Risk management system based on financial management

Abstract

The invention discloses a risk management system based on financial management, and relates to the technical field of risk management of financial management. The risk management system based on financial management comprises a transmission path security analysis module; a qualified node transmission delay analysis module; and a qualified node transmission optimization module. According to the method, financial data transmission path security analysis is carried out, whether financial data transmission security isolation is carried out is judged, then financial data qualified node transmission delay analysis is carried out on qualified nodes, whether delay risk classification is carried out is judged, and finally qualified node transmission optimization is carried out on risk classification data. The effect of improving the safety during risk identification based on the cross-regional enterprise financial data is achieved, and the problem of low safety during risk identification based on the cross-regional enterprise financial data in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of financial risk management, and particularly to a risk management system based on financial management. Background Art

[0002] Financial management includes financial objectives and functions, valuation concepts, market risk and rate of return, multi-variable and factor valuation models, option valuation, principles of capital investment, risk and real options in capital budgeting, etc.; risk management is divided into three stages: risk identification, risk measurement, and risk control. Financial data in different regions can use data isolation technology to improve security: storing data in a dedicated server or virtual private cloud to avoid sharing or transmitting data among multiple network nodes; however, data isolation technology may require additional resources, and when multiple tasks or users access the isolated data simultaneously, resource competition may occur, which may lead to a decrease in the speed of data transmission and processing, thereby increasing latency. By optimizing resource utilization to reduce latency, the risk of data exposure may increase during the process of reducing latency, resulting in a decrease in security.

[0003] Existing systems mainly help enterprises prioritize high-risk areas by quantitatively analyzing the probability of occurrence and impact degree of financial risks.

[0004] For example, the method for identifying financial management risks of enterprises based on financial big data disclosed in the invention patent announcement with the publication number of CN113674072B includes: the node that submits a fund change request in the enterprise financial management platform determines the number of convolutions for the fund change request data according to the sorting serial number of its own activity value, and takes the convolution result as a digital digest; determines a common key according to the activity value and sorting serial number of the fund change request node; generates a digital signature according to the common key and the digital digest, and sends the fund change request data and the digital signature to the financial data verification node; makes financial data changes according to the verification result of the financial data verification node on the fund change request data and the digital signature, compares the enterprise financial data with the early warning threshold, and generates financial management risk early warning information.

[0005] For example, the risk identification method and system for enterprise financial information data management based on big data disclosed in the invention patent application with the publication number of CN118396765A include: performing data clustering processing on the enterprise financial operation data set by using the DBSCAN clustering algorithm, establishing a BP enterprise financial data prediction model based on the BP neural network, using the HHO Harris hawk optimization algorithm to improve the parameters in the BP enterprise financial data prediction model, inputting the training enterprise financial operation data set into the BP-HH0 enterprise financial data prediction model for training, and determining whether the enterprise financial risk prediction status is greater than the preset enterprise financial risk threshold. If it is greater than the enterprise financial risk threshold, enterprise financial risk warning information is generated.

[0006] However, in the process of implementing the technical solution of the present invention in the embodiments of the present application, it is found that the above technology has at least the following technical problems: In the prior art, for large enterprises with branches, when the enterprise needs to allocate resources between multiple regions or branches, financial data needs to be transmitted in real time between systems at different locations. By transmitting financial data in real time, the headquarters can better monitor the changing trends of financial data of each branch, allocate resources in the shortest time, and ensure the health of capital flow and the smooth operation of the enterprise. These financial data may be scattered in systems of different networks. When transmitting across multiple network systems, since the transmission path may pass through multiple insecure network nodes, it is vulnerable to theft, tampering, or damage, resulting in the leakage of enterprise financial information and low security when identifying risks based on cross-regional enterprise financial data. Summary of the Invention

[0007] The embodiments of the present application provide a risk management system based on financial management, which solves the problem of low security when identifying risks based on cross-regional enterprise financial data in the prior art and realizes the improvement of security when identifying risks based on cross-regional enterprise financial data.

[0008] The embodiments of the present application provide a risk management system based on financial management, including: a transmission path security analysis module, a qualified node transmission delay analysis module, and a qualified node transmission optimization module. Among them, the transmission path security analysis module is used to analyze the security of the financial data transmission path to obtain the node security evaluation result and determine whether to perform financial data transmission security isolation; the qualified node transmission delay analysis module is used to analyze the transmission delay of qualified nodes for financial data and determine whether to perform delay risk classification; the qualified node transmission optimization module is used to optimize the transmission of qualified nodes for the risk classification data obtained after delay risk classification, and the risk classification data includes low-risk financial data and high-risk financial data.

[0009] Further, the process of obtaining the node security evaluation result by analyzing the security of the financial data transmission path is as follows: Obtain the security data of the financial data transmission path, which is obtained by processing the security parameters of the transmission path and the preset transmission path security parameters obtained from the database; Combine the security data of the financial data transmission path and the preset node and quantization weight group obtained from the database to obtain the node security evaluation result; The node security evaluation result represents the quantitative analysis data of the security impact of the transmission path security parameters acting together on the network node to transmit financial data; The preset node and quantization weight group includes the preset node and financial data volume weight, the preset node traffic and quantity weight, the preset node and noise weight, the preset node and financial data loss weight, and the preset node and financial data retransmission weight; The security data of the financial data transmission path includes the financial data volume and node quantization value, the node traffic and quantity quantization value, the node and noise quantization value, the node and financial data loss quantization value, and the node and financial data retransmission quantization value; The transmission path security parameters include the node traffic change amount, the financial data volume, the node quantity, the channel noise, the financial data loss rate, and the financial data retransmission rate.

[0010] Further, the node security evaluation result is obtained by combining the financial data transmission path security data with the preset nodes and quantization weight groups obtained from the database. The specific process is as follows: The financial data volume and node quantization value are obtained by processing the obtained node and financial data volume processing group. The financial data volume and node quantization value represent the quantization analysis data of the comprehensive influence degree of the node traffic change volume and the financial data volume on the security of the network node transmitting financial data. The node and financial data volume processing group includes the node traffic change volume, the financial data volume, the preset node traffic change volume, the preset financial data volume, and the preset financial data volume weight. The node traffic and quantity quantization value is obtained by processing the obtained node traffic and quantity processing group. The node traffic and quantity quantization value represents the quantization analysis data of the comprehensive influence degree of the node traffic change volume and the node quantity on the security of the network node transmitting financial data. The node traffic and quantity processing group includes the node traffic change volume, the node quantity, the preset node traffic change volume, the preset node quantity, and the preset node quantity weight. The node and noise quantization value is obtained by processing the obtained node and noise processing group. The node and noise quantization value represents the quantization analysis data of the comprehensive influence degree of the node traffic change volume and the channel noise on the security of the network node transmitting financial data. The node and noise processing group includes the node traffic change volume, the channel noise, the preset node traffic change volume, the preset channel noise, and the preset channel noise weight. The node and financial data loss quantization value is obtained by processing the obtained node and financial data loss processing group. The node and financial data loss quantization value represents the quantization analysis data of the comprehensive influence degree of the node traffic change volume and the financial data loss rate on the security of the network node transmitting financial data. The node and financial data loss processing group includes the node traffic change volume, the financial data loss rate, the preset node traffic change volume, the preset financial data loss rate, and the preset financial loss weight. The node and financial data retransmission quantization value is obtained by processing the obtained node and financial data retransmission processing group. The node and financial data retransmission quantization value represents the quantization analysis data of the comprehensive influence degree of the node traffic change volume and the financial data retransmission rate on the security of the network node transmitting financial data. The node and financial data retransmission processing group includes the node traffic change volume, the financial data retransmission rate, the preset node traffic change volume, the preset financial data retransmission rate, and the preset financial retransmission weight. The node security evaluation result is obtained by processing the financial data transmission path security data and the preset nodes and quantization weight groups obtained from the database. The preset nodes and quantization weight groups are used to reflect the influence of the financial data transmission path security data on the node security evaluation result within a preset time period.

[0011] Further, the specific process of determining whether to perform secure isolation of financial data transmission is as follows: Compare the node security assessment result with the preset node security threshold obtained from the database; when the node security assessment result is not lower than the preset node security threshold, do not perform secure isolation of financial data transmission and obtain qualified nodes. Otherwise, perform secure isolation of financial data transmission and obtain qualified nodes and unqualified nodes. The secure isolation of financial data transmission means classifying the network nodes corresponding to financial data through data isolation technology; Compare the number of qualified nodes and unqualified nodes. If the number of qualified nodes is greater than the number of unqualified nodes, perform data format division to obtain homogeneous financial data. Otherwise, send a prompt to the preset personnel to add a preset number of standby network nodes until the number of qualified nodes is greater than the number of unqualified nodes. The homogeneous financial data refers to financial data with the same data format and transmitted using the same preset transmission protocol.

[0012] Further, after determining whether to perform secure isolation of financial data transmission, it also includes monitoring the load of qualified nodes; The specific process of monitoring the load of qualified nodes is as follows: Monitor the load situation of qualified nodes to obtain the qualified node load value, which is represented by the data volume corresponding to the homogeneous financial data processed by the qualified nodes within a unit time; When the qualified node load value is less than the preset average node load threshold, continue to analyze the transmission delay of qualified nodes for financial data. Otherwise, perform load balancing processing.

[0013] Further, the specific process of analyzing the transmission delay of qualified nodes for financial data is as follows: Obtain the qualified node transmission delay data by processing the qualified node transmission delay parameters and the preset qualified node transmission delay parameters obtained from the database; Obtain the qualified node transmission delay assessment result by processing the qualified node transmission delay data and the preset qualified node and transmission delay weight group obtained from the database; The qualified node transmission delay assessment result represents the quantitative data of the influence of the qualified node transmission delay parameters on the delay situation of transmitting homogeneous financial data by qualified nodes; The qualified node transmission delay assessment result is used to evaluate the delay situation of transmitting homogeneous financial data by qualified nodes within the preset qualified time period of the preset nodes; The qualified node transmission delay data includes the qualified response and audit quantization value, the type quantity and qualified response quantization value, the qualified response and read quantization value, and the qualified response and retransmission quantization value; The qualified node transmission delay parameters include the average node response duration, the average number of financial data audits, the number of qualified data types, the average number of financial data reads, and the retransmission rate of qualified node financial data.

[0014] Further, the process of obtaining the qualified node transmission delay evaluation result by processing the qualified node transmission delay data and the preset qualified node and transmission delay weight group obtained from the database is as follows: The qualified response and audit quantization value is obtained by processing the qualified response and audit processing group. The qualified response and audit quantization value is used to reflect the comprehensive influence degree of the average node response duration and the average number of financial data audit times on the delay of transmitting the same type of financial data by the qualified node. The qualified response and audit processing group includes the average node response duration, the average number of financial data audit times, the preset average node response duration, the preset average number of financial data audit times, and the preset financial data audit weight; The type quantity and qualified response quantization value is obtained by processing the type quantity and qualified response processing group. The type quantity and qualified response quantization value is used to reflect the comprehensive influence degree of the average node response duration and the number of qualified data types on the delay of transmitting the same type of financial data by the qualified node. The type quantity and qualified response processing group includes the average node response duration, the number of qualified data types, the preset average node response duration, the preset number of qualified data types, and the preset qualified data type weight; The qualified response and read quantization value is obtained by processing the qualified response and read processing group. The qualified response and read quantization value is used to reflect the comprehensive influence degree of the average node response processing value and the average number of financial data read times on the delay of transmitting the same type of financial data by the qualified node. The qualified response and read processing group includes the average node response duration, the average number of financial data read times, the preset average node response duration, and the preset average number of financial data read times; The qualified response and retransmission quantization value is obtained by processing the qualified response and retransmission processing group. The qualified response and retransmission quantization value is used to reflect the comprehensive influence degree of the average node response duration and the retransmission rate of the qualified node financial data on the delay of transmitting the same type of financial data by the qualified node. The qualified response and retransmission processing group includes the average node response duration, the retransmission rate of the qualified node financial data, the preset average node response duration, and the preset retransmission rate of the qualified node financial data.

[0015] Further, the specific process of determining whether to perform delay risk classification is as follows: Compare the qualified node transmission delay evaluation result with the preset qualified node transmission delay threshold obtained from the database; When the qualified node transmission delay evaluation result is greater than the preset qualified node transmission delay threshold, mark the corresponding same type of financial data as high-risk financial data; When the qualified node transmission delay evaluation result is not greater than the preset qualified node transmission delay threshold, mark the corresponding same type of financial data as low-risk financial data.

[0016] Further, the specific process of optimizing the transmission of qualified nodes is as follows: The low-risk financial data is compressed and then the optimized financial data transmission is performed; the optimized financial data transmission means data transmission through an optimized transmission path; the optimized transmission path means sending a prompt to a preset person to select the transmission path with the least number of network nodes according to the preset number of qualified nodes; when the number of optimized transmission paths is greater than 1, the risk classification data is distributed, and the data distribution means evenly dividing the risk classification data according to the data volume and then dispersing it to the network nodes; the high-risk financial data is compressed and the abnormal monitoring of the requests of qualified nodes is performed.

[0017] Further, the specific process of the abnormal monitoring of the requests of qualified nodes is as follows: Monitoring the request frequency evaluation value of qualified nodes, where the request frequency evaluation value is represented by the number of requests received by qualified nodes per unit time; when the request frequency evaluation value is greater than the preset request frequency of qualified nodes, the corresponding qualified node is re-marked as an unqualified node; re-analyzing the security of the financial data transmission path for high-risk financial data, and when the monitored node security evaluation result is not lower than the preset node security threshold, continue to perform the optimized financial data transmission; when the monitored node security evaluation result is lower than the preset node security threshold, re-perform the security isolation of the financial data transmission.

[0018] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By analyzing the security of the financial data transmission path and determining whether to perform the security isolation of the financial data transmission, then analyzing the transmission delay of the qualified nodes for the financial data of the qualified nodes and determining whether to perform the delay risk classification, and finally optimizing the transmission of the qualified nodes for the risk classification data, the reliability of the optimized transmission of the qualified nodes for the risk classification data is improved, and further the security of risk identification based on cross-regional enterprise financial data is improved, effectively solving the problem of low security in risk identification based on cross-regional enterprise financial data in the prior art.

[0019] 2. By processing the security parameters of the transmission path and the preset transmission path security parameters obtained from the database to obtain the security data of the financial data transmission path, and then combining the security data of the financial data transmission path and the preset node and quantization weight group to obtain the node security evaluation result, the reliability of the analysis of the security of the financial data transmission path is improved, and further the accurate evaluation of the security of the network node transmitting financial data is realized.

[0020] 3. By marking the financial data of the same type corresponding to the qualified node transmission delay evaluation result greater than the preset qualified node transmission delay threshold as high-risk financial data, and marking the financial data of the same type corresponding to the qualified node transmission delay evaluation result not greater than the preset qualified node transmission delay threshold as low-risk financial data, the accurate refinement of delay risk classification is realized, and further the improvement of the accuracy of delay risk classification is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 FIG. is a schematic structural diagram of a risk management system based on financial management provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] In the embodiment of the present application, by providing a risk management system based on financial management, the problem of low security in risk identification based on financial data of cross-regional enterprises in the prior art is solved. By analyzing the security of the financial data transmission path to obtain the node security evaluation result and determining whether to perform financial data transmission security isolation, then analyzing the qualified node transmission delay of the financial data for the qualified nodes and determining whether to perform delay risk classification. If risk classification is performed, the financial data of the same type corresponding to the qualified node transmission delay evaluation result greater than the preset qualified node transmission delay threshold is marked as high-risk financial data, and the financial data of the same type corresponding to the qualified node transmission delay evaluation result not greater than the preset qualified node transmission delay threshold is marked as low-risk financial data. Finally, the qualified node transmission is optimized for the risk classification data obtained after the delay risk classification, and the improvement of the security in risk identification based on financial data of cross-regional enterprises is realized.

[0023] The technical solution in the embodiment of the present application for solving the problem of low security in risk identification based on financial data of cross-regional enterprises has the following general idea: By analyzing the security of the financial data transmission path and determining whether to perform financial data transmission security isolation, then analyzing the qualified node transmission delay of the financial data for the qualified nodes and determining whether to perform delay risk classification, and finally optimizing the qualified node transmission for the risk classification data, the effect of improving the security in risk identification based on financial data of cross-regional enterprises is achieved.

[0024] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments.

[0025] As Figure 1As shown in the figure, it is a schematic structural diagram of a risk management system based on financial management provided by an embodiment of the present application, including: a transmission path security analysis module, a qualified node transmission delay analysis module, and a qualified node transmission optimization module. Among them, the transmission path security analysis module is used to analyze the security of the financial data transmission path to obtain the node security evaluation result and judge whether to perform financial data transmission security isolation; the qualified node transmission delay analysis module is used to analyze the transmission delay of qualified nodes for financial data and judge whether to perform delay risk classification; the qualified node transmission optimization module is used to optimize the transmission of qualified nodes for the risk classification data obtained after delay risk classification, and the risk classification data includes low-risk financial data and high-risk financial data.

[0026] In this embodiment, the node security evaluation result is monitored through the transmission path security analysis module. When the monitored node security evaluation result is not lower than the preset node security threshold, financial data transmission security isolation is not performed and qualified nodes are obtained. Otherwise, financial data transmission security isolation is performed and qualified nodes and unqualified nodes are obtained. At the same time, the load condition of the qualified nodes is monitored to obtain the qualified node load value. When the qualified node load value is less than the preset node load average threshold, the transmission delay analysis of qualified nodes for financial data continues. Otherwise, balancing processing is performed; the qualified node transmission delay analysis module monitors the qualified node transmission delay evaluation result and performs delay risk classification based on the qualified node transmission delay evaluation result to obtain risk classification data; the qualified node transmission optimization module monitors the qualified node acquisition request frequency evaluation value. When the request frequency evaluation value is greater than the preset qualified node request frequency, the corresponding qualified node is re-marked as an unqualified node; at the same time, the security of the financial data transmission path for high-risk financial data is re-analyzed. When the monitored node security evaluation result is not lower than the preset node security threshold, the optimization of financial data transmission continues. Otherwise, the financial data transmission security isolation continues.

[0027] In this embodiment, the greater the node security evaluation result, the higher the security, the fewer attacks the network node may suffer, the stronger the transmission ability of financial data may be, and the smaller the evaluation result of the transmission delay of the qualified node corresponding to the qualified node may be; while the greater the evaluation result of the transmission delay of the qualified node, it may mean that the network stability of the network node is reduced, thus increasing the risk of data leakage or transmission interruption, resulting in a reduction in the node security evaluation result; the node security evaluation result and the evaluation result of the transmission delay of the qualified node affect each other. For example, in a large enterprise with branches, when the enterprise needs to allocate resources among multiple regions or branches, the secure and efficient transmission of financial data becomes a crucial link. By monitoring the node security evaluation result and the evaluation result of the transmission delay of the qualified node corresponding to the financial data when resources need to be allocated among multiple regions or branches, the security of financial data transmission is ensured, and thus the security in risk identification based on cross-regional enterprise financial data is improved.

[0028] Further, perform security analysis on the financial data transmission path to obtain the node security evaluation result. The specific process is as follows: Obtain the financial data transmission path security data, which is obtained by processing the transmission path security parameters and the preset transmission path security parameters retrieved from the database; Combine the financial data transmission path security data and the preset node and quantization weight group retrieved from the database to obtain the node security evaluation result; The node security evaluation result represents the quantization data of the security impact of the transmission path security parameters acting together on the network node for transmitting financial data; The node security evaluation result is used to evaluate the security of the network node for transmitting financial data within a preset time period; The preset node and quantization weight group includes the preset node and financial data volume weight, the preset node traffic and quantity weight, the preset node and noise weight, the preset node and financial data loss weight, the preset node and financial data retransmission weight; The financial data transmission path security data includes the financial data volume and node quantization value, the node traffic and quantity quantization value, the node and noise quantization value, the node and financial data loss quantization value, and the node and financial data retransmission quantization value; The transmission path security parameters include the node traffic change amount, the financial data volume, the node quantity, the channel noise, the financial data loss rate, and the financial data retransmission rate; The preset transmission path security parameters include the preset node traffic change amount, the preset financial data volume, the preset node quantity, the preset channel noise, the preset financial data loss rate, the preset financial data retransmission rate, and the preset transmission path security weight group; The preset transmission path security weight group includes the preset financial data volume weight, the preset node quantity weight, the preset channel noise weight, the preset financial loss weight, and the preset financial retransmission weight; The node traffic change amount is represented by the maximum value corresponding to the absolute value of the difference between the initial state node traffic and the final state node traffic within a preset time period; The financial data loss rate is represented by the result of the ratio operation of the difference between the financial data volume in the initial state and the financial data volume in the final state within a preset time period and the financial data volume in the initial state; The financial data retransmission rate is represented by the maximum value of the retransmission rate of the financial data within a preset time period.

[0029] It should be added that the specific process of analyzing the transmission delay of qualified nodes for financial data is as follows: obtaining the transmission delay data of qualified nodes by processing the transmission delay parameters of qualified nodes and the preset transmission delay parameters of qualified nodes obtained from the database; obtaining the evaluation result of the transmission delay of qualified nodes by processing the transmission delay data of qualified nodes and the preset combination of qualified nodes and transmission delay weights; the evaluation result of the transmission delay of qualified nodes represents the quantified data of the impact of the transmission delay parameters of qualified nodes on the delay situation of transmitting the same type of financial data by qualified nodes; the evaluation result of the transmission delay of qualified nodes is used to evaluate the delay situation of transmitting the same type of financial data by qualified nodes within the qualified time period of the preset nodes; the preset combination of nodes and transmission delay weights includes the preset qualified response and audit weight, the preset qualified response and type quantity weight, the preset qualified response and read weight, and the preset qualified response and retransmission weight; the transmission delay data of qualified nodes includes the qualified response and audit quantization value, the type quantity and qualified response quantization value, the qualified response and read quantization value, and the qualified response and retransmission quantization value; the transmission delay parameters of qualified nodes include the average node response duration, the average number of financial data audits, the number of qualified data types, the average number of financial data reads, and the retransmission rate of financial data of qualified nodes; the preset transmission delay parameters of qualified nodes include the preset average node response duration, the preset average number of financial data audits, the preset number of qualified data types, the preset average number of financial data reads, the preset retransmission rate of financial data of qualified nodes, and the preset financial node delay weight combination; the preset financial node delay weight combination includes the preset financial data audit weight, the preset qualified data type weight, the preset financial data read weight, and the preset financial retransmission weight of qualified nodes; the average node response duration represents the average value of the response durations of qualified nodes within the qualified time period of the preset nodes; the average number of financial data audits represents the average value of the number of audits of the same type of financial data within the qualified time period of the preset nodes; the preset number of qualified data types represents the average value of the number of data formats corresponding to the same type of financial data; the average number of financial data reads represents the average value of the number of reads of the same type of financial data within the qualified time period of the preset nodes; the preset qualified time period of nodes represents the preset time period during the process of analyzing the transmission delay of qualified nodes for financial data.

[0030] In this embodiment, the aforementioned database is the database provided by the risk management system based on financial management in the embodiments of the present application for storing various types of set data. The database includes, but is not limited to, the preset node traffic change amount, the preset financial data amount, the preset number of nodes, the preset channel noise, etc. The various values therein are directly set by technicians. For example, the preset node traffic change amount is represented by the maximum value of the node traffic change amount in the historical time period, the preset financial data amount is represented by the maximum value of the financial data amount in the historical time period, the preset number of nodes is represented by the maximum value of the number of nodes in the historical time period, the preset channel noise is represented by the maximum value of the channel noise in the historical time period, the preset financial data loss rate is represented by the maximum value of the financial data loss rate in the historical time period, and the preset financial data retransmission rate is represented by the maximum value of the financial data retransmission rate in the historical time period.

[0031] Specifically, the unit of both the node traffic change amount and the preset node traffic change amount is Mbps, the unit of both the financial data amount and the preset financial data amount is Bytes, the unit of both the number of nodes and the preset number of nodes is piece, the unit of both the channel noise and the preset channel noise is decibel, and the financial data loss rate, the financial data retransmission rate, the preset financial data loss rate, and the preset financial data retransmission rate have no unit.

[0032] The preset average node response duration is represented by the average value of the response durations of qualified nodes in the preset time period, the average value of the preset financial data audit times is represented by the average value of the financial data audit times of qualified nodes in the preset time period, the preset number of qualified data types is represented by the number of types of the same type of financial data in the preset time period, the average value of the preset financial data read times is represented by the average value of the read times of the same type of financial data in the preset time period, and the preset retransmission rate of qualified node financial data is represented by the average value of the retransmission rates of the same type of financial data in the preset time period.

[0033] Specifically, the unit of both the average node response duration and the preset average node response duration is millisecond, the unit of the average value of the financial data audit times, the average value of the financial data read times, the average value of the preset financial data audit times, and the average value of the preset financial data read times is time, the unit of both the preset number of qualified data types and the preset number of qualified data types is piece, and the retransmission rate of qualified node financial data and the preset retransmission rate of qualified node financial data have no unit.

[0034] Monitor and count the initial state node traffic and the final state node traffic within a preset time period through network performance measurement tools (such as Narus Intelligence, NetDetector, etc.), and represent the node traffic change amount by the maximum value corresponding to the absolute value of the difference between the initial state node traffic and the final state node traffic; monitor and count the maximum value of the financial data volume within a preset time period through network performance measurement tools to obtain the financial data volume; monitor and count the number of network nodes within a preset time period through network performance measurement tools to obtain the number of nodes; monitor and count the maximum value of the network node channel noise within a preset time period through a noise meter to obtain the channel noise; monitor and count the financial data volume in the initial state and the financial data volume in the final state within a preset time period through network performance measurement tools, and represent the financial data loss rate by the result of the ratio operation of the difference result between the financial data volume in the initial state and the financial data volume in the final state and the financial data volume in the initial state; monitor and count the maximum value of the retransmission rate of the financial data within a preset time period through network performance measurement tools to obtain the maximum value of the retransmission rate of the financial data.

[0035] Monitor and count the average value of the response durations of all qualified nodes within a preset qualified node time period through network performance measurement tools to obtain the average node response duration; monitor and count the average value of the number of audits of the same type of financial data within a preset qualified node time period through network performance measurement tools to obtain the average value of the financial data audit times; monitor and count the average value of the number of data formats corresponding to the same type of financial data within a preset qualified node time period through network performance measurement tools to obtain the number of preset qualified data types; monitor and count the average value of the number of times of reading the same type of financial data within a preset qualified node time period through network performance measurement tools to obtain the average value of the financial data reading times; monitor and count the maximum value of the retransmission rate of the same type of financial data within a preset qualified node time period through network performance measurement tools to obtain the retransmission rate of the financial data of qualified nodes, achieving an improvement in the accuracy of obtaining the evaluation result of the transmission delay of qualified nodes, and further achieving the effect of improving the security when identifying risks based on cross-regional enterprise financial data.

[0036] Furthermore, combine the financial data transmission path security data and the preset nodes and quantization weight groups obtained from the database to obtain the node security evaluation result. The specific process is as follows: Process the obtained node and financial data volume processing group to obtain the financial data volume and the node quantization value, that is , the financial data volume and the node quantization value are used to reflect the comprehensive influence degree of the node traffic change volume and the financial data volume on the security of the network node transmitting financial data; the node and financial data volume processing group includes the node traffic change volume, the financial data volume, the preset node traffic change volume, the preset financial data volume, and the preset financial data volume weight. The financial data volume and the node quantization value are represented by the result of the ratio operation of the node traffic change processing value, the sum of the financial data volume and the preset financial data volume and twice the preset financial data volume, and the result of the product operation of the preset financial data volume weight. The financial data volume and the node quantization value represent the result of weighting the proportion of the preset financial data volume weight to the node traffic change volume and the preset node traffic change volume and the proportion of the financial data volume and the preset financial data volume; the node traffic change processing value is represented by the result of the ratio operation of the sum of the node traffic change volume and the preset node traffic change volume and twice the preset node traffic change volume; the node traffic and quantity quantization value is obtained by processing the obtained node traffic and quantity processing group, that is , the node traffic and quantity quantization value is used to reflect the comprehensive influence degree of the node traffic change volume and the node quantity on the security of the network node transmitting financial data; the node traffic and quantity processing group includes the node traffic change volume, the node quantity, the preset node traffic change volume, the preset node quantity, and the preset node quantity weight. The node traffic and quantity quantization value is represented by the result of the ratio operation of the node traffic change processing value, the sum of the node quantity and the preset node quantity and twice the preset node quantity, and the result of the product operation of the preset node quantity weight. The node traffic and quantity quantization value represents the result of weighting the proportion of the preset node weight to the node traffic change volume and the preset node traffic change volume and the proportion of the node quantity and the preset node quantity; the node and noise quantization value is obtained by processing the obtained node and noise processing group, that is , the node and noise quantization value is used to reflect the comprehensive influence degree of the node traffic change volume and the channel noise on the security of the network node transmitting financial data; the node and noise processing group includes the node traffic change volume, the channel noise, the preset node traffic change volume, the preset channel noise, and the preset channel noise weight. The node and noise quantization value is represented by the result of the ratio operation of the node traffic change processing value, the sum of the channel noise and the preset channel noise and twice the preset channel noise, and the result of the product operation of the preset channel noise weight. The node and noise quantization value represents the result of weighting the proportion of the preset channel noise weight to the node traffic change volume and the preset node traffic change volume and the proportion of the channel noise and the preset channel noise; the node and financial data loss quantization value is obtained by processing the obtained node and financial data loss processing group, that is , the node and financial data loss quantification value is used to reflect the comprehensive influence degree of the node traffic change amount and the financial data loss rate on the security of the network node transmitting financial data; the node and financial data loss processing group includes the node traffic change amount, the financial data loss rate, the preset node traffic change amount, the preset financial data loss rate, and the preset financial loss weight. The node and financial data loss quantification value is represented by the result of multiplying the result of the ratio operation of the node traffic change processing value, the sum of the financial data loss rate and the preset financial data loss rate and twice the preset financial data loss rate, and the preset financial loss weight. The node and financial data loss quantification value represents the result of weighting the proportion of the preset financial loss weight to the node traffic change amount and the preset node traffic change amount, and the proportion of the financial data loss rate and the preset financial data loss rate; the node and financial data retransmission quantification value is obtained by processing the obtained node and financial data retransmission processing group, that is , the node and financial data retransmission quantification value is used to reflect the comprehensive influence degree of the node traffic change amount and the financial data retransmission rate on the security of the network node transmitting financial data; the node and financial data retransmission processing group includes the node traffic change amount, the financial data retransmission rate, the preset node traffic change amount, the preset financial data retransmission rate, and the preset financial retransmission weight. The node and financial data retransmission quantification value is represented by the result of multiplying the result of the ratio operation of the node traffic change processing value, the financial data retransmission rate and twice the preset financial data retransmission rate, and the preset financial retransmission weight. The node and financial data retransmission quantification value represents the result of weighting the proportion of the preset financial retransmission weight to the node traffic change amount and the preset node traffic change amount, and the proportion of the financial data retransmission rate and the preset financial data retransmission rate; the node security evaluation result is obtained by processing the financial data transmission path security data and the preset node and quantization weight group obtained from the database; the preset node and quantization weight group is used to reflect the influence of the financial data transmission path security data on the node security evaluation result within a preset time period; the preset transmission path security weight group is used to reflect the influence of the node and financial data processing group on the financial data transmission path security data within a preset time period; the node and financial data processing group includes the node and financial data volume processing group, the node traffic and quantity processing group, the node and noise processing group, the node and financial data loss processing group, and the node and financial data retransmission processing group; Among them, the node security evaluation result is obtained by the following method: ; ; ; ; ; ; Wherein, represents the node security assessment result in the th preset time period, , represents the number of the preset time period, represents the total number of the preset time periods, represents the financial data volume and node quantization value in the th preset time period, represents the node traffic and quantity quantization value in the th preset time period, represents the node and noise quantization value in the th preset time period, represents the node and financial data loss quantization value in the th preset time period, represents the node and financial data retransmission quantization value in the th preset time period, represents the weight of the preset node and financial data volume, represents the weight of the preset node traffic and quantity, represents the weight of the preset node and noise, represents the weight of the preset node and financial data loss, represents the weight of the preset node and financial data retransmission.

[0037] represents the change in node traffic in the th preset time period, represents the financial data volume in the th preset time period, represents the number of nodes in the th preset time period, represents the channel noise in the th preset time period, represents the financial data loss rate in the th preset time period, represents the financial data retransmission rate in the th preset time period, represents the preset change in node traffic, represents the preset financial data volume, represents the preset number of nodes, represents the preset channel noise, represents the preset financial data loss rate, represents the preset financial data retransmission rate, represents the weight of the preset financial data volume, represents the weight of the preset node, represents the preset channel noise weight, represents the preset financial loss weight, represents the preset financial retransmission weight.

[0038] In this embodiment, the algorithm of this embodiment combines the analysis of the security data of the financial data transmission path to obtain the node security evaluation result. In this embodiment, an exponential function (decreasing function) is applied to process the security data of the financial data transmission path, which helps to more accurately display the change of the security of the network node transmitting financial data within a preset time period (the security data of the financial data transmission path is inversely proportional to the node security evaluation result). The larger the financial data volume and the node quantization value, the greater the comprehensive influence degree of the node traffic change volume and the financial data volume on the security of the network node transmitting financial data, resulting in a decrease in the node security evaluation result; the larger the node traffic and the quantity quantization value. It means that the comprehensive influence degree of the node traffic change volume and the node quantity on the security of the network node transmitting financial data is greater, resulting in a decrease in the node security evaluation result; the larger the node and the noise quantization value, it means that the comprehensive influence degree of the node traffic change volume and the channel noise on the security of the network node transmitting financial data is greater, resulting in a decrease in the node security evaluation result; the larger the node and the financial data loss quantization value, it means that the comprehensive influence degree of the node traffic change volume and the financial data loss rate on the security of the network node transmitting financial data is greater, resulting in a decrease in the node security evaluation result; the larger the node and the financial data retransmission quantization value, it means that the comprehensive influence degree of the node traffic change volume and the financial data retransmission rate on the security of the network node transmitting financial data is greater, resulting in a decrease in the node security evaluation result; in summary, the security data of the financial data transmission path is inversely proportional to the node security evaluation result.

[0039] In the algorithm of this embodiment, the security data of the financial data transmission path does not exist independently, and there is a mutual correlation between the independent variables, which needs to be comprehensively analyzed. When the financial data volume increases, the traffic that the node needs to process will also increase accordingly, which may lead to an increase in the node traffic change volume; the increase in the number of nodes may lead to an increase in the node traffic change volume because there is more traffic and the network topology is more complex; the increase in channel noise may lead to an increase in the data transmission error rate, which in turn leads to an increase in the financial data loss rate and the financial data retransmission rate; the increase in the node traffic change volume may increase the risk of data loss because network congestion may be more serious, resulting in an increase in the financial data loss rate; the increase in the node traffic change volume may also lead to an increase in the retransmission rate because network congestion may reduce the possibility of successful transmission of financial data at one time, resulting in an increase in the financial data retransmission rate; by analyzing the comprehensive influence between parameters, the accurate evaluation of the security of the network node transmitting financial data within a preset time period is realized, and thus the effect of improving the security when identifying risks based on cross-regional enterprise financial data is achieved.

[0040] It should be noted that this embodiment provides two sets of mapping groups obtained from the database, which are respectively used to reflect the mapping relationship between the financial data transmission path security data and the corresponding preset nodes and the quantization weight group, and the mapping relationship between the nodes and the financial data processing group and the corresponding preset transmission path security weight group; the mapping relationship in the mapping set can be a one-to-one or many-to-one relationship; for example, in this embodiment, the value range of the weight is 0-1. By inputting the real-time financial data transmission path security data into the corresponding mapping group, the preset nodes and the quantization weight group can be obtained, and by inputting the nodes and the financial data processing group into the corresponding mapping group, the preset transmission path security weight group can be obtained.

[0041] Furthermore, the specific process of determining whether to perform financial data transmission security isolation is as follows: compare the node security evaluation result with the preset node security threshold obtained from the database; when the node security evaluation result is not lower than the preset node security threshold, do not perform financial data transmission security isolation and obtain qualified nodes, otherwise perform financial data transmission security isolation and obtain qualified nodes and unqualified nodes. Financial data transmission security isolation means classifying the network nodes corresponding to the financial data through data isolation technology; qualified nodes refer to the network nodes whose node security evaluation results are not lower than the preset node security threshold; unqualified nodes refer to the network nodes whose node security evaluation results are lower than the preset node security threshold. Compare the number of qualified nodes and unqualified nodes. If the number of qualified nodes is greater than the number of unqualified nodes, perform data format division to obtain homogeneous financial data. Data format division means dividing the financial data of the same format into the same type of data. Otherwise, send a prompt to the preset personnel to add a preset number of standby network nodes until the number of qualified nodes is greater than the number of unqualified nodes. Homogeneous financial data refers to financial data with the same data format and transmitted using the same preset transmission protocol.

[0042] It should be added that after determining whether to perform financial data transmission security isolation, it also includes monitoring the load of qualified nodes; the specific process of monitoring the load of qualified nodes is as follows: monitor the load situation of qualified nodes to obtain the qualified node load value, and the qualified node load value is represented by the data volume corresponding to the homogeneous financial data processed by the qualified nodes per unit time; compare the qualified node load value with the preset node load average threshold obtained from the database; when the qualified node load value is less than the preset node load average threshold, continue to analyze the transmission delay of the financial data qualified nodes, otherwise perform load balancing processing; load balancing processing means dispersing the homogeneous financial data of a preset data volume to the standby network nodes through a load balancing algorithm to avoid overloading a single node.

[0043] In this embodiment, the preset node security threshold is represented by the average value of the node security evaluation results in the historical time period, and the preset node load average threshold is represented by the average value of the qualified node load values of the qualified nodes within the preset time period; classifying the network nodes corresponding to the financial data through the data isolation technology can prevent data leakage, unauthorized access, or data tampering, thereby improving the security of the financial data; dividing the financial data in the same format into the same type of data, and the data format may include numerical format, text format, etc., and different preset transmission protocols are adopted for different types of the same data, such as Transmission Control Protocol, User Datagram Protocol, etc.; during the transmission of the financial data, through the load balancing algorithm, such as the round-robin method, the same type of financial data with the preset data volume is dispersed to the standby network nodes to ensure that the load of the network nodes remains balanced, thereby improving the overall performance and stability of the system, and further improving the security when risk identification is performed based on the cross-regional enterprise financial data.

[0044] Further, the qualified node transmission delay evaluation result is obtained by processing the qualified node transmission delay data and the preset qualified node and transmission delay weight group obtained from the database. The specific process is as follows: the qualified response and audit quantization value is obtained by processing the qualified response and audit processing group, that is , the qualified response and audit quantization value is used to reflect the comprehensive influence degree of the node average response duration and the average value of the financial data audit times on the delay of the qualified node transmitting the same type of financial data. The qualified response and audit processing group includes the node average response duration, the average value of the financial data audit times, the preset node average response duration, the preset average value of the financial data audit times, and the preset financial data audit weight; the qualified response and audit quantization value is obtained by performing a product operation on the result of the ratio operation of the sum of the node average response processing value, the average value of the financial data audit times, and the preset average value of the financial data audit times to twice the preset average value of the financial data audit times and the preset financial data audit weight. The qualified response and audit quantization value represents the result of weighting the proportion of the preset financial data audit weight to the node average response duration and the preset node average response duration and the proportion of the average value of the financial data audit times and the preset average value of the financial data audit times; the node average response processing value is represented by the result of the ratio operation of the sum of the node average response duration and the preset node average response duration to twice the preset node average response duration; the type quantity and qualified response quantization value is obtained by processing the type quantity and the qualified response processing group, that is , the number of types and the qualified response quantization value are used to reflect the comprehensive influence degree of the average node response duration and the number of qualified data types on the delay of qualified nodes transmitting the same type of financial data. The number of types and the qualified response processing group include the average node response duration, the number of qualified data types, the preset average node response duration, the preset number of qualified data types, and the preset weight of qualified data types. The number of types and the qualified response quantization value are obtained by multiplying the result of the ratio operation of the sum of the average node response processing value, the number of qualified data types, and the preset number of qualified data types to twice the preset number of qualified data types, and the preset weight of qualified data types. The qualified response and audit quantization value represents the result of weighting the proportion of the preset weight of qualified data types to the average node response duration and the preset average node response duration, and the proportion of the number of qualified data types and the preset number of qualified data types. By processing the qualified response and read processing group, the qualified response and read quantization value is obtained, that is , the qualified response and read quantization value is used to reflect the comprehensive influence degree of the average node response processing value and the average number of financial data read times on the delay of qualified nodes transmitting the same type of financial data. The qualified response and read processing group includes the average node response duration, the average number of financial data read times, the preset average node response duration, and the preset average number of financial data read times. The qualified response and read quantization value is obtained by multiplying the result of the ratio operation of the sum of the average node response processing value, the average number of financial data read times, and the preset average number of financial data read times to twice the preset average number of financial data read times, and the preset weight of financial data read. The qualified response and read quantization value represents the result of weighting the proportion of the preset weight of financial data read to the average node response duration and the preset average node response duration, and the proportion of the average number of financial data read times and the preset average number of financial data read times. By processing the qualified response and retransmission processing group, the qualified response and retransmission quantization value is obtained, that is , the qualified response and retransmission quantization value is used to reflect the comprehensive influence degree of the average node response duration and the retransmission rate of qualified node financial data on the delay of qualified nodes transmitting the same type of financial data. The qualified response and retransmission processing group includes the average node response duration, the retransmission rate of qualified node financial data, the preset average node response duration, and the preset retransmission rate of qualified node financial data. The qualified response and retransmission quantization value is obtained by multiplying the result of the ratio operation of the sum of the average node response processing value, the retransmission rate of qualified node financial data, and the preset retransmission rate of qualified node financial data to twice the preset retransmission rate of qualified node financial data, and the preset weight of qualified node financial retransmission. The qualified response and retransmission quantization value represents the result of weighting the proportion of the preset weight of financial data read to the average node response duration and the preset average node response duration, and the proportion of the retransmission rate of qualified node financial data and the preset retransmission rate of qualified node financial data. Among them, the evaluation result of the qualified node transmission delay is obtained through the following method: ; ; ; ; ; In the formula, represents the evaluation result of the qualified node transmission delay within the qualified time period of the th preset node, , represents the number of the qualified time period of the preset node, represents the total number of the qualified time periods of the preset node, represents the qualified response and audit quantization value within the qualified time period of the th preset node, represents the type quantity and qualified response quantization value within the qualified time period of the th preset node, represents the qualified response and read quantization value within the qualified time period of the th preset node, represents the qualified response and retransmission quantization value within the qualified time period of the th preset node, represents the preset qualified response and audit weight, represents the preset qualified response and type quantity weight, represents the preset qualified response and read weight, represents the preset qualified response and retransmission weight.

[0045] represents the average node response duration within the qualified time period of the th preset node, represents the average value of the financial data audit times within the qualified time period of the th preset node, represents the quantity of qualified data types within the qualified time period of the th preset node, represents the average value of the financial data read times within the qualified time period of the th preset node, represents the qualified node financial data retransmission rate within the qualified time period of the th preset node, represents the average node response duration of the preset node, represents the average value of the preset financial data audit times, represents the quantity of preset qualified data types, Represents the average value of the preset number of times of financial data reading Represents the retransmission rate of financial data of preset qualified nodes Represents the audit weight of preset financial data Represents the weight of preset qualified data types Represents the reading weight of preset financial data Represents the retransmission weight of preset qualified node finances

[0046] In this embodiment, the algorithm of this embodiment obtains the evaluation result of the transmission delay of qualified nodes through the analysis of the transmission delay data of qualified nodes. In this embodiment, by applying the hyperbolic tangent function to process the transmission delay data of qualified nodes, it helps to more accurately display the change of the delay situation of qualified nodes transmitting the same type of financial data within the qualified time period of preset nodes (the transmission delay data of qualified nodes is directly proportional to the evaluation result of the transmission delay of qualified nodes). The larger the qualified response and the audit quantization value, the greater the comprehensive influence degree of the average response duration of the node and the average value of the number of financial data audits on the delay of qualified nodes transmitting the same type of financial data, resulting in an increase in the evaluation result of the transmission delay of qualified nodes; the larger the number of types and the qualified response quantization value, the greater the comprehensive influence degree of the average response duration of the node and the number of qualified data types on the delay of qualified nodes transmitting the same type of financial data, resulting in an increase in the evaluation result of the transmission delay of qualified nodes; the larger the qualified response and the reading quantization value, the greater the comprehensive influence degree of the average response processing value of the node and the average value of the number of times of financial data reading on the delay of qualified nodes transmitting the same type of financial data, resulting in an increase in the evaluation result of the transmission delay of qualified nodes; the larger the qualified response and the retransmission quantization value, the greater the comprehensive influence degree of the average response duration of the node and the retransmission rate of financial data of qualified nodes on the delay of qualified nodes transmitting the same type of financial data, resulting in an increase in the evaluation result of the transmission delay of qualified nodes. In summary, the transmission delay data of qualified nodes is directly proportional to the evaluation result of the transmission delay of qualified nodes.

[0047] In the algorithm of this embodiment, the qualified node transmission delay data does not exist independently, and there is a mutual correlation between independent variables, which requires comprehensive analysis. The longer the average response time of the node, the more likely it is to cause delays in the audit process and increase the average number of audit times. And the larger the average number of financial data audit times, the more likely it is to introduce additional processing steps and extend the response time. The larger the number of qualified data types, the more likely it is to cause the average response time of the node to be longer, because different types of financial data may require different processing logics, which will increase the node response delay. The larger the average number of financial data reading times, the more likely it is to increase the load of the node, resulting in an increase in the average response time of the node. The larger the number of qualified data types, the more likely it is to increase the number of audits, resulting in an increase in the average number of financial data audit times. The larger the retransmission rate of qualified node financial data, the more likely it is to cause more read requests, and then the average number of financial data reading times increases. By analyzing the comprehensive influence between parameters, the accurate evaluation of the delay situation of qualified nodes transmitting the same type of financial data within the preset qualified time period of the nodes is realized, and further the improvement of security when identifying risks based on cross-regional enterprise financial data is realized.

[0048] It should be noted that the preset node and transmission delay weight group are used to reflect the influence of qualified node transmission delay data on the evaluation result of qualified node transmission delay; the preset financial node delay weight group is used to reflect the influence degree of the qualified delay processing group on the delay situation of qualified nodes transmitting the same type of financial data. The qualified delay processing group includes the qualified response and audit processing group, the type quantity and qualified response processing group, the qualified response and reading processing group, and the qualified response and retransmission processing group.

[0049] This embodiment provides two mapping groups obtained from the database. The preset node and transmission delay weight group can be obtained by inputting the real-time qualified node transmission delay data into the corresponding mapping group, and the preset financial node delay weight group can be obtained by inputting the qualified delay processing group into the corresponding mapping group. The two mapping groups provided in this embodiment are respectively used to reflect the mapping relationship between the qualified node transmission delay data and the corresponding preset node and transmission delay weight group, and the mapping relationship between the qualified delay processing group and the corresponding preset financial node delay weight group. The mapping relationship in the mapping set can be a one-to-one or many-to-one relationship. For example, in this embodiment, the value range of the weight is 0-1.

[0050] Furthermore, the specific process of determining whether to perform delay risk classification is as follows: Compare the evaluation result of qualified node transmission delay with the preset qualified node transmission delay threshold obtained from the database; when the evaluation result of qualified node transmission delay is greater than the preset qualified node transmission delay threshold, mark the corresponding same type of financial data as high-risk financial data; when the evaluation result of qualified node transmission delay is not greater than the preset qualified node transmission delay threshold, mark the corresponding same type of financial data as low-risk financial data.

[0051] It should be added that the specific process of optimizing the transmission of qualified nodes is as follows: After compressing the low-risk financial data, optimize the financial data transmission; Optimizing the financial data transmission means transmitting data through optimizing the transmission path; Optimizing the transmission path means sending a prompt to a preset person to select the transmission path with the fewest network nodes according to the preset number of qualified nodes from more to less; When the number of optimized transmission paths is greater than 1, distribute the risk classification data, and data distribution means evenly distributing the risk classification data according to the data volume and then dispersing it to the network nodes; Financial data compression means sending a prompt to a preset person to set a preset compression algorithm; Perform financial data compression and abnormal monitoring of qualified node requests on high-risk financial data.

[0052] The specific process of abnormal monitoring of qualified node requests is as follows: Monitor the request frequency evaluation value obtained by the qualified node, and the request frequency evaluation value is represented by the number of requests received by the qualified node within a unit time; Compare the request frequency evaluation value with the preset qualified node request frequency obtained from the database; When the request frequency evaluation value is greater than the preset qualified node request frequency, re-mark the corresponding qualified node as an unqualified node; Re-analyze the security of the financial data transmission path for high-risk financial data. When the monitored node security evaluation result is not lower than the preset node security threshold, continue to optimize the financial data transmission; When the monitored node security evaluation result is lower than the preset node security threshold, re-perform financial data transmission security isolation.

[0053] In this embodiment, the preset qualified node transmission delay threshold is represented by twice the average value of the qualified node transmission delay evaluation results of the qualified nodes within the preset node qualified time period, and the preset qualified node request frequency is represented by the average value of the frequency evaluation values of the qualified nodes within the preset node qualified time period; By dividing high-risk financial data and low-risk financial data, targeted optimization of qualified node transmission can be carried out, which helps to improve the reliability of qualified node transmission optimization; Performing abnormal monitoring of qualified node requests can be used to reduce the interference of abnormal behaviors (such as illegal tampering, etc.) on financial data and reduce the network node load; The preset person selects the preset compression algorithm with the maximum compression speed by monitoring the compression speed of the preset compression algorithm for the same type of financial data. The preset compression algorithms include Huffman coding, LZW coding, predictive coding, etc.; By re-analyzing the security of the financial data transmission path for high-risk financial data, it helps to prevent the loss of financial data due to security threats during the transmission process, thereby achieving an improvement in security when performing risk identification based on cross-regional enterprise financial data.

[0054] In summary, by analyzing the security of the financial data transmission path and determining whether to perform financial data transmission security isolation, then analyzing the transmission delay of qualified nodes for financial data and determining whether to perform delay risk classification, and finally optimizing the transmission of qualified nodes for the risk classification data, the reliability of optimizing the transmission of qualified nodes for the risk classification data is improved. Furthermore, the security of risk identification based on cross-regional enterprise financial data is enhanced, effectively solving the problem of low security in risk identification based on cross-regional enterprise financial data in the prior art.

[0055] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0056] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0057] These computer program instructions can also be stored in a computer-readable memory capable of guiding a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implements the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0058] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide means for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1Steps of the functions specified in one or more boxes.

[0059] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0060] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A risk management system based on financial management, characterized in that It includes a transmission path security analysis module, a qualified node transmission delay analysis module, and a qualified node transmission optimization module: Among them, the transmission path security analysis module is used to conduct a security analysis of the financial data transmission path to obtain the node security evaluation result and determine whether to perform financial data transmission security isolation; The qualified node transmission delay analysis module is used to conduct a financial data qualified node transmission delay analysis on the qualified nodes and determine whether to perform delay risk classification; The qualified node transmission optimization module is used to optimize the qualified node transmission for the risk classification data obtained after the delay risk classification, and the risk classification data includes low-risk financial data and high-risk financial data.

2. The risk management system based on financial management according to claim 1, wherein, The process of conducting a security analysis of the financial data transmission path to obtain the node security evaluation result is as follows: Obtain the financial data transmission path security data, which is obtained by processing the transmission path security parameters and the preset transmission path security parameters obtained from the database; Combine the financial data transmission path security data and the preset node and quantization weight group obtained from the database to obtain the node security evaluation result; The node security evaluation result represents the quantization data of the security impact of the transmission path security parameters acting on the network node to transmit financial data; The preset node and quantization weight group includes the preset node and financial data volume weight, the preset node traffic and quantity weight, the preset node and noise weight, the preset node and financial data loss weight, and the preset node and financial data retransmission weight; The financial data transmission path security data includes the financial data volume and node quantization value, the node traffic and quantity quantization value, the node and noise quantization value, the node and financial data loss quantization value, and the node and financial data retransmission quantization value; The transmission path security parameters include the node traffic change amount, the financial data volume, the node quantity, the channel noise, the financial data loss rate, and the financial data retransmission rate.

3. The risk management system based on financial management according to claim 2, wherein, The process of combining the financial data transmission path security data and the preset node and quantization weight group obtained from the database to obtain the node security evaluation result is as follows: Process the obtained node and financial data volume processing group to obtain the financial data volume and node quantization value, which is used to reflect the comprehensive influence degree of the node traffic change amount and the financial data volume on the security of the network node to transmit financial data; The node and financial data volume processing group includes the node traffic change amount, the financial data volume, the preset node traffic change amount, the preset financial data volume, and the preset financial data volume weight; Process the obtained node traffic and quantity processing group to obtain the node traffic and quantity quantization value, which is used to reflect the comprehensive influence degree of the node traffic change amount and the node quantity on the security of the network node to transmit financial data; The node traffic and quantity processing group includes the node traffic change amount, the node quantity, the preset node traffic change amount, the preset node quantity, and the preset node quantity weight; By processing the obtained nodes and the noise processing group, a node and noise quantization value is obtained, and the node and noise quantization value is used to reflect the comprehensive influence degree of the node traffic change amount and the channel noise on the security of the financial data transmitted by the network node; The node and noise processing group includes a node traffic change amount, a channel noise, a preset node traffic change amount, a preset channel noise, and a preset channel noise weight; By processing the obtained nodes and the financial data loss processing group, a node and financial data loss quantization value is obtained, and the node and financial data loss quantization value is used to reflect the comprehensive influence degree of the node traffic change amount and the financial data loss rate on the security of the financial data transmitted by the network node; The node and financial data loss processing group includes a node traffic change amount, a financial data loss rate, a preset node traffic change amount, a preset financial data loss rate, and a preset financial loss weight; By processing the obtained nodes and the financial data retransmission processing group, a node and financial data retransmission quantization value is obtained, and the node and financial data retransmission quantization value is used to reflect the comprehensive influence degree of the node traffic change amount and the financial data retransmission rate on the security of the financial data transmitted by the network node; The node and financial data retransmission processing group includes a node traffic change amount, a financial data retransmission rate, a preset node traffic change amount, a preset financial data retransmission rate, and a preset financial retransmission weight; By processing the financial data transmission path security data and the preset node and quantization weight group obtained from the database, a node security evaluation result is obtained; The preset node and quantization weight group is used to reflect the influence of the financial data transmission path security data on the node security evaluation result within a preset time period.

4. The risk management system based on financial management according to claim 3, wherein The specific process of determining whether to perform financial data transmission security isolation is as follows: Compare the node security evaluation result with the preset node security threshold obtained from the database; When the node security evaluation result is not lower than the preset node security threshold, financial data transmission security isolation is not performed and qualified nodes are obtained. Otherwise, financial data transmission security isolation is performed and qualified nodes and unqualified nodes are obtained. The financial data transmission security isolation means classifying the network nodes corresponding to the financial data through data isolation technology; Compare the number of qualified nodes and unqualified nodes. If the number of qualified nodes is greater than the number of unqualified nodes, data format division is performed to obtain the same type of financial data. Otherwise, a prompt is sent to the preset personnel to increase the preset number of standby network nodes until the number of qualified nodes is greater than the number of unqualified nodes. The same type of financial data means financial data with the same data format and transmitted using the same preset transmission protocol.

5. The risk management system based on financial management according to claim 4, wherein, After determining whether to perform financial data transmission security isolation, it also includes monitoring the load of qualified nodes; The specific process of the qualified node load monitoring is as follows: Monitor the load situation of qualified nodes to obtain a qualified node load value, and the qualified node load value is represented by the data volume corresponding to the same type of financial data processed by the qualified nodes per unit time; When the qualified node load value is less than the preset average node load threshold, continue the analysis of the transmission delay of qualified nodes for financial data; otherwise, perform balancing processing.

6. The risk management system based on financial management according to claim 1, characterized in that, The specific process of analyzing the transmission delay of qualified nodes for financial data of qualified nodes is as follows: Process the qualified node transmission delay parameters and the preset qualified node transmission delay parameters obtained from the database to obtain qualified node transmission delay data; Process the qualified node transmission delay data and the preset qualified node and transmission delay weight group obtained from the database to obtain the qualified node transmission delay evaluation result; The qualified node transmission delay evaluation result represents the quantitative data of the influence of the qualified node transmission delay parameters on the delay situation of transmitting the same type of financial data by qualified nodes; The qualified node transmission delay evaluation result is used to evaluate the delay situation of transmitting the same type of financial data by qualified nodes within the qualified time period of the preset nodes; The qualified node transmission delay data includes the qualified response and audit quantization value, the type quantity and qualified response quantization value, the qualified response and read quantization value, and the qualified response and retransmission quantization value; The qualified node transmission delay parameters include the average node response duration, the average number of financial data audits, the quantity of qualified data types, the average number of financial data reads, and the retransmission rate of qualified node financial data.

7. The risk management system based on financial management according to claim 6, wherein The process of obtaining the qualified node transmission delay evaluation result by processing the qualified node transmission delay data and the preset qualified node and transmission delay weight group obtained from the database is as follows: Process the qualified response and audit processing group to obtain the qualified response and audit quantization value. The qualified response and audit quantization value is used to reflect the comprehensive influence degree of the average node response duration and the average number of financial data audits on the delay of transmitting the same type of financial data by qualified nodes. The qualified response and audit processing group includes the average node response duration, the average number of financial data audits, the preset average node response duration, the preset average number of financial data audits, and the preset financial data audit weight; Process the type quantity and qualified response processing group to obtain the type quantity and qualified response quantization value. The type quantity and qualified response quantization value is used to reflect the comprehensive influence degree of the average node response duration and the quantity of qualified data types on the delay of transmitting the same type of financial data by qualified nodes. The type quantity and qualified response processing group includes the average node response duration, the quantity of qualified data types, the preset average node response duration, the preset quantity of qualified data types, and the preset qualified data type weight; Process the qualified response and read processing group to obtain the qualified response and read quantization value. The qualified response and read quantization value is used to reflect the comprehensive influence degree of the average node response processing value and the average number of financial data reads on the delay of transmitting the same type of financial data by qualified nodes. The qualified response and read processing group includes the average node response duration, the average number of financial data reads, the preset average node response duration, and the preset average number of financial data reads; The qualified response and retransmission quantization value is obtained by processing the qualified response and retransmission processing group. The qualified response and retransmission quantization value is used to reflect the comprehensive influence degree of the average node response duration and the retransmission rate of qualified node financial data on the delay of qualified nodes transmitting the same type of financial data. The qualified response and retransmission processing group includes the average node response duration, the retransmission rate of qualified node financial data, the preset average node response duration, and the preset retransmission rate of qualified node financial data.

8. The risk management system based on financial management according to claim 1, wherein, The specific process of determining whether to perform delay risk classification is as follows: Compare the qualified node transmission delay evaluation result with the preset qualified node transmission delay threshold obtained from the database; When the qualified node transmission delay evaluation result is greater than the preset qualified node transmission delay threshold, mark the corresponding type of financial data as high-risk financial data; When the qualified node transmission delay evaluation result is not greater than the preset qualified node transmission delay threshold, mark the corresponding type of financial data as low-risk financial data.

9. The risk management system based on financial management according to claim 8, wherein, The specific process of optimizing the transmission of qualified nodes is as follows: Perform financial data compression on the low-risk financial data and then optimize the financial data transmission; The optimized financial data transmission means transmitting data by optimizing the transmission path; The optimized transmission path means sending a prompt to a preset person to select the transmission path with the fewest network nodes according to the preset number of qualified nodes; When the number of optimized transmission paths is greater than 1, perform data distribution on the risk classification data. The data distribution means evenly dividing the risk classification data according to the data volume and then dispersing it to the network nodes; Perform financial data compression and abnormal request monitoring for qualified nodes on the high-risk financial data.

10. The risk management system based on financial management according to claim 9, characterized in that, The specific process of the abnormal request monitoring for qualified nodes is as follows: Monitor the request frequency evaluation value of the qualified node, which is represented by the number of requests received by the qualified node per unit time; When the request frequency evaluation value is greater than the preset qualified node request frequency, re-mark the corresponding qualified node as an unqualified node; Re-analyze the security of the financial data transmission path for the high-risk financial data. When the monitored node security evaluation result is not lower than the preset node security threshold, continue to optimize the financial data transmission; When the monitored node security evaluation result is lower than the preset node security threshold, re-perform financial data transmission security isolation.

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