CN120509393A

CN120509393A - Role-based contract review methods, devices, equipment, media and products

Info

Publication number: CN120509393A
Application number: CN202510506460.XA
Authority: CN
Inventors: 孙雪颜; 马飞; 陈金辉; 郭晓峰; 何敏
Original assignee: Kingdee Software China Co Ltd
Current assignee: Kingdee Software China Co Ltd
Priority date: 2025-04-22
Filing date: 2025-04-22
Publication date: 2025-08-19

Abstract

The present application relates to a role-based customized contract review method, apparatus, computer device, computer-readable storage medium, and computer program product. The method comprises the steps of obtaining user role information and contract data, carrying out role configuration according to a target role configuration module and the user role information to obtain a role examination list and a role examination flow, carrying out feature extraction on the contract data according to a pre-trained deep learning model and the role examination list to obtain role examination features, analyzing the contract data according to a pre-trained artificial intelligent model to obtain contract analysis data, and carrying out contract examination on the contract analysis data and the role examination features according to the role examination flow to obtain contract examination results. By adopting the method, the examination flow and the key point can be automatically adjusted according to the roles of different users, and personalized contract examination service is provided.

Description

Role customization-based contract review method, device, equipment, medium and product

Technical Field

The present application relates to the field of intelligent contract auditing technology, and in particular, to a role-based customized contract auditing method, apparatus, computer device, computer readable storage medium, and computer program product.

Background

Along with the development of intelligent contract auditing technology, many contract auditing works adopt the intelligent contract auditing technology to conduct intelligent auditing on the contract, but the contract auditing work of one enterprise usually involves multiple roles and departments, but in the prior art, the intelligent auditing design is only conducted on the content of the contract itself, and the user role service cannot be combined, so that the requirements of different enterprise roles on contract auditing cannot be met.

Disclosure of Invention

In view of the foregoing, there is a need for a role-based customized contract review method, apparatus, computer device, computer readable storage medium, and computer program product that can automatically adjust review flows and emphasis according to roles of different users, providing personalized contract review services.

In a first aspect, the present application provides a role-based customized contract review method, including:

acquiring user role information and contract data;

Performing role configuration according to the target role configuration module and the user role information to obtain a role examination list and a role examination flow;

Extracting the characteristics of the contract data according to the pre-trained deep learning model and the role examination list to obtain role examination characteristics;

Analyzing the contract data according to a pre-trained artificial intelligent model to obtain contract analysis data;

And carrying out contract examination on the contract analysis data and the character examination characteristics according to the character examination flow to obtain a contract examination result.

In one embodiment, the performing role configuration according to the target role configuration module and the user role information to obtain a role review list and a role review flow includes:

Performing role synchronization on the built-in roles of the target role configuration module according to the user role information to obtain a target built-in role;

acquiring the role examination flow and the role examination data from the target role configuration module according to the target built-in role;

And constructing the role examination list according to the role examination data.

In one embodiment, the role review data comprises review item annotation data and review rules, and the constructing the role review list according to the role review data comprises the following steps:

determining the to-be-annotated examination item according to the examination item annotation data;

and constructing the role examination list according to the examination rules and the examination items to be marked.

In one embodiment, the method further comprises:

Performing fine adjustment on the target role configuration module according to the contract analysis data to obtain a fine adjustment role configuration module;

Performing supplementary update on the fine-tuning role configuration module according to the role examination characteristics to obtain an updated role configuration module;

and updating the target role configuration module into the updated role configuration module.

In one embodiment, the feature extraction of the contract data according to the pre-trained deep learning model and the role review list to obtain role review features includes:

Preprocessing the contract data according to the deep learning model to obtain preprocessed contract data;

Determining target role feature requirements according to the role review list;

And performing role demand feature extraction on the preprocessing contract data according to the deep learning model and the target role feature demand to obtain the role examination feature.

In one embodiment, after the contract analysis data and the character review feature are subjected to contract review according to the character review process, the method further includes:

generating a report according to the contract examination result to obtain a contract examination report;

performing role risk assessment on the contract examination result according to the role information to obtain potential risk data;

A role suggestion is generated based on the risk potential data and the role information.

In a second aspect, the present application also provides a role-based customized contract review device, including:

the acquisition module is used for acquiring user role information and contract data;

The role configuration module is used for performing role configuration according to the target role configuration module and the user role information to obtain a role examination list and a role examination flow;

The feature extraction module is used for extracting the features of the contract data according to the pre-trained deep learning model and the role examination list to obtain role examination features;

The analysis module is used for analyzing the contract data according to the pre-trained artificial intelligent model to obtain contract analysis data;

And the contract checking module is used for checking the contract according to the contract analysis data and the character checking characteristics according to the character checking flow to obtain a contract checking result.

In a third aspect, the present application also provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:

acquiring user role information and contract data;

In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

acquiring user role information and contract data;

In a fifth aspect, the application also provides a computer program product comprising a computer program which, when executed by a processor, performs the steps of:

acquiring user role information and contract data;

The contract checking method, the device, the computer equipment, the computer readable storage medium and the computer program product based on role customization are used for acquiring user role information and contract data, performing role configuration according to a target role configuration module and the user role information to obtain a role checking list and a role checking flow, performing feature extraction on the contract data according to a pre-trained deep learning model and the role checking list to obtain role checking features, analyzing the contract data according to a pre-trained artificial intelligent model to obtain contract analysis data, and performing contract checking on the contract analysis data and the role checking features according to the role checking flow to obtain a contract checking result. Therefore, customized role configuration is provided for each role through the target role configuration module, and the most relevant contract terms aiming at the user role information can be rapidly identified and highlighted in the contract checking process, so that time is saved, the efficiency of the whole checking flow is improved, feature extraction is carried out on the contract data by utilizing the deep learning model and the role checking list, the contract data is analyzed according to the pre-trained artificial intelligent model, contract analysis data is obtained, the most relevant feature data and analysis data of the customized checking and the role checking list can be realized, errors caused by neglecting specific requirements of the roles can be reduced, and the accuracy of the follow-up contract checking step is ensured.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are needed in the description of the embodiments of the present application or the related technologies will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other related drawings may be obtained according to these drawings without inventive effort to those of ordinary skill in the art.

FIG. 1 is an application environment diagram of a role-based customized contract review method in one embodiment;

FIG. 2 is a flow diagram of a role-based customized contract review method in one embodiment;

FIG. 3 is a flow diagram of a role-based customized contract review method in one embodiment;

FIG. 4 is a flow chart of a role-based customized contract review method in another embodiment;

FIG. 5 is a block diagram of the structure of a role-based customized contract review arrangement in one embodiment;

fig. 6 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

The contract examination method based on role customization, provided by the embodiment of the application, can be applied to an application environment shown in figure 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. The server 104 obtains the character checking list and the character checking flow by obtaining the user character information and the contract data, performing character configuration according to the target character configuration module and the user character information, performing feature extraction on the contract data according to the pre-trained deep learning model and the character checking list to obtain character checking features, analyzing the contract data according to the pre-trained artificial intelligent model to obtain contract analysis data, and performing contract checking on the contract analysis data and the character checking features according to the character checking flow to obtain contract checking results. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices and portable wearable devices, where the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart vehicle devices, projection devices, and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The head-mounted device may be a Virtual Reality (VR) device, an augmented Reality (Augmented Reality, AR) device, smart glasses, or the like. The server 104 may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud computing services.

In an exemplary embodiment, as shown in fig. 2, a role-based customized contract review method is provided, and the method is applied to the server 104 in fig. 1 for illustration, and includes the following steps 202 to 210. Wherein:

step 202, user role information and contract data are acquired.

The user role information can be specific job identity information such as purchasing, selling, finance, technology and the like, and the contract data can be contract documents or other data storage contract data, and is not limited to the specific job identity information.

In some embodiments, the user login system may obtain the role information selected by the user during login, or may invoke the user role recognition module in other manners to recognize and confirm the user role information of the user used by the current system, which is not limited thereto.

In some embodiments, the contract data may be obtained by obtaining a contract document uploaded by the user, or the contract data required to be processed by the target user may be directly obtained from the contract data to be checked.

And 204, performing role configuration according to the target role configuration module and the user role information to obtain a role examination list and a role examination flow.

The target role configuration module is capable of being preset and used for dynamically configuring a role examination list and a role examination flow according to examination requirements and attention points of each role in the information of different user roles.

In some embodiments, performing role configuration according to the target role configuration module and the user role information to obtain a role examination list and a role examination flow, wherein the role examination list and the role examination flow are obtained by performing role synchronization on built-in roles of the target role configuration module according to the user role information to obtain target built-in roles, obtaining the role examination flow and the role examination data from the target role configuration module according to the target built-in roles, and constructing the role examination list according to the role examination data.

The role synchronization means that user role information is synchronized to a target role configuration module, so that the target role configuration module can perform customized configuration according to a current role.

In some embodiments, the built-in roles of the target role configuration module are subjected to role synchronization according to the user role information to obtain the target built-in roles, so that the target role configuration module can determine the examination requirements and the attention points of the current roles according to the current target built-in roles, and therefore customization configuration is performed more accurately according to the examination requirements and the attention points, and the role examination flow and the role examination data are acquired.

In some embodiments, the examination requirement and the focus point of the current role are determined according to the target built-in role, then the role examination flow and the role examination data meeting the examination requirement and the focus point are obtained from the target role configuration module, for example, if the user role information is a purchasing role, an examination list of the purchasing role is allocated, and in the examination flow, the purchasing examination flow is allocated automatically based on the purchasing role.

In some embodiments, the role review data includes review item annotation data and review rules, and constructing a role review list from the role review data includes determining to-be-annotated review items from the review item annotation data, and constructing the role review list from the review rules and to-be-annotated review items.

Wherein, the examination item labeling data is used for labeling examination items of contract data, and the examination rules are corresponding examination rules set for different roles.

In some embodiments, the item to be annotated is determined according to the item annotation data, and then the item to be annotated is combined with the audit rule, so that a role audit list aiming at the target built-in role can be constructed, and the audit efficiency of the subsequent contract audit is improved.

And 206, extracting features of the combined data according to the pre-trained deep learning model and the role review list to obtain role review features.

The pre-trained deep learning model is pre-trained according to the feature extraction data set related to each character type, and can be used for extracting the deep learning model related to the character according to the requirements of different characters, and the deep learning technology is not limited.

In some embodiments, feature extraction is performed on the contract data according to the pre-trained deep learning model and the role review list to obtain role review features, including preprocessing the contract data according to the deep learning model to obtain preprocessed contract data, determining target role feature requirements according to the role review list, and performing role requirement feature extraction on the preprocessed contract data according to the deep learning model and the target role feature requirements to obtain the role review features.

In some embodiments, the pre-processing of the contract data is performed according to the deep learning model with pre-training to obtain pre-processed contract data, so that redundant data in the contract data can be removed, and the processing efficiency of contract auditing is improved.

In some embodiments, the character review list is read by adopting a pre-trained deep learning model, the target character feature requirements are determined according to the character review list, namely, the review data list required to be extracted and the target character feature requirements can be quickly confirmed, and character requirement feature extraction is carried out on the pre-processed contract data according to the deep learning model and the target character feature requirements to obtain character review features, so that character review features required to be subjected to important review are automatically adjusted according to roles of different users, and personalized contract review services are provided.

In some specific embodiments, for example, in a role review list, for a legal role, features related to legal compliance, such as a term type, keywords of legal terms, etc., for a financial role, features related to finance, such as amount, payment condition, financial terms, etc., for a business role, features related to business execution, such as delivery time, quality of service terms, etc., need to be extracted, but are not limited thereto.

And step 208, analyzing the contract data according to the pre-trained artificial intelligence model to obtain contract analysis data.

The pre-trained artificial intelligent model can be obtained by adopting a GPT model to perform fine adjustment aiming at the legal field data, and can also be realized by adopting other artificial intelligent technologies, and the method is not limited to the method.

In some embodiments, the pre-trained GPT model may be loaded for in-depth understanding and analysis of contract text.

In some embodiments, analysis of the contract data according to a pre-trained artificial intelligence model may result in deep data regarding some of the contract data that may be further understood and inferred, and the artificial intelligence model may be better understood than the deep learning model and may be used to further infer and analyze the accuracy of the contract, facilitating subsequent risk assessment of the contract and providing risk advice analysis steps.

In some embodiments, the method further includes trimming the target role configuration module according to the contract analysis data to obtain a trimmed role configuration module, performing supplemental update on the trimmed role configuration module according to the role review feature to obtain an updated role configuration module, and updating the target role configuration module to the updated role configuration module.

In some embodiments, contract analysis data from artificial intelligence model analysis may further infer some censored item data associated with the persona, thereby enabling accurate fine-tuning of the target persona configuration module.

In some embodiments, when feature extraction can be performed on the same data based on the current user role information, a deep learning technology can be utilized to use the extracted role review feature related to the current user role information to supplement and update the role review list of the current user role, so that the accuracy of the subsequent role review list construction work related to the role is improved.

In this embodiment, by updating the fine-tuning target role configuration module, a dynamic configuration role review list and flow can be implemented, and the review requirements of different regions and industries may be different, and the requirements of the enterprise vary with the change of time and market conditions, so that the real-time performance of the scheme can be effectively ensured by adopting the target role configuration module dynamically updated in real time.

And 210, performing contract examination on the contract analysis data and the character examination characteristics according to the character examination flow to obtain a contract examination result.

The role examination process is an examination process realized by a role customization examination engine.

In some embodiments, the customized contract review step is automatically performed by the role customization review engine in combination with the contract analysis data and the role review feature to obtain a contract review result for the current role, so that key terms and potential risks of the corresponding role can be more accurately identified.

The contract checking method based on role customization comprises the steps of obtaining user role information and contract data, performing role configuration according to a target role configuration module and the user role information to obtain a role checking list and a role checking flow, performing feature extraction on the contract data according to a pre-trained deep learning model and the role checking list to obtain role checking features, analyzing the contract data according to a pre-trained artificial intelligent model to obtain contract analysis data, and performing contract checking on the contract analysis data and the role checking features according to the role checking flow to obtain contract checking results. Therefore, customized role configuration is provided for each role through the target role configuration module, and the most relevant contract terms aiming at the user role information can be rapidly identified and highlighted in the contract checking process, so that time is saved, the efficiency of the whole checking flow is improved, feature extraction is carried out on the contract data by utilizing the deep learning model and the role checking list, the contract data is analyzed according to the pre-trained artificial intelligent model, contract analysis data is obtained, the most relevant feature data and analysis data of the customized checking and the role checking list can be realized, errors caused by neglecting specific requirements of the roles can be reduced, and the accuracy of the follow-up contract checking step is ensured.

In an exemplary embodiment, as shown in fig. 3, in order to improve the readability of the contract review results and the specific review presentation effect, the role-based customized contract review method further includes steps 302 to 306. Wherein:

And 302, generating a report according to the contract examination result to obtain a contract examination report.

Wherein the contract review report may be a visual presentation of the contract review results.

In some embodiments, the contract review report is generated according to the contract review result, and the content of the contract review result, which is subjected to important review by the corresponding role, can be specially marked on the contract review report so as to generate the contract review report with higher readability.

And step 304, performing role risk assessment on the qualified examination result according to the role information to obtain potential risk data.

The risk potential data refers to some index data which do not meet a preset range or some examination item data which do not meet a preset condition in the contract examination result.

In some embodiments, the role risk assessment is performed on the contract inspection result according to the role information to obtain potential risk data, so that some role risk data related to the role information in the contract inspection result can be effectively determined, and potential risk data related to the role information is obtained. Thus, potential risk data related to a character can be effectively inferred using customized character risk assessment.

Step 306, generating role suggestions based on the risk potential data and the role information.

Wherein the character suggestion is a suggestion of a pointer to a specific character.

In some embodiments, processing recommendations for role information may be generated based on the risk potential data and the role information to improve the effectiveness and pertinence of the recommendations.

For a clearer understanding of the solution of the present application, the following is described with reference to fig. 4:

Firstly, as shown in fig. 4, when an operating user enters a contract checking system corresponding to the scheme, the scheme identifies the role information of the current operating user to obtain the role information of the user, and performs customized configuration through roles to realize role synchronization of the role information of the user, annotate checking items, confirm checking rules and other checking data, constructs a role checking list of the role information of the user to obtain a role checking list and a role checking flow, performs feature extraction on the combined data according to a pre-trained deep learning model and the role checking list to obtain role checking features, analyzes the contract data by adopting a pre-trained artificial intelligent model to obtain contract analysis data, and finally performs customized role checking flow through the role customized checking engine to obtain a contract checking result for identifying key terms and potential risks of the corresponding roles in the contract data.

Secondly, if the deep learning model finds new examination item characteristics in the contract examination process, the role customizing configuration module is updated in a supplementary mode, or when the artificial intelligent model finds configuration and flow which can be used for fine tuning the role customizing configuration module through analysis of contract data, the customizing configuration module is fine-tuned, so that the real-time performance of the scheme is improved.

Additionally, it should be noted that in an enterprise, the audit flow and collaboration of the same contract by the buyer, sales person, technician and financial staff typically involves the steps and sub-processes of (1) drafting the contract and preliminary audit (2) audit flow and role sub-process (3) collaboration and flow (4) final audit and signing.

Specifically, (1) contract drafting and preliminary auditing, the contract drafting step usually drafts the contract draft by a business department (such as sales or purchasing department) according to business requirements. And the preliminary audit is that after the drafting of the contract is finished, a responsible person of the drafting department carries out the preliminary audit first to ensure that the content of the contract meets the service requirement.

(2) The auditing flow and the role division are performed, the auditing content of the purchasing personnel can be whether the purchasing amount is within the budget, whether the qualification of the supplier meets the requirement, whether the delivery time and the quality standard meet the purchasing requirement, the auditing flow of the purchasing personnel can be the purchasing terms of the purchasing personnel auditing contract, the purchasing policy is ensured to be met, and for the key purchasing contract, the purchasing personnel may need to submit to an upper-level lead or a purchasing committee of the purchasing department for further auditing. The sales personnel can check the sales terms, such as payment mode, delivery time and after-sales service, and the credit rating of the customer meets the requirements of the company. The method comprises the steps of judging whether the contract accords with the sales strategy and market positioning of a company, checking the sales terms of the contract by a sales person, ensuring that the terms can be executed, and submitting the important sales contract to a superior lead or sales committee of a sales department for further checking. The technical staff checks whether the technical specification meets the project requirements, whether the technical delivery terms are clear, such as the delivery, installation and debugging of software or equipment, and whether the technical support and the service terms are reasonable. And a technical personnel auditing process, wherein the technical personnel audits technical terms of the contract, ensures that the technical requirements are clear and can be realized, and further auditing by technical experts or technical departments may be required for complex technical contracts. The financial staff checks whether the payment condition is reasonable, whether the contract amount is within the budget range, whether tax terms are compliant, and whether the clear acceptance and refund terms exist. And the financial staff auditing process comprises the steps of auditing the financial terms of the contract by the financial staff to ensure that the financial risk is controllable, and further auditing the important financial terms by a superior leader or financial committee which is required to be submitted to a financial department.

(3) The cooperation and circulation are realized, the contract can be intelligently circulated to the auditors with different roles according to preset rules by means of workflow, the auditors of different departments can audit the cooperation in sections or items in the system according to own responsibilities and authorities, the auditors can record audit opinions in the system, and other auditors can view and communicate in real time.

(4) The method comprises the steps of final auditing and signing, legal compliance auditing of a contract by a legal department, legal validity of contract terms is ensured, final approval of important contracts which may be submitted to a company advanced management layer or a board of directors is performed by an advanced management layer, and signing of the contract, wherein after the auditing is passed, the contract is signed by a contract signing department or a person and the other party.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a role-based custom contract checking device for realizing the role-based custom contract checking method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitations in one or more embodiments of the role-based customized contract checking device provided below may be referred to above for the limitation of the role-based customized contract checking method, which is not repeated here.

In one exemplary embodiment, as shown in FIG. 5, there is provided a role-based customized contract review apparatus 500 comprising an acquisition module 501, a role configuration module 502, a feature extraction module 503, an analysis module 504, and a contract review module 505, wherein:

an obtaining module 501, configured to obtain user role information and contract data;

the role configuration module 502 is configured to perform role configuration according to the target role configuration module and the user role information, so as to obtain a role examination list and a role examination flow;

The feature extraction module 503 is configured to perform feature extraction on the synthetic data according to the pre-trained deep learning model and the role review list, so as to obtain role review features;

The analysis module 504 is configured to analyze the contract data according to the pre-trained artificial intelligence model to obtain contract analysis data;

The contract checking module 505 is configured to perform contract checking on the contract analysis data and the character checking feature according to the character checking flow, so as to obtain a contract checking result.

In some embodiments, the role configuration module 502 is further configured to perform role synchronization on the built-in roles of the target role configuration module according to the user role information to obtain a target built-in role, obtain a role review flow and role review data from the target role configuration module according to the target built-in role, and construct a role review list according to the role review data.

In some embodiments, the role review data includes review item annotation data and review rules, and the role configuration module 502 is further configured to determine a review item to be annotated based on the review item annotation data, and construct a role review manifest based on the review rules and the review item to be annotated.

In some embodiments, the device further comprises a fine tuning update module for fine tuning the target character configuration module according to the contract analysis data to obtain a fine tuning character configuration module, performing supplementary update on the fine tuning character configuration module according to the character examination characteristics to obtain an updated character configuration module, and updating the target character configuration module to the updated character configuration module.

In some embodiments, the feature extraction module 503 is further configured to preprocess the contract data according to the deep learning model, to obtain preprocessed contract data;

determining target role feature requirements according to the role review list;

and carrying out character demand feature extraction on the preprocessing contract data according to the deep learning model and the target character feature demand to obtain character examination features.

In some embodiments, the device further comprises a risk assessment suggestion module for generating a report according to the contract examination result to obtain a contract examination report, performing role risk assessment on the contract examination result according to the role information to obtain potential risk data, and generating a role suggestion based on the potential risk data and the role information.

The contract checking device based on role customization comprises the steps of obtaining user role information and contract data, performing role configuration according to a target role configuration module and the user role information to obtain a role checking list and a role checking flow, performing feature extraction on the contract data according to a pre-trained deep learning model and the role checking list to obtain role checking features, analyzing the contract data according to a pre-trained artificial intelligent model to obtain contract analysis data, and performing contract checking on the contract analysis data and the role checking features according to the role checking flow to obtain contract checking results. Therefore, customized role configuration is provided for each role through the target role configuration module, and the most relevant contract terms aiming at the user role information can be rapidly identified and highlighted in the contract checking process, so that time is saved, the efficiency of the whole checking flow is improved, feature extraction is carried out on the contract data by utilizing the deep learning model and the role checking list, the contract data is analyzed according to the pre-trained artificial intelligent model, contract analysis data is obtained, the most relevant feature data and analysis data of the customized checking and the role checking list can be realized, errors caused by neglecting specific requirements of the roles can be reduced, and the accuracy of the follow-up contract checking step is ensured.

The various modules in the role-based customized contractual review devices described above may be implemented in whole or in part in software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one exemplary embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 6. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store a target character configuration module, a deep learning model, and an artificial intelligence model. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a role-based customized contract review method.

It will be appreciated by those skilled in the art that the structure shown in FIG. 6 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

In one exemplary embodiment, a computer device is provided that includes a memory having a computer program stored therein and a processor that when executed implements the steps of the role-based customized contract review method described above.

In one embodiment, a computer readable storage medium is provided having a computer program stored thereon which, when executed by a processor, implements the steps of the role-based customized contract review method described above.

In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of the role-based customized contract review method described above.

It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are both information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data are required to meet the related regulations.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile memory and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (RESISTIVE RANDOM ACCESS MEMORY, reRAM), magneto-resistive Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (PHASE CHANGE Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computation, an artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) processor, or the like, but is not limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the present application.

The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.

Claims

1. A contract review method based on role customization, characterized in that the method includes:

Obtain user role information and contract data;

Perform role configuration according to the target role configuration module and the user role information to obtain a role review list and a role review process;

Extracting features from the contract data based on the pre-trained deep learning model and the role review checklist to obtain role review features;

Analyzing the contract data according to a pre-trained artificial intelligence model to obtain contract analysis data;

A contract review is performed on the contract analysis data and the role review characteristics according to the role review process to obtain a contract review result.

2. The method according to claim 1, wherein the step of configuring roles according to the target role configuration module and the user role information to obtain a role review list and a role review process comprises:

Synchronize the built-in roles of the target role configuration module according to the user role information to obtain the target built-in role;

Acquiring the role review process and role review data from the target role configuration module according to the target built-in role;

The role review list is constructed based on the role review data.

3. The method according to claim 2, wherein the role review data comprises review item annotation data and review rules; and the step of constructing the role review checklist based on the role review data comprises:

Determining the review items to be marked according to the review item marking data;

The role review list is constructed according to the review rules and the review items to be marked.

4. The method according to claim 1, further comprising:

Fine-tuning the target role configuration module according to the contract analysis data to obtain a fine-tuned role configuration module;

Supplement and update the fine-tuning role configuration module according to the role review characteristics to obtain an updated role configuration module;

The target role configuration module is updated to the updated role configuration module.

5. The method according to claim 1, wherein extracting features from the contract data based on the pre-trained deep learning model and the role review checklist to obtain role review features comprises:

Determine target role characteristic requirements based on the role review checklist;

The pre-processed contract data is subjected to role requirement feature extraction according to the deep learning model and the target role feature requirements to obtain the role review feature.

6. The method according to claim 1, characterized in that after performing a contract review on the contract analysis data and the role review characteristics according to the role review process to obtain a contract review result, the method further comprises:

Generate a report based on the contract review results to obtain a contract review report;

Performing a role risk assessment on the contract review result according to the role information to obtain potential risk data;

A role suggestion is generated based on the potential risk data and the role information.

7. A contract review device based on role customization, characterized in that the device includes:

Acquisition module, used to obtain user role information and contract data;

A role configuration module, configured to configure roles according to the target role configuration module and the user role information, and obtain a role review list and a role review process;

A feature extraction module, configured to extract features from the contract data based on a pre-trained deep learning model and the role review list to obtain role review features;

An analysis module, configured to analyze the contract data based on a pre-trained artificial intelligence model to obtain contract analysis data;

The contract review module is used to perform a contract review on the contract analysis data and the role review characteristics according to the role review process to obtain a contract review result.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein the processor implements the steps of the method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.