Multi-source data fusion procurement compliance analysis method

Abstract

The invention discloses a procurement compliance analysis method based on multi-source data fusion, relates to the technical field of procurement analysis, and realizes multi-platform data fusion and summarization and compliance detection of a whole procurement process by aggregating multi-source data sources including data of a procurement system, a contract system, a financial system, a bidding system and the like to form a data warehouse. According to the procurement compliance analysis method based on multi-source data fusion, by designing the procurement compliance analysis method based on multi-source data fusion, a data warehouse is formed by aggregating multi-source data sources and performing structured processing, so that multi-platform data fusion and summarization are realized; according to the established data warehouse, compliance detection in a single-business process and cross-process business compliance detection are carried out, compliance detection of full-process coverage of purchasing is realized, detection result display is systematically provided, and compliance monitoring and early warning of the purchasing process are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of procurement analysis, and in particular to a procurement compliance analysis method based on multi-source data fusion. Background Art

[0002] With the development of the economy, the volume of procurement-related business of large state-owned enterprises, governments and public institutions has gradually increased. In order to achieve digital transformation, government enterprises and institutions have established a comprehensive management system for procurement, bidding, finance, contracts and other management tasks with the help of information technology. However, since the various management businesses are related and operate independently, multiple systems of the procurement process have been formed, and there is a problem of information islands, resulting in compliance testing of procurement compliance within a single system, and failure to combine the data of the entire procurement process system to conduct compliance testing of cross-process businesses. For this reason, this application proposes a procurement compliance analysis method with multi-source data fusion to solve the above problems. Summary of the invention

[0003] 1. Technical issues to be resolved

[0004] In view of the shortcomings of the prior art, the present invention provides a procurement compliance analysis method based on multi-source data fusion, which integrates the related data of multiple platforms to build a data warehouse for compliance detection of the entire procurement process, thereby solving the problems raised in the above background.

[0005] (II) Technical solution

[0006] To achieve the above objectives, the technical solution adopted by the present invention is: a procurement compliance analysis method based on multi-source data fusion, characterized in that: the analysis system comprises the following steps:

[0007] Step 1: The system provides a standardized interface for multi-system data docking, through which the data of each business platform and other data of the procurement business process are connected;

[0008] Step 2: After connecting the data of each system, sort out the data associations and process them to form a standardized structured data warehouse;

[0009] Step 3: Use the data warehouse built in step 2 as the data source for each test item to conduct compliance analysis of the entire procurement process;

[0010] Step 4: After testing the entire procurement process data through the test items in step 3, generate a procurement compliance test report to display the compliance status of each test item.

[0011] Preferably, in the step 2, data warehouse platform data is constructed, which includes procurement business data, other data, and commodity historical price ledger; wherein the procurement business data includes procurement platform data, bidding platform data, contract platform data, and financial platform data; other data includes construction platform data and third-party public platform data;

[0012] The system sorts out the data connections between various systems, structures the data of all connected platforms, establishes data associations, removes redundant data, and forms a data warehouse that integrates the data of purchase requisition ledgers, purchase order ledgers, bidding ledgers, contract ledgers, and financial ledgers based on the nodes of the entire procurement process, providing data support for subsequent compliance analysis.

[0013] In addition, the system collects and organizes historical transaction prices of purchased goods to form a historical price record ledger, providing a historical basis for the rationality of quotations and compliance of contract amounts.

[0014] Preferably, in step 3, the compliance detection system detection items include single business detection items, and the details are as follows:

[0015] (1) The designated manufacturer of the goods to be purchased shall be tested. The manufacturer's documents in the purchase requisition record shall be checked to see whether the reason is stated. If not, it is non-compliant.

[0016] (2) Procurement form compliance detection: Check whether the estimated price in the procurement ledger matches the procurement method. The system can flexibly configure the amount range of each procurement method. If they do not match, it is non-compliant.

[0017] (3) Bid collusion detection: by checking the bid price, bid documents, and electronic bidding information in the bidding information in the bidding ledger.

[0018] Preferably, the single service detection item in step 3 specifically includes:

[0019] (1) The system checks the consistency of the bid amounts of each bidding unit. If the bid amounts of more than two bidding units are the same, it is considered non-compliant.

[0020] (2) The system conducts similarity checks on the three major parts of the bid documents of each bidding unit, namely, the commercial bid, the technical bid, and the quotation request. If the similarity is too high, it is non-compliant. The system also checks for spelling errors in the bid documents of each unit. If there are multiple consistent errors in the bid documents, it is non-compliant.

[0021] (3) The system checks the consistency of each bidding unit’s electronic bid information, including the computer MAC address, cost software encryption lock serial number, and IP address. If there is any consistency, it is non-compliant.

[0022] Preferably, the details of the cross-process service detection items in step 3 are as follows:

[0023] (1) Detection of non-bids: The system combines the data of procurement ledger, bidding ledger and contract ledger to check whether there is bidding information in the corresponding procurement ledger and bidding ledger and whether the procurement method is correct based on the contract ledger amount for the three types of contracts stipulated by law: construction contracts with an estimated value of more than RMB 4 million, goods procurement contracts with an estimated value of more than RMB 2 million, and service procurement contracts with an estimated value of more than RMB 1 million. If the contract amount meets the bidding requirements but there is no corresponding information in the bidding ledger, it is non-compliant.

[0024] (2) Time compliance check of the bidding process. The system combines the bidding ledger and contract ledger data to check the time compliance of all processes from the bidding process to the contract signing process. If the time interval does not meet the national requirements, it is considered non-compliant.

[0025] (3) Bid collusion detection: The system combines the bidding records and the data information of the third-party public platform to detect the social security information of the bidding unit’s authorized person and the company’s related information. If the social security payment unit of the bidding authorized person does not match the bidding unit, it is not compliant. If the information provided by the third-party platform contains information such as the legal person and shareholders of two or more companies, it is not compliant.

[0026] (4) Bid rigging detection: The system compares the bid price in the bidder’s quotation list with the historical price record range by combining the bidding record and the historical price record. If the bid price is lower than the historical price lower limit or higher than the historical price upper limit by a certain percentage, it is considered non-compliant.

[0027] (5) Detection of false bidding: The system combines the bidding ledger, contract ledger and construction platform data to compare the construction record time with the bidding time and contract signing time. If construction is carried out before bidding, it is not in compliance with regulations.

[0028] (6) Contract omission and error detection: The system combines the contract information and payment information in the contract ledger and the financial ledger, and uses the contract information in the financial ledger to check the contract ledger. If the information does not match, the contract is incorrectly entered and is not compliant. If the contract information in the financial ledger has no matching record in the contract ledger, the contract is omit and is not compliant.

[0029] (III) Beneficial effects

[0030] The beneficial effects of the present invention are:

[0031] This procurement compliance analysis method based on multi-source data fusion is designed to form a data warehouse by aggregating multi-source data sources for structured processing, realize multi-platform data fusion and aggregation, and conduct compliance detection within a single business process and cross-process business compliance detection based on the constructed data warehouse, thereby realizing compliance detection covering the entire procurement process, and systematically providing display of detection results, effectively improving compliance monitoring and early warning of the procurement process. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of the system detection of the present invention;

[0033] Figure 2 This is a structural diagram of the data warehouse of the present invention;

[0034] Figure 3 This is a compliance test report diagram of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] like Figure 1-3 As shown, the present invention provides a technical solution: a procurement compliance analysis method based on multi-source data fusion, the steps of which are as follows Figure 1 As shown, the specific implementation steps are as follows:

[0037] Step 1: The system provides a standardized interface for multi-system data docking, through which the data of each business platform and other data of the procurement business process are docked;

[0038] Step 2: After connecting the data of each system, sort out the data associations and process them to form a standardized structured data warehouse;

[0039] In step 2, build the data warehouse platform data such as Figure 2 The data shown includes three parts: procurement business data, other data, and historical price records of goods; procurement business data includes procurement platform data, bidding platform data, contract platform data, and financial platform data; other data includes construction platform data and third-party public platform data.

[0040] The system sorts out the data connections between various systems, structures the data of all connected platforms, establishes data associations, removes redundant data, and forms a data warehouse that integrates the data of purchase requisition ledgers, purchase order ledgers, bidding ledgers, contract ledgers, and financial ledgers based on the nodes of the entire procurement process, providing data support for subsequent compliance analysis.

[0041] In addition, the system collects and organizes historical transaction prices of purchased goods to form a historical price record ledger, providing a historical basis for the rationality of quotations and compliance of contract amounts.

[0042] Step 3: Use the data warehouse built in step 2 as the data source for each test item to conduct compliance analysis of the entire procurement process

[0043] In step 3, the compliance detection system detection items include single business detection items and cross-process business detection items. Details are as follows:

[0044] 1. Single business detection item:

[0045] (1) The designated manufacturer of the goods to be purchased shall be tested. The manufacturer's documents in the purchase requisition record shall be checked to see whether the reason is stated. If not, it is non-compliant.

[0046] (2) Procurement form compliance detection: Check whether the estimated price in the procurement ledger matches the procurement method. The system can flexibly configure the amount range of each procurement method. If they do not match, it is non-compliant.

[0047] (3) Bid collusion detection: by checking the bid price, bid documents, and electronic bidding information in the bidding information in the bidding ledger.

[0048] The single business detection items in step 3 specifically include:

[0049] (1) The system checks the consistency of the bid amounts of each bidding unit. If the bid amounts of more than two bidding units are the same, it is considered non-compliant.

[0050] (2) The system conducts similarity checks on the three major parts of the bid documents of each bidding unit, namely, the commercial bid, the technical bid, and the quotation request. If the similarity is too high, it is non-compliant. The system also checks for spelling errors in the bid documents of each unit. If there are multiple consistent errors in the bid documents, it is non-compliant.

[0051] (3) The system checks the consistency of each bidding unit’s electronic bid information, including the computer MAC address, cost software encryption lock serial number, and IP address. If there is any consistency, it is non-compliant.

[0052] 2. Cross-process business detection items:

[0053] (1) Detection of non-bids: The system combines the data of procurement ledger, bidding ledger and contract ledger to check whether there is bidding information in the corresponding procurement ledger and bidding ledger and whether the procurement method is correct based on the contract ledger amount for the three types of contracts stipulated by law: construction contracts with an estimated value of more than RMB 4 million, goods procurement contracts with an estimated value of more than RMB 2 million, and service procurement contracts with an estimated value of more than RMB 1 million. If the contract amount meets the bidding requirements but there is no corresponding information in the bidding ledger, it is non-compliant.

[0054] (2) Time compliance check of the bidding process. The system combines the bidding ledger and contract ledger data to check the time compliance of all processes from the bidding process to the contract signing process. If the time interval does not meet the national requirements, it is considered non-compliant.

[0055] (3) Bid collusion detection: The system combines the bidding records and the data information of the third-party public platform to detect the social security information of the bidding unit’s authorized person and the company’s related information. If the social security payment unit of the bidding authorized person does not match the bidding unit, it is not compliant. If the information provided by the third-party platform contains information such as the legal person and shareholders of two or more companies, it is not compliant.

[0056] (4) Bid rigging detection: The system compares the bid price in the bidder’s quotation list with the historical price record range by combining the bidding record and the historical price record. If the bid price is lower than the historical price lower limit or higher than the historical price upper limit by a certain percentage, it is considered non-compliant.

[0057] (5) Detection of false bidding: The system combines the bidding ledger, contract ledger and construction platform data to compare the construction record time with the bidding time and contract signing time. If construction is carried out before bidding, it is not in compliance with regulations.

[0058] (6) Contract omission and error detection: The system combines the contract information and payment information in the contract ledger and the financial ledger, and uses the contract information in the financial ledger to check the contract ledger. If the information does not match, the contract is incorrectly entered and is not compliant. If the contract information in the financial ledger has no matching record in the contract ledger, the contract is omit and is not compliant.

[0059] Step 4: After testing the entire procurement process data through the test items in step 3, generate a procurement compliance test report such as Figure 3 , display the compliance status of each test item

[0060] The beneficial effect of the present invention is that the present invention designs a procurement compliance analysis method with multi-source data fusion, which forms a data warehouse by aggregating and structured processing of multi-source data sources, realizes multi-platform data fusion and aggregation, and performs compliance detection within a single business process and cross-process business compliance detection based on the constructed data warehouse, thereby realizing compliance detection covering the entire procurement process, and systematically providing a display of detection results, effectively improving compliance monitoring and early warning of the procurement process.

[0061] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A procurement compliance analysis method based on multi-source data fusion, characterized by: The analysis system includes the following steps: Step 1: The system provides a standardized interface for multi-system data docking, through which the data of each business platform and other data of the procurement business process are connected; Step 2: After connecting the data of each system, sort out the data associations and process them to form a standardized structured data warehouse; Step 3: Use the data warehouse built in step 2 as the data source for each test item to conduct compliance analysis of the entire procurement process; Step 4: After testing the entire procurement process data through the test items in step 3, generate a procurement compliance test report to display the compliance status of each test item.

2. According to claim 1, a procurement compliance analysis method based on multi-source data fusion is characterized by: In the step 2, the data warehouse platform data is constructed, which includes procurement business data, other data, and commodity historical price ledgers; the procurement business data includes procurement platform data, bidding platform data, contract platform data, and financial platform data; other data includes construction platform data and third-party public platform data; The system sorts out the data connections between various systems, structures the data of all docked platforms, establishes data associations, removes redundant data, and forms a data warehouse that integrates the data of purchase requisition ledgers, purchase order ledgers, bidding ledgers, contract ledgers, and financial ledgers based on the nodes of the entire procurement process, providing data support for subsequent compliance analysis; In addition, the system collects and organizes historical transaction prices of purchased goods to form a historical price record ledger, providing a historical basis for the rationality of quotations and compliance of contract amounts.

3. The procurement compliance analysis method based on multi-source data fusion according to claim 2 is characterized by: In step 3, the compliance detection system detection items include single business detection items, details of which are as follows: (1) Test the designated manufacturer of the goods to be purchased. Check whether the manufacturer's document in the purchase requisition record specifies the reason. If not, it is non-compliant; (2) Procurement form compliance detection: Check whether the estimated price in the procurement ledger matches the procurement method. The system can flexibly configure the amount range of each procurement method. If they do not match, it is non-compliant; (3) Bid collusion detection: by checking the bid price, bid documents, and electronic bidding information in the bidding information in the bidding ledger.

4. The procurement compliance analysis method based on multi-source data fusion according to claim 3 is characterized by: The single service detection item in step 3 specifically includes: (1) The system checks the consistency of the bid amounts of each bidding unit. If the bid amounts of more than two bidding units are the same, it is considered non-compliant; (2) The system conducts similarity checks on the three major parts of the bid documents of each bidding unit, namely, the commercial bid, the technical bid, and the quotation request. If the similarity is too high, it will be considered non-compliant. The system also checks for spelling errors in the bid documents of each unit. If there are multiple consistent errors in the bid documents, it will be considered non-compliant. (3) The system checks the consistency of each bidding unit’s electronic bid information, including the computer MAC address, cost software encryption lock serial number, and IP address. If there is any consistency, it is non-compliant.

5. The procurement compliance analysis method based on multi-source data fusion according to claim 1 is characterized by: The details of the cross-process business detection items in step 3 are as follows: (1) Detection of non-bids: The system combines the data of procurement ledger, bidding ledger and contract ledger to check whether there is bidding information in the corresponding procurement ledger and bidding ledger and whether the procurement method is correct based on the contract ledger amount for the three types of contracts stipulated by law: construction contracts with an estimated value of more than RMB 4 million, goods procurement contracts with an estimated value of more than RMB 2 million, and service procurement contracts with an estimated value of more than RMB 1 million. If the contract amount meets the bidding requirements but there is no corresponding information in the bidding ledger, it is non-compliant; (2) Time compliance test of the bidding process. The system combines the bidding ledger and contract ledger data to test the time compliance of all the processes from the bidding process to the contract signing process. If the time interval does not meet the national requirements, it is considered non-compliant; (3) Bid collusion detection: The system combines the bidding record and the data information of the third-party public platform to detect the human resources and social security information of the bidding unit's bidding authorization person and the company's related information. If the social security payment unit of the bidding authorization person does not match the bidding unit, it is not compliant; if the information provided by the third-party platform shows correlation between the legal persons, shareholders, etc. of two or more companies, it is not compliant; (4) Bid rigging detection: the system compares the bid price in the bidder's bid list with the historical price record range by combining the bidding record and the historical price record. If the bid price is lower than the historical price lower limit or higher than the historical price upper limit by a certain percentage, it is considered non-compliant; (5) Detection of false bidding: the system combines the bidding ledger, contract ledger and construction platform data to compare the construction record time with the bidding time and contract signing time. If construction is carried out before bidding, it is not compliant; (6) Contract omission and error detection: The system combines the contract information and payment information in the contract ledger and the financial ledger, and uses the contract information in the financial ledger to check the contract ledger. If the information does not match, the contract is incorrectly entered and is not compliant. If the contract information in the financial ledger has no matching record in the contract ledger, the contract is omit and is not compliant.

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