Contract automation full-link management method and system

Abstract

The invention relates to the technical field of electronic contract management, in particular to a contract automatic full-link management method and system. The method comprises the following steps: inputting a storage address rule, a storage path rule and a delay pull time rule of an electronic contract of a current loan institution, and constructing a pull rule base; the big data platform matches and counts the difference between the electronic contract information and the loan order information; performing compensation pulling on the missing electronic contract according to the missing electronic contract details and the pulling rule base; the electronic contract is retrieved according to the missing electronic contract details and the pulling rule base, electronic contract information is read through the AI technology, and whether the electronic contract is valid or not is verified through the signature recognition technology. The invention provides an automatic full-link contract management method based on rule configuration, big data statistics and artificial intelligence recognition. Closed-loop management of unified pulling, missing recognition, automatic compensation and compliance verification of multi-mechanism electronic contracts is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electronic contract management, and in particular to a contract automatic full-link management method and system. BACKGROUND

[0002] With the rapid development of Internet finance and digital credit business, electronic contracts have become important legal documents for establishing the rights and obligations of both parties, especially in the loan assistance service mode, millions of electronic contracts are generated every day to record transaction terms and ensure the legality and traceability of transactions. However, under the existing technical conditions, electronic contracts still face many technical problems in many links such as generation, storage, pulling and verification: for example, due to the reasons such as the loan institutions not issuing contracts in time, the loan assistance platforms not pulling contracts in time, the storage path configuration not being uniform, the contract document information being incorrect, etc., a large number of electronic contracts are missing or invalid, which seriously affects the rights protection and compliance audit of both parties. At the same time, for the missing detection of electronic contracts, the automatic compensation pulling of missing contracts, the accuracy verification of document content and multi-dimensional statistical analysis, the current system relies on a large amount of manual intervention, which has the problems of high labor cost, low processing efficiency, poor verification accuracy, etc.

[0003] Specifically, the existing loan assistance companies often need to interface with hundreds of licensed loan institutions, and the electronic contracts of different institutions differ in storage address, access path, available time and interface method, etc., which makes it impossible to pull all contract data uniformly after the loan is completed. Secondly, in the face of millions of contract data per day, the traditional static query method based on databases such as PostgreSQL cannot quickly and accurately complete the statistical analysis of missing contracts. Thirdly, when the contract is confirmed as missing, manual communication with the loan institution is required to reissue the contract, and manual storage and archiving operations are required, which consumes a large amount of human resources. Finally, after the contract is retrieved, it is necessary to verify whether the contract document and the standard template are consistent, and the compliance verification process including the legality of the seal highly depends on manual comparison, which cannot be automated, restricting the safety and scalability of the overall business process. SUMMARY

[0004] The purpose of the present application is to provide a contract automatic full-link management method and system to solve the problems raised in the background.

[0005] To achieve the above purpose, the technical solution of the present application is: a contract automatic full-link management method, comprising:

[0006] S1, input the storage address rule, storage path rule and delayed pulling time rule of the current loan institution electronic contract, and construct a pulling rule library;

[0007] S2, the big data platform matches and statistics the difference between the electronic contract information and the loan order information, obtains the total contract quantity, the existing contract quantity, the missing contract quantity and the missing electronic contract details, and pushes the missing electronic contract details to the loan assistance institution at a fixed time;

[0008] S3, the loan assistance institution compensates and pulls the missing electronic contract according to the missing electronic contract details and the pulling rule library, and feeds back the compensation and pulling state;

[0009] S4, the loan assistance institution retrieves the electronic contract according to the missing electronic contract details and the pulling rule library, reads the electronic contract information through AI technology, fills in the complete and correct electronic contract information according to the electronic contract template and the missing electronic contract details, verifies whether the electronic contract is valid by using the signature recognition technology, and feeds back the verification result.

[0010] Preferably, in S1, the pulling rule library includes the electronic contract storage address, path, pulling time window, interface type and authentication method configured for each loan institution, and the pulling rule library is saved in the rule management database in a persistent configuration manner.

[0011] Preferably, in S2, the big data platform uses a multi-dimensional joint comparison strategy to analyze the difference between the electronic contract information and the loan order information in units of days, and generates an electronic contract missing detail list according to the difference;

[0012] In the electronic contract missing detail list, the contents include the total contract quantity, the existing contract quantity, the missing contract quantity and the missing electronic contract details.

[0013] Preferably, the multi-dimensional joint comparison strategy is a difference analysis method based on cross matching and field alignment of loan order dimension, contract generation dimension and contract pulling record dimension, which is used to identify whether there is a corresponding valid electronic contract in the loan business and generate a missing contract detail list, as follows:

[0014] S2.1, taking the loan order number, loan institution identifier and loan time in the loan order information table as the main index dimension, a loan business primary key set is constructed;

[0015] S2.2, taking the contract number, contract storage path and pulling time in the pulled electronic contract record as the reference dimension, cross-researching the primary key set;

[0016] S2.3, by comparing whether the loan order number exists in the pulling record, whether the contract pulling time is within the configured time range, and whether the contract storage path is valid, the contract missing state is determined;

[0017] S2.4, the records with the missing state are generated into a missing electronic contract detail table.

[0018] Preferably, in S3, in the process of compensating for the missing electronic contract pulling, if the detection pulling fails, an automatic retry mechanism is triggered, retrying at a set time interval until the maximum number of failures is reached, and generating an abnormal warning information after exceeding the retry threshold; if the detection pulling succeeds, the missing electronic contract details are deleted.

[0019] Preferably, in S3, the operation of compensating for pulling is executed by task scheduling engine, asynchronous queue processing, multi-threaded pulling, task priority management and failed task rollback.

[0020] Preferably, in S4, the process of identifying electronic contract information by AI technology is as follows: performing OCR identification on PDF and picture format contracts, comparing the identified structured fields with the contract template content at the field level, judging the field consistency and outputting a consistency score.

[0021] Preferably, in S4, the signature recognition technology includes region extraction of signature images in electronic contracts, signature text content recognition, signature time reading and digital signature legality verification, for judging whether the signature is real and effective.

[0022] Preferably, the specific method of the feedback verification result is as follows:

[0023] When the electronic contract identification result is invalid, it is marked as an invalid contract and stored in the abnormal information record table, and a warning reminder mechanism is triggered; when the electronic contract identification result is valid, the contract information is automatically archived to the database and the contract state field is updated to valid.

[0024] On the other hand, the present application provides a contract automation full-link management system, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to realize the contract automation full-link management method described above.

[0025] Compared with the prior art, the above technical scheme of the present application has the following beneficial technical effects:

[0026] 1. In the present application, based on the unified configuration and automatic scheduling mechanism of multi-institution electronic contract pulling rules, the problem of inconsistent electronic contract pulling caused by different loan institutions contract formats, paths and times can be solved.

[0027] 2. In the present application, through statistical analysis of big data platform and artificial intelligence identification technology, the consistency and legality of electronic contract documents and signatures are verified, precise identification and automatic compensation pulling of large-scale contract missing are realized, and the full-process verification ability of electronic contracts in terms of legal effectiveness and compliance is guaranteed. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 Flow chart of an embodiment of the present application. DETAILED DESCRIPTION

[0029] Embodiment one, as shown in the figure, the contract automation full-link management method proposed by the present application, the specific implementation steps are as follows: Figure 1

[0030] S1, input the storage address rule, storage path rule and delay pull time rule of the current loan institution electronic contract, and construct the pull rule library;

[0031] In this embodiment S1, the pull rule library includes the electronic contract storage address, path, pull time window, interface type and authentication method configured for each loan institution, and the pull rule library is saved in the rule management database in a persistent configuration manner.

[0032] In this embodiment, the pull rule library supports dynamic field mapping configuration and protocol adaptation plug-in mechanism, matches the interface fields through JSON or YAML structured rule description syntax, and automatically adapts RESTful interface, SFTP pull mode or encrypted interface data through plug-in mechanism; the pull rule library supports hot update mechanism in system running, and the rules are managed through version control and change log after configuration change, and the rules are checked and the system is automatically triggered to take effect after configuration change.

[0033] S2, the big data platform matches and statistics the difference between the electronic contract information and the loan order information, obtains the total contract quantity, the existing contract quantity, the missing contract quantity and the missing electronic contract details, and pushes the missing electronic contract details to the loan assistance institution at regular intervals;

[0034] In this embodiment S2, the big data platform uses multi-dimensional joint comparison strategy to analyze the difference between the electronic contract information and the loan order information in units of days, and generates an electronic contract missing detail list according to the difference;

[0035] Among them, the content of the electronic contract missing detail list includes the total contract quantity, the existing contract quantity, the missing contract quantity and the missing electronic contract details.

[0036] In this embodiment, the multi-dimensional joint comparison strategy is a difference analysis method based on cross matching and field alignment of loan order dimension, contract generation dimension and contract pull record dimension, which is used to identify whether there is a corresponding effective electronic contract in the loan business, and generate a missing contract detail list, as follows:

[0037] ​S2.1, taking the loan order number, loan institution identifier and loan time in the loan order information table as the main index dimension, a loan business primary key set is constructed;

[0038] S2.2, taking the contract number, contract storage path and pull time in the pulled electronic contract record as the reference dimension, cross-referencing of the primary key set is performed;

[0039] S2.3, by comparing whether the loan order number exists in the pull record, whether the contract pull time is within the configured time range, and whether the contract storage path is valid, the contract missing state is determined;

[0040] S2.4, the record of which the missing state is established is generated into a missing electronic contract detail table.

[0041] In the embodiment, the missing electronic contract detail table further includes a missing classification field and a traceability field, the missing classification field includes type identifiers such as no contract issued, interface timeout, path configuration error, etc., and the traceability field includes information such as original loan order number, failed interface call log number and pull retry number, etc., which are used to support subsequent contract exception compensation, system monitoring and contract accountability management.

[0042] In the embodiment, the multi-dimensional joint comparison strategy adopts a primary key mapping mechanism based on a hash index and a distributed reconciliation calculation model based on a MapReduce framework, which supports batch comparison, exception extraction and distributed detail aggregation.

[0043] In the embodiment, in the process of pushing the missing electronic contract details to the loan assisting institutions, a message queue pushing mechanism based on Kafka or an HTTP interface return mechanism is used to realize data synchronization, and the pushing frequency can be daily timing or exception triggering.

[0044] S3, the loan assisting institutions compensate and pull the missing electronic contracts according to the missing electronic contract details and the pull rule library, and feed back the compensation pull state;

[0045] In the embodiment S3, in the process of compensating and pulling the missing electronic contracts, if the pull fails, an automatic retry mechanism is triggered, and the retry is performed at a set time interval until the maximum number of failures is reached, and an exception warning information is generated after the retry threshold is exceeded; if the pull is successful, the missing electronic contract details are deleted.

[0046] In the embodiment S3, the compensation pull operation is executed by means of task scheduling engine, asynchronous queue processing, multi-threaded pull, task priority management and failed task rollback.

[0047] In this embodiment, during the compensation pulling process, the system will capture the failure reason information when detecting the pulling failure and record it to the failure tracking log, including but not limited to: interface timeout, interface return empty, file storage path abnormal, authentication failure or rule parameter mismatch. The system automatically marks the fault level based on the failure type, and serves as the basis for subsequent pulling retry strategy adjustment or manual troubleshooting.

[0048] In this embodiment, the task scheduling engine supports dynamic priority allocation based on the pulling task source agency, historical failure times, early warning level and other information. The scheduler will automatically adjust the number of concurrent threads and the length of the queue when the task is issued according to the current system load.

[0049] S4, the loan agency retrieves the electronic contract according to the missing electronic contract details and the pulling rule library, reads the electronic contract information through AI technology, fills in the complete and correct electronic contract information according to the electronic contract template and the missing electronic contract details, verifies whether the electronic contract is valid using signature recognition technology, and feeds back the verification result;

[0050] In this embodiment S4, the process of AI technology to identify electronic contract information is as follows: performing OCR identification on PDF and picture format contracts, comparing the identified structured fields with the contract template content at the field level, judging the field consistency and outputting a consistency score.

[0051] In this embodiment S4, the signature recognition technology includes region extraction of signature images in the electronic contract, signature text content identification, signature time reading and digital signature legality verification, which is used to judge whether the signature is real and effective.

[0052] In this embodiment, the specific method of the feedback verification result is as follows:

[0053] When the electronic contract recognition result is invalid, it is marked as an invalid contract and stored in the abnormal information record table, and the early warning reminder mechanism is triggered at the same time; when the electronic contract recognition result is valid, the contract information is automatically archived to the database and the contract state field is updated to valid.

[0054] In the present embodiment, when comparing the structured fields of the electronic contract with the contract template fields, a fuzzy matching mechanism and key field priority weight setting are introduced, allowing for slight adjustment of field order, approximate matching of similar fields, or content tolerance identification; the digital signature legality verification includes checking whether the signature is from a trusted certificate authority, whether it has a complete timestamp chain and tamper-proof marking, and simultaneously conducting double matching with the original signature event hash value registered in the business side storage record; during the verification process, the contracts that fail to be identified are classified and warned according to problem type and risk level, and the warning levels are divided into three categories: slight abnormality, structural abnormality, and serious signing abnormality; the system triggers different response strategies according to the level, including regular re-inspection, manual review prompt.

[0055] In embodiment two, the present application proposes a contract automation full-link management system, which is applied to the contract automation full-link management method proposed in embodiment one, and includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to realize the contract automation full-link management method in embodiment one.

[0056] The embodiments of the present application are described in detail above in combination with the drawings, but the present application is not limited thereto, and various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the purpose of the present application.

Claims

1. A method for automated end-to-end contract management, characterized in that, Includes the following steps: S1. Enter the storage address rules, storage path rules, and delayed retrieval time rules of the current lending institution's electronic contracts to build a retrieval rule base; S2. The big data platform matches and analyzes the differences between electronic contract information and loan order information to obtain the total number of contracts, the number of existing contracts, the number of missing contracts, and the details of missing electronic contracts. The details of missing electronic contracts are then pushed to the loan assistance institution on a regular basis. S3. The loan assistance institution retrieves the missing electronic contracts based on the details of the missing electronic contracts and the retrieval rule base, and provides feedback on the status of the retrieval. S4. The loan assistance institution retrieves the electronic contract based on the missing electronic contract details and the rule base, reads the electronic contract information using AI technology, fills in the complete and correct electronic contract information based on the electronic contract template and the missing electronic contract details, verifies the validity of the electronic contract using signature recognition technology, and provides feedback on the verification results.

2. The method for automated end-to-end contract management according to claim 1, characterized in that: In step S1, the rule base retrieval includes the electronic contract storage address, path, retrieval time window, interface type, and authentication method configured for each lending institution. The rule base is retrieved and saved to the rule management database in a persistent configuration manner.

3. The method for automated end-to-end contract management according to claim 2, characterized in that: In S2, the big data platform uses a multi-dimensional joint comparison strategy to analyze the differences between electronic contract information and loan order information on a daily basis, and generates a list of missing details of electronic contracts based on the differences. The list of missing electronic contracts includes the total number of contracts, the number of existing contracts, the number of missing contracts, and details of the missing electronic contracts.

4. The method for automated end-to-end contract management according to claim 3, characterized in that: The multi-dimensional joint comparison strategy is a difference analysis method based on cross-matching and field alignment of loan order dimensions, contract generation dimensions, and contract retrieval record dimensions. It is used to identify whether there are corresponding valid electronic contracts in the loan business and generate a list of missing contract details, as follows: S2.1 Construct a primary key set for loan disbursement business using the loan order number, loan institution identifier, and loan disbursement time in the loan order information table as the main index dimensions; S2.

2. Using the contract number, contract storage path, and retrieval time in the retrieved electronic contract records as reference dimensions, perform a cross-retrieval of the primary key set; S2.

3. Determine the contract missing status by comparing whether the loan order number exists in the retrieved records, whether the contract retrieval time is within the configured time range, and whether the contract storage path is valid. S2.4 Generate a list of missing electronic contracts for records with missing status.

5. The method for automated end-to-end contract management according to claim 4, characterized in that: In step S3, during the process of compensating for missing electronic contracts, if a failure is detected, an automatic retry mechanism is triggered, and the retry is performed at set time intervals until the maximum number of failures is reached. An abnormal warning message is generated after the retry threshold is exceeded. If the detection is successful, the missing electronic contract details are deleted.

6. The method for automated end-to-end contract management according to claim 5, characterized in that: In S3, the compensation fetching operation is executed through a task scheduling engine, asynchronous queue processing, multi-threaded fetching, task priority management, and rollback of failed tasks.

7. The method for automated end-to-end contract management according to claim 6, characterized in that: In S4, the process of AI technology recognizing electronic contract information is as follows: OCR recognition is performed on PDF and image format contracts, the recognized structured fields are compared with the contract template content at the field level, the field consistency is judged, and a consistency score is output.

8. The method for automated end-to-end contract management according to claim 7, characterized in that: In S4, the signature recognition technology includes region extraction of the signature image in the electronic contract, recognition of the signature text content, reading of the signature time, and verification of the legality of the digital signature, which is used to determine whether the signature is genuine and valid.

9. The method for automated end-to-end contract management according to claim 8, characterized in that: The specific method for providing feedback verification results is as follows: When the electronic contract identification result is invalid, it is marked as an invalid contract and stored in the abnormal information record table, and an early warning reminder mechanism is triggered at the same time; when the electronic contract identification result is valid, the contract information is automatically archived to the database and the contract status field is updated to valid.

10. A contract automation end-to-end management system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: The processor executes a computer program to implement the contract automation end-to-end management method as described in any one of claims 1-9.

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