Building industry false trade early warning method and device

Abstract

The invention discloses a building industry false trade early warning method and device. The method comprises the following steps: determining an advance payment data deviation value based on contract content; determining a contract deviation value based on the object of the contract to be checked, the business range of the payee and the query result; based on invoice information, determining a first deviation value of the cancel-after-verification advance payment value; acquiring an expenditure flow corresponding to each cancel-after-verification advance payment value corresponding to the advance payment data; determining a second deviation value of the cancel-after-verification advance payment value based on expenditure flow information; and determining whether the advance payment data belongs to the building industry false trade based on the advance payment data deviation value, the contract deviation value, and the first deviation value and the second deviation value of the cancelled advance payment value. According to the invention, whether advance payment data belongs to building industry false trade can be accurately determined.

Description

Technical Field

[0001] The present invention relates to the technical field of construction industry, and in particular to a false trade early warning method and device for the construction industry. Background Art

[0002] In order to ensure the smooth progress of the construction process in the construction industry, funds are needed. However, if the flow records are missing, the flow amounts are inconsistent, the recipients are inconsistent, and the accounts have not been written off for a long time, there may be false trade, which will damage the interests of legitimate enterprises and affect the healthy development of the construction industry. Therefore, it is necessary to identify and warn of false trade in the construction industry in advance.

[0003] The existing methods for identifying false trade in the construction industry are often through data outliers, data abnormal trends, data abnormal proportions, audits, etc., which have technical problems such as data lag, lack of sufficient disclosure and sufficient data, strong subjective judgment and weak objective judgment. Summary of the invention

[0004] In view of this, the present invention provides a method and device for early warning of false trade in the construction industry, which can solve the technical problems of lagging false trade data in the construction industry, lack of sufficient public and sufficient data, strong subjective judgment and weak objective judgment.

[0005] In order to solve the above technical problems, the present invention is implemented as follows.

[0006] A false trade early warning method for the construction industry, the method comprising the following steps:

[0007] Step S1: obtaining prepayment data, determining the contract corresponding to the prepayment data through a contract database, and determining a deviation value of the prepayment data based on the contract content;

[0008] Step S2: taking the contract corresponding to the advance payment data as the contract to be verified, obtaining the construction industry project review report, querying the construction industry project review report based on the subject matter of the contract to be verified, determining the business scope of the payee based on the third-party platform, and determining the contract deviation value based on the subject matter of the contract to be verified, the business scope of the payee and the query result;

[0009] Step S3: obtaining the prepayment value that has been written off corresponding to the prepayment data and the invoice corresponding to the prepayment value that has been written off, wherein the prepayment value that has been written off is part or all of the prepayment that has been used after being offset by the invoice; determining a first deviation value of the prepayment value that has been written off based on the invoice information;

[0010] Step S4: obtaining the expenditure flow corresponding to each prepayment value that has been written off corresponding to the prepayment data; determining a second deviation value of the prepayment value that has been written off based on the expenditure flow information;

[0011] Step S5: Determine whether the prepayment data belongs to false trade in the construction industry based on the prepayment data deviation value, the contract deviation value, the first deviation value of the written-off prepayment value, and the second deviation value.

[0012] Preferably, the step S1: obtaining prepayment data, determining the contract corresponding to the prepayment data through a contract database, and determining the prepayment data deviation value based on the contract content, includes:

[0013] Step S11: obtaining prepayment data, determining the payee of the prepayment, and determining the contract corresponding to the prepayment data through the contract database;

[0014] Step S12: if there is no contract corresponding to the prepayment data in the contract database, determining that the prepayment data deviation value is 3;

[0015] Otherwise, if there is a contract corresponding to the prepayment data in the contract database, the current business status and litigation information of the prepayment recipient are obtained through the third-party platform; if the current business status is "abnormal operation" and the litigation information is "unresolved major legal disputes", the prepayment data deviation value is determined to be 2;

[0016] Otherwise, semantic analysis is performed on the contract corresponding to the advance payment data to extract the construction project type, payment amount, and payment cycle in the contract corresponding to the advance payment data; the construction project types include housing construction projects and infrastructure projects, and each construction project type corresponds to a proportional factor; the proportional factor is used to characterize the fluctuation range of the advance payment write-off ratio relative to the theoretical advance payment write-off ratio, and the proportional factors of different construction project types are different; the theoretical advance payment write-off ratio is equal to the number of days from the statistical date to the project establishment date of the construction project corresponding to the advance payment data divided by the project cycle, and the upper limit value is 1; obtain the ratio corresponding to the advance payment data The example factor, the current date and the value of the prepaid payment that has been written off, the value of the prepaid payment that has been written off is divided by the payment amount as the prepaid payment write-off ratio; based on the payment cycle, the theoretical prepaid payment write-off ratio corresponding to the current date is determined, based on the theoretical prepaid payment write-off ratio and the proportional factor, the fluctuation range of the theoretical prepaid payment write-off ratio is determined; if the prepaid payment write-off ratio is within the fluctuation range of the theoretical prepaid payment write-off ratio, the prepaid payment data deviation value is determined to be 0; otherwise, a first value is calculated, the first value is equal to the sum of the absolute values ​​of the differences between the prepaid payment write-off ratio and the two boundaries of the fluctuation range of the theoretical prepaid payment write-off ratio, and the prepaid payment data deviation value is set to be equal to the first value.

[0017] Preferably, the proportional factor of construction raw material suppliers is 0.8, the proportional factor of machinery and equipment rental suppliers is 0.7, the proportional factor of professional labor service suppliers is 0.6, the proportional factor of construction material processors is 0.75, the proportional factor of logistics and warehousing service providers is 0.85, and the proportional factor of design and consulting service providers is 0.9.

[0018] Preferably, the step S2: taking the contract corresponding to the advance payment data as the contract to be verified, obtaining the construction industry project review report, querying the construction industry project review report based on the subject matter of the contract to be verified, determining the business scope of the payee based on a third-party platform, and determining the contract deviation value based on the subject matter of the contract to be verified, the business scope of the payee and the query result, includes:

[0019] Step S21: taking the contract corresponding to the advance payment data as the contract to be checked; obtaining a construction industry project review report, wherein the construction industry project review report supports semantic query, and obtaining a query result, wherein the query result includes that the construction industry project review report is found and that the construction industry project review report is not found;

[0020] Step S22: If the query result is that no construction industry project review report is found and at least one of the contract content, supplier qualification review, project progress, financial records, and risk assessment does not meet the preset conditions, then the contract deviation value is determined to be 3;

[0021] If the query result is that no construction industry project review report is found and the contract content, supplier qualification review, project progress, financial records, and risk assessment all meet the preset conditions, then the contract deviation value is determined to be 1;

[0022] If the query result is a construction industry project review report, the business scope of the payee and the tax amount of each business type in the business scope in the year when the contract to be verified is signed are determined based on the third-party platform; the cosine similarity between the subject matter of the contract to be verified and each word in the business scope of the payee is calculated;

[0023] If the cosine similarities are all less than 0, the contract deviation value is determined to be 2;

[0024] Otherwise, the cosine similarity with the largest cosine similarity value is taken as the maximum cosine similarity, and the business type corresponding to the maximum cosine similarity is determined, and the income amount is inferred based on the tax amount of the business type in the current year; the value of the prepayment data divided by the income amount of the business type in the current year is calculated as the income percentage; the maximum cosine similarity multiplied by the income percentage is taken as the confidence level of the contract to be verified, and the contract deviation value is the inverse of the confidence level.

[0025] Preferably, the step S3: obtaining the prepayment value that has been written off corresponding to the prepayment data and the invoice corresponding to the prepayment value that has been written off, wherein the prepayment value that has been written off is part or all of the prepayment that has been used after being offset by the invoice; and determining the first deviation value of the prepayment value that has been written off based on the invoice information, comprises:

[0026] Step S31: obtaining the consumption content of the invoice corresponding to the prepayment value that has been written off, and recording the invoice whose consumption content does not match the subject matter of the contract corresponding to the prepayment data as an abnormal invoice; and counting the number of abnormal invoices;

[0027] Step S32: Calculate the proportion of abnormal invoices to all invoices corresponding to the value of the prepaid payment that has been written off. If the proportion exceeds a first preset threshold, the deviation value of the prepaid payment that has been written off is recorded as 1; otherwise, the first deviation value of the prepaid payment that has been written off is assigned to the proportion of abnormal invoices to all invoices corresponding to the value of the prepaid payment that has been written off.

[0028] Preferably, the step S4: obtaining the expenditure flow corresponding to each written-off prepayment value corresponding to the prepayment data; and determining the second deviation value of the written-off prepayment value based on the expenditure flow information, comprises:

[0029] Obtain the expenditure flow corresponding to each written-off prepayment value corresponding to the prepayment data;

[0030] If the transaction record is missing or incomplete, the second deviation value of the written-off prepayment value is assigned to 2.5; if the difference between the transaction amount and the amount agreed in the contract exceeds the first preset threshold, the second deviation value of the written-off prepayment value is assigned to 2; if the actual payee corresponding to the transaction record is inconsistent with the payee specified in the contract, the second deviation value of the written-off prepayment value is assigned to 2.5;

[0031] The step S5: determining whether the prepayment data belongs to false trade in the construction industry based on the prepayment data deviation value, the contract deviation value, the first deviation value of the written-off prepayment value, and the second deviation value, includes:

[0032] The deviation value of the advance payment data, the contract deviation value, the first deviation value and the second deviation value of the written-off advance payment value are summed up. If the result is greater than 3, it is determined that the advance payment data belongs to false trade in the construction industry.

[0033] The present invention provides a false trade early warning device for the construction industry, the device comprising:

[0034] The first module is configured to obtain prepayment data, determine the contract corresponding to the prepayment data through the contract database, and determine the deviation value of the prepayment data based on the contract content;

[0035] The second module is configured to take the contract corresponding to the advance payment data as the contract to be verified, obtain the construction industry project review report, query the construction industry project review report based on the subject matter of the contract to be verified, determine the business scope of the payee based on the third-party platform, and determine the contract deviation value based on the subject matter of the contract to be verified, the business scope of the payee and the query result;

[0036] The third module is configured to obtain the prepayment value that has been written off corresponding to the prepayment data and the invoice corresponding to the prepayment value that has been written off, wherein the prepayment value that has been written off is part or all of the prepayment that has been used after being offset by the invoice; and determine a first deviation value of the prepayment value that has been written off based on the invoice information;

[0037] The fourth module is configured to obtain the expenditure flow corresponding to each prepayment value that has been written off corresponding to the prepayment data; and determine the second deviation value of the prepayment value that has been written off based on the expenditure flow information;

[0038] Judgment module: configured to determine whether the prepayment data belongs to false trade in the construction industry based on the prepayment data deviation value, the contract deviation value, the first deviation value of the written-off prepayment value, and the second deviation value.

[0039] The present invention provides a computer-readable storage medium, wherein a plurality of instructions are stored in the storage medium; the plurality of instructions are used for a processor to load and execute the method as described above.

[0040] An electronic device provided by the present invention is characterized in that the electronic device comprises:

[0041] A processor, which is used to execute multiple instructions;

[0042] A memory for storing a plurality of instructions;

[0043] The plurality of instructions are used to be stored by the memory and loaded and executed by the processor to implement the method as described above.

[0044] Beneficial effects:

[0045] (1) The data of the present invention are all derived from a unified system, and the data are fully integrated. There is no need for human operation and aggregation, and no personal attitude is mixed in. The data is highly accurate and the data source is accurate. There are no cross-system or cross-industry problems. The contract information and payment information are traceable, and the data can be aggregated in real time.

[0046] (2) The present invention supports querying supplier credit information to reduce capital payment risks and supports data analysis by unit aggregation. Its technology solves the problem of isolated enterprise data and the inability to integrate with business systems. It relies on comprehensive external authoritative data to form a visual statistical analysis query function, which is provided to users for analysis and decision-making.

[0047] (3) The present invention can obtain real-time data, interactively verify the results of each module, and make the evaluation results objective.

[0048] (4) The present invention can comprehensively consider the contract content, prepayment content, and transaction information to accurately determine whether the prepayment data belongs to false trade in the construction industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the process of the false trade early warning method for the construction industry of the present invention;

[0050] Figure 2 It is a structural schematic diagram of the false trade early warning device for the construction industry of the present invention. DETAILED DESCRIPTION

[0051] The present invention is described in detail below in conjunction with the accompanying drawings and embodiments.

[0052] like Figure 1 As shown, the present invention proposes a false trade early warning method for the construction industry, comprising:

[0053] Step S1: obtaining prepayment data, determining the contract corresponding to the prepayment data through a contract database, and determining a deviation value of the prepayment data based on the contract content;

[0054] Step S2: taking the contract corresponding to the advance payment data as the contract to be verified, obtaining the construction industry project review report, querying the construction industry project review report based on the subject matter of the contract to be verified, determining the business scope of the payee based on the third-party platform, and determining the contract deviation value based on the subject matter of the contract to be verified, the business scope of the payee and the query result;

[0055] Step S3: obtaining the prepayment value that has been written off corresponding to the prepayment data and the invoice corresponding to the prepayment value that has been written off, wherein the prepayment value that has been written off is part or all of the prepayment that has been used after being offset by the invoice; determining a first deviation value of the prepayment value that has been written off based on the invoice information;

[0056] Step S4: obtaining the expenditure flow corresponding to each prepayment value that has been written off corresponding to the prepayment data; determining a second deviation value of the prepayment value that has been written off based on the expenditure flow information;

[0057] Step S5: Determine whether the prepayment data belongs to false trade in the construction industry based on the prepayment data deviation value, the contract deviation value, the first deviation value of the written-off prepayment value, and the second deviation value.

[0058] The step S1: obtaining prepayment data, determining the contract corresponding to the prepayment data through a contract database, and determining the prepayment data deviation value based on the contract content, includes:

[0059] Step S11: obtaining prepayment data, determining the payee of the prepayment, and determining the contract corresponding to the prepayment data through the contract database;

[0060] Step S12: if there is no contract corresponding to the prepayment data in the contract database, determining that the prepayment data deviation value is 3;

[0061] Otherwise, if there is a contract corresponding to the prepayment data in the contract database, the current business status and litigation information of the prepayment recipient are obtained through the third-party platform; if the current business status is "abnormal operation" and the litigation information is "unresolved major legal disputes", the prepayment data deviation value is determined to be 2;

[0062] Otherwise, semantic analysis is performed on the contract corresponding to the advance payment data to extract the construction project type, payment amount, and payment cycle in the contract corresponding to the advance payment data; the construction project types include housing construction projects and infrastructure projects, and each construction project type corresponds to a proportional factor; the proportional factor is used to characterize the fluctuation range of the advance payment write-off ratio relative to the theoretical advance payment write-off ratio, and the proportional factors of different construction project types are different; the theoretical advance payment write-off ratio is equal to the number of days from the statistical date to the project establishment date of the construction project corresponding to the advance payment data divided by the project cycle, and the upper limit value is 1; obtain the ratio corresponding to the advance payment data The example factor, the current date and the value of the prepaid payment that has been written off, the value of the prepaid payment that has been written off is divided by the payment amount as the prepaid payment write-off ratio; based on the payment cycle, the theoretical prepaid payment write-off ratio corresponding to the current date is determined, based on the theoretical prepaid payment write-off ratio and the proportional factor, the fluctuation range of the theoretical prepaid payment write-off ratio is determined; if the prepaid payment write-off ratio is within the fluctuation range of the theoretical prepaid payment write-off ratio, the prepaid payment data deviation value is determined to be 0; otherwise, a first value is calculated, the first value is equal to the sum of the absolute values ​​of the differences between the prepaid payment write-off ratio and the two boundaries of the fluctuation range of the theoretical prepaid payment write-off ratio, and the prepaid payment data deviation value is set to be equal to the first value.

[0063] Furthermore, the proportional factor of suppliers of construction raw materials is 0.8, the proportional factor of suppliers of machinery and equipment rental is 0.7, the proportional factor of suppliers of professional labor services is 0.6, the proportional factor of building materials processors is 0.75, the proportional factor of suppliers of logistics and warehousing services is 0.85, and the proportional factor of suppliers of design and consulting services is 0.9.

[0064] In the present invention, the scale factor of suppliers of building raw materials, such as steel, cement, concrete, bricks and tiles, glass, wood, etc., is set to 0.8, because the supply of raw materials is relatively stable, but price fluctuations may affect the cost. The scale factor of suppliers of mechanical equipment rental, such as cranes, excavators, mixers, transport vehicles, etc., is set to 0.7, because the operational risks and technical requirements involved in equipment rental are high, and the equipment maintenance cost needs to be considered. Professional labor service providers, such as civil engineering, electrical installation, pipeline laying, decoration and renovation, etc. The scale factor is set to 0.6, because the quality and efficiency of labor services directly affect the progress and quality of the project, and personnel management is relatively complex. Building material processing, such as prefabricated components, door and window manufacturing, waterproof material production, etc., the scale factor is set to 0.75, because the process and technology involved in the processing link are high, and quality control is crucial. Logistics and warehousing services, such as material transportation, on-site warehousing management, etc. The scale factor is set to 0.85, because the reliability and timeliness of logistics and warehousing services have a greater impact on the project progress and involve more external factors. Design and consulting service providers, such as architectural design, structural design, project management consulting, etc. The scaling factor is set at 0.9 because the professionalism and innovation of design and consulting services are critical to project success but are generally lower risk.

[0065] In the present invention, according to business needs, the OSP platform is considered to use scheduled tasks to organize data every day, and the SVR service developed by the platform in Java is called. The service is responsible for processing abnormal capital flow business data information according to business logic, and uses the OSP development platform to develop a front-end display interface for users to query and use.

[0066] Through the xxjob distributed task integrated by the OSP platform, configure the scheduled task and execute the following Java service:

[0067] Query and obtain all prepayment ledgers related to prepayment payment vouchers with a certificate issuance date after January 1, 2023 (specific date supports configuration) through Java background service;

[0068] The judgment logic is as follows

[0069] <1> Authentication and authorization: Use the CAS protocol to verify user identity and load corresponding data based on user roles and permissions.

[0070] Permission control: Implement RBAC (Role-Based Access Control) role-based access control mechanism when querying the database to ensure that users can only see the data they have access to.

[0071] When the user logs in to the system, the system will load the corresponding prepayment ledger according to the user's role and permissions. The user can select a specific start date, and the system will display all prepayment records after that date.

[0072] <2> Specific data screening is divided into two categories:

[0073] Database query optimization: Use SQL query language, combined with index optimization, to quickly retrieve records that meet the conditions.

[0074] Multi-threaded processing: For processing large amounts of data, multi-threaded or multi-process parallel processing is used to speed up processing.

[0075] Cache mechanism: Use cache technologies such as Redis to store frequently accessed data to reduce database pressure.

[0076] Prepayments with long-term unwritten balances: For example, for prepayments with long-term unwritten balances, the proportional factor corresponding to the construction raw materials supply type is [-0.05, 0.03]. The calculated theoretical prepayment write-off ratio is 70%, and the fluctuation range of the theoretical prepayment write-off ratio is determined to be 65%-73%. If the prepayment write-off ratio is 68%, the prepayment write-off ratio is within the fluctuation range of the theoretical prepayment write-off ratio.

[0077] <3> Auxiliary filtering data conditions:

[0078] Contract information association: Link the prepayment records with the corresponding contract information through database association query.

[0079] Front-end display logic: Dynamically display the "Contract Advance Payment Ratio" on the front-end page, and decide whether to highlight it based on whether a contract is associated and whether the contract advance payment ratio is greater than or equal to 20%.

[0080] <4> External system connection: obtain supplier risk information through the connection with the capital platform customer management information.

[0081] Data synchronization mechanism: Establish regular data synchronization tasks to ensure that the supplier risk status in the local database is up to date.

[0082] The system will automatically match the supplier information corresponding to the advance payment and compare it with the supplier risk information in the comprehensive management platform for fund analysis and prevention. If the supplier is found to be a risky supplier, a yellow mark will be placed on the corresponding cell in the front-end interface.

[0083] In the present invention, the third-party platform is, for example, Qixinbao, Tianyancha and other third-party platforms.

[0084] The step S2: taking the contract corresponding to the advance payment data as the contract to be verified, obtaining the construction industry project review report, querying the construction industry project review report based on the subject matter of the contract to be verified, determining the business scope of the payee based on the third-party platform, and determining the contract deviation value based on the subject matter of the contract to be verified, the business scope of the payee and the query result, including:

[0085] Step S21: taking the contract corresponding to the advance payment data as the contract to be checked; obtaining a construction industry project review report, wherein the construction industry project review report supports semantic query, and obtaining a query result, wherein the query result includes that the construction industry project review report is found and that the construction industry project review report is not found;

[0086] Step S22: If the query result is that no construction industry project review report is found and at least one of the contract content, supplier qualification review, project progress, financial records, and risk assessment does not meet the preset conditions, then the contract deviation value is determined to be 3;

[0087] If the query result is that no construction industry project review report is found and the contract content, supplier qualification review, project progress, financial records, and risk assessment all meet the preset conditions, then the contract deviation value is determined to be 1;

[0088] If the query result is a construction industry project review report, the business scope of the payee and the tax amount of each business type in the business scope in the year when the contract to be verified is signed are determined based on the third-party platform; the cosine similarity between the subject matter of the contract to be verified and each word in the business scope of the payee is calculated;

[0089] If the cosine similarities are all less than 0, the contract deviation value is determined to be 2;

[0090] Otherwise, the cosine similarity with the largest cosine similarity value is taken as the maximum cosine similarity, and the business type corresponding to the maximum cosine similarity is determined, and the income amount is inferred based on the tax amount of the business type in the current year; the value of the prepayment data divided by the income amount of the business type in the current year is calculated as the income percentage; the maximum cosine similarity multiplied by the income percentage is taken as the confidence level of the contract to be verified, and the contract deviation value is the inverse of the confidence level.

[0091] In the present invention, checking the contract content refers to verifying the terms of the advance payment in the contract to ensure its rationality and compliance. Auditing the supplier's qualifications refers to confirming the supplier's operating status, credit record and historical cooperation. Assessing the project progress refers to checking the actual progress of the project to ensure that the advance payment is consistent with the project progress. Reviewing financial records refers to checking financial records to ensure that the payment and use of the advance payment are in compliance with the contract agreement and financial regulations. Risk assessment refers to comprehensively evaluating the above inspection results, assessing the risk level of the advance payment, and determining whether further measures are needed.

[0092] In the present invention, the business scope of the payee and the tax amount of each business type in the business scope in the year when the contract to be verified is signed are determined based on a third-party platform; the purpose of calculating the cosine similarity between the subject matter of the contract to be verified and each word in the business scope of the payee is to determine whether the contract to be verified deviates from the main business, that is, whether there is abnormal trade business.

[0093] Consider using the OSP platform's scheduled tasks to collate data every month based on business needs, and call the platform's SVR service developed in Java. This service is responsible for processing false trade information according to business logic, and uses the OSP development platform to develop a front-end display interface for users to query and use.

[0094] The step S3: obtaining the prepayment value that has been written off corresponding to the prepayment data and the invoice corresponding to the prepayment value that has been written off, wherein the prepayment value that has been written off is part or all of the prepayment that has been used after being offset by the invoice; based on the invoice information, determining a first deviation value of the prepayment value that has been written off, includes:

[0095] Step S31: obtaining the consumption content of the invoice corresponding to the prepayment value that has been written off, and recording the invoice whose consumption content does not match the subject matter of the contract corresponding to the prepayment data as an abnormal invoice; and counting the number of abnormal invoices;

[0096] Step S32: Calculate the proportion of abnormal invoices to all invoices corresponding to the value of the prepaid payment that has been written off. If the proportion exceeds a first preset threshold, the deviation value of the prepaid payment that has been written off is recorded as 1; otherwise, the first deviation value of the prepaid payment that has been written off is assigned to the proportion of abnormal invoices to all invoices corresponding to the value of the prepaid payment that has been written off.

[0097] In the present invention, according to business needs, the OSP platform is considered to use scheduled tasks to organize data every month, and the SVR service developed by the platform in Java is called. The service is responsible for processing and organizing abnormal invoice information according to business logic, and using the OSP development platform to develop a front-end display interface for users to query and use.

[0098] The step S4: obtaining the expenditure flow corresponding to each prepayment value that has been written off corresponding to the prepayment data; determining the second deviation value of the prepayment value that has been written off based on the expenditure flow information, includes:

[0099] Obtain the expenditure flow corresponding to each written-off prepayment value corresponding to the prepayment data;

[0100] If the transaction record is missing or incomplete, the second deviation value of the written-off advance payment value is assigned to 2.5; if the difference between the transaction amount and the amount agreed in the contract exceeds the first preset threshold, the second deviation value of the written-off advance payment value is assigned to 2; if the actual payee corresponding to the transaction record is inconsistent with the payee specified in the contract, the second deviation value of the written-off advance payment value is assigned to 2.5.

[0101] The step S5: determining whether the prepayment data belongs to false trade in the construction industry based on the prepayment data deviation value, the contract deviation value, the first deviation value of the written-off prepayment value, and the second deviation value, includes:

[0102] The deviation value of the advance payment data, the contract deviation value, the first deviation value and the second deviation value of the written-off advance payment value are summed up. If the result is greater than 3, it is determined that the advance payment data belongs to false trade in the construction industry.

[0103] The present invention provides a false trade early warning device for the construction industry, the device comprising:

[0104] The first module is configured to obtain prepayment data, determine the contract corresponding to the prepayment data through the contract database, and determine the deviation value of the prepayment data based on the contract content;

[0105] The second module is configured to take the contract corresponding to the advance payment data as the contract to be verified, obtain the construction industry project review report, query the construction industry project review report based on the subject matter of the contract to be verified, determine the business scope of the payee based on the third-party platform, and determine the contract deviation value based on the subject matter of the contract to be verified, the business scope of the payee and the query result;

[0106] The third module is configured to obtain the prepayment value that has been written off corresponding to the prepayment data and the invoice corresponding to the prepayment value that has been written off, wherein the prepayment value that has been written off is part or all of the prepayment that has been used after being offset by the invoice; and determine a first deviation value of the prepayment value that has been written off based on the invoice information;

[0107] The fourth module is configured to obtain the expenditure flow corresponding to each prepayment value that has been written off corresponding to the prepayment data; and determine the second deviation value of the prepayment value that has been written off based on the expenditure flow information;

[0108] Judgment module: configured to determine whether the prepayment data belongs to false trade in the construction industry based on the prepayment data deviation value, the contract deviation value, the first deviation value of the written-off prepayment value, and the second deviation value.

[0109] The present invention does not elaborate on some of the well-known technologies that belong to those skilled in the art.

[0110] The above specific embodiments only describe the design principle of the present invention. The shapes and names of the components in the description may be different and are not limited. Therefore, those skilled in the art in the field of the present invention may modify or replace the technical solutions recorded in the above embodiments; and these modifications and replacements do not deviate from the creative purpose and technical solutions of the present invention and should all fall within the protection scope of the present invention.

Claims

1. A false trade early warning method for the construction industry, characterized in that: include: Step S1: obtaining prepayment data, determining the contract corresponding to the prepayment data through a contract database, and determining a deviation value of the prepayment data based on the contract content; Step S2: taking the contract corresponding to the advance payment data as the contract to be verified, obtaining the construction industry project review report, querying the construction industry project review report based on the subject matter of the contract to be verified, determining the business scope of the payee based on the third-party platform, and determining the contract deviation value based on the subject matter of the contract to be verified, the business scope of the payee and the query result; Step S3: obtaining the prepayment value that has been written off corresponding to the prepayment data and the invoice corresponding to the prepayment value that has been written off, wherein the prepayment value that has been written off is part or all of the prepayment that has been used after being offset by the invoice; Determining a first deviation value of the written-off advance payment value based on the invoice information; Step S4: Obtain the expenditure flow corresponding to each written-off prepayment value corresponding to the prepayment data; Determining a second deviation value of the written-off prepayment value based on the expenditure flow information; Step S5: Determine whether the prepayment data belongs to false trade in the construction industry based on the prepayment data deviation value, the contract deviation value, the first deviation value of the written-off prepayment value, and the second deviation value.

2. The method according to claim 1, characterized in that The step S1: obtaining prepayment data, determining the contract corresponding to the prepayment data through a contract database, and determining the prepayment data deviation value based on the contract content, includes: Step S11: obtaining prepayment data, determining the payee of the prepayment, and determining the contract corresponding to the prepayment data through the contract database; Step S12: if there is no contract corresponding to the prepayment data in the contract database, determining that the prepayment data deviation value is 3; Otherwise, if there is a contract corresponding to the prepayment data in the contract database, the current business status and litigation information of the prepayment recipient are obtained through the third-party platform; if the current business status is "abnormal operation" and the litigation information is "unresolved major legal disputes", the prepayment data deviation value is determined to be 2; Otherwise, semantic analysis is performed on the contract corresponding to the advance payment data to extract the construction project type, payment amount, and payment cycle in the contract corresponding to the advance payment data; the construction project types include housing construction projects and infrastructure projects, and each construction project type corresponds to a proportional factor; the proportional factor is used to characterize the fluctuation range of the advance payment write-off ratio relative to the theoretical advance payment write-off ratio, and the proportional factors of different construction project types are different; the theoretical advance payment write-off ratio is equal to the number of days from the statistical date to the project establishment date of the construction project corresponding to the advance payment data divided by the project cycle, and the upper limit value is 1; obtain the ratio corresponding to the advance payment data The example factor, the current date and the value of the prepaid payment that has been written off, the value of the prepaid payment that has been written off is divided by the payment amount as the prepaid payment write-off ratio; based on the payment cycle, the theoretical prepaid payment write-off ratio corresponding to the current date is determined, based on the theoretical prepaid payment write-off ratio and the proportional factor, the fluctuation range of the theoretical prepaid payment write-off ratio is determined; if the prepaid payment write-off ratio is within the fluctuation range of the theoretical prepaid payment write-off ratio, the prepaid payment data deviation value is determined to be 0; otherwise, a first value is calculated, the first value is equal to the sum of the absolute values ​​of the differences between the prepaid payment write-off ratio and the two boundaries of the fluctuation range of the theoretical prepaid payment write-off ratio, and the prepaid payment data deviation value is set to be equal to the first value.

3. The method as claimed in claim 2, characterized in that The proportional factor for suppliers of construction raw materials is 0.8, the proportional factor for suppliers of machinery and equipment rental is 0.7, the proportional factor for suppliers of professional labor services is 0.6, the proportional factor for building materials processors is 0.75, the proportional factor for suppliers of logistics and warehousing services is 0.85, and the proportional factor for suppliers of design and consulting services is 0.

9.

4. The method according to claim 1, characterized in that The step S2: taking the contract corresponding to the advance payment data as the contract to be verified, obtaining the construction industry project review report, querying the construction industry project review report based on the subject matter of the contract to be verified, determining the business scope of the payee based on the third-party platform, and determining the contract deviation value based on the subject matter of the contract to be verified, the business scope of the payee and the query result, including: Step S21: taking the contract corresponding to the advance payment data as the contract to be checked; obtaining a construction industry project review report, wherein the construction industry project review report supports semantic query, and obtaining a query result, wherein the query result includes that the construction industry project review report is found and that the construction industry project review report is not found; Step S22: If the query result is that no construction industry project review report is found and at least one of the contract content, supplier qualification review, project progress, financial records, and risk assessment does not meet the preset conditions, then the contract deviation value is determined to be 3; If the query result is that no construction industry project review report is found and the contract content, supplier qualification review, project progress, financial records, and risk assessment all meet the preset conditions, then the contract deviation value is determined to be 1; If the query result is a construction industry project review report, the business scope of the payee and the tax amount of each business type in the business scope in the year when the contract to be verified is signed are determined based on the third-party platform; the cosine similarity between the subject matter of the contract to be verified and each word in the business scope of the payee is calculated; If the cosine similarities are all less than 0, the contract deviation value is determined to be 2; Otherwise, the cosine similarity with the largest cosine similarity value is taken as the maximum cosine similarity, and the business type corresponding to the maximum cosine similarity is determined, and the income amount is inferred based on the tax amount of the business type in the current year; the value of the prepayment data divided by the income amount of the business type in the current year is calculated as the income percentage; the maximum cosine similarity multiplied by the income percentage is taken as the confidence level of the contract to be verified, and the contract deviation value is the inverse of the confidence level.

5. The method according to claim 1, characterized in that The step S3: obtaining the prepayment value that has been written off corresponding to the prepayment data and the invoice corresponding to the prepayment value that has been written off, wherein the prepayment value that has been written off is part or all of the prepayment that has been used after being offset by the invoice; Determining a first deviation value of the written-off advance payment value based on the invoice information includes: Step S31: obtaining the consumption content of the invoice corresponding to the prepayment value that has been written off, and recording the invoice whose consumption content does not match the subject matter of the contract corresponding to the prepayment data as an abnormal invoice; Count the number of abnormal invoices; Step S32: Calculate the proportion of abnormal invoices to all invoices corresponding to the value of the prepaid payment that has been written off. If the proportion exceeds a first preset threshold, the deviation value of the prepaid payment that has been written off is recorded as 1; otherwise, the first deviation value of the prepaid payment that has been written off is assigned to the proportion of abnormal invoices to all invoices corresponding to the value of the prepaid payment that has been written off.

6. The method according to any one of claims 1 to 5, characterized in that The step S4: obtaining the expenditure flow corresponding to each written-off prepayment value corresponding to the prepayment data; Determining a second deviation value of the written-off prepayment value based on the expenditure flow information includes: Obtain the expenditure flow corresponding to each written-off prepayment value corresponding to the prepayment data; If the transaction record is missing or incomplete, the second deviation value of the written-off prepayment value is assigned to 2.5; if the difference between the transaction amount and the amount agreed in the contract exceeds the first preset threshold, the second deviation value of the written-off prepayment value is assigned to 2; if the actual payee corresponding to the transaction record is inconsistent with the payee specified in the contract, the second deviation value of the written-off prepayment value is assigned to 2.5; The step S5: determining whether the prepayment data belongs to false trade in the construction industry based on the prepayment data deviation value, the contract deviation value, the first deviation value of the written-off prepayment value, and the second deviation value, includes: The deviation value of the advance payment data, the contract deviation value, the first deviation value and the second deviation value of the written-off advance payment value are summed up. If the result is greater than 3, it is determined that the advance payment data belongs to false trade in the construction industry.

7. A false trade warning device for the construction industry, characterized in that: include: The first module is configured to obtain prepayment data, determine the contract corresponding to the prepayment data through the contract database, and determine the deviation value of the prepayment data based on the contract content; The second module is configured to take the contract corresponding to the advance payment data as the contract to be verified, obtain the construction industry project review report, query the construction industry project review report based on the subject matter of the contract to be verified, determine the business scope of the payee based on the third-party platform, and determine the contract deviation value based on the subject matter of the contract to be verified, the business scope of the payee and the query result; The third module is configured to obtain the prepayment value that has been written off corresponding to the prepayment data and the invoice corresponding to the prepayment value that has been written off, wherein the prepayment value that has been written off is part or all of the prepayment that has been used after being offset by the invoice; Determining a first deviation value of the written-off advance payment value based on the invoice information; The fourth module is configured to obtain the expenditure flow corresponding to each written-off prepayment value corresponding to the prepayment data; Determining a second deviation value of the written-off prepayment value based on the expenditure flow information; Judgment module: configured to determine whether the prepayment data belongs to false trade in the construction industry based on the prepayment data deviation value, the contract deviation value, the first deviation value of the written-off prepayment value, and the second deviation value.

8. A computer-readable storage medium, characterized in that: The storage medium stores a plurality of instructions; the plurality of instructions are used for a processor to load and execute the method as described in any one of claims 1 to 6.

9. An electronic device, characterized in that: The electronic device comprises: A processor, which is used to execute multiple instructions; A memory for storing a plurality of instructions; The plurality of instructions are used to be stored in the memory and loaded and executed by the processor according to any one of claims 1 to 6.

Images