Problem analysis method and device, computer equipment, storage medium and product

Abstract

The invention relates to the technical field of data analysis, in particular to a problem analysis method and device, computer equipment, a storage medium and a product. The method comprises the steps of determining fund use data corresponding to a fund flow direction; determining at least one fund associated party having an association relationship with the project responsible party corresponding to the fund flow direction; and performing problem analysis on the fund flow direction according to the fund use data and the fund associated parties to obtain a problem detection result of the fund flow direction. According to the method, the analysis accuracy of problem analysis on the fund flow direction is improved, comprehensive abnormal problem mining for the fund flow direction is realized, and supervision for the abnormal problem of the fund flow direction is effectively realized.

Description

Technical Field

[0001] This application relates to the field of data analysis technology, and in particular to a problem analysis method, apparatus, computer equipment, storage medium, and product. Background Technology

[0002] With the significant increase in the scale of expenditures by universities and research institutions (such as research funding), their supervision has become a key area of ​​auditing due to the wide range of personnel involved, high frequency of disbursements, and complex related matters. Currently, relevant data is usually scattered across multiple information systems such as financial management, research management, human resources management, salary management, and contract management, resulting in problems such as inconsistent data standards and complex correlation logic. This makes it difficult to effectively verify non-compliant situations such as disbursement of funds to related parties (labor fees) or payment to related companies (cooperation funds) using existing technologies. Summary of the Invention

[0003] Therefore, it is necessary to provide a problem analysis method, apparatus, computer equipment, storage medium, and product that can effectively verify the flow of funds for auditing related interests in response to the above-mentioned technical problems.

[0004] Firstly, this application provides a problem analysis method. The method includes:

[0005] Determine the fund usage data corresponding to the fund flow;

[0006] Identify at least one funding-related party that has an association with the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members;

[0007] Based on the fund usage data and the respective fund-related parties, a problem analysis is performed on the fund flow to obtain the problem detection results for the fund flow.

[0008] In one embodiment, the step of performing a problem analysis on the fund flow based on the fund usage data and each of the fund-related parties to obtain a problem detection result for the fund flow includes:

[0009] Identify the recipients of funds included in the fund usage data;

[0010] Based on the fund recipients and related parties, a problem analysis is performed on the fund flow to obtain the problem detection results for the fund flow.

[0011] In one embodiment, the step of performing a problem analysis on the fund flow based on the fund recipient and each of the fund-related parties to obtain a problem detection result for the fund flow includes:

[0012] If the recipient of the funds belongs to the users associated with the funds among the fund-related parties, then the problem detection result is determined to be a fund problem included in the fund flow.

[0013] If the recipient of the funds belongs to a fund-related enterprise included in the fund-related parties, then the problem detection result is determined to be a fund problem included in the fund flow.

[0014] In one embodiment, the step of performing a problem analysis on the fund flow based on the fund recipient and each of the fund-related parties to obtain a problem detection result for the fund flow includes:

[0015] If the recipient of the funds is a user and the recipient of the funds is not one of the fund-related parties, the fund flow is analyzed based on the fund usage data to determine the amount of funds and the frequency of disbursement, and a first analysis result is obtained.

[0016] Based on the fund usage data, the fund flow is analyzed by the region of fund disbursement to obtain a second analysis result;

[0017] Based on the fund usage data, the fund flow is analyzed by the age of the fund recipients to obtain a third analysis result;

[0018] Based on the first analysis result, the second analysis result, and the third analysis result, the problem detection result of the fund flow is determined.

[0019] In one embodiment, the step of performing a problem analysis on the fund flow based on the fund recipient and each of the fund-related parties to obtain a problem detection result for the fund flow includes:

[0020] If the fund recipient is an enterprise and the fund recipient is not one of the fund-related parties, determine the enterprise-related users corresponding to the fund recipient;

[0021] Based on the problem analysis of the fund flow by relevant users of the enterprise, the problem detection results of the fund flow are obtained.

[0022] In one embodiment, the step of analyzing the fund flow based on relevant users of the enterprise to obtain the problem detection result of the fund flow includes:

[0023] Based on the correlation between the project manager and the relevant users of the enterprise, a problem analysis of the fund flow is performed to obtain the problem detection results of the fund flow.

[0024] Secondly, this application also provides a problem analysis apparatus. The apparatus includes:

[0025] The first determination module is used to determine the fund usage data corresponding to the fund flow;

[0026] The second determining module is used to determine at least one fund-related party that has an association with the project responsible party corresponding to the fund flow; wherein, the project responsible party includes the project leader and project members;

[0027] The analysis module is used to perform problem analysis on the fund flow based on the fund usage data and each of the fund-related parties, and to obtain the problem detection results of the fund flow.

[0028] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0029] Determine the fund usage data corresponding to the fund flow;

[0030] Identify at least one funding-related party that has an association with the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members;

[0031] Based on the fund usage data and the respective fund-related parties, a problem analysis is performed on the fund flow to obtain the problem detection results for the fund flow.

[0032] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0033] Determine the fund usage data corresponding to the fund flow;

[0034] Identify at least one funding-related party that has an association with the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members;

[0035] Based on the fund usage data and the respective fund-related parties, a problem analysis is performed on the fund flow to obtain the problem detection results for the fund flow.

[0036] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0037] Determine the fund usage data corresponding to the fund flow;

[0038] Identify at least one funding-related party that has an association with the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members;

[0039] Based on the fund usage data and the respective fund-related parties, a problem analysis is performed on the fund flow to obtain the problem detection results for the fund flow.

[0040] The aforementioned problem analysis methods, apparatus, computer equipment, storage media, and products determine the fund usage data corresponding to the fund flow; identify at least one fund-related party with a relationship to the project manager corresponding to the fund flow; wherein, the project manager includes the project leader and project members; and perform problem analysis on the fund flow based on the fund usage data and each fund-related party to obtain the problem detection results of the fund flow. As can be seen from the above, in the process of problem analysis, this application first obtains the fund usage data corresponding to the fund flow and at least one fund-related party with a relationship to the project manager corresponding to the fund flow. This achieves the acquisition of data related to the problem analysis of the fund flow, ensuring the accuracy of subsequent problem analysis of the fund flow, realizing comprehensive anomaly detection of fund flows, and effectively monitoring anomalies in fund flows. Attached Figure Description

[0041] Figure 1 An application environment diagram of a problem analysis method provided in this application embodiment;

[0042] Figure 2 A flowchart illustrating the first problem analysis method provided in this application embodiment;

[0043] Figure 3 A flowchart illustrating the second problem analysis method provided in this application embodiment;

[0044] Figure 4 A flowchart illustrating the third problem analysis method provided in this application embodiment;

[0045] Figure 5 A structural block diagram of a problem analysis device provided in an embodiment of this application;

[0046] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0048] The problem analysis method provided in this application embodiment can be applied to, for example, Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed on the cloud or other network servers. The process involves determining the fund usage data corresponding to the fund flow; identifying at least one fund-related party with a connection to the project responsible party corresponding to the fund flow; where the project responsible party includes the project leader and project members; and performing problem analysis on the fund flow based on the fund usage data and each fund-related party to obtain the problem detection results for the fund flow. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Server 104 can be implemented using a standalone server or a server cluster composed of multiple servers.

[0049] In one embodiment, such as Figure 2 As shown, a problem analysis method is provided, which can be applied to... Figure 1 Taking server 104 as an example, the following steps are included:

[0050] S201, determine the fund usage data corresponding to the fund flow.

[0051] Among them, the data on the use of funds refers to the details of the payment of labor fees generated during the flow of funds; the data on the use of funds may include, but is not limited to: payment order number, payment date, payment department, payment person information (name, ID number (masked), employee number, department), type of labor fee (such as labor remuneration, expert consultation fee), information of the recipient (name, ID number (masked), bank card number (masked), professional title, unit), amount of funds paid, taxable amount, reason for payment, fund information (fund source project number, project name), and financial accounting information (financial voucher number, financial expenditure summary, etc.).

[0052] It should be noted that the system can connect to the corresponding personnel management system, payroll system, financial accounting system, scientific research management system, tax reporting system, etc., to collect and summarize relevant data from each system and obtain the fund usage data corresponding to the fund flow.

[0053] In one embodiment of this application, an ETL (Extract, Transform, Load) tool or API (Application Programming Interface) is used to establish a connection with relevant systems such as the human resources management system, payroll system, and financial accounting system. A "timed incremental synchronization" strategy (such as daily synchronization) is adopted to collect only newly added or changed payment records, thereby collecting fund usage data corresponding to fund flows and ensuring data real-time performance and low system load.

[0054] To further explain, data transmission uses SSL (Secure Sockets Layer, a low-level encryption protocol) encryption to provide technical security. Sensitive fields such as ID card numbers and bank card numbers are anonymized during storage (e.g., retaining the first 3 and last 4 digits), and strict role-based access control ensures that only authorized administrators can access the complete information.

[0055] In another embodiment of this application, the amount of funds disbursed in the fund usage data is linked to the financial data. At the data level, in the voucher entry stage of the financial accounting system, a "labor service fee disbursement number" is added as a mandatory or associative field, or in the payroll system, a "financial voucher number" is added. At the logical level, in the auditing platform, the "disbursement number" is used as the core association key. Through SQL queries or the creation of data views, the "labor service fee disbursement details table" is linked in real time with the "financial voucher table" and "accounting entry table." The output then forms a "six-element basic information database," where each record fully includes: who disbursed (disbursing department / person), what amount of money was disbursed (source / reason of funds), when it was disbursed (disbursement date), where it is reflected (voucher number / entry), who it was disbursed to (fund recipient), and how much was disbursed (amount of funds). This database supports drilling down from any aggregated statistical result to the lowest level of financial vouchers.

[0056] S202, identify at least one related party with a connection to the project responsible for the fund flow.

[0057] The project responsible parties include the project leader and project members.

[0058] In this application, "funding related party" refers to a user or enterprise that has a conflict of interest with the project leader and its project members. In one embodiment of this application, when it is necessary to determine at least one funding related party that has a conflict of interest with the project leader and its project members corresponding to the fund flow, the system can be connected to the human resources system to obtain internal related information such as "family relationship information" and "off-campus part-time job information" of faculty and staff, "same department information" in the organizational structure, and "project member information" in the scientific research management system. Furthermore, under the premise of compliance, external related information such as "senior personnel information" of the project leader and its project members' related enterprises can be collected through enterprise credit information disclosure.

[0059] Furthermore, a graph database can be used to store at least one related party to the project manager and their members whose funding flows correspond to the project's responsible party. Using each faculty member and external funding recipient's unique "person ID" as a node, and "relatives," "colleagues," "project partners," "part-time jobs," and "affiliated company executives" as edges, a visualized network of vested interests can be constructed. During a query, it is possible to quickly identify whether there is a direct or indirect connection between two individuals.

[0060] S203, based on the data on fund usage and the relevant parties involved in the funds, conducts a problem analysis on the flow of funds and obtains the problem detection results of the flow of funds.

[0061] It should be noted that when it is necessary to conduct problem analysis on the flow of funds based on the fund usage data and the various fund-related parties, and obtain the problem detection results of the fund flow, the following can be included: identifying the fund recipients included in the fund usage data; conducting problem analysis on the flow of funds based on the fund recipients and the various fund-related parties, and obtaining the problem detection results of the fund flow.

[0062] Further explanation: When problem analysis is required, the following can be included: 1. Fund Distribution Analysis: Calculate the statistical distribution of funds disbursed by a single person in a single instance. Mark records where the amount is frequently slightly lower than a preset amount (which can be the personal income tax threshold), or situations where multiple people under the same project disburse similar amounts and the total amount is abnormal (e.g., >500,000 yuan). 2. Frequency Distribution Analysis: Statistically analyze the number of disbursements and time intervals for the same "disburser-recipient" combination within a certain period (e.g., monthly). Mark combinations with excessively high frequency (e.g., ≥4 times / month) or abnormally fixed disbursement dates (e.g., the 5th of each month). 3. Surname Distribution Analysis: Statistically analyze the surname distribution of labor fee recipients by disbursing department. Calculate the "surname concentration" (number of recipients with a certain surname / total number of recipients in the department). Mark departments with excessively high concentration (e.g., ≥40%) and where the surname is not a common surname, suggesting the possible existence of "small group" benefit transfers. 4. Age Reasonableness Analysis: Logically verify the "labor fee type" with the recipient's "age" and "professional title". For example, records of recipients of funds marked "expert consultation fees" who are under 18 or over 80 years old, and whose professional titles are below intermediate level or who are not well-known members of society.

[0063] Based on the analysis results from the above dimensions, a problem detection result is generated. The problem detection result may include a list of financial problems, and each record is marked with a risk level (high, medium, low) and trigger rules.

[0064] In one embodiment of this application, a unique "funding issue number" can be generated for each funding issue based on the issue detection results. Subsequent financial data is periodically scanned, and key fields such as "voucher number," "fund recipient ID," and "issuance slip number" are used to automatically match whether corresponding refund vouchers, reversal entries, or other rectification actions exist. For issues marked for rectification, the system can automatically perform "data re-examination" (e.g., checking whether the relevant account balance or project expenditure has returned to normal after the refund). Combined with the conclusions of manual review, the issue is ultimately closed or escalated, and a rectification verification report is automatically generated.

[0065] Furthermore, auditors can review issues within the system, manually enter rectification explanations (such as "Explanation of the situation has been filed" or "Mistakenly issued documents have been recovered"), and upload electronic scans of relevant supporting materials. The system records the rectification time and the responsible person.

[0066] The aforementioned problem analysis method identifies the fund usage data corresponding to the fund flow; identifies at least one fund-related party with a connection to the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members; and performs problem analysis on the fund flow based on the fund usage data and each fund-related party to obtain the problem detection results of the fund flow. As can be seen from the above, this application, in the process of problem analysis, first obtains the fund usage data corresponding to the fund flow, as well as at least one fund-related party with a connection to the project manager corresponding to the fund flow. This achieves the acquisition of data related to the problem analysis of the fund flow, ensuring the accuracy of subsequent problem analysis of the fund flow, realizing comprehensive anomaly detection of fund flows, and effectively monitoring anomalies in fund flows.

[0067] In one embodiment, such as Figure 3 As shown, when it is necessary to conduct a problem analysis on the flow of funds based on the data on fund usage and the various parties involved in the funds, and to obtain the problem detection results of the fund flow, the following can be included:

[0068] S301, Identify the recipients of funds included in the fund usage data.

[0069] S302, based on the fund recipients and related parties, conduct a problem analysis on the fund flow to obtain the problem detection results of the fund flow.

[0070] In one embodiment of this application, when it is necessary to perform problem analysis on the flow of funds based on the fund recipient and each fund affiliate to obtain the problem detection result of the flow of funds, the following may be included: if the fund recipient belongs to the fund affiliate user included in each fund affiliate, then the problem detection result is determined to be a fund problem included in the flow of funds; if the fund recipient belongs to the fund affiliate enterprise included in each fund affiliate, then the problem detection result is determined to be a fund problem included in the flow of funds.

[0071] As an example, if there are issues with funds being transferred to related companies, the query platform can be used to trace the information of the receiving company and its multiple layers of parent and subsidiary companies through equity penetration information (e.g., tracing up to three layers above and down to three layers below). All former and current shareholders, legal representatives, and senior executives of all related companies after penetration will be matched with the project leader and project team members. Once a match is found, it is preliminarily considered a problem.

[0072] In another embodiment of this application, when it is necessary to perform problem analysis on the fund flow based on the fund recipient and each fund affiliate to obtain the problem detection result of the fund flow, the following may also be included: when the fund recipient is a user and the fund recipient is not one of the fund affiliates, analyze the fund flow based on the fund usage data to determine the amount of funds and the frequency of disbursement, and obtain a first analysis result; analyze the fund flow based on the fund usage data to determine the fund disbursement region, and obtain a second analysis result; analyze the fund flow based on the fund usage data to determine the fund recipient's age, and obtain a third analysis result; determine the problem detection result of the fund flow based on the first analysis result, the second analysis result, and the third analysis result.

[0073] Specifically, when determining the problem detection result of fund flow based on the first analysis result, the second analysis result, and the third analysis result, if the number of abnormalities in the first analysis result, the second analysis result, and the third analysis result exceed the preset number threshold, then the problem detection result is determined to be a fund problem included in the fund flow; if the number of abnormalities in the first analysis result, the second analysis result, and the third analysis result does not exceed the preset number threshold, then the problem detection result is determined to be a fund problem not included in the fund flow.

[0074] The quantity threshold can be set or adjusted according to the actual situation.

[0075] Specifically, if the quantity threshold is two, then verify whether the number of abnormal results in the first analysis result, the second analysis result, and the third analysis result is greater than two. If so, then determine that the problem detection result is a financial problem included in the fund flow.

[0076] As an example, when analyzing fund flows and disbursement frequency based on fund usage data, the following can be included: sorting the fund amount (i.e., disbursement amount) and disbursement frequency in descending order and performing basic statistics. Specifically, determining whether the number of people with fund amounts greater than the average fund amount exceeds a first threshold, and determining whether the number of people with disbursement frequencies greater than the average disbursement frequency exceeds a second threshold. If the number of people with fund amounts greater than the average fund amount exceeds the first threshold, or the number of people with disbursement frequencies greater than the average disbursement frequency exceeds the second threshold, then the first analysis result is determined to be abnormal.

[0077] As an example, when analyzing the flow of funds based on fund usage data, the following can be included: determining whether the region where the project manager is located is the same as the region where the funds are distributed, and determining whether the region where the project manager's family members are located is the same as the region where the funds are distributed. If the region where the project manager is located is the same as the region where the funds are distributed, or if the region where the project manager's family members are located is the same as the region where the funds are distributed, then the second analysis result is determined to be abnormal.

[0078] As an example, when analyzing the age of fund recipients based on fund usage data, anomalies can be screened for where the recipient is under 18 or over 80 (or 75) years old at the time of receipt. Specifically, determine if the fund recipient's age is under 18 or over 80; if so, the third analysis result indicates an anomaly. Further, examine the summary of financial vouchers in the fund usage data; if terms such as "summer camp," "nursing home," or "questionnaire" are present, then, assuming the fund recipient's age is under 18 or over 80, the third analysis result indicates no anomalies.

[0079] In another embodiment of this application, when it is necessary to perform problem analysis on the flow of funds based on the fund recipient and each fund-related party to obtain the problem detection result of the flow of funds, the following may also be included: when the fund recipient is an enterprise and the fund recipient is not one of the fund-related parties, determine the enterprise-related users corresponding to the fund recipient; perform problem analysis on the flow of funds based on the enterprise-related users to obtain the problem detection result of the flow of funds.

[0080] When it is necessary to conduct problem analysis on the flow of funds based on relevant users of the enterprise and obtain the problem detection results of the flow of funds, the following can be included: conduct problem analysis on the flow of funds based on the correlation between the project leader and relevant users of the enterprise and obtain the problem detection results of the flow of funds.

[0081] Specifically, a name correlation analysis was conducted between the project leader and relevant users of the enterprise to obtain the fourth analysis result; the amount and frequency of fund disbursements were analyzed based on the fund usage data to obtain the fifth analysis result; and the detection results of the fund flow problem were determined based on the fourth and fifth analysis results.

[0082] Specifically, when determining the problem detection result of fund flow based on the fourth and fifth analysis results, if the number of abnormalities in the fourth and fifth analysis results exceeds a preset threshold, the problem detection result is determined to be a fund problem included in the fund flow; if the number of abnormalities in the fourth and fifth analysis results does not exceed the preset threshold, the problem detection result is determined to be a fund problem not included in the fund flow.

[0083] The quantity threshold can be set or adjusted according to the actual situation.

[0084] As an example, relevance can include name similarity, family relationships, and company names. Specifically, when analyzing name similarity, if either the amount or frequency is greater, the similarity between the names of the receiving company's shareholders, legal representatives, and executives and the names of the project leader and project team members (e.g., two out of three characters are the same) is increased in suspicion weight. When analyzing family relationships, if either the amount or frequency is greater, and the names of the company's shareholders, legal representatives, executives, project leaders, and project team members show possible family combinations, the weight is increased (e.g., two names overlap by two characters; one person's name is a combination of the other two names). When inferring from company names, if either the amount or frequency is greater, the company name containing the names of the project leader and project team members is suspicious; if it also contains the names of their relatives, the weight is increased.

[0085] The above-mentioned problem analysis method analyzes the flow of funds based on the recipients and related parties, and obtains the problem detection results of the fund flow. This enables comprehensive discovery of abnormal issues in the flow of funds and effectively monitors these abnormalities.

[0086] In one embodiment, such as Figure 4 As shown, when it is necessary to conduct problem analysis on the flow of funds, the following can be included:

[0087] S401, determine the fund usage data corresponding to the fund flow.

[0088] S402, identify at least one related party with a connection to the project responsible for the fund flow.

[0089] S403, Identify the recipients of funds included in the fund usage data.

[0090] S404, If the recipient of funds is a user associated with funds among the various fund-related parties, then the problem detection result is determined to be a fund problem included in the fund flow.

[0091] S405, if the recipient of funds is a related enterprise among the related parties of funds, then the problem detection result is determined to be a fund problem included in the fund flow.

[0092] S406, when the fund recipient is a user and the fund recipient is not one of the fund-related parties, the fund flow is analyzed based on the fund usage data to determine the amount of funds and the frequency of disbursements, and the first analysis result is obtained.

[0093] S407, based on the fund usage data, analyze the fund flow by the region where the funds were distributed, and obtain the second analysis result.

[0094] S408, based on the fund usage data, analyze the age of the fund recipients to obtain the third analysis result.

[0095] S409, Based on the results of the first analysis, the second analysis, and the third analysis, determine the problem detection results of the fund flow.

[0096] S410, when the fund recipient is an enterprise and the fund recipient is not one of the fund-related parties, determine the enterprise-related users corresponding to the fund recipient.

[0097] S411, based on the problem analysis of the fund flow by relevant users of the enterprise, obtain the problem detection results of the fund flow.

[0098] In one embodiment of this application, an auditing model is used to analyze the flow of funds of individual users.

[0099] The audit model is a multi-dimensional feature weighted scoring model. When the information of the project leader and his relatives cannot be obtained or is incomplete, causing the direct matching model to fail to screen effectively, the model calculates the "suspicion score" of each fund recipient through hierarchical progressive analysis of "amount frequency feature → regional feature → age feature". If the score exceeds the threshold, "funding problem" is output.

[0100] (a) First layer: Analysis of fund amount and frequency of disbursement (basic screening)

[0101] Data processing: Taking the labor costs (funds) of a certain scientific research project as an example, we group the data by "name of fund recipient" and count the "cumulative amount of funds disbursed" and "frequency of disbursement" (i.e., number of months of disbursement) for each fund recipient. Then, we sort the two sets of data in descending order to form a "fund recipient amount sorting table" and a "fund recipient frequency sorting table".

[0102] Statistical indicators are calculated based on the "Fund Recipient Amount Ranking Table" and the "Fund Recipient Frequency Ranking Table" to calculate the average cumulative amount of funds disbursed and the average frequency of disbursements for all fund recipients.

[0103] Key personnel are identified by screening recipients based on the average cumulative amount of funds disbursed and the average frequency of disbursements. Those with cumulative disbursements exceeding the average amount and those with disbursements exceeding the average frequency are selected. If the difference between the amount of funds disbursed to a recipient and the average amount exceeds a first threshold, or the difference between the frequency of disbursements to a recipient and the average frequency exceeds a second threshold, then that recipient is designated as a key target.

[0104] Time-based screening: For key individuals under close monitoring, further verify the disbursement time. If there are cases of "continuous disbursement every year including June, August, October, and December", mark them as "highly suspicious individuals".

[0105] (II) Second layer: Analysis of fund disbursement regions (regional correlation screening)

[0106] Based on "regional correlation," the relationship between the fund recipient and the project manager is inferred, which is divided into two dimensions: "comparison with the project manager / relatives in terms of region" and "comparison with people in the same region."

[0107] The comparison with the project manager's or relatives' locations includes: Data preparation: obtaining the project manager's registered residence or permanent residence (based on administrative division code or city name), and information on the locations of the project manager's relatives that is already known. Judgment and weighting: If the fund recipient and the project manager are in the same region, the suspected weight is increased by value A (e.g., A can be 30%); if the two have the same surname, the suspected weight is increased by an additional value B (e.g., B can be 20%). If the fund recipient and a relative of the project manager are in the same region, the suspected weight is increased by A; if the two have the same surname, the suspected weight is increased by an additional value B.

[0108] Comparisons between people in the same region include: Regional exclusion: First, exclude cases where the fund recipient is from a "designated city" (to avoid misjudging normal local partners), and only analyze fund recipients from non-designated cities.

[0109] Number of recipients: Count the number of fund recipients in the same non-designated city. If the number exceeds the threshold (the threshold can be adjusted according to the project size), the corresponding financial vouchers need to be retrieved to verify the project information and the person in charge of the project.

[0110] Project Exclusion: If the project information in the fund usage data contains preset keywords (indicating the need to conduct on-site research in other locations and the reasonableness of distributing labor fees to multiple people in multiple regions), then the fund recipients in that region will be excluded; if there are no such keywords, the region will be listed as a suspected problem area.

[0111] Frequency and Surname Weighting: For fund recipients in suspected problematic areas, if there are instances of continuous payment of labor fees for 3 months or more, the suspected weighting increases by 25%; if the surname of the fund recipient is the same as that of the project manager or their relatives, the suspected weighting increases by an additional 20%.

[0112] (III) Third layer: Age rationality analysis (anomaly screening)

[0113] Identify unreasonable fund disbursements by focusing on "abnormal age" and pinpoint suspicious cases after ruling out compliant scenarios.

[0114] Age threshold setting: The age of the recipient of labor service fees at the time of receipt is used as the core indicator, and two abnormal thresholds are set: age less than 18 years old and age greater than 75 years old (or 80 years old, which can be adjusted according to the local retirement policy).

[0115] Anomaly Verification and Elimination: Individuals under 18 years of age: Retrieve the corresponding financial documents and review the document summary. If the summary contains terms such as "summer camp," "questionnaire," or "student subsidy" (indicating compliant student participation program subsidies), then exclude the recipient of the funds; if no such terms are found, directly classify them as suspicious individuals.

[0116] For individuals over 75 years of age: their information will be searched through publicly available online channels (such as academic platforms, industry association websites, and news reports). If the search results indicate that the individual is an expert in the academic field or a well-known figure in the industry (there is a reasonable basis for their re-employment to participate in scientific research), then the recipient of the funding will be excluded; if no relevant "designated personnel" information is found, they will be listed as a suspicious individual.

[0117] Weighting: If a suspected person meets any of the suspicious conditions in the second-level "Regional Analysis", the suspected weight in the Regional Analysis should be combined with the base weight of age abnormality (for example, the base weight can be 50%) to further increase the suspicious level.

[0118] Finally, the total suspected weight of suspicious individuals is compared with a preset weight threshold. If the total suspected weight is greater than the weight threshold, the problem detection result of the suspicious individuals is determined to be a financial problem included in the fund flow.

[0119] In another embodiment of this application, an audit model can be used to analyze the flow of funds in a company's labor resource distribution process, which may include the following:

[0120] When information about the project leader and their relatives is unavailable or incomplete, a progressive analysis based on "amount frequency - name characteristics - company name" can be used to analyze the company's cash flow.

[0121] (a) First layer: Analysis of fund amount and frequency of disbursement (basic screening)

[0122] Data calculation: Taking the enterprise as the "outsourcing fee receiving enterprise" as an example, we will count the "funds amount" and "disbursement frequency" of each enterprise, and then calculate the average funds amount and average disbursement frequency of each enterprise.

[0123] Key personnel are identified by screening individuals based on the average cumulative amount of funds disbursed by the enterprise and the average frequency of disbursements. Individuals with a cumulative amount of funds disbursed exceeding the average amount and individuals with a disbursement frequency exceeding the average frequency are selected. If the difference between the amount of funds disbursed by an individual and the average amount of funds disbursed exceeds a first threshold, or the difference between the frequency of disbursements disbursed by an individual and the average frequency of disbursements disbursed exceeds a second threshold, then that individual is designated as a key target for monitoring.

[0124] (II) Second layer: Name similarity and family relationship analysis (association screening)

[0125] For key targets, the correlation between the names of relevant enterprise users and the names of project leaders can be used to infer whether there is a conflict of interest.

[0126] Among them, enterprise-related users include shareholders, legal representatives, and senior executives.

[0127] Name similarity analysis includes: Data extraction: obtaining the names of shareholders, legal representatives, and senior executives of key companies, as well as the names of project leaders and project team members.

[0128] Similarity determination: (1) The name similarity is analyzed by “character matching method”. If the name of the enterprise-related user and the name of the project leader are three-character names and two characters are the same (such as “Zhang Sanfang” and “Zhang Sanyuan”), the suspected weight increases by 30%. (2) The name similarity is determined by analyzing family relationships. If the name of one of the enterprise-related users is a combination of the names of two people in the project leader (such as “Zhang San” and “Li Si”’s child is named “Zhang Lizi”), the potential family relationship is determined, and the suspected weight increases by 35%.

[0129] Scope of association: Family relationship inference should cover two dimensions simultaneously: "within the enterprise's relevant users" and "between the enterprise's relevant users and the project leader" to avoid omitting family relationships across groups.

[0130] (III) Third layer: Enterprise name inference (feature screening)

[0131] By identifying companies whose names contain key names, suspected related companies can be directly identified.

[0132] Basic screening includes: verifying the names of key companies. If the name contains the name of the project leader or a member of the project team (e.g., "Zhang San Technology Co., Ltd." contains the name of the project leader "Zhang San"), the company is judged as suspicious, and the weight of the suspicious company is increased by 40%.

[0133] Weighting upgrades include: if the company name contains both the names of project-related personnel and their relatives (e.g., "Zhang San Li Si Technology Co., Ltd." contains "Zhang San" (person in charge) and "Li Si" (person in charge's spouse)), an additional 25% weighting will be added to the base weighting.

[0134] Finally, the total suspected weight of the enterprise is compared with the preset weight threshold. If the total suspected weight is greater than the weight threshold, the problem detection result of the enterprise is determined to be a financial problem included in the fund flow.

[0135] The aforementioned problem analysis method identifies the fund usage data corresponding to the fund flow; identifies at least one fund-related party with a connection to the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members; and performs problem analysis on the fund flow based on the fund usage data and each fund-related party to obtain the problem detection results of the fund flow. As can be seen from the above, this application, in the process of problem analysis, first obtains the fund usage data corresponding to the fund flow, as well as at least one fund-related party with a connection to the project manager corresponding to the fund flow. This achieves the acquisition of data related to the problem analysis of the fund flow, ensuring the accuracy of subsequent problem analysis of the fund flow, realizing comprehensive anomaly detection of fund flows, and effectively monitoring anomalies in fund flows.

[0136] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0137] Based on the same inventive concept, this application also provides a problem analysis apparatus for implementing the problem analysis method described above. The solution provided by this apparatus is similar to the solution described in the above method; therefore, the specific limitations in one or more problem analysis apparatus embodiments provided below can be found in the limitations of the problem analysis method described above, and will not be repeated here.

[0138] In one embodiment, such as Figure 5As shown, a problem analysis device is provided, comprising: a first determining module 10, a second determining module 20, and an analysis module 30, wherein:

[0139] The first determining module 10 is used to determine the fund usage data corresponding to the fund flow.

[0140] The second determining module 20 is used to identify at least one funding-related party that has a connection with the project manager corresponding to the fund flow. The project manager includes the project leader and project members.

[0141] Analysis module 30 is used to analyze the flow of funds based on the data on fund usage and the relevant parties, and to obtain the results of the detection of problems in the flow of funds.

[0142] In one embodiment, the recipient of funds included in the fund usage data is determined;

[0143] Based on the recipients of funds and the various related parties, a problem analysis of the fund flow is conducted to obtain the problem detection results of the fund flow.

[0144] In one embodiment, if the fund recipient is a fund-related user included in each fund-related party, then the problem detection result is determined to be a fund problem included in the fund flow.

[0145] If the recipient of the funds is a related company among the various related parties, then the problem detection result is determined to be a funding issue included in the fund flow.

[0146] In one embodiment, when the fund recipient is a user and the fund recipient is not one of the fund-related parties, the fund flow is analyzed based on the fund usage data to determine the amount of funds and the frequency of disbursement, and a first analysis result is obtained.

[0147] Based on the data on fund usage, the fund flow was analyzed by the regions where funds were distributed, resulting in the second analysis result;

[0148] Based on the data on fund usage, an analysis of the age of fund recipients was conducted to determine the third analysis result.

[0149] Based on the results of the first, second, and third analyses, the detection results of the fund flow problem were determined.

[0150] In one embodiment, when the fund recipient is an enterprise and the fund recipient is not one of the fund-related parties, the enterprise-related users corresponding to the fund recipient are determined.

[0151] Based on the analysis of issues related to fund flows by relevant enterprise users, the results of fund flow problem detection were obtained.

[0152] In one embodiment, the flow of funds is analyzed for problems based on the correlation between the project manager and relevant users of the enterprise, and the results of the problem detection of the flow of funds are obtained.

[0153] The aforementioned problem analysis device determines the fund usage data corresponding to the fund flow; identifies at least one fund-related party with a connection to the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members; and performs problem analysis on the fund flow based on the fund usage data and each fund-related party to obtain the problem detection results of the fund flow. As can be seen from the above, in the process of problem analysis, this application first obtains the fund usage data corresponding to the fund flow and at least one fund-related party with a connection to the project manager corresponding to the fund flow. This achieves the acquisition of data related to the problem analysis of the fund flow, ensuring the accuracy of subsequent problem analysis of the fund flow, realizing comprehensive anomaly detection of fund flows, and effectively monitoring anomalies in fund flows.

[0154] Each module in the aforementioned problem analysis device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0155] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a problem analysis method. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0156] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0157] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0158] Determine the fund usage data corresponding to the fund flow;

[0159] Identify at least one related party that has a connection with the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members;

[0160] Based on the data on fund usage and the relevant parties involved in the funds, an analysis of the fund flow was conducted to obtain the results of the fund flow problem detection.

[0161] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0162] Identify the recipients of funds included in the fund usage data;

[0163] Based on the recipients of funds and the various related parties, a problem analysis of the fund flow is conducted to obtain the problem detection results of the fund flow.

[0164] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0165] If the recipient of the funds is a user associated with the funds among the various fund-related parties, then the problem detection result is determined to be a fund problem included in the fund flow.

[0166] If the recipient of the funds is a related company among the various related parties, then the problem detection result is determined to be a funding issue included in the fund flow.

[0167] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0168] When the recipient of funds is a user and the recipient is not a party associated with the funds, the flow of funds is analyzed based on the fund usage data to determine the amount and frequency of fund disbursements, thus obtaining the first analysis result.

[0169] Based on the data on fund usage, the fund flow was analyzed by the regions where funds were distributed, resulting in the second analysis result;

[0170] Based on the data on fund usage, an analysis of the age of fund recipients was conducted to determine the third analysis result.

[0171] Based on the results of the first, second, and third analyses, the detection results of the fund flow problem were determined.

[0172] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0173] When the recipient of funds is an enterprise and the recipient of funds is not one of the related parties of the funds, determine the relevant users of the enterprise corresponding to the recipient of funds.

[0174] Based on the analysis of issues related to fund flows by relevant enterprise users, the results of fund flow problem detection were obtained.

[0175] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0176] Based on the correlation between the project leader and relevant enterprise users, a problem analysis of fund flow is conducted to obtain the problem detection results of fund flow.

[0177] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0178] Determine the fund usage data corresponding to the fund flow;

[0179] Identify at least one related party that has a connection with the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members;

[0180] Based on the data on fund usage and the relevant parties involved in the funds, an analysis of the fund flow was conducted to obtain the results of the fund flow problem detection.

[0181] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0182] Identify the recipients of funds included in the fund usage data;

[0183] Based on the recipients of funds and the various related parties, a problem analysis of the fund flow is conducted to obtain the problem detection results of the fund flow.

[0184] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0185] If the recipient of the funds is a user associated with the funds among the various fund-related parties, then the problem detection result is determined to be a fund problem included in the fund flow.

[0186] If the recipient of the funds is a related company among the various related parties, then the problem detection result is determined to be a funding issue included in the fund flow.

[0187] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0188] When the recipient of funds is a user and the recipient is not a party associated with the funds, the flow of funds is analyzed based on the fund usage data to determine the amount and frequency of fund disbursements, thus obtaining the first analysis result.

[0189] Based on the data on fund usage, the fund flow was analyzed by the regions where funds were distributed, resulting in the second analysis result;

[0190] Based on the data on fund usage, an analysis of the age of fund recipients was conducted to determine the third analysis result.

[0191] Based on the results of the first, second, and third analyses, the detection results of the fund flow problem were determined.

[0192] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0193] When the recipient of funds is an enterprise and the recipient of funds is not one of the related parties of the funds, determine the relevant users of the enterprise corresponding to the recipient of funds.

[0194] Based on the analysis of issues related to fund flows by relevant enterprise users, the results of fund flow problem detection were obtained.

[0195] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0196] Based on the correlation between the project leader and relevant enterprise users, a problem analysis of fund flow is conducted to obtain the problem detection results of fund flow.

[0197] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0198] Determine the fund usage data corresponding to the fund flow;

[0199] Identify at least one related party that has a connection with the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members;

[0200] Based on the data on fund usage and the relevant parties involved in the funds, an analysis of the fund flow was conducted to obtain the results of the fund flow problem detection.

[0201] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0202] Identify the recipients of funds included in the fund usage data;

[0203] Based on the recipients of funds and the various related parties, a problem analysis of the fund flow is conducted to obtain the problem detection results of the fund flow.

[0204] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0205] If the recipient of the funds is a user associated with the funds among the various fund-related parties, then the problem detection result is determined to be a fund problem included in the fund flow.

[0206] If the recipient of the funds is a related company among the various related parties, then the problem detection result is determined to be a funding issue included in the fund flow.

[0207] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0208] When the recipient of funds is a user and the recipient is not a party associated with the funds, the flow of funds is analyzed based on the fund usage data to determine the amount and frequency of fund disbursements, thus obtaining the first analysis result.

[0209] Based on the data on fund usage, the fund flow was analyzed by the regions where funds were distributed, resulting in the second analysis result;

[0210] Based on the data on fund usage, an analysis of the age of fund recipients was conducted to determine the third analysis result.

[0211] Based on the results of the first, second, and third analyses, the detection results of the fund flow problem were determined.

[0212] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0213] When the recipient of funds is an enterprise and the recipient of funds is not one of the related parties of the funds, determine the relevant users of the enterprise corresponding to the recipient of funds.

[0214] Based on the analysis of issues related to fund flows by relevant enterprise users, the results of fund flow problem detection were obtained.

[0215] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0216] Based on the correlation between the project leader and relevant enterprise users, a problem analysis of fund flow is conducted to obtain the problem detection results of fund flow.

[0217] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0218] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0219] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0220] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A problem analysis method, characterized in that, The method includes: Determine the fund usage data corresponding to the fund flow; Identify at least one funding-related party that has an association with the project manager corresponding to the fund flow; wherein the project manager includes the project leader and project members; Based on the fund usage data and the respective fund-related parties, a problem analysis is performed on the fund flow to obtain the problem detection results for the fund flow.

2. The method according to claim 1, characterized in that, The step of analyzing the fund flow based on the fund usage data and each of the fund-related parties to obtain the problem detection results of the fund flow includes: Identify the recipients of funds included in the fund usage data; Based on the fund recipients and related parties, a problem analysis is performed on the fund flow to obtain the problem detection results for the fund flow.

3. The method according to claim 2, characterized in that, The step of analyzing the flow of funds based on the fund recipients and related parties to obtain problem detection results for the fund flow includes: If the recipient of the funds belongs to the users associated with the funds among the fund-related parties, then the problem detection result is determined to be a fund problem included in the fund flow. If the recipient of the funds belongs to a fund-related enterprise included in the fund-related parties, then the problem detection result is determined to be a fund problem included in the fund flow.

4. The method according to claim 2, characterized in that, The step of analyzing the flow of funds based on the fund recipients and related parties to obtain problem detection results for the fund flow includes: If the recipient of the funds is a user and the recipient of the funds is not one of the fund-related parties, the fund flow is analyzed based on the fund usage data to determine the amount of funds and the frequency of disbursement, and a first analysis result is obtained. Based on the fund usage data, the fund flow is analyzed by the region of fund disbursement to obtain a second analysis result; Based on the fund usage data, the fund flow is analyzed by the age of the fund recipients to obtain a third analysis result; Based on the first analysis result, the second analysis result, and the third analysis result, the problem detection result of the fund flow is determined.

5. The method according to claim 2, characterized in that, The step of analyzing the flow of funds based on the fund recipients and related parties to obtain problem detection results for the fund flow includes: If the fund recipient is an enterprise and the fund recipient is not one of the fund-related parties, determine the enterprise-related users corresponding to the fund recipient; Based on the problem analysis of the fund flow by relevant users of the enterprise, the problem detection results of the fund flow are obtained.

6. The method according to claim 5, characterized in that, The step of analyzing the fund flow based on relevant users of the enterprise to obtain the problem detection results of the fund flow includes: Based on the correlation between the project manager and the relevant users of the enterprise, a problem analysis of the fund flow is performed to obtain the problem detection results of the fund flow.

7. A problem analysis device, characterized in that, The device includes: The first determination module is used to determine the fund usage data corresponding to the fund flow; The second determining module is used to determine at least one fund-related party that has an association with the project responsible party corresponding to the fund flow; wherein, the project responsible party includes the project leader and project members; The analysis module is used to perform problem analysis on the fund flow based on the fund usage data and each of the fund-related parties, and to obtain the problem detection results of the fund flow.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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