Enterprise contract risk analysis system based on large model

Abstract

The invention discloses an enterprise contract risk analysis system based on a large model, and belongs to the technical field of enterprise contract services. Performing multi-dimensional supervision and data processing of contract specifications and contract risks on different contract signing parties to obtain local signing supervision processing data corresponding to the different contract signing parties, and performing multi-dimensional risk processing analysis on the local signing supervision processing data corresponding to the different contract signing parties. Obtaining single-party signing standard risk state prompts and signed contract signing risk state prompts corresponding to different contract signing parties; the technical problems that in an existing scheme, the independent supervision implementation effect of contract specifications and contract risks of different signing parties of an enterprise contract is poor, and the multi-dimensional risk processing prompt effect is poor are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise contract services, and in particular to an enterprise contract risk analysis system based on a large model. Background Art

[0002] Enterprise contract risk analysis is the process of identifying, evaluating and planning responses to various risks that may exist in a contract; this process aims to ensure that the enterprise can minimize potential adverse effects and maximize benefits when signing and performing contracts.

[0003] When implementing existing enterprise contract risk analysis programs, most of them still focus on data supervision and processing analysis of a single contract signatory. They are unable to conduct multi-dimensional supervision, processing and analysis of contract specifications and contract risks of different contract signatories, and adaptively perform local or overall specification optimization management and risk optimization management based on the analysis results. As a result, the implementation of autonomous supervision of contract specifications and contract risks of different signatories to enterprise contracts is not effective, and the multi-dimensional risk processing prompts are not effective. Summary of the Invention

[0004] The purpose of the present invention is to provide an enterprise contract risk analysis system based on a large model, which is used to solve the technical problems of poor implementation of autonomous supervision of contract specifications and contract risks of different signatories of enterprise contracts and poor multi-dimensional risk processing prompts in existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A large-model-based enterprise contract risk analysis system includes a contract supervision platform, an enterprise contract signing multi-dimensional supervision processing module and an enterprise contract signing multi-dimensional risk analysis module connected to the contract supervision platform; The enterprise contract signing multi-dimensional supervision processing module is used to conduct multi-dimensional supervision and data processing of contract specifications and contract risks for different contract signatories, and obtain the local signing supervision processing data corresponding to different contract signatories; The enterprise contract signing multi-dimensional risk analysis module is used to perform multi-dimensional risk processing analysis based on the local signing supervision processing data corresponding to different contract signatories, and obtain the unilateral signing specification risk status prompts corresponding to different contract signatories and the signed contract signing risk status prompts; Wherein, the first signing supervision sequence and the second signing supervision sequence in the local signing supervision processing data corresponding to different contract signatories are obtained; Process and calculate all elements in the first signed supervision sequence and the second signed supervision sequence respectively to obtain digital data corresponding to different signed supervision sequences; Data analysis is performed on the different digital data obtained by calculation, and based on the analysis results, unilateral signing specification risk status prompts of different signatories and signed contract signing risk status prompts are adaptively generated.

[0006] Preferably, when actively supervising and processing the contract specifications of different contract signatories, corresponding signing supervision instructions are generated according to the identity of the signatories, and targeted contract specifications and qualified risk supervision are implemented for the signatories according to the generated signing supervision instructions; According to the contract type, several standard signature items and standard signature keyword sets, several risk signature items and risk signature keyword sets corresponding to the signatory parties are obtained; When digitally processing a number of regulatory signature items and regulatory signature keyword sets, and a number of risk signature items and risk signature keyword sets obtained from the respective signatories, the total number of specifications N1 of the regulatory signature items and the total number of risks N2 of the risk signature items are counted respectively, and the regulatory consensus value JYk corresponding to different signature item types is calculated using the formula JYk=Nk-N´k; where k is 1 and 2, representing the regulatory signature item type and risk signature item type respectively; Nk is N1 and N2; and N´k is N´1 and N´2, representing the total number of standard specifications corresponding to the regulatory signature item type and the total number of standard risks corresponding to the risk signature item type respectively.

[0007] Preferably, if the regulatory consistency value is 0, the corresponding signed item type is marked as a normal signed item type; If the regulatory consistency value is not 0, the signature item type is marked as an abnormal signature item type.

[0008] Preferably, when performing a processing analysis for consistent supervision content on a normal signature item type, the signature keyword sets associated with all signature items of the normal signature item type are sequentially analyzed using a signature supervision identification model, and signature supervision values ​​QJi corresponding to different signature items of the normal signature item type are output; i represents different signature items of the normal signature item type, i=1, 2, 3, ..., n; n is a positive integer; The expression of the signed supervision identification model is Where QXi is the set of signature keywords associated with different signature items; Ui is the standard set of signature keywords associated with different signature items; a and b are both positive integers, determined by the total number of signature keywords in the signature keyword sets associated with different signature items that do not belong to the standard set of signature keywords to which they belong; All the signing supervision values ​​obtained by the normal signing item type supervision processing are sorted and combined to obtain the first signing supervision sequence corresponding to the normal signing item type.

[0009] Preferably, when analyzing the inconsistency of regulatory items for abnormal signed item types, all signed items of the abnormal signed item type are traversed and matched with their corresponding standard signed item sets, and all standard signed items that are not matched in the standard signed item set are marked as abnormal matching signed items; Obtaining preset signature item influence coefficients corresponding to all abnormal matching signature items and sorting and combining them to obtain a second signature supervision sequence corresponding to the abnormal signature item type; The first signing supervision sequence and the second signing supervision sequence obtained by the signatory for different aspects of supervision processing are sorted and combined to obtain the local signing supervision processing data corresponding to the signatory.

[0010] Preferably, obtaining a first signing supervision sequence and a second signing supervision sequence in the local signing supervision processing data corresponding to different contract signatories; And all elements of the first signed regulatory sequence are passed through the formula The first regulatory risk value GF1 is calculated; where M1 and M2 are the total number of a and b elements in the first signed regulatory sequence, respectively; A1 and A2 are both regulatory risk standard values ​​for inconsistent regulatory content, and A1>A2; And all elements of the second signed regulatory sequence are passed through the formula The second standard risk value GF2 is calculated; where j is the different abnormal matching signature items in the second signature supervision sequence; j=1, 2, 3,..., N3; N3 is a positive integer; YXj is the signature item influence coefficient corresponding to the different abnormal matching signature items; B is the standard risk value of inconsistent supervision items.

[0011] Preferably, data analysis is performed on the calculated first standard risk value and the second standard risk value; If the first standard risk value is (0, 1) and the second standard risk value is (0, 1), it indicates that the unilateral signing standard of the signatory party is slightly abnormal and the unilateral signing risk is slightly abnormal; If the first standard risk value is greater than or equal to 1 and the second standard risk value is greater than or equal to 1, it will prompt that the unilateral signing standard of the signatory is severely abnormal and the unilateral signing risk is severely abnormal.

[0012] Preferably, if the first standard risk value belongs to (0, 1) and the second standard risk value belongs to (0, 1), it is prompted that the signing risk of the contract is slightly abnormal; If the first standard risk value is greater than or equal to 1 and the second standard risk value is greater than or equal to 1, it indicates that the signing risk of the contract to be signed is severely abnormal.

[0013] Compared with the existing solutions, the present invention achieves the following beneficial effects: The present invention obtains local signing supervision processing data corresponding to different contract signatories through multi-dimensional supervision and data processing of contract specifications and contract risks of different contract signatories. It can not only obtain active supervision processing status data corresponding to different aspects of different signatories, but also provide reliable multi-dimensional supervision processing data support for subsequent risk processing analysis prompts corresponding to different aspects of different signatories, thereby improving the implementation effect of autonomous supervision of contract specifications and contract risks of different signatories of enterprise contracts.

[0014] The present invention implements multi-dimensional risk processing analysis on the local signing supervision processing data corresponding to different contract signatories, and obtains unilateral signing standard risk status prompts and signed contract signing risk status prompts corresponding to different contract signatories. Compared with the existing technical solutions that can only perform supervision analysis and prompts on a single aspect of risk status, the present invention can achieve diverse and comprehensive supervision analysis and prompts, effectively improving the standard supervision and risk supervision prompt effects of different signatories of enterprise contracts. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below with reference to the accompanying drawings.

[0016] Figure 1 This is a module block diagram of a large model-based enterprise contract risk analysis system of the present invention.

[0017] Figure 2 This is a block diagram of the operation principle of a large model-based enterprise contract risk analysis system of the present invention.

[0018] Figure 3 This is a principle block diagram of data analysis of the first standard risk value and the second standard risk value in the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] like Figures 1 to 2 As shown, the present invention is a large-scale model-based enterprise contract risk analysis system, comprising a contract supervision platform, and an enterprise contract signing multi-dimensional supervision processing module and an enterprise contract signing multi-dimensional risk analysis module connected to the contract supervision platform; The enterprise contract signing multi-dimensional supervision processing module is used to conduct multi-dimensional supervision and data processing of contract specifications and contract risks for different contract signatories, and obtain the local signing supervision processing data corresponding to different contract signatories; including: Among them, different perspectives include the perspective of Party A and the perspective of Party B, the two parties signing the contract; When proactively supervising and processing contract specifications for different contract signatories, corresponding signing supervision instructions are generated based on the signatory's identity, and targeted contract specifications and qualified risk supervision are implemented for the signatory based on the generated signing supervision instructions; Unlike most existing technical solutions that still focus on supervision and data analysis from the perspective of a single signatory, and are therefore unable to provide reliable multi-dimensional signatory supervision data support for subsequent contract risk analysis prompts, in the embodiments of the present invention, by conducting supervision and data processing analysis on contract signatories in different aspects, the diversity and reliability of the enterprise's contract risk supervision analysis can be effectively improved.

[0021] According to the contract type, several standard signature items and standard signature keyword sets, several risk signature items and risk signature keyword sets corresponding to the signatory parties are obtained; Among them, different types of contracts are pre-set with a number of standard signature items and standard signature keyword sets, and a number of risk signature items and risk signature keyword sets. These standard signature items and standard signature keyword sets, and risk signature items and risk signature keyword sets can all be obtained through evaluation and screening by professional technicians in this field based on all historical signature supervision data of the corresponding contract type; When digitally processing the number of specification signature items and specification signature keyword sets, and the number of risk signature items and risk signature keyword sets obtained by the signatory, the total number of specifications N1 of the number of specification signature items and the total number of risks N2 of the number of risk signature items are counted respectively, and the regulatory consistency value JYk corresponding to different signature item types is calculated using the formula JYk=Nk-N´k; where k is 1 and 2, representing the specification signature item type and the risk signature item type, respectively; JYk is JY1 and JY2, representing the regulatory consistency values ​​corresponding to the specification signature item type and the risk signature item type, respectively; Nk is N1 and N2; N´k is N´1 and N´2, representing the total number of standard specifications corresponding to the specification signature item type and the total number of standard risks corresponding to the risk signature item type, respectively. The total number of standard specifications and the total number of standard risks are determined based on the specification design requirement data of the contract type to which they belong, and can also be determined based on the preliminary test data of the contract type to which they belong; The regulatory consensus value is used to integrate and calculate the signature item data to digitally represent the signature item type corresponding to the signature item; If the regulatory consistency value is 0, the corresponding signature item type is marked as a normal signature item type; If the regulatory consistency value is not 0, the corresponding signed item type is marked as an abnormal signed item type; In an embodiment of the present invention, supervision and data processing analysis are performed on the signature items of the different signatories of the contract in terms of corresponding norms and risks, and the signature types corresponding to the different signature items are analyzed and dynamically marked based on the analysis results. At the same time, reliable signature item supervision and processing data support can be provided for subsequent supervision and expansion analysis in different aspects.

[0022] When analyzing the consistency of regulatory content for normal signature item types, the signature keyword sets associated with all signature items of the normal signature item type are sequentially analyzed through the signature supervision identification model, and the signature supervision values ​​QJi corresponding to different signature items of the normal signature item type are output; i represents different signature items of the normal signature item type, i=1, 2, 3, ..., n; n is a positive integer, representing the total number of all signature items; The expression of the signed supervision identification model is Where QXi is the set of signature keywords associated with different signature items; Ui is the standard set of signature keywords associated with different signature items, which is determined based on the specification design requirements data of the contract type to which it belongs, or based on the preliminary test data of the contract type to which it belongs; a and b are both positive integers, a<b, and are determined based on the total number of signature keywords in the signature keyword set associated with different signature items that do not belong to the standard set of signature keywords to which they belong; Signing supervision values ​​contain values ​​of 0, a, or b; The signature supervision value is used to perform data analysis on the signature keyword set associated with the signature item of the normal signature item type to digitally represent the supervision status of the signature item; A signature supervision value of 0 indicates that the supervision status of the signature item is normal; A signed supervision value of a indicates that the supervision status of the signed item is slightly abnormal; A signed supervision value with a value of b indicates that the supervision status of the signed item is severely abnormal; Sort and combine all the signing supervision values ​​obtained from the normal signing item type supervision process to obtain a first signing supervision sequence corresponding to the normal signing item type; In an embodiment of the present invention, when performing extended analysis on all normal signature item types obtained through screening, data analysis is performed on the signature keyword sets associated with the signature items of all normal signature item types, and the signature supervision values ​​corresponding to different signature items and their corresponding supervision statuses are output, thereby realizing a combination of active supervision and digital processing of contract specifications for different contract signatories, and improving the active supervision effect of different contract signatories in terms of contract specifications.

[0023] Furthermore, when analyzing the inconsistency of regulatory items for abnormal signature item types, all signature items of the abnormal signature item type are traversed and matched with their corresponding standard signature item sets, and all standard signature items that are not matched in the standard signature item set are marked as abnormal matching signature items; Different contract types are pre-assigned a corresponding standard signature item set. Each standard signature item in the standard signature item set is associated with a preset signature item impact coefficient. The signature item impact coefficient is used to digitally represent the signature item impact corresponding to the corresponding standard signature item. The specific value of the signature item impact coefficient can be determined by the historical economic losses generated by the signature item or the total number of historical omissions. Obtaining preset signature item influence coefficients corresponding to all abnormal matching signature items and sorting and combining them to obtain a second signature supervision sequence corresponding to the abnormal signature item type; Among them, when analyzing the inconsistent supervision items of the abnormal signature item types obtained through screening, all signature items of the abnormal signature item type are traversed, matched and combined with their corresponding standard signature item sets, realizing the active supervision and digital processing combination of contract risks for different contract signatories, and improving the active supervision effect of different contract signatories in terms of contract risks. Sort and combine the first signing supervision sequence and the second signing supervision sequence obtained by the signatory for different aspects of supervision processing to obtain the local signing supervision processing data corresponding to the signatory; In an embodiment of the present invention, by performing multi-dimensional supervision and data processing on contract specifications and contract risks of different contract signatories, local signing supervision processing data corresponding to different contract signatories are obtained, which can not only obtain active supervision processing status data corresponding to different aspects of different signatories, but also provide reliable multi-dimensional supervision processing data support for subsequent risk processing analysis prompts corresponding to different aspects of different signatories, thereby improving the implementation effect of autonomous supervision of contract specifications and contract risks of different signatories of enterprise contracts.

[0024] The enterprise contract signing multi-dimensional risk analysis module is used to perform multi-dimensional risk processing analysis based on the local signing supervision processing data corresponding to different contract signatories, and obtain the unilateral signing standard risk status prompts corresponding to different contract signatories and the signed contract signing risk status prompts; including: Obtain the first signing supervision sequence and the second signing supervision sequence in the local signing supervision processing data corresponding to different contract signatories; And all elements of the first signed regulatory sequence are passed through the formula Calculate the first regulatory risk value GF1; where M1 and M2 are the total number of a and b elements in the first signed regulatory sequence, respectively; A1 and A2 are both regulatory risk standard values ​​for inconsistent regulatory content, with A1 > A2. This value is determined based on the regulatory design requirements data for the contract type, or based on previous test data for the contract type. And all elements of the second signed regulatory sequence are passed through the formula The second regulatory risk value GF2 is calculated; where j represents the different abnormal matching signature items in the second regulatory signing sequence; j = 1, 2, 3, ..., N3; N3 is a positive integer, representing the total number of all abnormal matching signature items in the second regulatory signing sequence; YXj represents the signature item impact coefficient corresponding to the different abnormal matching signature items; B represents the regulatory risk standard value for inconsistent regulatory items, which is determined based on the regulatory design requirement data for the contract type to which it belongs, or can also be determined based on the preliminary test data for the contract type to which it belongs; Among them, the first standard risk value and the second standard risk value respectively integrate and calculate the previous abnormal supervision processing data from different aspects to digitally represent the abnormal status of the unilateral signing standard and the abnormal status of the unilateral signing risk of different signatories; Performing data analysis on the calculated first standard risk value and second standard risk value; like Figure 3 As shown, if the first standard risk value is 0 and the second standard risk value is 0, it indicates that the unilateral signing standard of the signatory is normal and the unilateral signing risk is normal; If the first standard risk value is 0 and the second standard risk value is 0, it indicates that the signing risk of the contract is normal; If the first standard risk value is (0, 1) and the second standard risk value is (0, 1), it indicates that the unilateral signing standard of the signatory party is slightly abnormal and the unilateral signing risk is slightly abnormal; If the first standard risk value is (0, 1) and the second standard risk value is (0, 1), it indicates that the signing risk of the contract is slightly abnormal; If the first standard risk value is greater than or equal to 1 and the second standard risk value is greater than or equal to 1, it will prompt that the unilateral signing standard of the signatory party is severely abnormal and the unilateral signing risk is severely abnormal; If the first standard risk value is greater than or equal to 1 and the second standard risk value is greater than or equal to 1, it indicates that the signing risk of the contract to be signed is severely abnormal.

[0025] It is worth noting that by analyzing the calculated first-standard risk value and second-standard risk value, we can obtain the unilateral signing standard status and unilateral signing risk status corresponding to different signatories, as well as the contract signing risk status corresponding to the signed contract; In an embodiment of the present invention, by implementing multi-dimensional risk processing analysis on the local signing supervision processing data corresponding to different contract signatories, unilateral signing standard risk status prompts and signed contract signing risk status prompts corresponding to different contract signatories are obtained. Compared with the existing technical solutions that can only perform supervision analysis and prompts on a single aspect of the risk status, the present invention can achieve diverse and comprehensive supervision analysis and prompts, effectively improving the standardized supervision and risk supervision prompt effects of different signatories to enterprise contracts.

[0026] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the embodiments of the invention described above are merely illustrative. For example, the division of modules is only a logical function division, and other division methods may be used in actual implementation.

[0027] Modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, and may be located in one place or distributed across multiple network modules. Some or all of these modules may be selected to achieve the objectives of this embodiment based on actual needs.

[0028] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing module, each module may exist physically separately, or two or more modules may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or hardware plus software functional modules.

[0029] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, but that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0030] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An enterprise contract risk analysis system based on a large model, characterized by: It includes a contract supervision platform, a multi-dimensional supervision processing module for enterprise contract signing and a multi-dimensional risk analysis module for enterprise contract signing that are connected to the contract supervision platform; The enterprise contract signing multi-dimensional supervision processing module is used to conduct multi-dimensional supervision and data processing of contract specifications and contract risks for different contract signatories, and obtain the local signing supervision processing data corresponding to different contract signatories; The enterprise contract signing multi-dimensional risk analysis module is used to perform multi-dimensional risk processing analysis based on the local signing supervision processing data corresponding to different contract signatories, and obtain the unilateral signing specification risk status prompts corresponding to different contract signatories and the signed contract signing risk status prompts; Wherein, the first signing supervision sequence and the second signing supervision sequence in the local signing supervision processing data corresponding to different contract signatories are obtained; Process and calculate all elements in the first signed supervision sequence and the second signed supervision sequence respectively to obtain digital data corresponding to different signed supervision sequences; Data analysis is performed on the different digital data obtained by calculation, and based on the analysis results, unilateral signing specification risk status prompts of different signatories and signed contract signing risk status prompts are adaptively generated.

2. The enterprise contract risk analysis system based on a large model according to claim 1 is characterized in that: When proactively supervising and processing contract specifications for different contract signatories, corresponding signing supervision instructions are generated based on the signatory's identity, and targeted contract specifications and qualified risk supervision are implemented for the signatory based on the generated signing supervision instructions; According to the contract type, several standard signature items and standard signature keyword sets, several risk signature items and risk signature keyword sets corresponding to the signatory parties are obtained; When digitally processing a number of regulatory signature items and regulatory signature keyword sets, and a number of risk signature items and risk signature keyword sets obtained from the respective signatories, the total number of specifications N1 of the regulatory signature items and the total number of risks N2 of the risk signature items are counted respectively, and the regulatory consensus value JYk corresponding to different signature item types is calculated using the formula JYk=Nk-N´k; where k is 1 and 2, representing the regulatory signature item type and risk signature item type respectively; Nk is N1 and N2; and N´k is N´1 and N´2, representing the total number of standard specifications corresponding to the regulatory signature item type and the total number of standard risks corresponding to the risk signature item type respectively.

3. The enterprise contract risk analysis system based on a large model according to claim 2 is characterized in that: If the regulatory consistency value is 0, the corresponding signature item type is marked as a normal signature item type; If the regulatory consistency value is not 0, the signature item type is marked as an abnormal signature item type.

4. The enterprise contract risk analysis system based on a large model according to claim 3 is characterized in that: When performing a processing analysis for consistent supervision content on a normal signature item type, the signature keyword set associated with all signature items of the normal signature item type is sequentially analyzed through the signature supervision identification model, and the signature supervision value QJi corresponding to different signature items of the normal signature item type is output; i represents different signature items of the normal signature item type, i=1, 2, 3, ..., n; n is a positive integer; The expression of the signed supervision identification model is Where QXi is the set of signature keywords associated with different signature items; Ui is the standard set of signature keywords associated with different signature items; a and b are both positive integers, determined by the total number of signature keywords in the signature keyword sets associated with different signature items that do not belong to the standard set of signature keywords to which they belong; All the signing supervision values ​​obtained by the normal signing item type supervision processing are sorted and combined to obtain the first signing supervision sequence corresponding to the normal signing item type.

5. The enterprise contract risk analysis system based on a large model according to claim 4 is characterized in that: When analyzing the inconsistency of regulatory items for abnormal signature item types, all signature items of the abnormal signature item type are traversed and matched with their corresponding standard signature item sets, and all standard signature items that are not matched in the standard signature item set are marked as abnormal matching signature items; Obtaining preset signature item influence coefficients corresponding to all abnormal matching signature items and sorting and combining them to obtain a second signature supervision sequence corresponding to the abnormal signature item type; The first signing supervision sequence and the second signing supervision sequence obtained by the signatory for different aspects of supervision processing are sorted and combined to obtain the local signing supervision processing data corresponding to the signatory.

6. The enterprise contract risk analysis system based on a large model according to claim 5 is characterized in that: Obtain the first signing supervision sequence and the second signing supervision sequence in the local signing supervision processing data corresponding to different contract signatories; And all elements of the first signed regulatory sequence are passed through the formula The first regulatory risk value GF1 is calculated; where M1 and M2 are the total number of a and b elements in the first signed regulatory sequence, respectively; A1 and A2 are both regulatory risk standard values ​​for inconsistent regulatory content, and A1>A2; And all elements of the second signed regulatory sequence are passed through the formula The second standard risk value GF2 is calculated; where j is the different abnormal matching signature items in the second signature supervision sequence; j=1, 2, 3,..., N3; N3 is a positive integer; YXj is the signature item influence coefficient corresponding to the different abnormal matching signature items; B is the standard risk value of inconsistent supervision items.

7. The enterprise contract risk analysis system based on a large model according to claim 6 is characterized in that: Performing data analysis on the calculated first standard risk value and second standard risk value; If the first standard risk value is (0, 1) and the second standard risk value is (0, 1), it indicates that the unilateral signing standard of the signatory party is slightly abnormal and the unilateral signing risk is slightly abnormal; If the first standard risk value is greater than or equal to 1 and the second standard risk value is greater than or equal to 1, it will prompt that the unilateral signing standard of the signatory is severely abnormal and the unilateral signing risk is severely abnormal.

8. The enterprise contract risk analysis system based on a large model according to claim 7 is characterized in that: If the first standard risk value is (0, 1) and the second standard risk value is (0, 1), it indicates that the signing risk of the contract is slightly abnormal; If the first standard risk value is greater than or equal to 1 and the second standard risk value is greater than or equal to 1, it indicates that the signing risk of the contract to be signed is severely abnormal.

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