Contract review method, terminal device and computer program product

Abstract

The invention is suitable for the technical field of data processing, and provides a contract review method, terminal equipment and a computer program product, and the method comprises the steps: setting contract discrimination models of different role sites, and during contract review, using different contract discrimination models to review the same contract at different sites, obtaining the risk discrimination results of the contracts in different sites; and obtaining a balance degree index of the contract data and a contract modification suggestion by comparing the risk degrees of terms in the risk judgment results. According to the method, the contract judgment model is used for examining the contract, the manual examination process is omitted, the automation degree of contract examination is improved, and then the contract examination efficiency is improved. Besides, contract discrimination models of different role sites are set, and the contract is audited from the different role sites, so that the limitation of contract audit is avoided, all-around and antagonistic risk insight of contract audit is realized, and the accuracy of contract audit is improved.

Description

Technical Field

[0001] This application belongs to the field of data processing technology, and in particular relates to a contract review method, terminal equipment, and computer program product. Background Technology

[0002] Contracts are the core vehicle of commercial activities, and the rigor, legality, and compliance of their terms directly affect a company's operational risks and interests. Currently, in the vast majority of companies and institutions, contract review still relies primarily on manual methods by legal personnel or professional lawyers. Reviewers need to read the entire contract word by word, identify key clauses, and compare them with internal regulations and laws, resulting in long review cycles, low efficiency, and severely impacting the speed of business operations. Summary of the Invention

[0003] This application provides a contract review method, terminal device, and computer program product, which can solve the problem of low contract review efficiency.

[0004] In a first aspect, embodiments of this application provide a contract review method, including: Obtain the contract data to be reviewed and the user's role information in the contract data; The contract data is input into multiple contract discrimination models. Each contract discrimination model performs a risk review on the terms in the contract data from its own set role position, and obtains the risk discrimination result output by each contract discrimination model. The different contract discrimination models set different role positions, and the risk discrimination result contains the risk level of each term in the corresponding role position. By comparing the risk levels of the clauses in each of the aforementioned risk assessment results, a balance index for the contract data is obtained, along with contract modification suggestions matching the user's role information. The balance index represents the fairness of the contract data.

[0005] This application establishes contract discrimination models with different role perspectives. During contract review, different models are used to examine the same contract from different standpoints, yielding risk assessment results from these varying perspectives. Finally, by comparing the risk levels of clauses in each risk assessment result, a balance index of the contract data is obtained, along with contract modification suggestions matched to the user's role information. This application uses contract discrimination models to review contracts, eliminating manual review processes, increasing the automation level of contract review, and thus improving efficiency. Furthermore, by establishing contract discrimination models with different role perspectives, this application avoids the limitations of traditional contract review, achieving comprehensive and adversarial risk insight, and improving the accuracy of contract review.

[0006] In one possible implementation of the first aspect, a balance index of the contract data is obtained by comparing the risk levels of the clauses in each of the risk assessment results, including: By comparing the risk levels of the clauses in each of the aforementioned risk assessment results, conflicting clauses in the contract data are identified, wherein the conflicting clauses are those with different risk levels in different roles and positions. Based on the content of the conflict clauses and the degree of risk of the conflict clauses in the risk assessment results, calculate the risk assessment value of the contract data in each of the respective roles and positions; Based on each of the aforementioned risk assessment values, the fairness of the contract data is evaluated to obtain the balance index of the contract data.

[0007] In this application, conflict clauses are clauses that are likely to cause disputes among the parties to the contract. First, the disputed clauses are identified based on the risk assessment results. Then, the risk level of the disputed clauses in the contract data is determined. Finally, a balance index is calculated based on the risk level of the disputed clauses, so that the calculated balance index can be matched with the risk level of the contract.

[0008] In one possible implementation of the first aspect, the calculation of the risk assessment value borne by the contract data in each of the respective roles, based on the content of the conflict clause and the risk level of the conflict clause in the risk assessment result, includes: For each of the aforementioned roles and positions, based on the risk assessment results, the risk quantification value of the conflict clause is determined according to the risk level of the conflict clause in the risk assessment results; Determine the global weight corresponding to the conflicting clause based on the clause type of the conflicting clause; Based on the context of the contract data, determine the weight scaling factor for the conflict clause; Based on the risk quantification value of the conflict clause, the global weight, and the weight scaling factor, the risk assessment value of the contract data in the role's position is determined.

[0009] In one possible implementation of the first aspect, the assessment of the fairness of the contract data based on each of the risk assessment values ​​to obtain a balance index of the contract data includes: Calculate the standard deviation and average value of each of the risk assessment values; The balance index of the contract data is calculated based on the standard deviation and the mean.

[0010] In one possible implementation of the first aspect, calculating the balance index of the contract data based on the standard deviation and the mean includes: Based on the standard deviation and the mean, calculate the initial balance of the contract data; Based on the risk quantification value of the conflicting clause in different risk assessment results, calculate the risk difference of the conflicting clause in different risk assessment results; Determine the conflict penalty factor based on the risk difference of all the aforementioned conflict clauses; The initial balance is corrected using the conflict penalty factor to obtain the balance index of the contract data.

[0011] In one possible implementation of the first aspect, determining the conflict penalty factor based on the risk difference of all the conflict clauses includes: The composite weight of the conflicting clause is obtained by multiplying the global weight of the conflicting clause by the weight scaling factor. The conflict penalty factor is determined based on the risk difference of all the aforementioned conflict clauses and all the aforementioned composite weights.

[0012] In one possible implementation of the first aspect, determining the conflict penalty factor based on the risk difference of all the conflict clauses and all the composite weights includes: Based on the risk difference of all the conflict clauses and all the composite weights, a conflict penalty factor is determined using a penalty factor calculation model. The penalty factor calculation model is as follows: , Let n be the conflict penalty factor, and n be the total number of conflicting clauses. For the risk difference of the i-th conflict clause, The composite weight of the i-th conflicting clause, This is the preset maximum conflict value.

[0013] In one possible implementation of the first aspect, after obtaining the contract data to be reviewed and the user's role information, the method further includes; Extract key elements from the contract data to generate structured contract data; Accordingly, the contract data is input into multiple contract discrimination models, and each of the contract discrimination models performs a risk review on the terms in the contract data from its own defined role, resulting in a risk discrimination result output by each contract discrimination model, including: Structured contract data is input into multiple contract discrimination models. Each contract discrimination model performs a risk review on the terms in the contract data from its own defined role, and the risk discrimination result output by each contract discrimination model is obtained.

[0014] Secondly, embodiments of this application provide a contract review apparatus, comprising: The data acquisition module is used to acquire the contract data to be reviewed and the user's role information in the contract data; The contract review module is used to input the contract data into multiple contract discrimination models. Each contract discrimination model performs a risk review on the terms in the contract data from its own set role position, and obtains the risk discrimination result output by each contract discrimination model. The different contract discrimination models set different role positions, and the risk discrimination result contains the risk level of each term in the corresponding role position. The results output module is used to compare the risk levels of the clauses in each of the risk assessment results to obtain the balance index of the contract data and contract modification suggestions matching the user's role information, wherein the balance index represents the fairness of the contract data.

[0015] Thirdly, embodiments of this application provide a terminal device, including: 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 implement the contract review method described in any one of the first aspects above.

[0016] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the contract review method described in any one of the first aspects above.

[0017] Fifthly, embodiments of this application provide a computer program product that, when run on a terminal device, causes the terminal device to execute the contract review method described in any one of the first aspects above. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the structure of contract review provided in an embodiment of this application; Figure 2 This is a flowchart illustrating a contract review method provided in one embodiment of this application; Figure 3 This is a flowchart illustrating a method for determining the balance index provided in an embodiment of this application; Figure 4 This is a flowchart illustrating a method for contract risk assessment provided in an embodiment of this application; Figure 5 This is a flowchart illustrating a method for determining the balance index provided in another embodiment of this application; Figure 6 This is a flowchart illustrating a method for determining a balance index using a conflict penalty factor, provided in an embodiment of this application. Figure 7 This is a schematic diagram of the structure of a contract review device provided in one embodiment of this application; Figure 8 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. Detailed Implementation

[0020] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0021] References to "one embodiment" or "some embodiments" in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized.

[0022] Contracts are the core vehicle of commercial activities, and the rigor, legality, and compliance of their terms directly affect a company's operational risks and interests. Therefore, accurate contract review is crucial when signing a contract. Currently, contract review still primarily relies on manual methods by legal personnel or professional lawyers. While this traditional manual review model has certain advantages in experience-based judgment and handling complex situations, its inherent limitations are becoming increasingly apparent, becoming a bottleneck restricting the improvement of operational efficiency and management level for enterprises. For example, manual review suffers from low efficiency, high labor costs, difficulty in standardizing review criteria, poor consistency in review quality, and easy omission of risk points.

[0023] Based on the above problems, this application proposes a contract review method that automatically reviews contracts using a trained large model, thereby improving the efficiency and accuracy of contract review.

[0024] Specifically, refer to Figure 1 The methodology of this application will be described.

[0025] This application constructs contract discrimination models based on different roles and positions, such as a contract discrimination model based on the position of Party A, a contract discrimination model based on the position of Party B, and a contract discrimination model based on a neutral position. The method of this application will be introduced below using the contract discrimination model based on the position of Party A and the discrimination model based on the position of Party B.

[0026] During the review process, the same contract data is input into both the client's (Party A's) and the contractor's (Party B's) contract assessment models for risk evaluation, yielding risk assessment results for each model. Finally, the risk game theory module synthesizes the risk assessment results from all models to determine the balance index of the contract under review, as well as contract modification suggestions from the user's perspective. The results display module then shows the balance index and contract modification suggestions for user review.

[0027] In addition, the generated contract modification suggestions and balance index can be used as training samples to further train the contract discrimination model, resulting in a more accurate contract discrimination model.

[0028] The following combination Figure 2 The contract review method of this application embodiment will be described in detail.

[0029] Figure 2 A schematic flowchart illustrating the contract review method provided in this application is shown, with reference to... Figure 2 The method is described in detail below: S101, Obtain the contract data to be reviewed and the user's role information in the contract data.

[0030] In this embodiment, the contract data is text data. After obtaining the contract data, key elements are extracted to generate structured contract data. Specifically, Natural Language Processing (NLP) and Optical Character Recognition (OCR) technologies are used to transform the unstructured contract data into structured contract data for subsequent processing.

[0031] Key elements may include the contracting parties, the subject matter, the amount, payment terms, delivery time, liability for breach of contract, and confidentiality clauses.

[0032] The user's role information in the contract data can be Party A, Party B, third party, etc.

[0033] S102, the contract data is input into multiple contract discrimination models. Each contract discrimination model performs a risk review on the terms in the contract data from its own set role position, and obtains the risk discrimination result output by each contract discrimination model. The different contract discrimination models set different role positions, and the risk discrimination result contains the risk level of each term in the corresponding role position.

[0034] In this embodiment, the roles and positions can include the position of Party A, the position of Party B, and a neutral position. The contract judgment model from Party A's perspective reviews the contract data from Party A's point of view, determining the degree of risk of the terms in the contract data for Party A. The contract judgment model from Party B's perspective reviews the contract data from Party B's point of view, determining the degree of risk of the terms in the contract data for Party B.

[0035] Specifically, contract judgment models can be used to determine the core objectives (core interests), risk appetite and advantageous terms, and negotiation bottom lines.

[0036] From the perspective of Party A, core objectives may include cost control and payment security; risk appetite may include avoiding payment delays and non-compliance with quality standards; and advantageous terms may include strict liability for breach of contract and acceptance criteria.

[0037] From the perspective of Party B, core objectives may include rapid payment and reduced liability; risk appetite may include avoiding payment delays and unlimited liability; advantageous terms may include advance payments and liability caps.

[0038] In this embodiment, the contract discrimination model is trained based on sample data. Sample data may include historical contracts, historical precedents, and industry standards.

[0039] In this embodiment, multiple contract discrimination models process the same contract data in parallel without interfering with each other, simulating the scenario of lawyers from various parties reviewing contracts, thereby improving work efficiency.

[0040] S103, compare the risk levels of the clauses in each of the risk assessment results to obtain the balance index of the contract data and the contract modification suggestions matching the user's role information, wherein the balance index represents the fairness of the contract data.

[0041] In this embodiment, the risk level can include high risk, medium risk, and low risk.

[0042] In this embodiment, the balance index is used to measure the evenness of risk distribution among the various roles.

[0043] In one implementation, the method for calculating the balance index may include: Find the number of clauses categorized as low-risk, medium-risk, and high-risk in each risk assessment result. Take a weighted sum of the numbers of low-risk, medium-risk, and high-risk clauses to obtain the contract risk value corresponding to the role's position in the risk assessment. Calculate the balance index based on the ratio of the contract risk values ​​for different role positions.

[0044] For example, if the weight of low risk is 2, the weight of medium risk is 3, and the weight of high risk is 5, and the risk assessment result output by the contract assessment model from Party A's perspective shows 10 low-risk clauses, 6 medium-risk clauses, and 2 high-risk clauses, then the contract risk value from Party A's perspective is 10×2 + 6×3 + 2×5 = 48. If the risk assessment result output by the contract assessment model from Party B's perspective shows 9 low-risk clauses, 7 medium-risk clauses, and 2 high-risk clauses, then the contract risk value from Party A's perspective is 9×2 + 7×3 + 2×5 = 49. The balance index is: 48 / 49×100% = 97%.

[0045] In another implementation, such as Figure 3 As shown, the methods for calculating the balance index can also include: S1031, compare the risk levels of the clauses in each of the risk assessment results to determine the conflicting clauses in the contract data, wherein the conflicting clauses are clauses with different risk levels in different roles.

[0046] In this embodiment, conflicting clauses are disputed clauses, that is, clauses that are deemed high-risk by one contract discrimination model but acceptable (e.g., medium-risk or low-risk) by another contract discrimination model.

[0047] Specifically, each clause in the contract data corresponds to a unique identifier. Based on the identifier of the clause, different risk assessment results are aligned, that is, the assessment results of the same clause are linked to form data pairs, so as to facilitate the comparison of the assessment results of the same clause.

[0048] According to the conflict determination rules, each data pair is evaluated to determine the conflict clauses.

[0049] Conflict determination rules can include: 1. Direct opposition: If one assessment result in a data pair is "high risk" and the other is "low risk," then it is determined to be a conflicting clause; 2. Opposing advantages: If one assessment result in a data pair is "our advantage" and the other is "our disadvantage" or "high risk," then it is determined to be a conflicting clause; 3. Conflicting modification intentions: If both parties agree that a clause is risky, but their proposed modifications to that clause are opposite, then it is determined to be a conflicting clause. For example, if Party A's suggestion is to "increase the penalty for breach of contract," but Party B's suggestion is to "reduce the penalty for breach of contract," and the two modification suggestions are completely opposite, then the clause is determined to be a conflicting clause.

[0050] In this embodiment, after identifying each conflicting clause, the conflicting clauses are stored in a "conflicting clause list" for subsequent processing.

[0051] S1032, Based on the content of the conflict clause and the risk level of the conflict clause in the risk assessment result, calculate the risk assessment value of the contract data in each of the respective roles.

[0052] In this embodiment, the importance of the conflict clause is determined based on its content, and the risk assessment value of the contract data in the positions of each role is calculated based on the importance of the conflict clause and the corresponding risk level.

[0053] For example, if the conflicting clause is Clause A, and Clause A's importance level is 3, Clause A is considered high-risk from Party A's perspective and low-risk from Party B's perspective. Calculate the risk assessment value of the contract data from Party A's perspective based on importance level 3 and high risk. Calculate the risk assessment value of the contract data from Party B's perspective based on importance level 3 and low risk.

[0054] In one approach, the method for determining the risk assessment value may include: Based on the content of the conflicting clauses, determine the importance of each conflicting clause, find the corresponding score for that importance, and add up the scores of all conflicting clauses to obtain a risk assessment value corresponding to a risk identification result.

[0055] In another way, such as Figure 4 As shown, methods for determining risk assessment values ​​may include: S11, for each of the aforementioned roles and positions, based on the risk assessment results, determine the risk quantification value of the conflict clause according to the risk level of the conflict clause in the risk assessment results.

[0056] In this embodiment, the risk level of conflict clauses is quantified into a numerical value to facilitate subsequent calculations.

[0057] Different levels of risk correspond to different risk quantification values. For example, high risk = 1.0, medium risk = 0.6, low risk = 0.3, and no risk = 0.0.

[0058] S12, Determine the global weight corresponding to the conflicting clause based on the clause type of the conflicting clause.

[0059] In this embodiment, different global weights are pre-set for different types of clauses. The global weight represents the general importance of that type of clause, establishing an objective and unified starting point for evaluation and ensuring consistency in system evaluation. For example, the global weight for a breach of contract clause is 0.9, and the weight for a notice of service clause is 0.3.

[0060] S13, determine the weight scaling factor of the conflict clause based on the context of the contract data.

[0061] In this embodiment, the weight scaling factor, also known as the context weight, is a weight that matches the context content of the current contract data, such as industry type, transaction size, or cooperation history, and is retrieved from a pre-stored database.

[0062] The weight scaling factor is a scenario-specific weight set to adjust the global weights. It enables personalized and precise risk assessment, allowing for specific analysis of specific problems.

[0063] For example, in software development contracts, the weighting scaling factor for intellectual property ownership clauses is significantly increased. In equipment procurement contracts, the weighting scaling factor for intellectual property ownership clauses is the baseline value.

[0064] S14. Based on the risk quantification value of the conflict clause, the global weight, and the weight scaling factor, determine the risk assessment value of the contract data in the role's position.

[0065] In this embodiment, the formula is used Calculate the risk assessment value. This is a risk assessment value. Let the risk quantification value be the j-th conflict clause. Let j be the global weight of the conflicting clause. Let be the weight scaling factor for the j-th conflicting clause, and m be the total number of conflicting clauses.

[0066] For each risk assessment result, a corresponding risk assessment value is calculated using the formula for calculating risk assessment value.

[0067] For example, if there are risk assessment results from both Party A's and Party B's perspectives, calculate the risk assessment value of the contract data from Party A's perspective. Calculate the risk assessment value of the contract data from Party B's perspective based on Party A's risk assessment result.

[0068] S1033, Based on each of the aforementioned risk assessment values, the fairness of the contract data is evaluated to obtain the balance index of the contract data.

[0069] In one approach, the difference between all risk assessment values ​​is calculated, and the corresponding balance index is found. Different balance indices are pre-set for different differences.

[0070] In another approach, each risk assessment value is input into a trained neural network, which then evaluates the fairness of the contract data to obtain a balance index.

[0071] In another way, such as Figure 5 As shown, the methods for calculating the balance index can also include: S21, calculate the standard deviation of each of the risk assessment values ​​and the average value of each of the risk assessment values.

[0072] S22, Calculate the balance index of the contract data based on the standard deviation and the mean.

[0073] In one approach, the ratio is obtained by dividing the standard deviation by the mean. The mean index is then obtained by subtracting the ratio from 1.

[0074] In another way, such as Figure 6 As shown, the implementation process of step S22 may include: S31, Calculate the initial balance of the contract data based on the standard deviation and the mean.

[0075] Specifically, the ratio is obtained by dividing the standard deviation by the mean. The initial balance is then obtained by subtracting the ratio from 1.

[0076] S32, calculate the risk difference of the conflicting clause in different risk assessment results based on the risk quantification value of the conflicting clause in different risk assessment results.

[0077] In this embodiment, the risk quantification values ​​of the same conflicting clause in different risk assessment results are subtracted to obtain the risk difference of the conflicting clause in different risk assessment results.

[0078] S33, determine the conflict penalty factor based on the risk difference of all the aforementioned conflict clauses.

[0079] In this embodiment, the preliminary balance is based solely on the uniformity of the distribution of the total risk value (risk assessment value) of the contract data across the roles and positions of all parties to assess risk. This approach fails to capture direct conflicts at the clause level. In contrast, the conflict penalty factor, determined based on the risk difference of conflict clauses, reflects direct conflicts at the clause level.

[0080] In one implementation, different penalty factors corresponding to different risk differences are pre-set. After obtaining the risk differences for conflict, the penalty factor corresponding to each risk difference is found. All the found penalty factors are added together to obtain the conflict penalty factor.

[0081] In another implementation, the product of the global weight of the conflict clause and the weight scaling factor is calculated to obtain the composite weight of the conflict clause; and the conflict penalty factor is determined based on the risk difference of all the conflict clauses and all the composite weights.

[0082] Specifically, based on the risk difference of all the conflict clauses and all the composite weights, a conflict penalty factor is determined using a penalty factor calculation model; wherein, the penalty factor calculation model is as follows: , Let n be the conflict penalty factor, and n be the total number of conflicting clauses. For the risk difference of the i-th conflict clause, The composite weight of the i-th conflicting clause, This is the preset maximum conflict value.

[0083] S34, the initial balance is corrected using the conflict penalty factor to obtain the balance index of the contract data.

[0084] In this embodiment, the formula The balance index is obtained. Among them, As a balance index, For the initial balance, It is a conflict penalty factor.

[0085] In this application, if multiple conflicting clauses exist in the contract data, and the positions of the two parties on these clauses are directly opposed, the conflict penalty factor quantifies this antagonism. By using the conflict penalty factor to correct the initial balance, the assessment of contract stability is ensured to be based not only on the overall distribution of risk assessment values ​​but also on direct conflicts at the clause level, making the final calculated balance index more accurate and thus providing more reliable risk management insights.

[0086] In one feasible approach, the method for generating the contract modification proposal in step S103 above may include: Conflicting clauses are ranked in descending order of importance (or negative impact). Importance can be assessed using a composite weight, which is the product of the global weight and a weight scaling factor.

[0087] Based on the type and mode of conflict, the system matches suggested modifications to the conflicting clause from the database. The database stores suggested modifications for different conflicting clauses.

[0088] Conflict patterns can include the aforementioned patterns of direct confrontation, opposing advantages, and conflict of intent to modify.

[0089] As an example, if the payment terms are conflict clauses, a suggested modification could be: "Given that the 'payment method' clause is the highest priority point of contention and seriously affects the balance of the contract, we suggest that we demonstrate flexibility in [related clauses, such as liability for breach of contract] in exchange for concessions from the other party on this clause."

[0090] In this embodiment, after obtaining the balance index and contract modification suggestions, the balance index of the contract data and the contract modification suggestions matched with the user's role information are displayed to the user.

[0091] The following is an illustration using a specific example.

[0092] The user (Party A) uploads the contract data to the system. The system then extracts key elements from the contract data. For example, payment terms: full payment within 30 days of delivery; liability for breach of contract: if Party B delays delivery, a penalty of 0.1% of the total contract amount will be charged per day.

[0093] The key elements are input into the contract judgment model from the perspective of Party A, and the output is the risk judgment result from Party A's perspective. For example, "Payment method" without prepayment is advantageous to Party A (low risk); "Liability for breach of contract" ratio is too low and insufficient to bind Party B, which is a high risk for Party A.

[0094] The contract assessment model inputs key elements from the supplier's perspective and outputs risk assessment results from the supplier's perspective. For example, the absence of prepayment in the "payment method" poses a high risk to the supplier's cash flow; the "liability for breach of contract" ratio is within an acceptable range (low risk) according to industry standards.

[0095] By comparing the risk levels of the clauses in each of the aforementioned risk assessment results, the payment method and liability for breach of contract are determined to be conflicting clauses.

[0096] The balance index calculated using the above method is 35, which indicates a serious imbalance. The verification of contractual rights and obligations is biased towards Party A, and Party B bears a significant financial burden, which is not conducive to long-term cooperation.

[0097] The system generated a report showing "Balance Index: 35 points (Imbalance)". The report used a comparison table to point out that the core conflict lies in "Payment Method" and "Liability for Breach of Contract". From the client's perspective, the suggested modification is: the current liability for breach of contract is too low; it is recommended to increase it to 0.5%. From a game theory perspective, the suggested modification is: if the current payment method is insisted upon, appropriate concessions can be made to the contractor regarding liability for breach of contract to facilitate cooperation.

[0098] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0099] Corresponding to the contract review method described in the above embodiments, Figure 7 A structural block diagram of the contract review device provided in the embodiments of this application is shown. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0100] Reference Figure 7 The device 300 may include: a data acquisition module 310, a contract review module 320, and a result output module 330.

[0101] The data acquisition module 310 is used to acquire the contract data to be reviewed and the user's role information in the contract data. The contract review module 320 is used to input the contract data into multiple contract discrimination models. Each contract discrimination model performs a risk review on the terms in the contract data from its own set role position, and obtains the risk discrimination result output by each contract discrimination model. The different contract discrimination models set different role positions, and the risk discrimination result contains the risk level of each term in the corresponding role position. The result output module 330 is used to compare the risk levels of the clauses in each of the risk assessment results to obtain the balance index of the contract data and contract modification suggestions matching the user's role information, wherein the balance index represents the fairness of the contract data.

[0102] In one possible implementation, the result output module 330 can specifically be used for: By comparing the risk levels of the clauses in each of the aforementioned risk assessment results, conflicting clauses in the contract data are identified, wherein the conflicting clauses are those with different risk levels in different roles and positions. Based on the content of the conflict clauses and the degree of risk of the conflict clauses in the risk assessment results, calculate the risk assessment value of the contract data in each of the respective roles and positions; Based on each of the aforementioned risk assessment values, the fairness of the contract data is evaluated to obtain the balance index of the contract data.

[0103] In one possible implementation, the result output module 330 can specifically be used for: For each of the aforementioned roles and positions, based on the risk assessment results, the risk quantification value of the conflict clause is determined according to the risk level of the conflict clause in the risk assessment results; Determine the global weight corresponding to the conflicting clause based on the clause type of the conflicting clause; Based on the context of the contract data, determine the weight scaling factor for the conflict clause; Based on the risk quantification value of the conflict clause, the global weight, and the weight scaling factor, the risk assessment value of the contract data in the role's position is determined.

[0104] In one possible implementation, the result output module 330 can specifically be used for: Calculate the standard deviation and average value of each of the risk assessment values; The balance index of the contract data is calculated based on the standard deviation and the mean.

[0105] In one possible implementation, the result output module 330 can specifically be used for: Based on the standard deviation and the mean, calculate the initial balance of the contract data; Based on the risk quantification value of the conflicting clause in different risk assessment results, calculate the risk difference of the conflicting clause in different risk assessment results; Determine the conflict penalty factor based on the risk difference of all the aforementioned conflict clauses; The initial balance is corrected using the conflict penalty factor to obtain the balance index of the contract data.

[0106] In one possible implementation, the result output module 330 can specifically be used for: The composite weight of the conflicting clause is obtained by multiplying the global weight of the conflicting clause by the weight scaling factor. The conflict penalty factor is determined based on the risk difference of all the aforementioned conflict clauses and all the aforementioned composite weights.

[0107] In one possible implementation, the result output module 330 can specifically be used for: Based on the risk difference of all the conflict clauses and all the composite weights, a conflict penalty factor is determined using a penalty factor calculation model. The penalty factor calculation model is as follows: , Let n be the conflict penalty factor, and n be the total number of conflicting clauses. For the risk difference of the i-th conflict clause, The composite weight of the i-th conflicting clause, This is the preset maximum conflict value.

[0108] In one possible implementation, the data acquisition module 310 can also be used for: Extract key elements from the contract data to generate structured contract data; Accordingly, the contract review module 320 can be specifically used for: Structured contract data is input into multiple contract discrimination models. Each contract discrimination model performs a risk review on the terms in the contract data from its own defined role, and the risk discrimination result output by each contract discrimination model is obtained.

[0109] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0110] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0111] This application also provides a terminal device, see [link to relevant documentation] Figure 8 The terminal device 400 may include: at least one processor 410, a memory 420, and a computer program stored in the memory 420 and executable on the at least one processor 410. When the processor 410 executes the computer program, it implements the steps in any of the above method embodiments, for example... Figure 2Steps S101 to S103 in the illustrated embodiment. Alternatively, when the processor 410 executes the computer program, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 7 The functions of the data acquisition module 310 to the result output module 330 are shown.

[0112] For example, a computer program may be divided into one or more modules / units, one or more of which are stored in memory 420 and executed by processor 410 to complete this application. The one or more modules / units may be a series of computer program segments capable of performing a specific function, which are used to describe the execution process of the computer program in terminal device 400.

[0113] Those skilled in the art will understand that Figure 8 This is merely an example of a terminal device and does not constitute a limitation on the terminal device. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0114] The processor 410 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0115] The memory 420 can be an internal storage unit of the terminal device or an external storage device, such as a plug-in hard drive, a smart media card (SMC), a secure digital (SD) card, or a flash card. The memory 420 is used to store the computer program and other programs and data required by the terminal device. The memory 420 can also be used to temporarily store data that has been output or will be output.

[0116] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0117] The contract review method provided in this application can be applied to terminal devices such as computers, tablets, laptops, netbooks, and personal digital assistants (PDAs). This application does not impose any restrictions on the specific type of terminal device.

[0118] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0119] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0120] In the embodiments provided in this application, it should be understood that the disclosed terminal devices, apparatuses, and methods can be implemented in other ways. For example, the terminal device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, apparatuses, or units, and may be electrical, mechanical, or other forms.

[0121] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0122] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0123] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by one or more processors, it can implement the steps of the various method embodiments described above.

[0124] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by one or more processors, it can implement the steps of the various method embodiments described above.

[0125] Similarly, as a computer program product, when the computer program product is run on a terminal device, it enables the terminal device to implement the steps in the above-described method embodiments.

[0126] The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0127] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A contract review method, characterized in that, include: Obtain the contract data to be reviewed and the user's role information in the contract data; The contract data is input into multiple contract discrimination models. Each contract discrimination model performs a risk review on the terms in the contract data from its own set role position, and obtains the risk discrimination result output by each contract discrimination model. The different contract discrimination models set different role positions, and the risk discrimination result contains the risk level of each term in the corresponding role position. By comparing the risk levels of the clauses in each of the aforementioned risk assessment results, a balance index for the contract data is obtained, along with contract modification suggestions matching the user's role information. The balance index represents the fairness of the contract data.

2. The contract review method as described in claim 1, characterized in that, By comparing the risk levels of the clauses in each of the aforementioned risk assessment results, a balance index for the contract data is obtained, including: By comparing the risk levels of the clauses in each of the aforementioned risk assessment results, conflicting clauses in the contract data are identified, wherein the conflicting clauses are those with different risk levels in different roles and positions. Based on the content of the conflict clauses and the degree of risk of the conflict clauses in the risk assessment results, calculate the risk assessment value of the contract data in each of the respective roles and positions; Based on each of the aforementioned risk assessment values, the fairness of the contract data is evaluated to obtain the balance index of the contract data.

3. The contract review method as described in claim 2, characterized in that, Based on the content of the conflict clauses and the degree of risk of the conflict clauses in the risk assessment results, the risk assessment value of the contract data in each of the respective roles is calculated, including: For each of the aforementioned roles and positions, based on the risk assessment results, the risk quantification value of the conflict clause is determined according to the risk level of the conflict clause in the risk assessment results; Determine the global weight corresponding to the conflicting clause based on the clause type of the conflicting clause; Based on the context of the contract data, determine the weight scaling factor for the conflict clause; Based on the risk quantification value of the conflict clause, the global weight, and the weight scaling factor, the risk assessment value of the contract data in the role's position is determined.

4. The contract review method as described in claim 3, characterized in that, The process of assessing the fairness of the contract data based on each of the aforementioned risk assessment values ​​to obtain a balance index for the contract data includes: Calculate the standard deviation and average value of each of the risk assessment values; The balance index of the contract data is calculated based on the standard deviation and the mean.

5. The contract review method as described in claim 4, characterized in that, The calculation of the balance index of the contract data based on the standard deviation and the mean includes: Based on the standard deviation and the mean, calculate the initial balance of the contract data; Based on the risk quantification value of the conflicting clause in different risk assessment results, calculate the risk difference of the conflicting clause in different risk assessment results; Determine the conflict penalty factor based on the risk difference of all the aforementioned conflict clauses; The initial balance is corrected using the conflict penalty factor to obtain the balance index of the contract data.

6. The contract review method as described in claim 5, characterized in that, The determination of the conflict penalty factor based on the risk difference of all the conflict clauses includes: The composite weight of the conflicting clause is obtained by multiplying the global weight of the conflicting clause by the weight scaling factor. The conflict penalty factor is determined based on the risk difference of all the aforementioned conflict clauses and all the aforementioned composite weights.

7. The contract review method as described in claim 6, characterized in that, The determination of the conflict penalty factor based on the risk difference of all the conflict clauses and all the composite weights includes: Based on the risk difference of all the conflict clauses and all the composite weights, a conflict penalty factor is determined using a penalty factor calculation model. The penalty factor calculation model is as follows: , Let n be the conflict penalty factor, and n be the total number of conflicting clauses. For the risk difference of the i-th conflict clause, The composite weight of the i-th conflicting clause, This is the preset maximum conflict value.

8. The contract review method as described in any one of claims 1 to 7, characterized in that, After obtaining the contract data to be reviewed and the user's role information, the method further includes: Extract key elements from the contract data to generate structured contract data; Accordingly, the contract data is input into multiple contract discrimination models, and each of the contract discrimination models performs a risk review on the terms in the contract data from its own defined role, resulting in a risk discrimination result output by each contract discrimination model, including: Structured contract data is input into multiple contract discrimination models. Each contract discrimination model performs a risk review on the terms in the contract data from its own defined role, and the risk discrimination result output by each contract discrimination model is obtained.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the contract review method as described in any one of claims 1 to 8.

10. A computer program product, characterized in that, When the computer program product is run on a terminal device, it causes the terminal device to perform the contract review method as described in any one of claims 1 to 8.

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