Multi-language financial contract intelligent auditing system based on block chain technology

Abstract

The embodiment of the invention provides a multi-language financial contract intelligent auditing system based on a block chain technology. In a specific implementation mode, the system comprises a first block chain, a second block chain, a third block chain, an auditing module, a backup module, an obtaining module and a supervision module. According to the embodiment, the multi-language financial contract is received and processed, the original text and the translated text are comprehensively audited by constructing the rule base, and the contract execution efficiency and accuracy are improved. Legal affairs, risk control and financial risk auditing are integrated, legal risks are reduced, and financial transaction safety is enhanced. Intelligent automatic auditing is achieved, and the labor burden is relieved. Three block chains are adopted for mutual backup, data integrity and safety are ensured, and faults are responded in time. Translated texts under the national legal system are intelligently recognized and processed, seamless joint of language and legal differences is achieved, and potential risks are reduced. And by utilizing the transparent traceability characteristic of the block chain, the auditing process is ensured to be open and transparent, and the market credibility is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of multilingual financial contract intelligent review based on blockchain technology. More specifically, it relates to a multilingual financial contract intelligent review system based on blockchain technology. Background Art

[0002] At present, with the integration and development of the global economy, cross-border financial transactions are becoming increasingly frequent, and the signing and execution of financial contracts have become an important link connecting economic activities in different countries and regions. However, the legal terms involved in financial contracts are complex and highly professional, and due to the differences in legal systems, language habits, and economic environments of various countries, the translation and understanding of contract texts have become a key link affecting the efficiency and accuracy of contract execution. The traditional financial contract review method relies on manual review, which is not only time-consuming and laborious, but also easily limited by personal experience, language ability, and professional knowledge level, making it difficult to fully and accurately identify potential risks in the contract.

[0003] In recent years, blockchain technology has shown great application potential in finance, supply chain management, copyright protection and other fields due to its decentralization, transparency and traceability. Applying blockchain technology to financial contract review can build a safe, efficient and reliable review environment and improve the automation and accuracy of contract review. However, most of the existing blockchain-based financial contract review systems focus on contract processing in a single language environment and lack effective support for multilingual contract texts.

[0004] In addition, financial contract review involves multiple risk dimensions, including but not limited to legal risk, risk control risk and financial risk. The identification and assessment of these risk points need to be based on the laws and regulations, industry norms and market conditions of different countries and regions. Traditional review systems often find it difficult to integrate these cross-domain and cross-cultural expertise, resulting in insufficient comprehensiveness and depth in risk review.

[0005] In addition, a single blockchain system may have the hidden danger of single point failure when facing risks such as data tampering, system failure or hacker attack. Summary of the invention

[0006] The purpose of the present disclosure is to provide a multilingual financial contract intelligent review system based on blockchain technology to solve at least one of the problems existing in the prior art, such as insufficient multilingual contract processing, incomplete risk review, and the existence of single point failure risks.

[0007] In order to achieve the above objectives, the present invention adopts the following technical solutions:

[0008] The present disclosure provides a multilingual financial contract intelligent review system based on blockchain technology, including:

[0009] A first blockchain, a second blockchain, a third blockchain, a review module, a backup module, an acquisition module, and a supervision module;

[0010] The acquisition module is used to obtain the latest original financial contract sent by the first blockchain and multiple translated texts thereof marked with corresponding country information in each risk review process;

[0011] The review module is used in each risk review process to:

[0012] Constructing a first rule base for the original text of financial contracts and a second rule base for the translated texts of corresponding countries respectively;

[0013] Identify and mark a first risk point in the original text of the financial contract according to the first rule base, and calculate a first risk score of the original text of the financial contract;

[0014] Identify and mark second risk points in the translated text of the corresponding country according to the second rule base, and calculate a second risk score of the translated text of the corresponding country;

[0015] In response to the user's review operation, based on the annotated original text of the financial contract, the first risk score, the annotated translation text of the corresponding country, and the second risk score, a modification suggestion, a review result, and circulation information are obtained, and an upload request is sent to the first blockchain to upload the modification suggestion, the review result, and the circulation information to the first blockchain;

[0016] A backup module, used to copy and store the data on the first blockchain to the second blockchain and the third blockchain;

[0017] A supervision module, used to detect and identify whether the data of any one of the first blockchain, the second blockchain, and the third blockchain is inconsistent with the data of the other two blockchains;

[0018] If data inconsistency is detected, an alarm signal is output and the blockchain with inconsistent data is marked as pending verification;

[0019] If the blockchain with inconsistent data is the first blockchain, reconfigure one of the second blockchain or the third blockchain as a new first blockchain;

[0020] The risk review process includes a legal risk review process, a risk control risk review process, and a financial risk review process.

[0021] Furthermore, the review module is further used to obtain a plurality of first preset risk keywords for the original text of the financial contract before building the first rule base;

[0022] In response to the user's first classification operation, the first preset risk keyword is divided into a first legal risk review keyword, a first risk control risk review keyword, and a first financial risk review keyword; so that the review module constructs a first rule base of the legal risk review process according to the first legal risk review keyword in the legal risk review process; constructs a first rule base of the risk control risk review process according to the first risk control risk review keyword in the risk control risk review process; and constructs a first rule base of the financial risk review process according to the first financial risk review keyword in the financial risk review process;

[0023] The review module is also used to obtain a plurality of second preset risk keywords for the translation text of the corresponding country before building the second rule base;

[0024] In response to the user's second classification operation, the second preset risk keywords are divided into second legal risk review keywords, second risk control risk review keywords, and second financial risk review keywords; so that the review module constructs a second rule base corresponding to the country in the legal risk review process according to the second legal risk review keywords in the legal risk review process; constructs a second rule base corresponding to the country in the risk control risk review process according to the second risk control risk review keywords in the risk control risk review process; and constructs a second rule base corresponding to the country in the financial risk review process according to the second financial risk review keywords in the financial risk review process.

[0025] Furthermore, the calculating of the first risk score of the original financial contract includes:

[0026] According to formula 1

[0027]

[0028] Calculate the first risk score R of the original financial contract 1score ; Wherein, is the ratio of the number of the i-th first risk points in the original text of the financial contract to the total number of all first risk points; A 1i is the weight of the i-th first risk point in the original text of the financial contract; n is the total number of types of first risk points in the original text of the financial contract;

[0029] Calculating the second risk score of the translated text of the corresponding country includes:

[0030] According to formula 2

[0031]

[0032] Calculate the second risk score R of the translated text for the corresponding country 2score; Wherein, is the ratio of the number of the i-th second risk points in the translation text of the corresponding country to the total number of all second risk points; A 2i is the weight of the i-th second risk point in the translated text of the corresponding country; m is the total number of types of second risk points in the translated text of the corresponding country.

[0033] Furthermore, the weight A of the i-th first risk point in the original text of the financial contract is 1i include:

[0034] According to formula 3

[0035]

[0036] Calculate the weight A of the first risk point of the i-th type in the original financial contract 1i Among them, Nr 1i Nr is the number of occurrences of the first risk point of the ith type in the original text of the financial contract; t1 is the total number of words in the original text of the financial contract; Ac i1 is the first adjustment coefficient of the i-th first risk point in the original text of the financial contract; n is the total number of types of first risk points in the original text of the financial contract;

[0037] According to formula 4

[0038]

[0039] Calculate the weight A of the i-th second risk point in the translated text of the corresponding country 2i Among them, Nr 2i Nr is the number of occurrences of the i-th second risk point in the translated text of the corresponding country; t2 is the total number of words in the translated text of the corresponding country; Ac i2 is the second adjustment coefficient of the i-th second risk point in the translated text of the corresponding country; and m is the total number of types of second risk points in the translated text of the corresponding country.

[0040] Furthermore, the first adjustment coefficient Ac of the i-th first risk point in the original text of the financial contract i1 include:

[0041] According to formula 5

[0042] Ac i1 =α i1 ×HRC i1 +(1-α i1 )×S i1

[0043] Calculate the first adjustment coefficient Ac of the first risk point of the i-th type in the original financial contract i1 , where αi1 is the first preset weight coefficient of the first risk point of the ith type in the original text of the financial contract, HRC i1 is the historical risk coefficient of the first risk point of the ith type in the original text of the financial contract; S i1 The average value of the first preset expert scores for the first risk point of the i-th type in the original text of the financial contract;

[0044] The second adjustment coefficient Ac of the i-th second risk point in the translation text of the corresponding country i2 include:

[0045] According to formula 6

[0046] Ac i2 =α i2 ×HRC i2 +(1-α i2 )×S i2

[0047] Calculate the second adjustment coefficient Ac of the i-th second risk point in the translated text of the corresponding country i2 , where α i2 is the second preset weight coefficient of the second risk point of the i-th type in the translated text of the corresponding country, HRC i2 is the historical risk coefficient of the i-th second risk point in the translated text of the corresponding country; S i2 The average value of the second preset expert scores for the i-th second risk point in the translated text of the corresponding country.

[0048] Furthermore, the first preset weight coefficient α of the i-th first risk point in the original text of the financial contract is i1 The value range is 0.7-0.8;

[0049] The second preset weight coefficient α of the i-th second risk point in the translated text of the corresponding country i2 The value range is 0.7-0.8.

[0050] Furthermore, the historical risk coefficient HRC1 of the original financial contract includes:

[0051] Acquire multiple signed historical financial contract texts to obtain a historical financial contract set;

[0052] Obtain the losses caused by each first risk point in each historical financial contract text;

[0053] In response to the user's evaluation operation, the scores of the impact of each first risk point in each historical financial contract text are obtained according to the losses caused by each first risk point in each historical financial contract text; and the maximum value of the scores of the impact of each first risk point in each historical financial contract text is obtained;

[0054] According to formula 7

[0055]

[0056] Calculate the average impact score of the first risk point of the i-th type in the historical financial contract set Among them, L 1ik is the impact score of the i-th first risk point in the historical financial contract set in the k-th historical financial contract text; u1 is the total number of historical financial contract texts;

[0057] According to formula 8

[0058]

[0059] Calculate the historical risk coefficient HRC of the first risk point of the i-th type in the original text of the financial contract i1 , where Nh 1i Nh is the total number of occurrences of the first risk point of the i-th type in the historical financial contract set; t1 is the total number of words in the historical financial contract set; is the average impact score of the first risk point of the i-th type in the historical financial contract set; L 1iMAX is the maximum value of the scores of the impact of the i-th first risk point in the historical financial contract set in each historical financial contract text;

[0060] The historical risk coefficient HRC2 of the i-th second risk point in the translated text of the corresponding country includes:

[0061] Obtain the historical translation texts of multiple corresponding countries that have signed, and obtain the historical translation collections of the corresponding countries;

[0062] Obtain the losses caused by each second risk point in the historical translation texts of each corresponding country;

[0063] In response to the user's evaluation operation, obtaining the scores of the impact of each second risk point in the historical translation text of each corresponding country according to the losses caused by each second risk point in the historical translation text of each corresponding country; and obtaining the maximum value of the scores of the impact of each second risk point in the historical translation text of each corresponding country;

[0064] According to formula 9

[0065]

[0066] Calculate the average impact score of the i-th second risk point in the historical translation collection Among them, L 2ikis the score for the impact of the i-th second risk point in the historical translation texts of the k-th corresponding country; u2 is the total number of historical translation texts of the corresponding country;

[0067] According to formula 10

[0068]

[0069] Calculate the historical risk coefficient HRC of the second risk point of the i-th type in the original text of the financial contract i2 , where Nh 2i Nh is the total number of occurrences of the i-th second risk point in the historical translation collection; t2 is the total number of words in the historical translation collection; is the average impact score of the i-th second risk point in the historical translation collection; L 2iMAX It is the maximum value of the scores of the impact of the i-th second risk point in the historical translation texts of each corresponding country.

[0070] Furthermore, the circulation information includes the review time, the reviewer, the previous processor information, and the next processor information.

[0071] Furthermore, the first blockchain adopts a first consensus mechanism;

[0072] The second blockchain adopts a second consensus mechanism;

[0073] The third blockchain adopts a third consensus mechanism.

[0074] Furthermore, the first consensus mechanism is selected from a PoS consensus mechanism or a DPoS consensus mechanism;

[0075] The second consensus mechanism and the third consensus mechanism are respectively selected from the PoW consensus mechanism.

[0076] The beneficial effects of the present disclosure are as follows:

[0077] The present disclosure can receive and process financial contracts containing original texts and translated texts in multiple languages ​​through the acquisition module, effectively solving the difficulties in understanding and executing cross-border financial contracts due to language differences. The review module builds rule bases for the original text and translated texts respectively, realizes comprehensive and accurate review of multilingual contract texts, and improves the efficiency and accuracy of contract execution.

[0078] This disclosure integrates the review process of multiple risk dimensions such as legal risk, risk control risk and financial risk. By building a refined rule base, it can comprehensively and deeply identify and evaluate potential risks in contracts. This not only helps to reduce legal risks, but also improves the security and stability of financial transactions.

[0079] The present disclosure realizes the intelligentization and automation of contract review. The review module can automatically identify risk points, calculate risk scores, and provide modification suggestions and review results, which greatly reduces the burden of manual review and improves review efficiency.

[0080] By introducing the backup module and the supervision module, the system realizes the real-time backup and consistency verification of the first blockchain data. Even if the main blockchain (the first blockchain) fails or is tampered with, the system can quickly restore the data from the backup blockchain (the second blockchain or the third blockchain) to ensure the integrity and security of the data. At the same time, the supervision module can promptly detect and handle data inconsistencies, effectively avoiding the risk of single point failure.

[0081] In addition, if two blockchains are backed up to each other, once one blockchain is attacked, it will only be possible to identify that the blockchain is attacked and fails, but it will not be possible to identify which specific blockchain has failed, and it will not be possible to respond to the failed blockchain in time, resulting in untimely problem handling. Based on this, the present disclosure adopts three blockchains. When the data of one blockchain is different from that of the other two, it can be discovered in time which specific blockchain has a problem and respond immediately.

[0082] The present invention can intelligently identify and process the translated texts under the corresponding national legal system, and can achieve seamless integration of language and legal differences through the review module. This not only improves the accuracy and efficiency of contract review, but also reduces the potential risks caused by language or legal misunderstandings, providing a more solid legal guarantee for cross-border financial transactions.

[0083] By utilizing the transparent and traceable characteristics of blockchain technology, this disclosure can ensure the openness and transparency of the contract review process and enhance the transparency and trust of the financial market. This will help enhance the confidence of investors and consumers and promote the healthy and stable development of the financial market.

[0084] More specifically, the legal risk review process refers to the legal review of foreign-related financial contracts and their translations by the legal department, including the legality, compliance, rigor and feasibility of the contract terms. The legal issues involved in the contract, such as applicable law, dispute resolution methods, etc., are reviewed to ensure that the contract complies with international law and the laws and regulations of relevant countries.

[0085] The risk control review process refers to the review of the financial terms and risk control measures of foreign-related financial contracts by the financial department; assessing the financial risks involved in the contract to formulate corresponding risk management measures.

[0086] The financial risk review process refers to the review of risk control measures for foreign-related financial contracts by the risk control department; assessing the compliance risks involved in the contract to formulate corresponding risk management measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] The specific implementation methods of the present disclosure are further described in detail below with reference to the accompanying drawings.

[0088] Figure 1 A schematic diagram showing an exemplary structure in which an embodiment of the present disclosure can be applied.

[0089] Figure 2 A schematic diagram showing the structure of a computer system for implementing the apparatus provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0090] In order to more clearly illustrate the present disclosure, the present disclosure is further described below in conjunction with the embodiments and drawings. Similar components in the drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the content described below is illustrative rather than restrictive, and should not be used to limit the scope of protection of the present disclosure.

[0091] like Figure 1 As shown, one embodiment of the present disclosure provides a multilingual financial contract intelligent review system based on blockchain technology, including:

[0092] A first blockchain, a second blockchain, a third blockchain, a review module, a backup module, an acquisition module, and a supervision module;

[0093] The acquisition module is used to obtain the latest financial contract original text sent by the first blockchain and multiple translation texts thereof marked with corresponding country information in each risk review process; in the present invention, the translation text is obtained by the user based on the translation of the financial contract original text, and the translation text here can be provided by any party to the contract transaction and can be recognized by all parties to the contract transaction.

[0094] The review module is used in each risk review process to:

[0095] Constructing a first rule base for the original text of financial contracts and a second rule base for the translated texts of corresponding countries respectively;

[0096] Identify and mark a first risk point in the original text of the financial contract according to the first rule base, and calculate a first risk score of the original text of the financial contract;

[0097] Identify and mark second risk points in the translated text of the corresponding country according to the second rule base, and calculate a second risk score of the translated text of the corresponding country;

[0098] In response to the user's review operation, based on the annotated original text of the financial contract, the first risk score, the annotated translation text of the corresponding country, and the second risk score, a modification suggestion, a review result, and circulation information are obtained, and an upload request is sent to the first blockchain to upload the modification suggestion, the review result, and the circulation information to the first blockchain;

[0099] A backup module, used to copy and store the data on the first blockchain to the second blockchain and the third blockchain;

[0100] A supervision module, used to detect and identify whether the data of any one of the first blockchain, the second blockchain, and the third blockchain is inconsistent with the data of the other two blockchains;

[0101] If data inconsistency is detected, an alarm signal is output and the blockchain with inconsistent data is marked as pending verification;

[0102] If the blockchain with inconsistent data is the first blockchain, reconfigure one of the second blockchain or the third blockchain as a new first blockchain;

[0103] The risk review process includes the legal risk review process, the risk control risk review process, and the financial risk review process.

[0104] The present disclosure can receive and process financial contracts containing original texts and translated texts in multiple languages ​​through the acquisition module, effectively solving the difficulties in understanding and executing cross-border financial contracts due to language differences. The review module builds rule bases for the original text and translated texts respectively, realizes comprehensive and accurate review of multilingual contract texts, and improves the efficiency and accuracy of contract execution.

[0105] This disclosure integrates the review process of multiple risk dimensions such as legal risk, risk control risk and financial risk. By building a refined rule base, it can comprehensively and deeply identify and evaluate potential risks in contracts. This not only helps to reduce legal risks, but also improves the security and stability of financial transactions.

[0106] The present disclosure realizes the intelligentization and automation of contract review. The review module can automatically identify risk points, calculate risk scores, and provide modification suggestions and review results, which greatly reduces the burden of manual review and improves review efficiency.

[0107] By introducing the backup module and the supervision module, the system realizes the real-time backup and consistency verification of the first blockchain data. Even if the main blockchain (the first blockchain) fails or is tampered with, the system can quickly restore the data from the backup blockchain (the second blockchain or the third blockchain) to ensure the integrity and security of the data. At the same time, the supervision module can promptly detect and handle data inconsistencies, effectively avoiding the risk of single point failure.

[0108] In addition, if two blockchains are backed up to each other, once one blockchain is attacked, it will only be possible to identify that the blockchain is attacked and fails, but it will not be possible to identify which specific blockchain has failed, and it will not be possible to respond to the failed blockchain in time, resulting in untimely problem handling. Based on this, the present disclosure adopts three blockchains. When the data of one blockchain is different from that of the other two, it can be discovered in time which specific blockchain has a problem and respond immediately.

[0109] The present invention can intelligently identify and process the translated texts under the corresponding national legal system, and can achieve seamless integration of language and legal differences through the review module. This not only improves the accuracy and efficiency of contract review, but also reduces the potential risks caused by language or legal misunderstandings, providing a more solid legal guarantee for cross-border financial transactions.

[0110] By utilizing the transparent and traceable characteristics of blockchain technology, this disclosure can ensure the openness and transparency of the contract review process and enhance the transparency and trust of the financial market. This will help enhance the confidence of investors and consumers and promote the healthy and stable development of the financial market.

[0111] More specifically, the legal risk review process refers to the legal review of foreign-related financial contracts and their translations by the legal department, including the legality, compliance, rigor and feasibility of the contract terms. The legal issues involved in the contract, such as applicable law, dispute resolution methods, etc., are reviewed to ensure that the contract complies with international law and the laws and regulations of relevant countries.

[0112] The risk control review process refers to the review of the financial terms and risk control measures of foreign-related financial contracts by the financial department; assessing the financial risks involved in the contract to formulate corresponding risk management measures.

[0113] The financial risk review process refers to the review of risk control measures for foreign-related financial contracts by the risk control department; assessing the compliance risks involved in the contract to formulate corresponding risk management measures.

[0114] More specifically, the review module is further used to obtain a plurality of first preset risk keywords for the original text of the financial contract before building the first rule base;

[0115] In response to the user's first classification operation, the first preset risk keyword is divided into a first legal risk review keyword, a first risk control risk review keyword, and a first financial risk review keyword; so that the review module constructs a first rule base of the legal risk review process according to the first legal risk review keyword in the legal risk review process; constructs a first rule base of the risk control risk review process according to the first risk control risk review keyword in the risk control risk review process; and constructs a first rule base of the financial risk review process according to the first financial risk review keyword in the financial risk review process;

[0116] The review module is also used to obtain a plurality of second preset risk keywords for the translation text of the corresponding country before building the second rule base;

[0117] In response to the user's second classification operation, the second preset risk keywords are divided into second legal risk review keywords, second risk control risk review keywords, and second financial risk review keywords; so that the review module constructs a second rule base corresponding to the country in the legal risk review process according to the second legal risk review keywords in the legal risk review process; constructs a second rule base corresponding to the country in the risk control risk review process according to the second risk control risk review keywords in the risk control risk review process; and constructs a second rule base corresponding to the country in the financial risk review process according to the second financial risk review keywords in the financial risk review process.

[0118] More specifically, the construction process of the first rule base includes:

[0119] The system first collects a plurality of first preset risk keywords for the original text of the financial contract. These keywords are usually related to common risk points in financial contracts, such as breach of contract clauses, interest rate changes, guarantee liabilities, etc. In response to the user's first classification operation, the system divides these first preset risk keywords into first legal risk review keywords, first wind control risk review keywords, and first financial risk review keywords. This step helps the system to build a corresponding rule base according to different types of risk points. Based on the classified risk keywords, the system formulates review rules for the original text of the financial contract. These rules may include keyword matching rules, risk point identification rules, risk score calculation rules, etc. All formulated rules are integrated into the first rule base for use in subsequent legal risk review processes, wind control risk review processes, and financial risk review processes.

[0120] The construction process of the second rule base includes the system collecting multiple second preset risk keywords for the translated texts of the corresponding countries. These keywords are usually related to risk points such as specific language expressions, cultural differences, legal differences, etc. in the translated text. In response to the user's second classification operation, the system divides these second preset risk keywords into second legal risk review keywords, second wind control risk review keywords, and second financial risk review keywords. This step also helps the system to build a corresponding rule base according to different types of risk points. Based on the classified risk keywords, the system formulates review rules for the translated texts of the corresponding countries. These rules may include language matching rules, cultural difference identification rules, legal difference identification rules, etc. All formulated rules are integrated into the second rule base for use in subsequent legal risk review processes, wind control risk review processes, and financial risk review processes.

[0121] In the process of building these two rule bases, natural language processing (NLP) technology can parse the complex text structure of financial contracts and extract key information, such as contract terms, amounts, dates, etc. It can also identify legal terms and professional expressions in contracts to more accurately assess risks. Keywords are automatically extracted from the contract text and matched with the preset risk keyword library. By optimizing the matching algorithm, the system can identify potential risk points and give corresponding risk warnings. For multilingual financial contracts, NLP technology can achieve cross-language text parsing and keyword extraction. Through translation models and language alignment technology, the system can accurately understand the content of contracts in different language versions.

[0122] Using historical contract data and risk events, machine learning algorithms can train risk prediction models.

[0123] These models can predict the risk level and potential risk points of a contract based on the characteristics of the contract text and risk keywords. As new data is continuously added, machine learning algorithms can continuously optimize and update risk prediction models. Through online learning and incremental learning technology, the system can update model parameters in real time to improve the accuracy and efficiency of risk identification.

[0124] Regular evaluation and update: The system should regularly evaluate the rule base to identify outdated or no longer applicable rules. According to new laws and regulations, industry standards and risk events, the system should promptly update the rule base to ensure the effectiveness and accuracy of the rules. The system should allow users to submit feedback and suggestions so that deficiencies in the rule base can be discovered and corrected in a timely manner. Through user feedback and data analysis, the system can continuously optimize the structure and content of the rule base and improve the practicality of the system and user experience.

[0125] Combining NLP and machine learning algorithms, this system can realize the automation and intelligent update of the rule base. By analyzing a large amount of contract text and risk event data, the system can automatically identify and extract new risk keywords and rule patterns, and update them to the rule base. This disclosure will not go into details here.

[0126] In this embodiment, the first preset risk keyword and the second preset risk keyword are obtained by the user based on laws, regulations and regulatory documents, judicial cases and precedents (such as foreign-related financial dispute cases), (company capital increase and shareholder rights protection cases), professional literature and research reports (legal risks and prevention and control in drafting foreign-related contracts and research reports on foreign-related financial legal services) and combined with experience.

[0127] More specifically, calculating the first risk score of the original financial contract includes:

[0128] According to formula 1

[0129]

[0130] Calculate the first risk score R of the original financial contract 1score ; Among them, P 1i A is the ratio of the number of the i-th first risk point in the original text of the financial contract to the total number of all first risk points; 1i is the weight of the i-th first risk point in the original text of the financial contract; n is the total number of types of first risk points in the original text of the financial contract;

[0131] Calculating the second risk score of the translated text for the corresponding country includes:

[0132] According to formula 2

[0133]

[0134] Calculate the second risk score R of the translated text for the corresponding country 2score ; Among them, P 2i A is the ratio of the number of the i-th second risk point in the translated text of the corresponding country to the total number of all second risk points; 2i is the weight of the i-th second risk point in the translated text of the corresponding country; m is the total number of types of second risk points in the translated text of the corresponding country.

[0135] More specifically, the weight A of the first risk point of the ith type in the original financial contract 1i include:

[0136] According to formula 3

[0137]

[0138] Calculate the weight A of the first risk point of the i-th type in the original financial contract 1i Among them, Nr 1i Nr is the number of occurrences of the first risk point of the ith type in the original text of the financial contract; t1 is the total number of words in the original text of the financial contract; Ac i1 is the first adjustment coefficient of the i-th first risk point in the original text of the financial contract; n is the total number of types of first risk points in the original text of the financial contract;

[0139] According to formula 4

[0140]

[0141] Calculate the weight A of the i-th second risk point in the translated text of the corresponding country 2i Among them, Nr 2i Nr is the number of occurrences of the i-th second risk point in the translated text of the corresponding country; t2 is the total number of words in the translated text of the corresponding country; Ac i2 is the second adjustment coefficient of the i-th second risk point in the translated text of the corresponding country; and m is the total number of types of second risk points in the translated text of the corresponding country.

[0142] More specifically, the first adjustment coefficient Ac of the first risk point of the i-th type in the original text of the financial contract i1 include:

[0143] According to formula 5

[0144] Ac i1 =α i1 ×HRC i1 +(1-α i1 )×S i1

[0145] Calculate the first adjustment coefficient Ac of the first risk point of the i-th type in the original financial contract i1 , where α i1 is the first preset weight coefficient of the first risk point of the ith type in the original text of the financial contract, HRC i1 is the historical risk coefficient of the first risk point of the ith type in the original text of the financial contract; S i1 The average value of the first preset expert scores for the first risk point of the i-th type in the original text of the financial contract;

[0146] The second adjustment coefficient Ac of the i-th second risk point in the translated text of the corresponding country i2 include:

[0147] According to formula 6

[0148] Ac i2 =α i2×HRC i2 +(1-α i2 )×S i2

[0149] Calculate the second adjustment coefficient Ac of the i-th second risk point in the translated text of the corresponding country i2 , where α i2 is the second preset weight coefficient of the second risk point of the i-th type in the translated text of the corresponding country, HRC i2 is the historical risk coefficient of the i-th second risk point in the translated text of the corresponding country; S i2 The average value of the second preset expert scores for the i-th second risk point in the translated text of the corresponding country.

[0150] More specifically, the first preset weight coefficient α of the first risk point of the i-th type in the original text of the financial contract i1 The value range is 0.7-0.8;

[0151] The second preset weight coefficient α of the i-th second risk point in the translated text of the corresponding country i2 The value range is 0.7-0.8.

[0152] This disclosure will i1 and α i2 Set to a higher value to reflect the greater importance of historical data in the risk identification process.

[0153] In one possible implementation, the historical risk coefficient HRC1 of the original financial contract includes:

[0154] Acquire multiple signed historical financial contract texts to obtain a historical financial contract set;

[0155] Obtain the losses caused by each first risk point in each historical financial contract text;

[0156] In response to the user's evaluation operation, the scores of the impact of each first risk point in each historical financial contract text are obtained according to the losses caused by each first risk point in each historical financial contract text; and the maximum value of the scores of the impact of each first risk point in each historical financial contract text is obtained;

[0157] According to formula 7

[0158]

[0159] Calculate the average impact score of the first risk point of the i-th type in the historical financial contract set Among them, L 1ikis the impact score of the i-th first risk point in the historical financial contract set in the k-th historical financial contract text; u1 is the total number of historical financial contract texts;

[0160] According to formula 8

[0161]

[0162] Calculate the historical risk coefficient HRC of the first risk point of the i-th type in the original text of the financial contract i1 , where Nh 1i is the total number of occurrences of the first risk point of the i-th type in the historical financial contract set; Nht1 is the total number of words in the historical financial contract set; is the average impact score of the first risk point of the i-th type in the historical financial contract set; L 1iMAx is the maximum value of the scores of the impact of the i-th first risk point in the historical financial contract set in each historical financial contract text;

[0163] The historical risk coefficient HRC2 of the i-th second risk point in the translated text of the corresponding country includes:

[0164] Obtain the historical translation texts of multiple corresponding countries that have signed, and obtain the historical translation collections of the corresponding countries;

[0165] Obtain the losses caused by each second risk point in the historical translation texts of each corresponding country;

[0166] In response to the user's evaluation operation, obtaining the scores of the impact of each second risk point in the historical translation text of each corresponding country according to the losses caused by each second risk point in the historical translation text of each corresponding country; and obtaining the maximum value of the scores of the impact of each second risk point in the historical translation text of each corresponding country;

[0167] According to formula 9

[0168]

[0169] Calculate the average impact score of the i-th second risk point in the historical translation collection Among them, L 2ik is the score for the impact of the i-th second risk point in the historical translation texts of the k-th corresponding country; u2 is the total number of historical translation texts of the corresponding country;

[0170] According to formula 10

[0171]

[0172] Calculate the historical risk coefficient HRC of the second risk point of the i-th type in the original text of the financial contracti2 , where Nh 2i Nh is the total number of occurrences of the i-th second risk point in the historical translation collection; t2 is the total number of words in the historical translation collection; is the average impact score of the i-th second risk point in the historical translation collection; L 2iMAX It is the maximum value of the scores of the impact of the i-th second risk point in the historical translation texts of each corresponding country.

[0173] The financial contract risk assessment method proposed in the present invention realizes a comprehensive and quantitative assessment of risk points in the original text of the financial contract and its corresponding national translation text through multiple formulas and steps, significantly improving the accuracy and efficiency of risk assessment.

[0174] This paper first defines the first risk point in the original text of the financial contract and the second risk point in the corresponding national translation text, and calculates the first risk score of the original text of the financial contract and the second risk score of the corresponding national translation text based on the number, weight and adjustment coefficient of these risk points. This quantitative assessment method not only makes the risk assessment results more objective and reliable, but also facilitates the horizontal comparison of the risk levels of different contract texts, providing strong data support for decision makers.

[0175] In terms of weight calculation, the disclosure fully considers the number of times the risk point appears, the total number of words in the contract text, and the adjustment coefficient of the risk point, so as to more accurately reflect the importance and potential impact of the risk point in the contract text. In particular, by introducing historical risk coefficients and the average value of expert scores, the accuracy and scientificity of weight calculation are further improved.

[0176] In addition, this disclosure also constructs a historical financial contract set and a historical translation set by acquiring multiple signed historical financial contract texts and historical translation texts of corresponding countries, and calculates the average impact score and historical risk coefficient of risk points based on these historical data. This not only helps to reveal the historical performance and future trends of risk points, but also provides a richer source of information and basis for the identification and evaluation of risk points.

[0177] In summary, the financial contract risk assessment method proposed in this disclosure has significant beneficial effects, including improving the accuracy, efficiency, objectivity and scientificity of risk assessment, providing financial institutions and enterprises with a powerful risk prevention and control tool when conducting foreign-related financial transactions, helping to reduce transaction risks and protect the legitimate rights and interests of both parties to the contract.

[0178] More specifically, the flow information includes the review time, reviewer, previous processor information, and next processor information.

[0179] More specifically, the first blockchain adopts the first consensus mechanism;

[0180] The second blockchain adopts the second consensus mechanism;

[0181] The third blockchain adopts the third consensus mechanism.

[0182] More specifically, the first consensus mechanism is selected from a Proof of Stake (PoS) consensus mechanism or a Delegated Proof of Stake (DPoS) consensus mechanism;

[0183] The second consensus mechanism and the third consensus mechanism are respectively selected from the Proof of Work (PoW) consensus mechanism.

[0184] In this embodiment, the PoS consensus mechanism is a consensus mechanism used to replace PoW (Proof of Work) in blockchain technology. Under the PoS consensus mechanism, participants can own the issued cryptocurrency and obtain voting rights by locking the pledged currency, which is used to vote on the consensus results of the network, thereby determining the generation of blocks.

[0185] The DPoS consensus mechanism is a blockchain consensus algorithm that aims to improve the performance and efficiency of the blockchain network by verifying and recording transactions through elected representatives (witnesses).

[0186] The PoW consensus mechanism is an algorithm used in a blockchain network to determine how new blocks are generated and the consensus results.

[0187] The PoW mechanism ensures the integrity of the network by adding new blocks through a large amount of computing resources, making any attempt to conduct a 51% attack or double spending very costly and resource-intensive. The PoW mechanism encourages decentralization and allows anyone with the necessary hardware to participate in the mining process, forming a distributed network of miners, making it difficult for any single entity to control the blockchain. Once a transaction is added to the blockchain, it becomes computationally infeasible to change it because the cumulative workload required to change past blocks is very large, which makes the blockchain highly resistant to tampering.

[0188] Compared with PoW, the PoS mechanism does not require a large amount of computing resources to compete for the right to record, thereby reducing energy consumption. Since the right to record is allocated according to the amount and time of holding coins under the PoS mechanism, the speed of generating new blocks is relatively fast, and the speed of transaction confirmation is also fast.

[0189] The DPoS mechanism verifies and records transactions through elected representatives, greatly improving the performance and efficiency of the blockchain network. The DPoS mechanism can well adapt to the needs of large-scale applications and has good scalability. Compared with PoW, the DPoS mechanism does not require a large amount of computing resources to compete for accounting rights, thereby reducing energy consumption.

[0190] The first blockchain of the present disclosure adopts the PoS consensus mechanism or the DPoS consensus machine to reduce energy consumption or improve data processing efficiency; while the second blockchain and the third blockchain adopt the PoW consensus mechanism to improve their ability to resist tampering and improve the security of the second blockchain and the third blockchain. The consensus mechanism of the second blockchain and the third blockchain in the present disclosure is different from the consensus mechanism of the first blockchain, which further improves the security of the system.

[0191] like Figure 2 As shown, a computer system suitable for implementing a multilingual financial contract intelligent audit system based on blockchain technology provided in the above-mentioned embodiment includes a central processing module (CPU), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage part into a random access memory (RAM). In RAM, various programs and data required for the operation of the computer system are also stored. The CPU, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0192] The following components are connected to the I / O interface: an input part including a keyboard, a mouse, etc.; an output part including a liquid crystal display (LCD), etc. and a speaker, etc.; a storage part including a hard disk, etc.; and a communication part including a network interface card such as a LAN card, a modem, etc. The communication part performs communication processing via a network such as the Internet. A drive is also connected to the I / O interface as needed. Removable media, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., are installed on the drive as needed so that the computer program read therefrom is installed into the storage part as needed.

[0193] In particular, according to this embodiment, the process described in the flowchart above can be implemented as a computer software program. For example, this embodiment includes a computer program product, which includes a computer program tangibly contained on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part, and / or installed from a removable medium.

[0194] The flow chart and schematic diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product of the present embodiment. In this regard, each square box in the flow chart or schematic diagram can represent a part of a module, program segment or code, and a part of the above-mentioned module, program segment or code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the schematic diagram and / or flow chart, and the combination of the square boxes in the schematic diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0195] In the description of the present disclosure, it should be noted that the orientation or positional relationship indicated by the terms "upper", "lower", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present disclosure and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present disclosure. Unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, and it can be the internal connection of two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present disclosure can be understood according to the specific circumstances.

[0196] It should also be noted that, in the description of the present disclosure, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or equipment. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or equipment including the elements.

[0197] Obviously, the above embodiments of the present disclosure are merely examples for clearly illustrating the present disclosure, and are not limitations on the implementation methods of the present disclosure. For ordinary technicians in this field, other different forms of changes or modifications can be made on the basis of the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present disclosure are still within the protection scope of the present disclosure.

Claims

1. A multilingual financial contract intelligent review system based on blockchain technology, characterized by: include: A first blockchain, a second blockchain, a third blockchain, a review module, a backup module, an acquisition module, and a supervision module; The acquisition module is used to obtain the latest original financial contract sent by the first blockchain and multiple translated texts thereof marked with corresponding country information in each risk review process; The review module is used in each risk review process to: Constructing a first rule base for the original text of financial contracts and a second rule base for the translated texts of corresponding countries respectively; Identify and mark a first risk point in the original text of the financial contract according to the first rule base, and calculate a first risk score of the original text of the financial contract; Identify and mark second risk points in the translated text of the corresponding country according to the second rule base, and calculate a second risk score of the translated text of the corresponding country; In response to the user's review operation, based on the annotated original text of the financial contract, the first risk score, the annotated translation text of the corresponding country, and the second risk score, a modification suggestion, a review result, and circulation information are obtained, and an upload request is sent to the first blockchain to upload the modification suggestion, the review result, and the circulation information to the first blockchain; A backup module, used to copy and store the data on the first blockchain to the second blockchain and the third blockchain; A supervision module, used to detect and identify whether the data of any one of the first blockchain, the second blockchain, and the third blockchain is inconsistent with the data of the other two blockchains; If data inconsistency is detected, an alarm signal is output and the blockchain with inconsistent data is marked as pending verification; If the blockchain with inconsistent data is the first blockchain, reconfigure one of the second blockchain or the third blockchain as a new first blockchain; The risk review process includes a legal risk review process, a risk control risk review process, and a financial risk review process.

2. The system according to claim 1, characterized in that The review module is also used to obtain a plurality of first preset risk keywords for the original text of the financial contract before building the first rule base; In response to a first classification operation by a user, the first preset risk keyword is divided into a first legal risk review keyword, a first wind control risk review keyword, and a first financial risk review keyword; so that the review module constructs a first rule base of the legal risk review process according to the first legal risk review keyword in the legal risk review process; In the risk control risk review process, a first rule base of the risk control risk review process is constructed according to the first risk control risk review keyword; in the financial risk review process, a first rule base of the financial risk review process is constructed according to the first financial risk review keyword; The review module is also used to obtain a plurality of second preset risk keywords for the translation text of the corresponding country before building the second rule base; In response to the user's second classification operation, the second preset risk keywords are divided into second legal risk review keywords, second risk control risk review keywords, and second financial risk review keywords; so that the review module constructs a second rule base corresponding to the country in the legal risk review process according to the second legal risk review keywords in the legal risk review process; constructs a second rule base corresponding to the country in the risk control risk review process according to the second risk control risk review keywords in the risk control risk review process; and constructs a second rule base corresponding to the country in the financial risk review process according to the second financial risk review keywords in the financial risk review process.

3. The system according to claim 1, characterized in that The calculating of the first risk score of the original financial contract includes: According to formula 1 Calculate the first risk score R of the original financial contract 1score ; Among them, P 1i A is the ratio of the number of the i-th first risk point in the original text of the financial contract to the total number of all first risk points; 1i is the weight of the i-th first risk point in the original text of the financial contract; n is the total number of types of first risk points in the original text of the financial contract; Calculating the second risk score of the translated text of the corresponding country includes: According to formula 2 Calculate the second risk score R of the translated text for the corresponding country 2score ; Among them, P 2i A is the ratio of the number of the i-th second risk point in the translated text of the corresponding country to the total number of all second risk points; 2i is the weight of the i-th second risk point in the translated text of the corresponding country; m is the total number of types of second risk points in the translated text of the corresponding country.

4. The system according to claim 3, characterized in that The weight A of the first risk point of the i-th type in the original text of the financial contract 1i include: According to formula 3 Calculate the weight A of the first risk point of the i-th type in the original financial contract 1i Among them, Nr 1i Nr is the number of occurrences of the first risk point of the ith type in the original text of the financial contract; t1 is the total number of words in the original text of the financial contract; Ac i1 is the first adjustment coefficient of the i-th first risk point in the original text of the financial contract; n is the total number of types of first risk points in the original text of the financial contract; According to formula 4 Calculate the weight A of the i-th second risk point in the translated text of the corresponding country 2i Among them, Nr 2i Nr is the number of occurrences of the i-th second risk point in the translated text of the corresponding country; t2 is the total number of words in the translated text of the corresponding country; Ac i2 is the second adjustment coefficient of the i-th second risk point in the translated text of the corresponding country; and m is the total number of types of second risk points in the translated text of the corresponding country.

5. The system according to claim 4, characterized in that The first adjustment coefficient Ac of the first risk point of the i-th type in the original text of the financial contract i1 include: According to formula 5 Ac i1 =a i1 ×HRC i1 +(1-a i1 )×S i1 Calculate the first adjustment coefficient Ac of the first risk point of the i-th type in the original financial contract i1 , where α i1 is the first preset weight coefficient of the first risk point of the ith type in the original text of the financial contract, HRC i1 is the historical risk coefficient of the first risk point of the ith type in the original text of the financial contract; S i1 The average value of the first preset expert scores for the first risk point of the i-th type in the original text of the financial contract; The second adjustment coefficient Ac of the i-th second risk point in the translation text of the corresponding country i2 include: According to formula 6 Ac i2 =a i2 ×HRC i2 +(1-a i2 )×S i2 Calculate the second adjustment coefficient Ac of the i-th second risk point in the translated text of the corresponding country i2 , where α i2 is the second preset weight coefficient of the second risk point of the i-th type in the translated text of the corresponding country, HRC i2 is the historical risk coefficient of the i-th second risk point in the translated text of the corresponding country; S i2 The average value of the second preset expert scores for the i-th second risk point in the translated text of the corresponding country.

6. The system according to claim 5, characterized in that The first preset weight coefficient α of the first risk point of the i-th type in the original text of the financial contract i1 The value range is 0.7-0.8; The second preset weight coefficient α of the i-th second risk point in the translated text of the corresponding country i2 The value range is 0.7-0.

8.

7. The system according to claim 5, characterized in that The historical risk coefficient HRC1 of the original financial contract includes: Acquire multiple signed historical financial contract texts to obtain a historical financial contract set; Obtain the losses caused by each first risk point in each historical financial contract text; In response to the user's evaluation operation, the scores of the impact of each first risk point in each historical financial contract text are obtained according to the losses caused by each first risk point in each historical financial contract text; and the maximum value of the scores of the impact of each first risk point in each historical financial contract text is obtained; According to formula 7 Calculate the average impact score of the first risk point of the i-th type in the historical financial contract set Among them, L 1ik is the impact score of the i-th first risk point in the historical financial contract set in the k-th historical financial contract text; u1 is the total number of historical financial contract texts; According to formula 8 Calculate the historical risk coefficient HRC of the first risk point of the i-th type in the original text of the financial contract i1 , where Nh 1i Nh is the total number of occurrences of the first risk point of the i-th type in the historical financial contract set; t1 is the total number of words in the historical financial contract set; is the average impact score of the first risk point of the i-th type in the historical financial contract set; L 1iMAX is the maximum value of the scores of the impact of the i-th first risk point in the historical financial contract set in each historical financial contract text; The historical risk coefficient HRC2 of the i-th second risk point in the translated text of the corresponding country includes: Obtain the historical translation texts of multiple corresponding countries that have signed, and obtain the historical translation collections of the corresponding countries; Obtain the losses caused by each second risk point in the historical translation texts of each corresponding country; In response to the user's evaluation operation, obtaining the scores of the impact of each second risk point in the historical translation text of each corresponding country according to the losses caused by each second risk point in the historical translation text of each corresponding country; and obtaining the maximum value of the scores of the impact of each second risk point in the historical translation text of each corresponding country; According to formula 9 Calculate the average impact score of the i-th second risk point in the historical translation collection Among them, L 2ik is the score for the impact of the i-th second risk point in the historical translation texts of the k-th corresponding country; u2 is the total number of historical translation texts of the corresponding country; According to formula 10 Calculate the historical risk coefficient HRC of the second risk point of the i-th type in the original text of the financial contract i2 , where Nh 2i Nh is the total number of occurrences of the i-th second risk point in the historical translation collection; t2 is the total number of words in the historical translation collection; is the average impact score of the i-th second risk point in the historical translation collection; L 2iMAX It is the maximum value of the scores of the impact of the i-th second risk point in the historical translation texts of each corresponding country.

8. The system according to claim 1, characterized in that The circulation information includes the review time, the reviewer, the previous processor information, and the next processor information.

9. The system according to claim 1, characterized in that The first blockchain adopts a first consensus mechanism; The second blockchain adopts a second consensus mechanism; The third blockchain adopts a third consensus mechanism.

10. The system according to claim 9, characterized in that The first consensus mechanism is selected from a PoS consensus mechanism or a DPoS consensus mechanism; The second consensus mechanism and the third consensus mechanism are respectively selected from the PoW consensus mechanism.

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