A data management system and method for supply chain finance platform

Abstract

The present invention discloses a data management system and method for a supply chain finance platform, and specifically relates to the technical field of supply chain finance services. The present invention copies the historical operation records of the logged-in user as a verification question data set, generates a verification question containing multiple real and false historical operation behaviors when performing identity authentication, and successfully authenticates the identity if all real historical operation behaviors are correctly and completely selected, which can effectively reduce the number of people who are not logged into the platform and effectively improve the security of platform data. It retrieves the supply chain transaction data and financial transaction data of enterprises in the platform, analyzes the supply chain transaction risks and financial transaction risks of different types of enterprises, and then determines whether it is necessary to adjust the enterprise operation authority, which can effectively reduce the enterprise transaction risks and promote the overall improvement of the transaction quality of platform enterprises. It provides a platform enterprise supply chain transaction risk assessment method and a platform enterprise financial transaction risk assessment method, which can improve the accuracy of risk assessment.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain financial services, and more specifically, to a data management system and method for a supply chain financial platform. Background Art

[0002] A supply chain finance platform refers to a platform that provides comprehensive financial services such as financing, settlement, and risk management to all participants in the supply chain through financial technology, based on real transactions between upstream and downstream companies in the supply chain. These platforms are usually jointly built by core enterprises, financial institutions, technology companies, and other parties. They aim to optimize supply chain resource allocation, improve capital operation efficiency, reduce financing costs, and enhance the overall competitiveness and risk resistance of the supply chain.

[0003] The data management system of the existing supply chain finance platform detects whether there are anomalies in user behavior data when providing services. If there are anomalies, it enters defense mode, encrypts the data using the AES encryption algorithm, regularly backs up network defense data, freezes the corresponding data after defense failure and restores the damaged data, and then calculates the data security protection quality index based on the abnormal data and protection data, and compares the calculated network security protection quality index with the preset value. If the calculation result is greater than or equal to the preset value, the network security protection effect meets the standard. Otherwise, the protection plan is optimized, which can ensure data security to a certain extent.

[0004] However, the existing data management system of the supply chain finance platform still has some shortcomings: the existing system does not provide a security protection plan for users to log in to the platform, and cannot ensure that all users who log in to the supply chain finance platform are themselves, which may lead to the leakage of personal privacy. The existing system only protects against security issues after the data is attacked externally, and ignores the transaction risks of enterprises in the supply chain finance platform, which is not conducive to ensuring the transaction quality of enterprises in the platform, promoting transactions among enterprises in the platform, and the development of the platform. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a data management system and method for a supply chain finance platform to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a data management system for a supply chain finance platform, comprising:

[0007] Enterprise data classification storage module: the enterprise data generated by the business transactions of the supply chain finance platform is divided by enterprise and classified into enterprise business data, enterprise financial data, human resources data and market data according to the data usage for storage;

[0008] Multi-end login management module: The login end is divided into the enterprise user end and the platform end. When the enterprise user end and the platform end log in to the supply chain finance platform, the login data set is collected for identity authentication. If the authentication is passed, the user is allowed to log in to the supply chain finance platform. If the authentication is not passed, the user is not allowed to log in to the supply chain finance platform.

[0009] Supply chain transaction risk analysis module: retrieves the supply chain transaction data of enterprises on the platform, analyzes the supply chain transaction risks of different types of enterprises, and transmits the analysis results to the intelligent supervision module;

[0010] Financial transaction risk analysis module: retrieves multi-category data of enterprises on the platform, analyzes the financial transaction risks of enterprises, and transmits the analysis results to the intelligent supervision module;

[0011] Intelligent supervision module: Based on the results of the enterprise supply chain transaction risk analysis or financial transaction risk analysis, it determines whether the enterprise's operating permissions need to be adjusted, generates a list of recommended enterprises when the enterprise makes a transaction selection on the platform, monitors the entire transaction process of the platform enterprise, and sends transaction abnormality warning prompts to the enterprises involved in the transaction when the transaction progress is abnormal;

[0012] Data security protection module: Use AES encryption algorithm to encrypt platform data, defend against abnormal platform login or network attack, freeze corresponding data and restore damaged data after defense fails, and automatically back up security protection records;

[0013] Data security assessment module: Calculate the data security protection quality index based on the backed-up security protection records, compare the calculated data security protection quality index with the preset value, if the calculation result is greater than or equal to the preset value, the data security protection effect meets the standard, otherwise it does not meet the standard, and transmit the evaluation result to the management center;

[0014] Database: used to store data information of all modules in the system.

[0015] Preferably, the specific steps of the multi-terminal user login platform in the multi-terminal login management module are as follows:

[0016] A1. Enterprise users enter their account number, password, enterprise name, and login user identity and then jump to identity verification. Platform supervisors enter their account number, password, and login user identity and then jump to identity verification.

[0017] A2. Copy the historical operation records of the logged-in user as a verification question data set, and generate a verification question containing multiple real and false historical operation behaviors when the logged-in user performs identity authentication. If the logged-in user correctly and completely selects all real historical operation behaviors, the identity authentication is successful. If the logged-in user selects false historical operation behaviors or fails to completely select all real operation behaviors, the identity authentication fails.

[0018] A3. After successful identity authentication, a set of dynamic passwords valid within a preset time will be sent to the mobile phone number bound to the login account. The logged-in user enters the correct dynamic password within the validity period of the dynamic password to log in to the supply chain finance platform;

[0019] A4. If identity authentication fails or the dynamic password becomes invalid, the login interface will be refreshed and a pop-up window will be sent to prompt the login failure. If the pop-up window prompts for login failure appear three times in a row, the account will be automatically locked and an account lock prompt will be sent to the mobile phone number bound to the login account;

[0020] A5. The logged-in user fills in the personal information that is consistent with that when registering the login account and submits the appeal. After the appeal is successful, the user needs to reset a new password that is not exactly the same as the original login password. After the setting is completed, the user will jump directly to the login interface. The logged-in user needs to complete the appeal within the preset time and log in with the new password for the first time. If the logged-in user fails to complete the appeal within the preset time and logs in with the new password for the first time, the account unlocking will be marked as failed and the user needs to appeal again.

[0021] Preferably, the supply chain transaction risk analysis module includes an enterprise supply chain transaction data retrieval unit, an enterprise supply chain transaction risk index calculation unit and a data transmission unit. After obtaining authorization, the enterprise supply chain transaction data retrieval unit retrieves the number of delivery business orders myci, the number of overdue delivery business orders mqci, the average overdue production coefficient Xsri and the average finished product rate coefficient Xpri of the i-th supplier enterprise, and retrieves the number of transportation business orders mysj, the number of overdue transportation business orders mqsj, the average overdue transportation coefficient Xyrj, the number of business orders with transportation damage mhsj and the average damage rate coefficient Xpri of the j-th logistics and transportation enterprise. hrj, retrieve the number of purchase business orders mygk, the number of purchase business orders with overdue payment mqgk, the average overdue payment coefficient Xcrk, the number of purchase business orders with shortfall mqlk and the average shortfall coefficient Xqrk of the k-th purchaser enterprise; the enterprise supply chain transaction risk index calculation unit calculates the supply chain transaction risk index Fci of the i-th supplier enterprise, the supply chain transaction risk index Fsj of the j-th logistics and transportation enterprise and the supply chain transaction risk index Fgk of the k-th purchaser enterprise based on the retrieved supply chain transaction data of the supplier enterprise, the logistics and transportation enterprise and the purchaser enterprise. The specific calculation formula is as follows: , , The data transmission unit transmits the calculated supply chain transaction risk index of each supplier enterprise, logistics and transportation enterprise and purchasing enterprise to the intelligent supervision module.

[0022] Preferably, the financial transaction risk analysis module includes an enterprise multi-category data retrieval unit, an enterprise financial transaction risk index calculation unit and a data transmission unit. The enterprise multi-category data retrieval unit retrieves the number of contracts signed by the enterprise mdi, the number of defaults of the enterprise mwi, the number of standard executions of the contract mzbi, the number of illegal executions of the contract mzwi, the historical volatility αvi of the enterprise's financial asset price, the Sharpe ratio αsi, the maximum drawdown MD, the enterprise current ratio αli, the liquidity coverage ratio LCR, the number of operational risk events of the enterprise mfci, the amount of operational risk loss wfi, the number of penalties for violations of the enterprise mcgi, the amount of penalties for violations wci, the registered capital of the enterprise wzi and the registration time of the enterprise Tzi in the platform after obtaining authorization; the enterprise financial transaction risk index calculation unit calculates the financial transaction risk index Fri of the i-th enterprise in the platform based on the retrieved enterprise multi-category data, and the specific formula is:

[0023] ; The data transmission unit transmits the calculated financial transaction risk index of each enterprise to the intelligent supervision module.

[0024] Preferably, the intelligent supervision module includes a risk analysis result receiving unit, a risk assessment unit, an intelligent decision-making unit, an intelligent recommendation unit, a transaction monitoring unit and a transaction abnormality warning unit. The risk analysis result receiving unit is used to receive the supply chain transaction risk index of each enterprise in the supply chain financial platform analyzed by the supply chain transaction risk analysis module and the financial transaction risk index of each enterprise in the supply chain financial platform analyzed by the financial transaction risk analysis module; the risk assessment unit compares the supply chain transaction risk index and the financial transaction risk index of each enterprise with their respective preset thresholds, and if the analysis result is greater than or equal to the preset value, it is determined that the corresponding supply chain transaction risk of the enterprise exceeds the standard or the financial risk exceeds the standard. The intelligent decision-making unit will close the enterprise's supply chain transaction rights on the platform when it determines that the enterprise's supply chain transaction risk exceeds the standard, and will close the enterprise's financial transaction rights on the platform when it determines that the enterprise's financial transaction risk exceeds the standard; the intelligent recommendation unit will arrange the enterprises whose supply chain transaction risk or financial transaction risk does not exceed the standard from low to high according to the values ​​of the corresponding indicators and update them in real time, and then generate a list of recommended enterprises in the transaction selection interface that is consistent with the arrangement order; the transaction monitoring unit monitors the supply chain transactions or financial transactions of enterprises on the platform throughout the entire process and updates the transaction progress in real time; the transaction abnormality warning unit will send transaction abnormality warning prompts to the enterprises involved in the transaction when the transaction progress is abnormal.

[0025] Preferably, when the intelligent decision-making unit closes the enterprise's supply chain transaction authority on the platform for the first time, it triggers the first supply chain transaction authority closing time; when the intelligent decision-making unit closes the enterprise's supply chain transaction authority on the platform for the second time, it triggers the second supply chain transaction authority closing time, ..., when the enterprise's supply chain transaction authority on the platform is closed for the nth time, the supply chain transaction nth authority closing time is triggered, and the first supply chain transaction authority closing time is < the second supply chain transaction authority closing time < ... < the nth supply chain transaction authority closing time. After the supply chain transaction authority closing time triggered by the enterprise expires, the enterprise's supply chain transaction authority will be returned; when the intelligent decision-making unit closes the enterprise's financial transaction authority on the platform for the first time, it triggers the first financial transaction authority closing time. When the intelligent decision-making unit closes the enterprise's financial transaction authority on the platform for the second time, it triggers the second financial transaction authority closing time, ..., when the enterprise's financial transaction authority on the platform is closed for the nth time, the financial transaction nth authority closing time is triggered, and the first financial transaction authority closing time is < the second financial transaction authority closing time < ... < the nth financial transaction authority closing time. After the financial transaction authority closing time triggered by the enterprise expires, the enterprise's financial transaction authority will be returned.

[0026] Preferably, the data security assessment module includes a security protection record retrieval unit, a data security protection quality index calculation unit, a data security evaluation unit and an evaluation result output unit. The security protection record retrieval unit is used to retrieve the number of abnormal logins Nyd and the number of abnormal login marks Nyb within a preset period, the number of successful network attack defenses Nfc and the number of failed defenses Nfs, the number of data information contained in the data before the i-th data transmission Nsxi and the number of data information lost after the transmission Nsdi, the time required for the i-th data recovery Thi, and the data recovery amount hsi; the data security protection quality index calculation unit calculates the data security protection quality index YC based on the retrieved security protection record data. The specific formula is: , where nsc is the number of data transmissions within a preset fixed period, and nsh is the number of data recovery times within a preset fixed period; the data security evaluation unit compares the calculated data security protection quality index with the preset value, and if the calculated result is greater than or equal to the preset value, the data security protection effect meets the standard, and if the calculated result is less than the preset value, the data security protection effect does not meet the standard; the evaluation result output unit transmits the evaluation result to the management center.

[0027] To achieve the above object, the present invention provides the following technical solution: a data management method for a supply chain financial platform, comprising the following steps:

[0028] S1: The enterprise data generated by the business transactions of the supply chain finance platform is divided into enterprise data, enterprise financial data, human resources data and market data according to the data usage and stored;

[0029] S2: The login end is divided into the enterprise user end and the platform end. When the enterprise user end and the platform end log in to the supply chain finance platform, the login data set is collected for identity authentication. If the authentication passes, the user is allowed to log in to the supply chain finance platform. If the authentication fails, the user is not allowed to log in to the supply chain finance platform.

[0030] S3: Retrieving the supply chain transaction data of enterprises on the platform and analyzing the supply chain transaction risks of different types of enterprises;

[0031] S4: Analyze the financial transaction risks of enterprises after retrieving multi-category data of enterprises on the platform;

[0032] S5: Determine whether the enterprise's operating authority needs to be adjusted based on the enterprise's supply chain transaction risk analysis results or financial transaction risk analysis results, generate a list of recommended enterprises when the enterprise makes a transaction selection on the platform, monitor the entire transaction process of the platform enterprise, and send transaction abnormality warning prompts to the enterprises involved in the transaction when the transaction progress is abnormal;

[0033] S6: Use the AES encryption algorithm to encrypt platform data, defend against platform login anomalies or network attacks, freeze corresponding data and restore damaged data after defense fails, and automatically back up security protection records;

[0034] S7: Calculate the data security protection quality index based on the backed-up security protection records, and compare the calculated data security protection quality index with the preset value. If the calculation result is greater than or equal to the preset value, the data security protection effect meets the standard, otherwise it does not meet the standard. The evaluation result is transmitted to the management center.

[0035] Technical effects and advantages of the present invention:

[0036] 1. The present invention sets up a multi-terminal login management module to provide a login user identity authentication method: copy the login user's historical operation record as a verification question data set, generate a verification question containing multiple real and false historical operation behaviors when the login user performs identity authentication, the login user correctly and completely selects all real historical operation behaviors, the identity authentication is successful, the login user selects false historical operation behaviors or does not completely select all real operation behaviors, the identity authentication fails, after the identity authentication is successful, a group of dynamic passwords valid within a preset time are sent to the mobile phone number bound to the login account, and the login user enters the correct dynamic password within the validity period of the dynamic password to log in to the supply chain financial platform; if the identity authentication fails or the dynamic password expires, the login interface will be refreshed and the A pop-up window will be sent to remind you that the login failed. If the pop-up window prompts that the login failed three times in a row, the account will be automatically locked and an account lock prompt will be sent to the mobile phone number bound to the login account. After the account is locked, the logged-in user needs to fill in the personal information that is consistent with the login account registration and submit an appeal. After a successful appeal, you need to reset a new password that is not exactly the same as the original login password. After the setting is completed, you will jump directly to the login interface. The logged-in user must complete the appeal within the preset time and then log in with the new password for the first time. If the logged-in user fails to complete the appeal within the preset time and then logs in with the new password for the first time, the account unlocking failure will be marked and the user needs to appeal again. This can effectively reduce the possibility of someone else logging into the platform, can effectively reduce the possibility of data leakage of platform enterprises, and can effectively improve the security of platform data.

[0037] 2. Set up a supply chain transaction risk analysis module and a financial transaction risk analysis module to retrieve the supply chain transaction data of enterprises in the platform and then analyze the supply chain transaction risks and financial transaction risks of different types of enterprises. Set up an intelligent supervision module to determine whether it is necessary to adjust the enterprise's operating permissions based on the enterprise's supply chain transaction risk analysis results or financial transaction risk analysis results. Generate a list of recommended enterprises when enterprises in the platform make transaction selections, monitor the entire transaction process of platform enterprises, and send transaction abnormality warning prompts to enterprises involved in the transaction when the transaction progress is abnormal. This can effectively reduce enterprise transaction risks, improve enterprise transaction quality, and promote the overall improvement of platform enterprise transaction quality. It provides a platform enterprise supply chain transaction risk assessment method and a platform enterprise financial transaction risk assessment method, which can effectively improve the assessment accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a system structure block diagram of the present invention.

[0039] Figure 2 It is a diagram of the method steps of the present invention. DETAILED DESCRIPTION

[0040] 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.

[0041] like Figure 1 The present embodiment shown provides a data management system for a supply chain financial platform, including an enterprise data classification storage module, a multi-terminal login management module, a supply chain transaction risk analysis module, a financial transaction risk analysis module, an intelligent supervision module, a data security protection module, a data security assessment module and a database. The enterprise data classification storage module is connected to the multi-terminal login management module, the supply chain transaction risk analysis module and the financial transaction risk analysis module. The supply chain transaction risk analysis module and the financial transaction risk analysis module are connected to the intelligent supervision module. The multi-terminal login management module, the data security protection module and the data security assessment module are connected in sequence. All modules in the system are connected to the database.

[0042] The enterprise data classification storage module divides the enterprise data generated by business transactions of the supply chain finance platform by enterprise and classifies them into enterprise business data, enterprise financial data, human resources data and market data according to data usage for storage.

[0043] What needs to be specifically explained in this embodiment is that dividing the enterprise data generated by the business transactions of the supply chain finance platform by enterprise means that the data of each enterprise in the platform is stored in its own enterprise data folder and the folder is named with the enterprise name plus the unified social credit code. At the same time, the enterprise data stored in the enterprise data folder is subdivided into four folders according to the data usage, namely enterprise business data, enterprise financial data, human resources data and market data, and classified and stored. The various types of data in the enterprise business data folder, enterprise financial data folder, human resources data folder and market data folder will be refined in the form of folders named after specific years.

[0044] The multi-terminal login management module divides the login end into the enterprise user end and the platform end, and collects the login data set for identity authentication when the enterprise user end and the platform end log in to the supply chain finance platform. If the verification passes, the login to the supply chain finance platform is allowed, and if the verification fails, the login to the supply chain finance platform is not allowed.

[0045] Furthermore, the specific steps of the multi-terminal user login platform in the multi-terminal login management module are as follows:

[0046] A1. Enterprise users enter their account number, password, enterprise name, and login user identity and then jump to identity verification. Platform supervisors enter their account number, password, and login user identity and then jump to identity verification.

[0047] A2. Copy the historical operation records of the logged-in user as a verification question data set, and generate a verification question containing multiple real and false historical operation behaviors when the logged-in user performs identity authentication. If the logged-in user correctly and completely selects all real historical operation behaviors, the identity authentication is successful. If the logged-in user selects false historical operation behaviors or fails to completely select all real operation behaviors, the identity authentication fails.

[0048] A3. After successful identity authentication, a set of dynamic passwords valid within a preset time will be sent to the mobile phone number bound to the login account. The logged-in user enters the correct dynamic password within the validity period of the dynamic password to log in to the supply chain finance platform;

[0049] A4. If identity authentication fails or the dynamic password becomes invalid, the login interface will be refreshed and a pop-up window will be sent to prompt the login failure. If the pop-up window prompts for login failure appear three times in a row, the account will be automatically locked and an account lock prompt will be sent to the mobile phone number bound to the login account;

[0050] A5. The logged-in user fills in the personal information that is consistent with that when registering the login account and submits the appeal. After the appeal is successful, the user needs to reset a new password that is not exactly the same as the original login password. After the setting is completed, the user will jump directly to the login interface. The logged-in user needs to complete the appeal within the preset time and log in with the new password for the first time. If the logged-in user fails to complete the appeal within the preset time and logs in with the new password for the first time, the account unlocking will be marked as failed and the user needs to appeal again.

[0051] In this embodiment, it should be specifically explained that the login user identity includes two types: enterprise users and platform supervisors. When the platform user registers an account, he will be given a user identity tag, and the platform user should select the user identity based on the real identity information; in the verification question generated when the login user authenticates his identity, the real historical operation behavior can be directly copied and extracted from the verification question data set, and the false historical operation behavior is generated by imitating the real historical operation behavior. For example, the real historical operation behavior is the issuance of a purchase payment of 500,000 for raw materials for steel structure manufacturing in the last month, and the false historical operation behavior can be the issuance of a purchase payment of 200,000 for raw materials for steel structure manufacturing in the last month or the issuance of a purchase payment of 500,000 for raw materials for wood product processing in the last month; when the login user logs in for the first time with a new password after an appeal, if the login user is an enterprise user, he only needs to enter the enterprise user's account, password, company name and login user identity to log in directly to the supply chain financial platform. If the platform supervisor only needs to enter the account, password and login user identity to log in directly to the supply chain financial platform, the login user does not need to perform identity authentication only when logging in for the first time with a new password after the appeal, and the login user needs to perform identity authentication in all other cases.

[0052] The supply chain transaction risk analysis module retrieves the supply chain transaction data of enterprises in the platform and analyzes the supply chain transaction risks of different types of enterprises, and transmits the analysis results to the intelligent supervision module.

[0053] Furthermore, the supply chain transaction risk analysis module includes an enterprise supply chain transaction data retrieval unit, an enterprise supply chain transaction risk index calculation unit and a data transmission unit. After obtaining authorization, the enterprise supply chain transaction data retrieval unit retrieves the number of delivery business orders myci, the number of overdue delivery business orders mqci, the average overdue production coefficient Xsri and the average yield coefficient Xpri of the i-th supplier enterprise, and retrieves the number of transportation business orders mysj, the number of overdue transportation business orders mqsj, the average overdue transportation coefficient Xyrj, the number of business orders with transportation damage mhsj and the average damage rate coefficient Xpri of the j-th logistics and transportation enterprise. Xhrj, retrieve the number of purchase business orders mygk, the number of purchase business orders with overdue payment mqgk, the average overdue payment coefficient Xcrk, the number of purchase business orders with shortfall mqlk and the average shortfall coefficient Xqrk of the k-th purchaser enterprise; the enterprise supply chain transaction risk index calculation unit calculates the supply chain transaction risk index Fci of the i-th supplier enterprise, the supply chain transaction risk index Fsj of the j-th logistics and transportation enterprise and the supply chain transaction risk index Fgk of the k-th purchaser enterprise based on the retrieved supply chain transaction data of the supplier enterprise, the logistics and transportation enterprise and the purchaser enterprise. The specific calculation formula is as follows: , , The data transmission unit transmits the calculated supply chain transaction risk index of each supplier enterprise, logistics and transportation enterprise and purchasing enterprise to the intelligent supervision module.

[0054] What needs to be specifically explained in this embodiment is that the average overdue production coefficient of a supplier enterprise is the average value of the ratio of the overdue production time to the agreed production time of each overdue delivery business order. For example, the number of overdue delivery business orders of a supplier enterprise is 3, and the overdue delivery business orders are represented by J1, J2 and J3 respectively. The agreed production time of J1 is 20 days, and the overdue production time is 4 days. The agreed production time of J2 is 25 days, and the overdue production time is 5 days. The agreed production time of J3 is 45 days, and the overdue production time is 9 days. Then, the average overdue coefficient Xsr of the supplier enterprise is (4 / 20+5 / 25+9 / 45) / 3=0.2. The yield rate is an existing public indicator, and its algorithm is fixed and will not be specifically explained or calculated here. The average yield rate coefficient is the average value of the yield rate of each delivery business order of the supplier enterprise, which is also an existing technology and will not be specifically calculated here.

[0055] In this embodiment, it should be specifically explained that the average overdue transportation coefficient of a logistics and transportation enterprise is the average value of the ratio of the overdue transportation time to the agreed transportation time of each overdue transportation business order. For example, the number of overdue transportation business orders of a logistics and transportation enterprise is 5, and the overdue transportation business orders are represented by J4, J5, J6 and J7 respectively. The agreed transportation time of J4 is 72h, the overdue transportation time is 9h, the agreed transportation time of J5 is 16h, the overdue transportation time is 2h, the agreed transportation time of J6 is 40h, and the overdue transportation time is 2h. The transportation time is 5h, the J7 agreed transportation time is 10h, and the overdue transportation time is 1h. The average overdue transportation coefficient Xyr of the logistics and transportation enterprise is (9 / 72+2 / 16+5 / 40+1 / 10) / 4=0.11875. The damage rate coefficient is the ratio of the number of damaged goods to the transported goods. It is a prior art and will not be calculated specifically here. The average damage rate coefficient of a logistics and transportation enterprise is the average value of the damage rate coefficients of each business order with transportation damage. It is also a prior art and will not be calculated specifically here.

[0056] What needs to be specifically explained in this embodiment is that the average overdue collection coefficient of a purchasing enterprise is the average value of the ratio of the overdue payment time to the agreed payment time for each overdue payment purchasing business order. For example, the number of overdue payment purchasing business orders of a purchasing enterprise is 3, and the overdue payment purchasing business orders are represented by J8, J9 and J10 respectively. The agreed payment time of J8 is 2h, and the overdue payment time is 0.5h. The agreed payment time of J9 is 6h, and the overdue payment time is 0.6h. The agreed payment time of J10 is 10h, and the overdue payment time is 1h. Then, the average overdue collection coefficient Xcr of the purchasing enterprise is (0.5 / 2+0.6 / 6+1 / 10) / 3=0.15, and the average shortage coefficient is the average value calculated by summing up the ratio of the shortage amount to the agreed collection amount for each purchasing business order with shortage, which is similar to the calculation principle of the average overdue collection coefficient, and the specific calculation instructions are not given here.

[0057] The financial transaction risk analysis module retrieves multiple categories of enterprise data on the platform and analyzes the enterprise's financial transaction risks, and transmits the analysis results to the intelligent supervision module.

[0058] Further, the financial transaction risk analysis module includes an enterprise multi-category data retrieval unit, an enterprise financial transaction risk index calculation unit and a data transmission unit. After obtaining authorization, the enterprise multi-category data retrieval unit retrieves the number of contracts signed by the enterprise mdi, the number of defaults of the enterprise mwi, the number of standard executions of the contract mzbi, the number of illegal executions of the contract mzwi, the historical volatility αvi of the enterprise's financial asset price, the Sharpe ratio αsi, the maximum drawdown MD, the enterprise current ratio αli, the liquidity coverage ratio LCR, the number of operational risk events of the enterprise mfci, the amount of operational risk loss wfi, the number of penalties for violations of the enterprise mcgi, the amount of penalties for violations wci, the registered capital of the enterprise wzi and the registration time of the enterprise Tzi; the enterprise financial transaction risk index calculation unit calculates the financial transaction risk index Fri of the i-th enterprise in the platform based on the retrieved enterprise multi-category data, and the specific formula is:

[0059] ; The data transmission unit transmits the calculated financial transaction risk index of each enterprise to the intelligent supervision module.

[0060] What needs to be specifically explained in this embodiment is that the historical volatility of the price of corporate financial assets is an indicator to measure the amplitude of price changes of financial assets, and is used to reflect the risk level of financial assets. High volatility means greater market risk. The calculation process of this indicator is prior art and is not specifically calculated here. The Sharpe ratio measures the excess return obtained for each unit of risk borne by the investment portfolio. The higher the corporate Sharpe ratio, the higher the return obtained under the same risk. The calculation formula of the corporate Sharpe ratio is: (portfolio return rate-risk-free return rate) / standard deviation of the portfolio return rate, where the portfolio return rate can be obtained by calculating the return rate and weight of each asset in the portfolio. The risk-free return rate usually selects the return rate of a fixed-income product as a benchmark. This indicator can be directly obtained through prior art. The maximum drawdown describes the investment. The maximum decline of the portfolio from the highest point to the lowest point of the net value, the maximum drawdown is an important indicator to measure the risk of the investment portfolio. It reflects the maximum loss that investors may face during the holding period. The larger the maximum drawdown, the higher the corresponding risk. The calculation formula is: Maximum drawdown = (peak - trough) / peak × 100%, which can be directly obtained through existing technology. The current ratio of an enterprise reflects the ability of an enterprise to repay current liabilities in the short term. The calculation formula is: Current ratio = Current assets / Current liabilities, which can be directly obtained through existing technology. The liquidity coverage ratio measures whether the enterprise can meet its liquidity needs through the highly liquid assets it holds under short-term stress scenarios. The higher the LCR, the lower the liquidity risk of the enterprise. The calculation formula is Liquidity coverage ratio = Qualified high-quality liquid assets / Net cash outflow in the next 30 days × 100%, which can be directly obtained through existing technology.

[0061] The intelligent supervision module determines whether it is necessary to adjust the enterprise's operating permissions based on the results of the enterprise's supply chain transaction risk analysis or the financial transaction risk analysis, generates a list of recommended enterprises when the enterprise makes a transaction selection on the platform, monitors the entire transaction process of the platform enterprise, and sends transaction abnormality warning prompts to the enterprises involved in the transaction when the transaction progress is abnormal.

[0062] Furthermore, the intelligent supervision module includes a risk analysis result receiving unit, a risk assessment unit, an intelligent decision-making unit, an intelligent recommendation unit, a transaction monitoring unit and a transaction abnormality warning unit. The risk analysis result receiving unit is used to receive the supply chain transaction risk index of each enterprise in the supply chain financial platform analyzed by the supply chain transaction risk analysis module and the financial transaction risk index of each enterprise in the supply chain financial platform analyzed by the financial transaction risk analysis module; the risk assessment unit compares the supply chain transaction risk index and the financial transaction risk index of each enterprise with their respective preset thresholds, and if the analysis result is greater than or equal to the preset value, it is determined that the corresponding supply chain transaction risk of the enterprise exceeds the standard or Financial transaction risk exceeds the limit; the intelligent decision-making unit will close the enterprise's supply chain transaction rights on the platform when it determines that the enterprise's supply chain transaction risk exceeds the limit, and will close the enterprise's financial transaction rights on the platform when it determines that the enterprise's financial transaction risk exceeds the limit; the intelligent recommendation unit will arrange the enterprises whose supply chain transaction risk or financial transaction risk does not exceed the limit from low to high according to the values ​​of the corresponding indicators and update them in real time, and then generate a list of recommended enterprises in the transaction selection interface that is consistent with the arrangement order; the transaction monitoring unit monitors the supply chain transactions or financial transactions of enterprises on the platform throughout the entire process and updates the transaction progress in real time; the transaction abnormality warning unit will send transaction abnormality warning prompts to the enterprises involved in the transaction when the transaction progress is abnormal.

[0063] What needs to be specifically explained in this embodiment is that the transaction selection interface only displays the enterprise information with the lowest transaction risk index, i.e., the first-ranked enterprise among the five different types of enterprises, namely, supplier enterprises, logistics and transportation enterprises, purchasing enterprises, financing enterprises, and funding enterprises. Clicking on supplier enterprises, logistics and transportation enterprises, purchasing enterprises, financing enterprises, or funding enterprises will bring up a complete list of recommended enterprises.

[0064] Further, when the intelligent decision-making unit closes the enterprise's supply chain transaction authority on the platform for the first time, it triggers the first supply chain transaction authority closing time; when the intelligent decision-making unit closes the enterprise's supply chain transaction authority on the platform for the second time, it triggers the second supply chain transaction authority closing time, ..., when the enterprise's supply chain transaction authority on the platform is closed for the nth time, it triggers the supply chain transaction nth authority closing time, the first supply chain transaction authority closing time < the second supply chain transaction authority closing time < ... < the nth supply chain transaction authority closing time, after the supply chain transaction authority closing time triggered by the enterprise expires, the enterprise's supply chain transaction authority will be returned; when the intelligent decision-making unit closes the enterprise's financial transaction authority on the platform for the first time, it triggers the first financial transaction authority closing time, when the intelligent decision-making unit closes the enterprise's financial transaction authority on the platform for the second time, it triggers the second financial transaction authority closing time, ..., when the enterprise's financial transaction authority on the platform is closed for the nth time, it triggers the nth financial transaction authority closing time, the first financial transaction authority closing time < the second financial transaction authority closing time < ... < the nth financial transaction authority closing time, after the financial transaction authority closing time triggered by the enterprise expires, the enterprise's financial transaction authority will be returned.

[0065] In this embodiment, it should be specifically explained that the first permission closing time of the supply chain transaction, the second permission closing time of the supply chain transaction, ..., and the nth permission closing time of the supply chain transaction can be set based on actual needs. Here is a possible setting method: set the first permission closing time of the supply chain transaction to Ta1, the second permission closing time of the supply chain transaction to Ta2, ..., and the nth permission closing time of the supply chain transaction to Tan, and the first permission closing time of the supply chain transaction, the second permission closing time of the supply chain transaction, ..., and the nth permission closing time of the supply chain transaction satisfy the following relationship: , ,......, The first financial transaction permission closing time, the second financial transaction permission closing time, ..., and the nth financial transaction permission closing time can be set based on actual needs. Here is a possible setting method: set the first financial transaction permission closing time to Tb1, the second financial transaction permission closing time to Tb2, ..., and the nth financial transaction permission closing time to Tbn. The first financial transaction permission closing time, the second financial transaction permission closing time, ..., and the nth financial transaction permission closing time satisfy the following relationship: , ,......, .

[0066] The data security protection module uses the AES encryption algorithm to encrypt platform data, and provides defense when platform login is abnormal or network attacks occur. If the defense fails, it freezes the corresponding data and restores the damaged data, and automatically backs up the security protection records.

[0067] The data security assessment module calculates the data security protection quality index based on the backed-up security protection records, and compares the calculated data security protection quality index with a preset value. If the calculation result is greater than or equal to the preset value, the data security protection effect meets the standard; otherwise, it does not meet the standard. The evaluation result is transmitted to the management center.

[0068] Further, the data security assessment module includes a security protection record retrieval unit, a data security protection quality index calculation unit, a data security evaluation unit and an evaluation result output unit. The security protection record retrieval unit is used to retrieve the number of abnormal logins Nyd and the number of abnormal login marks Nyb within a preset period, the number of successful network attack defenses Nfc and the number of failed defenses Nfs, the number of data information contained in the data before the i-th data transmission Nsxi and the number of data information lost after the transmission Nsdi, the time required for the i-th data recovery Thi, and the data recovery amount hsi; the data security protection quality index calculation unit calculates the data security protection quality index YC based on the retrieved security protection record data. The specific formula is: , where nsc is the number of data transmissions within a preset fixed period, and nsh is the number of data recovery times within a preset fixed period; the data security evaluation unit compares the calculated data security protection quality index with the preset value, and if the calculated result is greater than or equal to the preset value, the data security protection effect meets the standard, and if the calculated result is less than the preset value, the data security protection effect does not meet the standard; the evaluation result output unit transmits the evaluation result to the management center.

[0069] The database is used to store data information of all modules in the system.

[0070] It should be specifically noted in this embodiment that the preset values ​​used are selected based on actual needs and are not limited to specific values ​​here.

[0071] like Figure 2 This embodiment provides a data management method for a supply chain finance platform, including the following steps:

[0072] S1: The enterprise data generated by the business transactions of the supply chain finance platform is divided into enterprise data, enterprise financial data, human resources data and market data according to the data usage and stored;

[0073] S2: The login end is divided into the enterprise user end and the platform end. When the enterprise user end and the platform end log in to the supply chain finance platform, the login data set is collected for identity authentication. If the authentication passes, the user is allowed to log in to the supply chain finance platform. If the authentication fails, the user is not allowed to log in to the supply chain finance platform.

[0074] S3: Retrieving the supply chain transaction data of enterprises on the platform and analyzing the supply chain transaction risks of different types of enterprises;

[0075] S4: Analyze the financial transaction risks of enterprises after retrieving multi-category data of enterprises on the platform;

[0076] S5: Determine whether the enterprise's operating authority needs to be adjusted based on the enterprise's supply chain transaction risk analysis results or financial transaction risk analysis results, generate a list of recommended enterprises when the enterprise makes a transaction selection on the platform, monitor the entire transaction process of the platform enterprise, and send transaction abnormality warning prompts to the enterprises involved in the transaction when the transaction progress is abnormal;

[0077] S6: Use the AES encryption algorithm to encrypt platform data, defend against platform login anomalies or network attacks, freeze corresponding data and restore damaged data after defense fails, and automatically back up security protection records;

[0078] S7: Calculate the data security protection quality index based on the backed-up security protection records, and compare the calculated data security protection quality index with the preset value. If the calculation result is greater than or equal to the preset value, the data security protection effect meets the standard, otherwise it does not meet the standard. The evaluation result is transmitted to the management center.

[0079] Finally: 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, 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 data management system for a supply chain finance platform, characterized by: include: Enterprise data classification storage module: the enterprise data generated by the business transactions of the supply chain finance platform is divided by enterprise and classified into enterprise business data, enterprise financial data, human resources data and market data according to the data usage for storage; Multi-end login management module: The login end is divided into the enterprise user end and the platform end. When the enterprise user end and the platform end log in to the supply chain finance platform, the login data set is collected for identity authentication. If the authentication is passed, the user is allowed to log in to the supply chain finance platform. If the authentication is not passed, the user is not allowed to log in to the supply chain finance platform. Supply chain transaction risk analysis module: retrieves the supply chain transaction data of enterprises on the platform, analyzes the supply chain transaction risks of different types of enterprises, and transmits the analysis results to the intelligent supervision module; The supply chain transaction risk analysis module includes an enterprise supply chain transaction data retrieval unit, an enterprise supply chain transaction risk index calculation unit and a data transmission unit. After obtaining authorization, the enterprise supply chain transaction data retrieval unit retrieves the number of delivery business orders myci, the number of overdue delivery business orders mqci, the average overdue production coefficient Xsri and the average finished product rate coefficient Xpri of the i-th supplier enterprise, and retrieves the number of transportation business orders mysj, the number of overdue transportation business orders mqsj, the average overdue transportation coefficient Xyrj, the number of business orders with transportation damage mhsj and the average damage rate coefficient Xh of the j-th logistics and transportation enterprise. rj, retrieve the number of purchase business orders mygk, the number of purchase business orders with overdue payment mqgk, the average overdue payment coefficient Xcrk, the number of purchase business orders with shortfall mqlk and the average shortfall coefficient Xqrk of the k-th purchaser enterprise; the enterprise supply chain transaction risk index calculation unit calculates the supply chain transaction risk index Fci of the i-th supplier enterprise, the supply chain transaction risk index Fsj of the j-th logistics and transportation enterprise and the supply chain transaction risk index Fgk of the k-th purchaser enterprise based on the retrieved supply chain transaction data of the supplier enterprise, the logistics and transportation enterprise and the purchaser enterprise. The specific calculation formula is as follows: , , The data transmission unit transmits the calculated supply chain transaction risk index of each supplier enterprise, logistics and transportation enterprise, and purchasing enterprise to the intelligent supervision module; Financial transaction risk analysis module: retrieves multi-category data of enterprises on the platform, analyzes the financial transaction risks of enterprises, and transmits the analysis results to the intelligent supervision module; The financial transaction risk analysis module includes an enterprise multi-category data retrieval unit, an enterprise financial transaction risk index calculation unit and a data transmission unit. The enterprise multi-category data retrieval unit retrieves the number of contracts signed by the enterprise mdi, the number of defaults mwi, the number of contract standard executions mzbi, the number of contract violation executions mzwi, the historical volatility αvi of the enterprise's financial asset price, the Sharpe ratio αsi, the maximum drawdown MD, the enterprise current ratio αli, the liquidity coverage ratio LCR, the number of enterprise operational risk events mfci, the amount of operational risk loss wfi, the number of enterprise violation penalties mcgi, the amount of violation penalties wci, the enterprise registered capital wzi and the enterprise registration time Tzi in the platform after obtaining authorization; the enterprise financial transaction risk index calculation unit calculates the financial transaction risk index Fri of the i-th enterprise in the platform based on the retrieved enterprise multi-category data, and the specific formula is: ； The data transmission unit transmits the calculated financial transaction risk index of each enterprise to the intelligent supervision module; Intelligent supervision module: Based on the results of the enterprise supply chain transaction risk analysis or financial transaction risk analysis, it determines whether the enterprise's operating permissions need to be adjusted, generates a list of recommended enterprises when the enterprise makes a transaction selection on the platform, monitors the entire transaction process of the platform enterprise, and sends transaction abnormality warning prompts to the enterprises involved in the transaction when the transaction progress is abnormal; Data security protection module: Use AES encryption algorithm to encrypt platform data, defend against abnormal platform login or network attack, freeze corresponding data and restore damaged data after defense fails, and automatically back up security protection records; Data security assessment module: Calculate the data security protection quality index based on the backed-up security protection records, compare the calculated data security protection quality index with the preset value, if the calculation result is greater than or equal to the preset value, the data security protection effect meets the standard, otherwise it does not meet the standard, and transmit the evaluation result to the management center; The data security assessment module includes a security protection record retrieval unit, a data security protection quality index calculation unit, a data security evaluation unit and an evaluation result output unit. The security protection record retrieval unit is used to retrieve the number of abnormal logins Nyd and the number of abnormal login marks Nyb within a preset period, the number of successful network attack defenses Nfc and the number of failed defenses Nfs, the number of data information contained in the data before the i-th data transmission Nsxi and the number of data information lost after the transmission Nsdi, the time required for the i-th data recovery Thi, and the data recovery amount hsi; the data security protection quality index calculation unit calculates the data security protection quality index YC based on the retrieved security protection record data. The specific formula is: , where nsc is the number of data transmissions within a preset fixed period, and nsh is the number of data recovery times within a preset fixed period; the data security evaluation unit compares the calculated data security protection quality index with a preset value, and if the calculated result is greater than or equal to the preset value, the data security protection effect meets the standard, and if the calculated result is less than the preset value, the data security protection effect does not meet the standard; The evaluation result output unit transmits the evaluation result to the management center.

2. The data management system of a supply chain finance platform according to claim 1, characterized in that: The specific steps of the multi-terminal user login platform in the multi-terminal login management module are as follows: A1. Enterprise users enter their account number, password, enterprise name, and login user identity and then jump to identity verification. Platform supervisors enter their account number, password, and login user identity and then jump to identity verification. A2. Copy the historical operation records of the logged-in user as a verification question data set, and generate a verification question containing multiple real and false historical operation behaviors when the logged-in user performs identity authentication. If the logged-in user correctly and completely selects all real historical operation behaviors, the identity authentication is successful. If the logged-in user selects false historical operation behaviors or fails to completely select all real operation behaviors, the identity authentication fails. A3. After successful identity authentication, a set of dynamic passwords valid within a preset time will be sent to the mobile phone number bound to the login account. The logged-in user enters the correct dynamic password within the validity period of the dynamic password to log in to the supply chain finance platform; A4. If identity authentication fails or the dynamic password becomes invalid, the login interface will be refreshed and a pop-up window will be sent to prompt the login failure. If the pop-up window prompts for login failure appear three times in a row, the account will be automatically locked and an account lock prompt will be sent to the mobile phone number bound to the login account; A5. The logged-in user fills in the personal information that is consistent with that when registering the login account and submits the appeal. After the appeal is successful, the user needs to reset a new password that is not exactly the same as the original login password. After the setting is completed, the user will jump directly to the login interface. The logged-in user needs to complete the appeal within the preset time and log in with the new password for the first time. If the logged-in user fails to complete the appeal within the preset time and logs in with the new password for the first time, the account unlocking will be marked as failed and the user needs to appeal again.

3. The data management system of a supply chain finance platform according to claim 1, characterized in that: The intelligent supervision module includes a risk analysis result receiving unit, a risk assessment unit, an intelligent decision-making unit, an intelligent recommendation unit, a transaction monitoring unit, and a transaction abnormality warning unit. The risk analysis result receiving unit is used to receive the supply chain transaction risk index of each enterprise in the supply chain financial platform analyzed by the supply chain transaction risk analysis module and the financial transaction risk index of each enterprise in the supply chain financial platform analyzed by the financial transaction risk analysis module; The risk assessment unit compares the supply chain transaction risk index and financial transaction risk index of each enterprise with their respective preset thresholds. If the analysis result is greater than or equal to the preset value, it is determined that the corresponding supply chain transaction risk or financial transaction risk of the enterprise exceeds the limit; The intelligent decision-making unit will shut down the enterprise's supply chain transaction rights on the platform when it determines that the enterprise's supply chain transaction risk exceeds the standard, and shut down the enterprise's financial transaction rights on the platform when it determines that the enterprise's financial transaction risk exceeds the standard; The intelligent recommendation unit arranges the enterprises whose supply chain transaction risks or financial transaction risks do not exceed the standards according to the values ​​of the corresponding indicators from low to high and updates them in real time, and then generates a list of recommended enterprises in the transaction selection interface in the same order of arrangement; the transaction monitoring unit monitors the supply chain transactions or financial transactions of enterprises in the platform throughout the entire process and updates the transaction progress in real time; the transaction abnormality warning unit sends transaction abnormality warning prompts to the enterprises involved in the transaction when the transaction progress is abnormal.

4. A data management system for a supply chain finance platform according to claim 3, characterized in that: When the intelligent decision-making unit closes the enterprise's supply chain transaction authority on the platform for the first time, it triggers the first supply chain transaction authority closing time. When the intelligent decision-making unit closes the enterprise's supply chain transaction authority on the platform for the second time, it triggers the second supply chain transaction authority closing time. ..., when the enterprise's supply chain transaction authority on the platform is closed for the nth time, the supply chain transaction nth authority closing time is triggered, and the first supply chain transaction authority closing time < the second supply chain transaction authority closing time < ... < the nth supply chain transaction authority closing time. After the supply chain transaction authority closing time triggered by the enterprise expires, the enterprise's supply chain transaction authority will be returned; when the intelligent decision-making unit closes the enterprise's financial transaction authority on the platform for the first time, it triggers the first financial transaction authority closing time. When the intelligent decision-making unit closes the enterprise's financial transaction authority on the platform for the second time, it triggers the second financial transaction authority closing time. ..., when the enterprise's financial transaction authority on the platform is closed for the nth time, the financial transaction nth authority closing time is triggered. The first financial transaction authority closing time < the second financial transaction authority closing time < ... < the nth financial transaction authority closing time. After the financial transaction authority closing time triggered by the enterprise expires, the enterprise's financial transaction authority will be returned.

5. A data management method for a supply chain finance platform, using a data management system for a supply chain finance platform as claimed in any one of claims 1 to 4, characterized in that: The following steps are involved: S1: The enterprise data generated by the business transactions of the supply chain finance platform is divided into enterprise data, enterprise financial data, human resources data and market data according to the data usage and stored; S2: The login end is divided into the enterprise user end and the platform end. When the enterprise user end and the platform end log in to the supply chain finance platform, the login data set is collected for identity authentication. If the authentication passes, the user is allowed to log in to the supply chain finance platform. If the authentication fails, the user is not allowed to log in to the supply chain finance platform. S3: Retrieving the supply chain transaction data of enterprises on the platform and analyzing the supply chain transaction risks of different types of enterprises; S4: Analyze the financial transaction risks of enterprises after retrieving multi-category data of enterprises on the platform; S5: Determine whether the enterprise's operating authority needs to be adjusted based on the enterprise's supply chain transaction risk analysis results or financial transaction risk analysis results, generate a list of recommended enterprises when the enterprise makes a transaction selection on the platform, monitor the entire transaction process of the platform enterprise, and send transaction abnormality warning prompts to the enterprises involved in the transaction when the transaction progress is abnormal; S6: Use the AES encryption algorithm to encrypt platform data, defend against platform login anomalies or network attacks, freeze corresponding data and restore damaged data after defense fails, and automatically back up security protection records; S7: Calculate the data security protection quality index based on the backed-up security protection records, and compare the calculated data security protection quality index with the preset value. If the calculation result is greater than or equal to the preset value, the data security protection effect meets the standard, otherwise it does not meet the standard. The evaluation result is transmitted to the management center.

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