and then aggregate and process the data to form a data indicator layer. Classify the indicator data according to capital, operating, credit risk, liquidity risk and market risk to form a financial risk data mart; After establishing the classification, collect early warnings of market risks involved by enterprises; Set risk appetite and limit indicators, and determine the classification of fund data during the statement stage based on the risk appetite statement of the financial institution; Point 4: It is used to monitor whether the indicators exceed the threshold and then issue risk warning; Determine whether specific monitoring data indicators are reasonable, and the analysis of risk warning monitoring technology obtains corresponding data analysis; Based on the corresponding data trusts, there are: through manual in-depth real-time retrieval: determine the overview, capital situation, equity situation, operating situation, credit risk situation, liquidity and market risk situation, as well as early warning analysis to display financial capital and risk information; In this embodiment: Step 2: Risk warning technology construction; Small point 1: Start from the macro perspective: Observe the overall data: From the perspective of the total score, first focus on displaying the capital, risk-return situation, and operating conditions of the financial institution as a whole, and determine.

[0026] Equity structure: Equity data provides insight into the equity structure of financial institutions, information on the top ten shareholders and basic information on directors.

[0027] Capital situation: capital data is used to display capital analysis, as well as the various returns and risks of capital.

[0028] Business performance: Business performance shows the financial indicators of financial institutions such as assets, income, and profits, as well as the comparison of business capabilities in the industry; Credit risk situation: Display the total amount of loans of financial institutions, non-performing assets, impairment provision balance and other credit risk situations, as well as the concentration risk situation of enterprises; Specific credit risk warning is based on the analysis of each data to display financial capital and risk information, based on the technical solution in the technology to determine the internal financial component data capital and risk return situation, as well as the operating conditions, according to the specific credit analysis and specific funds linked to the two data integration solutions to determine the specific data analysis of financial capital quantity and capital trend; Point 2: Early warning, analysis of data trust market archives, deadline determination, and evaluation and judgment based on corresponding capital information assets and data; Point 3: Using market and liquidity risk: showing the VaR value of market risk of financial institutions and the annual profit and loss of trading books, as well as the 30-day liquidity gap, and highlighting the information relationship between the VAR data of market risk of financial institutions and the loss or profit of trading books; Set up a data margin fund pool; In the storage of trust data and subsequent reserve funds, it is ensured that when an early warning is issued, the reserve funds can be promptly withdrawn to fill the gap, ensuring the stability of the market and making data analysis more accurate to avoid decoupling from actual financial data; Risk warnings and specific warning types use warning analysis: According to the warning threshold set in the first step, the warning information of various preference and limit indicators is displayed. After the threshold is determined, when the risk threshold is triggered, a warning is issued in time, and the determined data can be analyzed more reasonably.

[0029] Step 3: Means of determining trust market risks According to the warning thresholds set in the first step, the warning information of various preference and limit indicators is displayed; Determine the data and specific data information generated by the trust market, combine the early warning threshold data analysis, based on the trust market risk, as a classification, summarize the problems generated by the trust risk, and determine the occurrence of the corresponding risk after summarization; Point 2: Use the trust market’s risk access accordingly, and independently obtain data based on trust market risks according to trust risk exposure; A technique for investigating the trust market, analyzing the structured data, and building a data model; Analyze information problems in the trust market and plan strategies for corresponding solutions; Minimize the impact, determine the risk report and solution; Sudden data anomalies require timely identification of the cause of the problem and timely correction of the data presented in the trust market stage; Based on the risk warning and analysis of the corresponding data, use the specific warning coordination plan and channels to determine the specific factors that cause risks to the specific market and the funds, or call on the reserve funds in the fund pool to make up for the loss and recover the funds after recovery.

[0030] In this embodiment: Step 4: Elimination technology after the risk occurs; The third step is to deal with the early warning signal. According to the early warning information generated in the second step, the early warning information will be issued to the corresponding early warning agency. After the early warning agency handles the early warning information, it will be reported, fed back and tracked until the early warning signal is lifted.

[0031] Step 4: Automatically generate a risk assessment report. (1) Create a risk assessment report template. The system has a built-in risk assessment report template function. You can create a risk assessment report template for the corresponding institution based on the type of financial institution. Financial institutions include banks, securities, trusts, etc. (2) Generate a report with one click. Select the template created in the first step and select the data date. According to the data date, the current risk data will be automatically collected and filled into the risk report to generate the first version of the risk assessment report. (3) Add qualitative analysis. Based on the data generated in the risk assessment report, edit the qualitative analysis content online. (4) Generate a risk assessment report. After editing, you can view the risk assessment report through preview and provide a download function.

[0032] In this embodiment: Step 5: Countermeasures for trust risk monitoring and early warning; Point 1: Implement the repair and responsibility after the risk occurs; Determine the remediation after the corresponding risks are generated, and fill the gaps as assets of the enterprises and individuals who need to bear them in the form of specific accountability information; Point 2: Ensure the data gains and losses before and after data repair, as well as the analysis and blocking of specific data; Verify the company's own operating conditions, implement asset filing for financial formats, build a cockpit, determine various data files, and manual information; During this period, data information coordination and supplementation were combined with: specific data analysis, and the subsequent implementation of information acquisition methods to make up for specific loopholes.

[0033] In this embodiment: Step 6: means of improving early warning; Based on the improvement of specific early warning methods, based on the data analysis in the specific early warning detection plan, as well as the information filing channel after the later data is written and the early warning disclosure based on data analysis; Improve the punishment measures after early warning, based on the behavior of financial crimes, to achieve information communication and networking in the cockpit, and to ensure asset implementation and business implementation mechanisms for financial fraud and trust behavior; Coordinate the summarization and sorting of various types of data, integrate the detection of information risks, obtain information and expand the specific information monitoring, and coordinate the conversion of information mismatch problems; Step 2: Determine the data update of the guidance data and the specific data connected to the cockpit; Determine the storage method: After the information is determined and summarized, it is stored in a server with networking function, and a redundant backup plan is activated to ensure the security of the data; A system for monitoring and early warning of trust market risks, comprising any one of the above-mentioned methods for monitoring and early warning of trust market risks: It includes a cockpit construction module 1, a data storage module 2 and an alarm module 3 for coordinating early warnings; The feature is that the cockpit construction module 1 includes a display module 11 for implementing data display, an output module 12 for calling out and printing data, and a data transmission module 13 for constructing corresponding data images; The display module 11 and the data transmission module 13 are bidirectionally arranged, and the output module 12 and the data transmission module 13 are bidirectionally arranged.

[0034] In this embodiment: the data storage module 2 is composed of: a storage server module 21, a redundant storage hard disk module 22, a bandwidth network module 23 and an analysis module 24 for data interaction; The storage server module 21 and the data storage module 2 are bidirectionally arranged, the redundant storage hard disk module 22 and the bandwidth network module 23 are unidirectionally arranged, and the analysis module 24 and the external redundant storage hard disk module 22 are unidirectionally controlled.

[0035] By adopting the storage server module 21, which is used for large-scale server computing decisions, it is determined that there is clear computing power support for the specific data operation and maintenance of various cockpits.

[0036] In this embodiment: the alarm module 3 is composed of: a preset trigger module 31, a decision module 32, an option module 33 for built-in programs, and a problem troubleshooting module 34; The preset trigger module 31 is bidirectionally set with the alarm module 3 , the decision module 32 is bidirectionally set with the preset trigger module 31 , the option module 33 is bidirectionally set with the decision module 32 , and the problem troubleshooting module 34 is bidirectionally set with the option module 33 .

[0037] The problem troubleshooting module 34 and the specific decision module 32 are used to analyze various types of information data, and the technology provided by the various options of the option module 33 is used to achieve data analysis in the decision module 32.

[0038] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in the field. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for monitoring and early warning of trust market risks, characterized by: Step 1: Obtaining the initial source of circulating funds data; Step 2: Risk warning technology construction; Step 3: Means of determining trust market risks; Step 4: Elimination techniques after risks occur; Step 5: Countermeasures for trust risk monitoring and early warning; Step 6: Means of improving early warning.

2. A trust market risk monitoring and early warning method according to claim 1, characterized in that: Step 1 is as follows: Point 1: The relationship between the financial currency pool in the buyer's market and the seller's market of the trust market and the ownership of trust bond option bonds; It is clear that there is a balance between the capital pool and the pool of bonds gathered, and the specific exchange rate relationship is linked to trust monitoring; Compare the review of the Ponzi scheme with the amount of funds owned by each owner; Point 2: The big data platform obtains the capital operation data of financial enterprises and verifies the contractual connection between the data and the data platform; Compare the inflow of international funds with the rise and fall of various trust markets; The relationship between the outflow of corporate financial capital loans and the circular comparison data of the existing trust market capital pool, and its rationality; (1) Identify the source of funds: Determine the source and outflow areas of funds, obtain the underlying financial data and the subsequent fund flow, pre-process the underlying data of financial institutions, and compare the data combing during the period with the negotiation contracts of the underlying data fund pool and the bond selling and redemption companies; (2) Early warning of the coordination status of the financial trust market and data monitoring and reading in the early warning method of the later plan. In addition, the quantitative analysis of the financial currency pool in the plan data, the acquisition of specific funds and the further acquisition and analysis of the corresponding treatment of residual funds of the trust fund; (3) Monitoring and early warning management of corresponding trust risks: sorting out and monitoring the specific risks of the corresponding amount of funds; (4) Constructing a data mart based on the trust market; The data include the specific debts of the sellers in the trust market and the balance of the residual fund pool, as well as the difference in the flow direction of the debts and residual funds in the plan; (5) Monitoring and early warning of specific financial market risks and corresponding data risk input; (6) Feedback on the balance of specific corresponding plans and the flow of funds in specific markets; Point 3: Classification of fund data: After preprocessing, save the original data, and then aggregate and process the data to form a data indicator layer. Classify the indicator data according to capital, operating, credit risk, liquidity risk and market risk to form a financial risk data mart; After establishing the classification, collect early warnings of market risks involved by enterprises; Set risk appetite and limit indicators, and determine the classification of fund data during the statement stage based on the risk appetite statement of the financial institution; Point 4: It is used to monitor whether the indicators exceed the threshold and then issue risk warning; Determine whether specific monitoring data indicators are reasonable, and the analysis of risk warning monitoring technology obtains corresponding data analysis; Based on the corresponding data trusts, there are: through manual in-depth real-time retrieval: determine the overview, capital situation, equity situation, operating situation, credit risk situation, liquidity and market risk situation, as well as early warning analysis to display financial capital and risk information.

3. A trust market risk monitoring and early warning method according to claim 2, characterized in that: Step 2 is as follows: Point 1: Start from the macro perspective: Observe the overview data: From the perspective of total score, first focus on the overall display of the capital and risk-return situation of the financial institution, as well as the determination of the operating situation; Equity structure: Equity data provides insight into the equity structure of financial institutions, information on the top ten shareholders and basic information on directors; Capital situation: capital analysis, as well as various returns and risks of capital are displayed through capital data; Business performance: Business performance shows the financial indicators of financial institutions such as assets, income, and profits, as well as the comparison of business capabilities in the industry; Credit risk situation: Display the total amount of loans of financial institutions, non-performing assets, impairment provision balance and other credit risk situations, as well as the concentration risk situation of enterprises; Specific credit risk warning is based on the analysis of each data to display financial capital and risk information, based on the technical solution in the technology to determine the internal financial component data capital and risk return situation, as well as the operating conditions, according to the specific credit analysis and specific funds linked to the two data integration solutions to determine the specific data analysis of financial capital quantity and capital trend; Point 2: Early warning, analysis of data trust market archives, deadline determination, and evaluation and judgment based on corresponding capital information assets and data; Point 3: Using market and liquidity risk: showing the VaR value of market risk of financial institutions and the annual profit and loss of trading books, as well as the 30-day liquidity gap, and highlighting the information relationship between the VAR data of market risk of financial institutions and the loss or profit of trading books; Set up a data margin fund pool; In the storage of trust data and subsequent reserve funds, it is ensured that when an early warning is issued, the reserve funds can be promptly withdrawn to fill the gap, ensuring the stability of the market and making data analysis more accurate to avoid decoupling from actual financial data; Risk warnings and specific warning types use warning analysis: According to the warning threshold set in the first step, the warning information of various preference and limit indicators is displayed. After the threshold is determined, when the risk threshold is triggered, a warning is issued in time, and the determined data can be analyzed more reasonably.

4. The method for monitoring and early warning of trust market risks according to claim 2, characterized in that: Step 3 is as follows: according to the warning threshold set in step 1, display the warning information of various preference and limit indicators; Determine the data and specific data information generated by the trust market, combine the early warning threshold data analysis, based on the trust market risk, as a classification, summarize the problems generated by the trust risk, and determine the occurrence of the corresponding risk after summarization; Point 2: Use the trust market’s risk access accordingly, and independently obtain data based on trust market risks according to trust risk exposure; A technique for investigating the trust market, analyzing the structured data, and building a data model; Analyze information problems in the trust market and plan strategies for corresponding solutions; Minimize the impact, determine the risk report and solution; Sudden data anomalies require timely identification of the cause of the problem and timely correction of the data presented in the trust market stage; Based on the risk warning and analysis of the corresponding data, use the specific warning coordination plan and channels to determine the specific factors that cause risks to the specific market and the funds, or call on the reserve funds in the fund pool to make up for the loss and recover the funds after recovery.

5. A trust market risk monitoring and early warning method according to claim 4, characterized in that: Step 4 is specifically as follows: Step 3, early warning signal handling; according to the early warning information generated in step 2, the early warning information is issued to the corresponding early warning agency, and after the early warning agency handles the early warning information, it is reported, fed back and tracked until the early warning signal is lifted; Step 4: Automatically generate risk assessment report; (1) Develop risk assessment report template; The system has a built-in risk assessment report template function. The risk assessment report template of the corresponding institution is formulated according to the category of financial institutions. Financial institutions include banks, securities, and trusts. (2) Generate a report with one click. Select the template formulated in the first step and select the data date. According to the data date, the current risk data is automatically collected and filled into the risk report to generate the first version of the risk assessment report. (3) Add qualitative analysis; based on the data generated in the risk assessment report, edit the qualitative analysis content online; (4) Generate a risk assessment report; after editing, the risk assessment report can be previewed and a download function is provided.

6. A trust market risk monitoring and early warning method according to claim 5, characterized in that: Step 5 is as follows: Point 1: Implement the repair and responsibility after the risk occurs; Determine the remediation after the corresponding risks are generated, and fill the gaps in the form of specific accountability information as the assets of the companies and individuals who need to bear them; Point 2: Ensure the data gains and losses before and after data repair, as well as the analysis and blocking of specific data; Verify the company's own operating conditions, implement asset filing for financial formats, build a cockpit, determine various data files, and manual information; During this period, data information coordination and supplementation were combined with: specific data analysis, and the subsequent implementation of information acquisition methods to make up for specific loopholes.

7. A trust market risk monitoring and early warning method according to claim 6, characterized in that: Step six is ​​specifically: based on the improvement of specific early warning methods, based on the data analysis in the specific early warning detection plan, as well as the information filing channel after the later data is written and the early warning disclosure based on data analysis; Improve the punishment measures after early warning, based on the behavior of financial crimes, to achieve information communication and networking in the cockpit, and to ensure asset implementation and business implementation mechanisms for financial fraud and trust behavior; Coordinate the summarization and sorting of various types of data, integrate the detection of information risks, obtain information and expand the specific information monitoring, and coordinate the conversion of information mismatch problems; Step 2: Determine the data update of the guidance data and the specific data connected to the cockpit; The storage method is determined as follows: after the summarized and sorted information is determined, it is stored in a server with networking function, and a redundant backup plan is activated to ensure the security of the data.

8. A system for monitoring and early warning of trust market risks, comprising a method for monitoring and early warning of trust market risks according to any one of claims 1 to 7, characterized in that: It includes a cockpit construction module (1), a data storage module (2) and an alarm module (3) for coordinating early warning; The invention is characterized in that: the cockpit construction module (1) comprises a display module (11) for implementing data display, an output module (12) for calling out and printing data, and a data transmission module (13) for constructing a corresponding data image; The display module (11) and the data transmission module (13) are bidirectionally arranged, and the output module (12) and the data transmission module (13) are bidirectionally arranged.

9. A trust market risk monitoring and early warning system according to claim 8, characterized in that: The data storage module (2) is respectively composed of: a storage server module (21), a redundant storage hard disk module (22), a bandwidth network module (23) and an analysis module (24) for data interaction; The storage server module (21) and the data storage module (2) are bidirectionally arranged, the redundant storage hard disk module (22) and the bandwidth network module (22) are unidirectionally arranged, and the analysis module (24) and the external redundant storage hard disk module (22) are unidirectionally controlled.

10. A trust market risk monitoring and early warning system according to claim 8, characterized in that: S2 specifically includes: the alarm module (3) is respectively composed of: a preset trigger module (31), a decision module (32), an option module (33) for a built-in program, and a problem troubleshooting module (34); The preset trigger module (31) is bidirectionally arranged with the alarm module (3), the decision module (32) is bidirectionally arranged with the preset trigger module (31), the option module (33) is bidirectionally arranged with the decision module (32), and the problem troubleshooting module (34) is bidirectionally arranged with the option module (33).

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