Fund flow monitoring method and system based on cloud computing

Abstract

The invention discloses a fund flow monitoring method and system based on cloud computing, and belongs to the technical field of internet consumption finance. The method comprises the following steps: acquiring network state data, fund flow data and cloud computing platform performance data; a network state evaluation value is obtained through comprehensive analysis according to the network state data, a cloud computing platform performance evaluation value is obtained through comprehensive analysis according to the cloud computing platform performance data, a fund abnormity evaluation value of each account is obtained through comprehensive analysis according to the fund flow data, and adjustment feedback is carried out according to the fund abnormity evaluation value of each account. Performing comprehensive analysis according to the network state evaluation value, the cloud computing platform performance evaluation value and the fund abnormity evaluation value of each account to obtain a cloud computing platform state evaluation value; and performing evaluation feedback according to the state evaluation value of the cloud computing platform. According to the invention, the independence of fund flow monitoring is enhanced, the guarantee of fund safety is improved, and the accuracy of fund flow monitoring is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet consumer finance, and in particular to a method and system for monitoring capital flows based on cloud computing. Background Art

[0002] In order to further strengthen the central government's management of special transfer payments to local governments, improve the standardization, security and effectiveness of the use of fiscal funds, and promote coordinated economic and social development, it is required that the existing funds flow monitoring methods must establish a sound funds flow monitoring system to ensure the compliance and security of funds flow.

[0003] The existing funds flow monitoring system mainly relies on technical means such as data crawlers and API interfaces to conduct automated collection, and enters transaction records, account balances, funds flow and other information into the monitoring system in real time and comprehensively, and uses an alarm mechanism to prompt abnormal situations.

[0004] For example, the patent application with publication number: CN116611907A discloses a method, device and electronic equipment for monitoring fund flows, including: classifying the fund flows of moving account flows and product transaction flows according to corresponding fund flow classification rules respectively, and after completing the fund flow classification, verifying the accuracy of the fund flow classification results of the moving account flows and the fund flow classification results of the product transaction flows, that is, the final fund flow classification results of the moving account flows and the fund flow classification results of the product transaction flows have good accuracy, that is, the accuracy of fund flow monitoring is good, and therefore, the accuracy of the subsequently determined fund flow application analysis results is also good.

[0005] For example, the invention patent announcement with announcement number: CN112884565B discloses a method and system for monitoring bank fund fluctuation data, including: monitoring fund fluctuations through multiple fund monitoring paths of an account array to obtain pending fund fluctuation data; determining first fund fluctuation data in the pending fund fluctuation data corresponding to multiple fund paths, the first fund fluctuation data being the fund fluctuation amplitude determined through monitoring; performing data segmentation on the first fund fluctuation data to obtain second fund fluctuation data; performing data matching on the second fund fluctuation data through a fund flow monitoring training model to obtain data-matched real-time fund monitoring data. The fund path is monitored, so that the fund destination is clear, and further analysis and processing are performed on the fund fluctuation and fund flow, and abnormal fluctuation data and abnormal flow data are monitored in real time.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the prior art, the cloud computing fund flow monitoring method is highly dependent on the cloud computing platform and related hardware facilities. Once the cloud computing platform fails or is improperly maintained, the fund flow monitoring may be interrupted, resulting in low monitoring accuracy. Summary of the invention

[0008] The embodiments of the present application provide a cloud computing-based funds flow monitoring method and system, thereby solving the problem that the cloud computing funds flow monitoring method in the prior art is highly dependent on the cloud computing platform and related hardware facilities. Once the cloud computing platform fails or is improperly maintained, the funds flow monitoring may be interrupted, resulting in low monitoring accuracy. This enhances the independence of funds flow monitoring and improves the security of funds.

[0009] The embodiment of the present application provides a cloud computing-based capital flow monitoring method, comprising the following steps: acquiring network status data, capital flow data, and cloud computing platform performance data; obtaining a network status evaluation value based on a comprehensive analysis of the network status data, obtaining a cloud computing platform performance evaluation value based on a comprehensive analysis of the cloud computing platform performance data, obtaining a capital anomaly evaluation value of each account based on a comprehensive analysis of the capital flow data, and performing adjustment feedback based on the capital anomaly evaluation value of each account, obtaining a cloud computing platform status evaluation value based on a comprehensive analysis of the network status evaluation value, the cloud computing platform performance evaluation value, and the capital anomaly evaluation value of each account; and performing evaluation feedback based on the cloud computing platform status evaluation value.

[0010] Furthermore, the step of obtaining a network status evaluation value based on a comprehensive analysis of the network status data includes: the network status data includes network bandwidth, network delay and packet loss rate; obtaining critical network bandwidth, critical network delay and critical packet loss rate from a funds monitoring database; and obtaining a network status evaluation value through a comprehensive analysis.

[0011] Furthermore, the step of obtaining a cloud computing platform performance evaluation value based on a comprehensive analysis of cloud computing platform performance data includes: the cloud computing platform performance data includes system response time and utilization rate of each process; obtaining the critical system response time, reference to utilization rate of each process and allowable deviation of utilization rate of each process from a funds monitoring database; and obtaining a cloud computing platform performance evaluation value through comprehensive analysis.

[0012] Furthermore, the step of obtaining an abnormal fund assessment value for each account based on a comprehensive analysis of fund flow data includes: the fund flow data includes fund flow velocity, transaction volume and net fund inflow; obtaining a reference fund flow velocity, an allowable deviation fund flow velocity, a reference transaction volume, an allowable deviation transaction volume, a reference net fund inflow and an allowable deviation net fund inflow from a fund monitoring database; and obtaining an abnormal fund assessment value for each account through a comprehensive analysis.

[0013] Furthermore, the step of adjusting feedback according to the abnormal funds assessment value of each account includes: obtaining the abnormal funds assessment threshold from the funds monitoring database; comparing the abnormal funds assessment value of each account with the abnormal funds assessment threshold; if the abnormal funds assessment value of an account is greater than or equal to the abnormal funds assessment threshold, the fund flow of the account is assessed as abnormal, and the fund flow of the account is terminated, and the abnormal area is further monitored; if the abnormal funds assessment value of an account is less than the abnormal funds assessment threshold, the fund flow of the account is assessed as normal, and no additional operations are performed.

[0014] Furthermore, the step of obtaining a cloud computing platform status evaluation value through comprehensive analysis based on the network status evaluation value, the cloud computing platform performance evaluation value and the fund abnormality evaluation value of each account includes: obtaining a critical network status evaluation value, a critical cloud computing platform performance evaluation value and a critical fund abnormality evaluation value from a fund monitoring database; and obtaining a cloud computing platform status evaluation value through comprehensive analysis.

[0015] Furthermore, the cloud computing platform status evaluation value is obtained as follows:

[0016]

[0017] In the formula, ζS represents the cloud computing platform status evaluation value, β 4 represents the cloud computing platform status assessment impact factor corresponding to the network status, β 5 represents the cloud computing platform status evaluation impact factor corresponding to the cloud computing platform performance, β 6 The cloud computing platform status assessment impact factor corresponding to the abnormal fund assessment value of each account, ζN 1 represents the network status evaluation value, ζN 0 represents the critical network status evaluation value, ζP 1 represents the performance evaluation value of the cloud computing platform, ζP 0 represents the critical cloud computing platform performance evaluation value, ζC 1j represents the abnormal evaluation value of funds of the jth account, ζC 0 represents the critical funds abnormality assessment value, e is a natural constant, where j is an account parameter, j=1,2,3,...,M, M is the number of accounts.

[0018] Furthermore, the step of providing evaluation feedback based on the cloud computing platform status evaluation value includes: obtaining the cloud computing platform status evaluation threshold from the funds monitoring database; comparing the cloud computing platform status evaluation value with the cloud computing platform status evaluation threshold; if the cloud computing platform status evaluation value is greater than or equal to the cloud computing platform status evaluation threshold, no additional operation is performed; if the cloud computing platform status evaluation value is less than the cloud computing platform status evaluation threshold, providing operation feedback based on the cloud computing platform status evaluation value.

[0019] Furthermore, the step of providing operation feedback based on the cloud computing platform status evaluation value includes: subtracting the cloud computing platform status evaluation threshold from the cloud computing platform status evaluation value, and marking the difference result as the cloud computing platform status evaluation difference; obtaining the current cloud computing platform status abnormality level based on the status abnormality level corresponding to the cloud computing platform status evaluation difference and the cloud computing platform status evaluation difference preset in the funds monitoring database, and providing evaluation feedback on the cloud computing platform and funds situation based on the current cloud computing platform status abnormality level.

[0020] The embodiment of the present application provides a cloud computing-based capital flow monitoring system, which is characterized in that it includes a data acquisition module, a data processing module, an evaluation feedback module and a capital monitoring database; wherein the data acquisition module is used to acquire network status data, capital flow data and cloud computing platform performance data; the data processing module is used to obtain a network status evaluation value based on a comprehensive analysis of the network status data, obtain a cloud computing platform performance evaluation value based on a comprehensive analysis of the cloud computing platform performance data, obtain a capital anomaly evaluation value of each account based on a comprehensive analysis of the capital flow data, and obtain a cloud computing platform status evaluation value based on a comprehensive analysis of the network status evaluation value, the cloud computing platform performance evaluation value and the capital anomaly evaluation value of each account; the evaluation feedback module is used to perform adjustment feedback based on the capital anomaly evaluation value of each account, and perform evaluation feedback based on the cloud computing platform status evaluation value.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0022] 1. The present invention provides a cloud computing-based funds flow monitoring method and system, thereby comprehensively grasping the key information of the cloud computing platform operation, including network status, funds flow status and cloud computing platform performance, thereby realizing accurate monitoring of the platform status and improving the accuracy of the platform's detection of funds flow.

[0023] 2. The present invention obtains a network status evaluation value by comprehensive analysis based on network status data, thereby being able to accurately determine the stability and efficiency of the network connection, thereby achieving optimization suggestions and fault warnings for the network environment.

[0024] 3. The present invention obtains the abnormal fund assessment value of each account through comprehensive analysis based on the fund flow data, and adjusts and feedbacks according to the abnormal fund assessment value of each account, so as to timely discover and deal with abnormal behavior in the fund flow, thereby achieving effective protection of fund security and risk prevention. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flow chart of a cloud computing-based funds flow monitoring method provided in an embodiment of the present application.

[0026] Figure 2 A graph showing changes in the cloud computing platform status assessment value of the cloud computing-based funds flow detection method provided in an embodiment of the present application.

[0027] Figure 3 A schematic diagram of the structure of a cloud computing-based funds flow monitoring system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The embodiments of the present application provide a cloud computing-based fund flow monitoring method and system, which solves the problem that the cloud computing fund flow monitoring method in the prior art is highly dependent on the cloud computing platform and related hardware facilities. Once the cloud computing platform fails or is improperly maintained, the fund flow monitoring may be interrupted, resulting in low monitoring accuracy. The network status evaluation value is obtained by comprehensive analysis of network status data, the cloud computing platform performance evaluation value is obtained by comprehensive analysis of cloud computing platform performance data, the fund abnormality evaluation value of each account is obtained by comprehensive analysis of fund flow data, and adjustment feedback is performed based on the fund abnormality evaluation value of each account. The cloud computing platform status evaluation value is obtained by comprehensive analysis based on the network status evaluation value, the cloud computing platform performance evaluation value and the fund abnormality evaluation value of each account; evaluation feedback is performed based on the cloud computing platform status evaluation value, thereby enhancing the independence of fund flow monitoring and improving the security of funds.

[0029] The technical solution in the embodiment of the present application is to solve the problem that the above-mentioned cloud computing fund flow monitoring method is highly dependent on the cloud computing platform and related hardware facilities. Once the cloud computing platform fails or is improperly maintained, the fund flow monitoring may be interrupted, resulting in low monitoring accuracy. The overall idea is as follows:

[0030] By acquiring network status data, capital flow data and cloud computing platform performance data; obtaining a network status evaluation value based on a comprehensive analysis of the network status data, obtaining a cloud computing platform performance evaluation value based on a comprehensive analysis of the cloud computing platform performance data, obtaining an abnormal capital evaluation value of each account based on a comprehensive analysis of the capital flow data, and performing adjustment feedback based on the abnormal capital evaluation value of each account, obtaining a cloud computing platform status evaluation value based on a comprehensive analysis of the network status evaluation value, the cloud computing platform performance evaluation value and the abnormal capital evaluation value of each account; performing evaluation feedback based on the cloud computing platform status evaluation value, thereby achieving real-time monitoring and evaluation of the cloud computing platform.

[0031] 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 and specific implementation methods.

[0032] like Figure 1As shown, it is a flow chart of a cloud computing-based funds flow monitoring method provided in an embodiment of the present application, the method comprising the following steps: acquiring network status data, funds flow data and cloud computing platform performance data; obtaining a network status evaluation value based on a comprehensive analysis of the network status data, obtaining a cloud computing platform performance evaluation value based on a comprehensive analysis of the cloud computing platform performance data, obtaining a funds abnormality evaluation value of each account based on a comprehensive analysis of the funds flow data, and performing adjustment feedback based on the funds abnormality evaluation value of each account, obtaining a cloud computing platform status evaluation value based on a comprehensive analysis of the network status evaluation value, the cloud computing platform performance evaluation value and the funds abnormality evaluation value of each account; and performing evaluation feedback based on the cloud computing platform status evaluation value.

[0033] In this embodiment, the comprehensive evaluation value obtained by comprehensive analysis of network status data is used to reflect the overall performance of the current network; the performance evaluation value obtained by comprehensive analysis of cloud computing platform performance data is used to evaluate the operation status of the cloud computing platform; through in-depth analysis of fund flow data, the abnormal fund evaluation value of each account can identify abnormal transaction patterns or potential risks. The cloud computing platform status evaluation value can reflect the overall health of the cloud computing platform, including three aspects: network, performance and fund flow. According to the evaluation value, further optimization measures can be taken to improve the overall performance and security of the cloud computing platform. The cloud computing-based fund flow monitoring method provided in the embodiment of the present application can efficiently integrate a large amount of data of the project units involved in each special transfer payment. When the fund flow is abnormal or illegal, the system can issue an early warning in time to remind the relevant departments to intervene and deal with it. And meeting the real-time monitoring and early warning functions can timely discover and correct illegal behaviors, ensure the safety and compliance of funds; and also realize the full transparency of the fund flow of special transfer payments, and enhance the trust and satisfaction of users. Promote information sharing among various project units, understand the fund flow in real time, and strengthen communication and collaboration.

[0034] In addition, the funds monitoring database is used to store data related to the cloud computing-based funds flow monitoring method, including: critical network bandwidth, critical network delay, network status assessment influencing factor corresponding to network bandwidth, critical system response time, reference to each process utilization, allowable deviation of each process utilization, funds abnormality assessment threshold, etc. The data in the funds monitoring database can be obtained through the internal systems of financial institutions, such as the bank's financial system, business system, credit system, etc., or through financial regulatory agencies such as the State Administration of Financial Supervision and Administration, China Securities Regulatory Commission, etc.

[0035] Furthermore, the step of obtaining a network status evaluation value based on a comprehensive analysis of the network status data includes: the network status data includes network bandwidth, network delay and packet loss rate; obtaining critical network bandwidth, critical network delay and critical packet loss rate from a funds monitoring database; and obtaining a network status evaluation value through a comprehensive analysis.

[0036] The network status evaluation value is obtained in the following manner:

[0037]

[0038] In the formula, ζN represents the network status evaluation value, α 1 represents the network status assessment impact factor corresponding to the network bandwidth, α 2 Represents the network status evaluation impact factor corresponding to network delay, α 3 represents the network status assessment impact factor corresponding to the packet loss rate, B 1 Indicates network bandwidth, B 0 represents the critical network bandwidth, D 1 Indicates network delay, D 0 represents the critical network delay, L 1 Indicates the packet loss rate, L 0 Indicates the critical packet loss rate.

[0039] α 1 , α 2 and α 3 The network status assessment influencing factors corresponding to the network bandwidth, network delay and packet loss rate preset in the fund monitoring database respectively represent the numerical values ​​of the influence degree of the network bandwidth, network delay and packet loss rate on the network status assessment value respectively, and can be directly obtained from the fund monitoring database when used. For example, the network bandwidth and the network status assessment influencing factors corresponding to the network bandwidth preset in the fund monitoring database form a mapping set, and the network status assessment influencing factors corresponding to the network bandwidth are obtained according to the network bandwidth input mapping set; the network delay and the network status assessment influencing factors corresponding to the network delay preset in the fund monitoring database form a mapping set, and the network status assessment influencing factors corresponding to the network delay are obtained according to the network delay input mapping set; the packet loss rate and the network status assessment influencing factors corresponding to the packet loss rate preset in the fund monitoring database form a mapping set, and the network status assessment influencing factors corresponding to the packet loss rate are obtained according to the packet loss rate input mapping set, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the influencing factor in this embodiment is between 0 and 1.

[0040] In this embodiment, the network bandwidth indicates the amount of data that can be transmitted per unit time, which can be measured by a network speed test tool or professional equipment; the network delay indicates the time required for a message to travel from one end of the network to the other end, which can be measured using the ping command or other network speed test tools; the packet loss rate indicates the ratio of the number of data packets lost in the test to the number of data packets sent, which can be calculated by sending a large number of data packets and counting the number of lost data packets. The network bandwidth, network delay and packet loss rate are interrelated. When the network bandwidth is insufficient, it may cause an increase in network delay and packet loss rate. When the network is congested, it may also cause an increase in delay and packet loss rate. The three indicators of network bandwidth, network delay and packet loss rate jointly reflect the health and performance of the network. By comprehensively analyzing these three indicators, the network status evaluation value obtained can accurately reflect the current status of the network and provide strong support for network optimization and improvement.

[0041] Furthermore, the step of obtaining a cloud computing platform performance evaluation value based on a comprehensive analysis of cloud computing platform performance data includes: the cloud computing platform performance data includes system response time and utilization rate of each process; obtaining the critical system response time, reference to utilization rate of each process and allowable deviation of utilization rate of each process from a funds monitoring database; and obtaining a cloud computing platform performance evaluation value through comprehensive analysis.

[0042] The cloud computing platform performance evaluation value is obtained in the following manner:

[0043]

[0044] In the formula, ζP represents the performance evaluation value of the cloud computing platform, α 4 represents the cloud computing platform performance evaluation impact factor corresponding to the system response time, α 5 represents the cloud computing platform performance evaluation impact factor corresponding to each process utilization, T 1 Represents the system response time, T 0 represents the critical system response time, P 1i represents the utilization rate of the i-th process, P 0i represents the utilization rate of the i-th reference process, P 2i It represents the utilization rate of the i-th allowed deviation process, i represents the process number, i=1,2,3,...,N, N is the number of processes.

[0045] α 4 and α 5The cloud computing platform performance evaluation impact factors corresponding to the system response time and each process utilization rate preset in the fund monitoring database respectively represent the numerical values ​​of the degree of influence of the system response time and each process utilization rate on the cloud computing platform performance evaluation value, and can be directly obtained from the fund monitoring database when used. For example, the system response time and the cloud computing platform performance evaluation impact factors corresponding to the system response time preset in the fund monitoring database form a mapping set, and the cloud computing platform performance evaluation impact factors corresponding to the system response time are obtained by inputting the mapping set according to the system response time; the cloud computing platform performance evaluation impact factors corresponding to the cloud computing platform utilization rates preset in the fund monitoring database form a mapping set, and the cloud computing platform performance evaluation impact factors corresponding to the process utilization rates are obtained by inputting the mapping set according to the process utilization rates, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the impact factor in this embodiment is between 0 and 1.

[0046] In this embodiment, the system response time refers to the time required from the user sending a request to the system returning the result, which can be measured by professional performance testing tools (such as JMeter, LoadRunner, etc.); each process utilization refers to the occupation of system resources by each process on the cloud computing platform, including CPU utilization, memory utilization, disk utilization and I / O utilization, which can be measured by monitoring tools provided by the operating system (such as top and htop commands of Linux, task manager of Windows, etc.) or professional resource monitoring tools (such as Zabbix, Nagi os, etc.). When the utilization of a process is too low, it means that the process is not fully utilizing the system resources, the system resources are in a relatively idle state or there is a problem with the system configuration; when the utilization of a process is too high, it means that the current task load of the system is heavy, and high utilization is likely to cause slow system response, thereby affecting system performance. Therefore, when the process utilization is too low or too high, the performance evaluation value of the cloud computing platform will be reduced. The system response time and the utilization of each process are interrelated. When the system resource utilization is high, it may lead to an increase in system response time because the system needs to process more requests and tasks; when the system response time is long, it may also mean that the system resource utilization is high or there are certain performance bottlenecks. The cloud computing platform performance evaluation value obtained by comprehensively analyzing the system response time and the utilization of each process can accurately reflect the current performance status of the cloud computing platform, further determine whether the cloud computing platform meets business needs, and take corresponding measures to optimize and improve it.

[0047] Furthermore, the step of obtaining an abnormal fund assessment value for each account based on a comprehensive analysis of fund flow data includes: the fund flow data includes fund flow velocity, transaction volume and net fund inflow; obtaining a reference fund flow velocity, an allowable deviation fund flow velocity, a reference transaction volume, an allowable deviation transaction volume, a reference net fund inflow and an allowable deviation net fund inflow from a fund monitoring database; and obtaining an abnormal fund assessment value for each account through a comprehensive analysis.

[0048] The abnormal fund assessment value of each account is obtained as follows:

[0049]

[0050] In the formula, ζC j represents the abnormal evaluation value of funds of the jth account, β 1 Indicates the abnormal capital assessment weight factor corresponding to the capital flow velocity, β 2 It represents the abnormal capital assessment weight factor corresponding to the trading volume, β 3 V represents the abnormal capital assessment weight factor corresponding to the net capital inflow. 1j represents the capital flow velocity of the jth account, V 0 Indicates the reference capital flow velocity, V 2 Indicates the allowable deviation of capital flow velocity, C 1j represents the transaction volume of the jth account, C 0 Indicates reference volume, C 2 Indicates the allowable deviation volume, F 1j represents the net inflow of funds in the jth account, F 0 Indicates the net inflow of reference funds, F 2 Indicates that deviation net inflow of funds is allowed.

[0051] β 1 , β 2 and β 3The fund abnormality assessment impact factors corresponding to the fund flow speed, trading volume and net fund inflow preset in the fund monitoring database respectively represent the numerical values ​​of the influence degree of the fund flow speed, trading volume and net fund inflow on the fund abnormality assessment value of each account respectively, and can be directly obtained from the fund monitoring database when used. For example, the fund flow speed and the fund abnormality assessment impact factors corresponding to the fund flow speed preset in the fund monitoring database form a mapping set, and the fund abnormality assessment impact factors corresponding to the fund flow speed are obtained according to the fund flow speed input mapping set; the trading volume and the fund abnormality assessment impact factors corresponding to the trading volume preset in the fund monitoring database form a mapping set, and the fund abnormality assessment impact factors corresponding to the trading volume are obtained according to the trading volume input mapping set; the net fund inflow and the fund abnormality assessment impact factors corresponding to the net fund inflow preset in the fund monitoring database form a mapping set, and the fund abnormality assessment impact factors corresponding to the net fund inflow are obtained according to the net fund inflow input mapping set, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the impact factor in this embodiment is between 0 and 1.

[0052] In this embodiment, the capital flow rate refers to the speed at which the account funds flow within a unit time, which can be obtained by calculating the ratio of the amount of inflow and outflow of account funds within a unit time to the unit time. The unit time can be 1 second, 1 minute or 1 hour. The method for obtaining the capital flow rate is: Where V 1j represents the capital flow velocity of the jth account, M 1j It represents the inflow and outflow amount of the jth account in a unit time, where the inflow and outflow amount represents the sum of the absolute value of the inflow amount and the absolute value of the outflow amount, and T represents the unit time. The trading volume refers to the frequency of account fund flow in a unit time, which can be obtained by calculating the ratio of the number of inflow and outflow of account funds in a unit time to the unit time. The unit time can be 1 second, 1 minute or 1 hour. The trading volume is obtained as follows: In the formula, C 1j represents the transaction volume of the jth account, N 1jrepresents the transaction volume of the jth account in a unit time, and T represents the unit time. Net capital inflow refers to the total amount of funds flowing into the account minus the total amount of funds flowing out in a unit time. It can be obtained by monitoring the trading activities of the account and counting the difference between the buy and sell amounts. The velocity of capital flow and the trading volume are usually positively correlated. When the velocity of capital flow increases, the trading volume of the account tends to increase, because more funds flow in the account, which promotes the active trading; net capital inflow is also closely related to the trading volume. When the net capital inflow is high, it may be caused by high trading volume, and when the net capital outflow is low, the trading volume may decrease. By comprehensively analyzing the three indicators of capital flow velocity, trading volume and net capital inflow, the abnormal capital assessment value of each account can accurately reflect the capital flow status, trading activity and market dynamics and trends of the market.

[0053] Furthermore, the step of adjusting feedback according to the abnormal funds assessment value of each account includes: obtaining the abnormal funds assessment threshold from the funds monitoring database; comparing the abnormal funds assessment value of each account with the abnormal funds assessment threshold; if the abnormal funds assessment value of an account is greater than or equal to the abnormal funds assessment threshold, the fund flow of the account is assessed as abnormal, and the fund flow of the account is terminated, and the abnormal area is further monitored; if the abnormal funds assessment value of an account is less than the abnormal funds assessment threshold, the fund flow of the account is assessed as normal, and no additional operations are performed.

[0054] In this embodiment, the abnormal fund assessment threshold refers to the critical value used to determine whether the fund flow is normal during the fund monitoring process. By automatically comparing the abnormal fund assessment value of each account with the abnormal fund assessment threshold, real-time monitoring of fund flow can be achieved, improving the efficiency and accuracy of monitoring. Once the abnormal fund assessment value of each account reaches or exceeds the threshold, the system can respond quickly, terminate the abnormal fund flow, and initiate further monitoring and investigation to prevent the spread of risks.

[0055] Furthermore, the step of obtaining a cloud computing platform status evaluation value through comprehensive analysis based on the network status evaluation value, the cloud computing platform performance evaluation value and the fund abnormality evaluation value of each account includes: obtaining a critical network status evaluation value, a critical cloud computing platform performance evaluation value and a critical fund abnormality evaluation value from a fund monitoring database; and obtaining a cloud computing platform status evaluation value through comprehensive analysis.

[0056] In this embodiment, there is a close correlation between the network status evaluation value, the cloud computing platform performance evaluation value and the fund abnormality evaluation value of each account, which together reflect the overall operation status of the cloud computing platform. The network status is one of the foundations for the operation of the cloud computing platform. A good network status can ensure the rapid transmission of data and the smooth provision of services, thereby improving the performance of the cloud computing platform. Therefore, the larger the network status evaluation value, the larger the cloud computing platform status evaluation value; the performance of the cloud computing platform directly affects its service quality. A high-performance cloud computing platform can provide more stable and efficient services. Therefore, the larger the cloud computing platform performance evaluation value, the larger the cloud computing platform status evaluation value; the instability of the network status may cause data transmission errors, service interruptions and other problems, thereby affecting the normal operation and business income of the cloud computing platform. When the fund abnormality evaluation value of each account is larger, the cloud computing platform status evaluation value is smaller. By analyzing the change trend and abnormal points of the cloud computing platform status evaluation value, the root cause of the problem can be located, and corresponding measures can be taken to repair and optimize it.

[0057] Furthermore, the cloud computing platform status evaluation value is obtained as follows:

[0058]

[0059] In the formula, ζS represents the cloud computing platform status evaluation value, β 4 represents the cloud computing platform status assessment impact factor corresponding to the network status, β 5 represents the cloud computing platform status evaluation impact factor corresponding to the cloud computing platform performance, β 6 The cloud computing platform status assessment impact factor corresponding to the abnormal fund assessment value of each account, ζN 1 represents the network status evaluation value, ζN 0 represents the critical network status evaluation value, ζP 1 represents the performance evaluation value of the cloud computing platform, ζP 0 represents the critical cloud computing platform performance evaluation value, ζC 1j represents the abnormal evaluation value of funds of the jth account, ζC 0 represents the critical funds abnormality assessment value, e is a natural constant, where j is an account parameter, j=1,2,3,...,M, M is the number of accounts.

[0060] The cloud computing platform status assessment impact factor corresponding to the network status is set to 0.2, the cloud computing platform performance is set to 0.4, the cloud computing platform performance is set to 0.4, the network status assessment value is set to 1.5, the critical network status assessment value is set to 1.4, the critical cloud computing platform performance assessment value is set to 1.6, the number of accounts is set to 1, the fund anomaly assessment value of the jth account is set to 1.2, and the critical fund anomaly assessment value is set to 1.4. When the cloud computing platform performance assessment value keeps changing, the cloud computing platform status assessment value is calculated. As shown in Table 1, the cloud computing platform status assessment value data table of the fund flow detection method based on cloud computing.

[0061] Table 1 Data table of cloud computing platform status evaluation value based on cloud computing capital flow detection method

[0062] serial number ζP ζS 1 1.5 0.782 2 1.55 0.797 3 1.6 0.812 4 1.65 0.827 5 1.7 0.842

[0063] like Figure 2 As shown in Table 1 and Figure 2 It can be seen that when the cloud computing platform status assessment influence factor corresponding to the network status, the cloud computing platform status assessment influence factor corresponding to the cloud computing platform performance, the cloud computing platform status assessment influence factor corresponding to the cloud computing platform performance, the network status assessment value, the critical network status assessment value, the critical cloud computing platform performance assessment value, the fund abnormality assessment value of each account, and the critical fund abnormality assessment value remain unchanged, the cloud computing platform performance assessment value increases, the cloud computing platform status assessment value will also increase.

[0064] In this embodiment, β 4 , β 5 and β 6The cloud computing platform status assessment impact factors corresponding to the network status, cloud computing platform performance and abnormal fund assessment values ​​of each account preset in the fund monitoring database respectively represent the numerical values ​​of the influence degree of the network status, cloud computing platform performance and fund situation on the cloud computing platform status assessment value respectively, and can be directly obtained from the fund monitoring database when used. For example, the network status assessment value and the cloud computing platform status assessment impact factors corresponding to the network status assessment value preset in the fund monitoring database form a mapping set, and the cloud computing platform status assessment impact factors corresponding to the network status assessment value are obtained by inputting the mapping set according to the network status assessment value; the abnormal fund assessment value of each account and the cloud computing platform status assessment impact factors corresponding to the abnormal fund assessment value of each account preset in the fund monitoring database form a mapping set, and the cloud computing platform status assessment impact factors corresponding to the abnormal fund assessment value of each account are obtained by inputting the mapping set according to the abnormal fund assessment value of each account; the cloud computing platform performance assessment value and the cloud computing platform status assessment impact factors corresponding to the cloud computing platform performance assessment value preset in the fund monitoring database form a mapping set, and the cloud computing platform status assessment impact factors corresponding to the cloud computing platform performance assessment value are obtained by inputting the mapping set according to the cloud computing platform performance assessment value, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the impact factor in this embodiment is between 0 and 1.

[0065] Furthermore, the step of providing evaluation feedback based on the cloud computing platform status evaluation value includes: obtaining the cloud computing platform status evaluation threshold from the funds monitoring database; comparing the cloud computing platform status evaluation value with the cloud computing platform status evaluation threshold; if the cloud computing platform status evaluation value is greater than or equal to the cloud computing platform status evaluation threshold, no additional operation is performed; if the cloud computing platform status evaluation value is less than the cloud computing platform status evaluation threshold, providing operation feedback based on the cloud computing platform status evaluation value.

[0066] In this embodiment, the cloud computing platform status evaluation threshold refers to the critical value used to determine whether the platform status is normal during the cloud computing platform status monitoring process. The cloud computing platform status evaluation value is compared with the evaluation threshold to determine whether the platform status is normal. If the evaluation value is greater than or equal to the evaluation threshold, it indicates that there may be a problem with the platform status and further analysis and processing is required; if the evaluation value is less than the evaluation threshold, it indicates that the platform status is normal and no additional operation is required. Through continuous monitoring and feedback of the platform status, potential security vulnerabilities and performance bottlenecks can be discovered and repaired in a timely manner, thereby improving the stability and reliability of the platform.

[0067] Furthermore, the step of providing operation feedback based on the cloud computing platform status evaluation value includes: subtracting the cloud computing platform status evaluation threshold from the cloud computing platform status evaluation value, and marking the difference result as the cloud computing platform status evaluation difference; obtaining the current cloud computing platform status abnormality level based on the status abnormality level corresponding to the cloud computing platform status evaluation difference and the cloud computing platform status evaluation difference preset in the funds monitoring database, and providing evaluation feedback on the cloud computing platform and funds situation based on the current cloud computing platform status abnormality level.

[0068] In this embodiment, by calculating the difference in the status evaluation of the cloud computing platform, the gap between the platform status and the ideal status can be accurately quantified, so that the staff can understand the platform status more accurately. According to the preset status abnormality level, the operation and maintenance personnel can quickly identify the problem level of the current platform, so as to make more timely adjustments. Among them, the status abnormality level includes slight abnormality, moderate abnormality and severe abnormality. When the cloud computing platform is in a slight abnormality, it may indicate that there are some subtle problems or performance bottlenecks in the platform. Some fine-tuning measures can be taken, such as optimizing resource allocation, adjusting system parameters, etc., to improve the platform performance; when the cloud computing platform is in a moderate abnormality, it may indicate that the platform has obvious performance problems or safety hazards, and it is necessary to analyze the cause of the problem more deeply and take corresponding measures to solve it, such as upgrading hardware equipment, optimizing software architecture, strengthening security protection, etc.; when the cloud computing platform is in a serious abnormality, it may indicate that the platform has serious performance problems or faces major safety hazards, and it is necessary to take immediate action, such as emergency shutdown and investigation, launching emergency plans, etc., to ensure the safe and stable operation of the platform. For example, the current cloud computing platform status assessment value is 0.75, and the cloud computing platform status assessment threshold is 0.6, so the current cloud computing platform status assessment difference is 0.15, and the cloud computing platform status assessment difference range corresponding to the slight abnormality level preset in the funds monitoring database is (0, 0.05), and the cloud computing platform status assessment difference range corresponding to the moderate abnormality level is [0.05, 0.1], and the cloud computing platform status assessment difference range corresponding to the severe abnormality level is greater than 0.1, so the current cloud computing platform status abnormality level is severe abnormality.

[0069] like Figure 3 As shown, it is a structural diagram of the cloud computing-based funds flow monitoring system provided in the embodiment of the present application. The cloud computing-based funds flow monitoring system provided in the embodiment of the present application includes: a data acquisition module, a data processing module, an evaluation feedback module and a funds monitoring database.

[0070] In summary, the embodiments of the present application obtain a network status evaluation value by comprehensive analysis based on network status data, obtain a cloud computing platform performance evaluation value by comprehensive analysis based on cloud computing platform performance data, obtain a fund anomaly evaluation value of each account by comprehensive analysis based on fund flow data, and obtain a cloud computing platform status evaluation value by comprehensive analysis based on the network status evaluation value, the cloud computing platform performance evaluation value and the fund anomaly evaluation value of each account; adjust feedback according to the fund anomaly evaluation value of each account, and perform evaluation feedback according to the cloud computing platform status evaluation value, thereby solving the problem that the cloud computing fund flow monitoring method in the prior art is highly dependent on the cloud computing platform and related hardware facilities. Once the cloud computing platform fails or is improperly maintained, the fund flow monitoring may be interrupted, resulting in low monitoring accuracy, thereby enhancing the independence of fund flow monitoring and improving the guarantee of fund security.

[0071] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may 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.

[0072] The present invention is described by flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0073] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0074] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0075] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0076] 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 equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for monitoring capital flow based on cloud computing, characterized in that: The following steps are involved: Obtain network status data, capital flow data, and cloud computing platform performance data; Obtain a network status evaluation value based on a comprehensive analysis of network status data, obtain a cloud computing platform performance evaluation value based on a comprehensive analysis of cloud computing platform performance data, obtain a fund abnormality evaluation value of each account based on a comprehensive analysis of fund flow data, and perform adjustment feedback based on the fund abnormality evaluation value of each account, and obtain a cloud computing platform status evaluation value based on a comprehensive analysis of the network status evaluation value, the cloud computing platform performance evaluation value, and the fund abnormality evaluation value of each account; Provide evaluation feedback based on the cloud computing platform status evaluation value.

2. The cloud computing-based fund flow monitoring method according to claim 1, characterized in that: The step of obtaining a network status evaluation value based on comprehensive analysis of the network status data comprises: The network status data includes network bandwidth, network delay and packet loss rate; Obtain critical network bandwidth, critical network delay and critical packet loss rate from the fund monitoring database; Comprehensive analysis is performed to obtain the network status assessment value.

3. The cloud computing-based fund flow monitoring method according to claim 1, characterized in that: The step of obtaining a cloud computing platform performance evaluation value based on comprehensive analysis of cloud computing platform performance data includes: The cloud computing platform performance data includes system response time and utilization rate of each process; Obtain critical system response time, reference utilization of each process and allowable deviation utilization of each process from the fund monitoring database; Comprehensive analysis is performed to obtain the performance evaluation value of the cloud computing platform.

4. The cloud computing-based fund flow monitoring method according to claim 1, characterized in that: The step of obtaining the abnormal fund evaluation value of each account based on comprehensive analysis of fund flow data includes: The fund flow data include fund flow velocity, transaction volume and net fund inflow; Obtain reference capital flow velocity, allowable deviation capital flow velocity, reference transaction volume, allowable deviation transaction volume, reference capital net inflow and allowable deviation capital net inflow from the capital monitoring database; Comprehensive analysis is performed to obtain the abnormal fund assessment value of each account.

5. The cloud computing-based fund flow monitoring method according to claim 1, characterized in that: The step of providing adjustment feedback according to the abnormal evaluation value of funds in each account includes: Obtaining the abnormal fund assessment threshold from the fund monitoring database; The abnormal funds assessment value of each account is compared with the abnormal funds assessment threshold. If the abnormal funds assessment value of an account is greater than or equal to the abnormal funds assessment threshold, the fund flow of the account is assessed as abnormal, and the fund flow of the account is terminated. The abnormal area is further monitored. If the abnormal funds assessment value of an account is less than the abnormal funds assessment threshold, the fund flow of the account is assessed as normal and no additional operations are performed.

6. The cloud computing-based fund flow monitoring method according to claim 1, characterized in that: The step of obtaining the cloud computing platform status evaluation value by comprehensive analysis based on the network status evaluation value, the cloud computing platform performance evaluation value and the fund abnormality evaluation value of each account comprises: Obtaining a critical network status assessment value, a critical cloud computing platform performance assessment value, and a critical fund anomaly assessment value from a fund monitoring database; Comprehensive analysis is performed to obtain the cloud computing platform status assessment value.

7. The cloud computing-based fund flow monitoring method according to claim 6, characterized in that: The cloud computing platform status evaluation value is obtained in the following manner: In the formula, ζS represents the cloud computing platform status evaluation value, β4 represents the cloud computing platform status evaluation influencing factor corresponding to the network status, β5 represents the cloud computing platform status evaluation influencing factor corresponding to the cloud computing platform performance, β6 represents the cloud computing platform status evaluation influencing factor corresponding to the abnormal fund evaluation value of each account, ζN1 represents the network status evaluation value, ζN0 represents the critical network status evaluation value, ζP1 represents the cloud computing platform performance evaluation value, ζP0 represents the critical cloud computing platform performance evaluation value, ζC 1j represents the abnormal fund assessment value of the j-th account, ζC0 represents the critical abnormal fund assessment value, e is a natural constant, where j is the account parameter, j=1,2,3,...,M, and M is the number of accounts.

8. The cloud computing-based fund flow monitoring method according to claim 1, characterized in that: The step of providing evaluation feedback according to the cloud computing platform status evaluation value comprises: Obtaining a cloud computing platform status assessment threshold from a fund monitoring database; The cloud computing platform status assessment value is compared with the cloud computing platform status assessment threshold. If the cloud computing platform status assessment value is greater than or equal to the cloud computing platform status assessment threshold, no additional operation is performed. If the cloud computing platform status assessment value is less than the cloud computing platform status assessment threshold, operation feedback is performed according to the cloud computing platform status assessment value.

9. The cloud computing-based fund flow monitoring method according to claim 8, characterized in that: The step of providing operation feedback according to the cloud computing platform status evaluation value comprises: Subtract the cloud computing platform status assessment threshold from the cloud computing platform status assessment value, and mark the difference result as the cloud computing platform status assessment difference; According to the status anomaly level corresponding to the cloud computing platform status assessment difference and the cloud computing platform status assessment difference preset in the funds monitoring database, the current cloud computing platform status anomaly level is obtained, and the cloud computing platform and funds situation are evaluated and fed back according to the current cloud computing platform status anomaly level.

10. A cloud computing-based funds flow monitoring system, using the cloud computing-based funds flow monitoring method according to any one of claims 1 to 9, characterized in that: It includes data acquisition module, data processing module, evaluation feedback module and fund monitoring database; Wherein, the data acquisition module is used to acquire network status data, capital flow data and cloud computing platform performance data; The data processing module is used to obtain a network status evaluation value based on a comprehensive analysis of the network status data, obtain a cloud computing platform performance evaluation value based on a comprehensive analysis of the cloud computing platform performance data, obtain a fund anomaly evaluation value of each account based on a comprehensive analysis of the fund flow data, and obtain a cloud computing platform status evaluation value based on a comprehensive analysis of the network status evaluation value, the cloud computing platform performance evaluation value, and the fund anomaly evaluation value of each account; The evaluation feedback module is used to provide adjustment feedback based on the abnormal fund evaluation value of each account and to provide evaluation feedback based on the cloud computing platform status evaluation value.

Images