Financial auditing method and system based on block chain technology

Abstract

The invention is suitable for the field of financial auditing, and provides a financial auditing method and system based on a block chain technology, and the system comprises an intelligent contract rule setting module, a distributed identity generation module, a fund application record verification module, an approval chain matching updating module, an approval chain integrity verification module, and an abnormal fund backtracking analysis module. According to the method, the transparency of fund flow and the traceability of auditing are enhanced, strong traceability is achieved, an enterprise can track the flow direction of funds, the compliance of an approval chain and detailed information of abnormal marks at any time, it is ensured that all fund operations are carried out in a clear rule framework, and the operation efficiency is improved. The non-tampering property of the block chain also provides credible evidence support for the audit result, which not only improves the transparency of internal fund management of the enterprise, but also provides a reliable compliance basis for the enterprise to cope with external audit and supervision.

Description

Technical Field

[0001] The present invention belongs to the field of financial auditing, and particularly relates to a financial auditing method and system based on blockchain technology. Background Art

[0002] Financial auditing mainly involves the review, verification, and analysis of a company's financial activities, aiming to evaluate the authenticity, integrity, and compliance of its financial data. This field encompasses a variety of technical methods, including traditional manual audits, rule-based automated audits, and emerging intelligent auditing technologies in recent years (such as blockchain, artificial intelligence, and big data analysis). Its core task is to comprehensively examine and analyze capital flows, transaction records, approval processes, etc., identify abnormal behaviors, potential risks, and systematic problems, while ensuring that financial operations comply with relevant laws, regulations, and corporate internal control policies. With the increase in business complexity and data volume, the field of financial auditing is gradually moving towards automation, intelligence, and precision to improve efficiency, transparency, and risk management capabilities.

[0003] In the prior art, the handling of abnormal funds is often limited to the marking and handling of current problems, lacking the ability to deeply analyze the historical transaction records and approval chains, and it is difficult to systematically discover potential hidden risks. For example, abnormal funds may be related to other approved fund applications in terms of approvers, project IDs, or capital flow directions, but traditional means lack automated rule screening and data correlation analysis, easily overlooking these historical problems and resulting in incomplete risk revelation.

[0004] In addition, the existing means have limited ability to trace the flow path of abnormal funds, unable to fully restore the entire process of funds from application, approval to final use. Especially for complex capital flow scenarios, it is difficult to identify the multi-level correlation problems therein. This limitation makes potential abnormal transactions or systematic loopholes easily covered up, thus affecting the enterprise's risk control effect and the comprehensiveness of financial auditing. Summary of the Invention

[0005] The purpose of the present invention is to provide a financial auditing method based on blockchain technology, aiming to solve the technical problems existing in the prior art determined in the background art.

[0006] The present invention is implemented as follows. A financial auditing method based on blockchain technology, the method includes:

[0007] Preset smart contract rules according to the enterprise's financial management policies and rules, including fund approval chain rules, fund flow rules, anomaly detection rules, and dynamic update rules, and deploy the created smart contract on the blockchain, recording the unique identifier;

[0008] Automatically generate a unique distributed identity for each applicant and business-related party based on personnel data, bind a permission level to each distributed identity according to the applicant's position and responsibilities, and write it into the blockchain;

[0009] When an applicant submits a funding application, record the applicant's distributed identity and application information, generate a unique application ID, and automatically write the application data into the blockchain. At the same time, trigger the verification of the smart contract, enter the approval process, and add an exception mark to the funding application with abnormal verification;

[0010] Identify the approval chain corresponding to the funding application, match the approvers who meet the permission level, record the distributed identity, operation time, and approval opinion of each approval operation, and update the blockchain record;

[0011] Continuously verify the integrity of the approval chain during the approval process. If one level of approval is not completed, suspend the current transaction; if the approval chain rules are bypassed, add an exception mark to the funding application and the approval chain;

[0012] Conduct a retrospective review of the funding applications with exception marks, track the complete flow path of the abnormal application, extract all relevant transaction records, and conduct a correlation analysis to generate a combined analysis report of abnormal funds.

[0013] As a further solution of the present invention, preset smart contract rules according to enterprise financial management policies and rules, including fund approval chain rules, fund flow rules, exception detection rules, and dynamic update rules, and deploy the created smart contract on the blockchain, record the unique identifier, specifically including:

[0014] Design fund approval chain rules for each type of funding application according to the type, amount, and risk level of the funding application, including large amounts of funds, small amounts of funds, and special funds, and define the approval process and levels required for the funding application;

[0015] Set fund flow rules, define the upper limit of the amount of a single funding application, set different thresholds according to different departments, projects, or cost centers, and set the maximum frequency of fund flow;

[0016] Define exception detection rules, define types of abnormal behaviors according to enterprise policies and risk predictions, and establish an exception detection model based on blockchain transaction data;

[0017] Add dynamic update rules, use the blockchain to store historical fund flow and exception detection data, and regularly analyze the applicability of all established rules;

[0018] Compile the fund approval chain rules, fund flow rules, and exception detection rules into executable smart contract code, and deploy the smart contract to the blockchain network, record the unique identifier.

[0019] As a further solution of the present invention, automatically generate a unique distributed identity for each applicant and business-related party according to the personnel data, bind a permission level to each distributed identity according to the applicant's position and responsibilities, and write it into the blockchain, specifically including:

[0020] Extract the basic information of the applicant and the information of the business-related party from the personnel system, and generate a unique blockchain-based distributed identity for each applicant and business-related party based on this;

[0021] Automatically bind a permission scope to each distributed identity according to the applicant's position, responsibilities and department, including fund application permission, approval permission and query permission. When binding permissions, preset a dynamic adjustment mechanism to allow permissions to change in real time according to time limits and behavior records;

[0022] Establish an approval chain rule, and bind each distributed identity to the corresponding approval chain permission level. The approval chain rule is used to screen which distributed identities are required to participate in the approval of different types of transactions, and the approval order of different distributed identities, and define the approval chain permission level of the distributed identity based on this;

[0023] Write each distributed identity and its bound permission level into the blockchain.

[0024] As a further solution of the present invention, when the applicant issues a fund application, record the applicant's distributed identity and application information, generate a unique application ID, and automatically write the application data into the blockchain, while triggering smart contract verification, entering the approval process, and adding an exception mark to the fund application with abnormal verification, specifically including:

[0025] When receiving the fund application issued by the applicant, obtain the information of the fund application, and generate a unique application ID based on the applicant's distributed identity, application timestamp and fund use;

[0026] Verify the integrity of the information of the fund application, and write the complete record of the fund application into the blockchain;

[0027] Call the smart contract to verify the compliance of the application according to the fund approval chain rule and the fund flow rule, and when it is identified that there is an abnormality in this fund application, add an exception mark to this fund application and write it into the blockchain;

[0028] Automatically generate an audit log for each fund application, including the applicant's distributed identity, application amount, use, and priority.

[0029] As a further aspect of the present invention, the approval chain corresponding to the fund application is identified, the approvers meeting the authority level are matched, and the distributed identity, operation time, and approval opinion of the approver are recorded for each approval operation, and the blockchain record is updated, specifically including:

[0030] Read the fund application data and match the corresponding approval chain rules for the fund application data;

[0031] According to the approval chain rules, screen the eligible approvers and send approval requests to each matched approver;

[0032] Record the approver information and approval process information for each approval;

[0033] After each approval is completed, automatically check whether the approval chain is completed according to the rules, and the rules include:

[0034] Whether the approval is carried out step by step in the order of the approval chain;

[0035] Whether any approval level is skipped or bypassed;

[0036] Whether all approvers meet the authority requirements;

[0037] If there is an incomplete approval according to the rules, automatically mark and record the abnormality;

[0038] If all approvals are completed, update the status of the fund application to approved and enter the fund disbursement process.

[0039] As a further aspect of the present invention, during the approval process, continuously verify the integrity of the approval chain. If one level of approval is not completed, suspend the current transaction; if the approval chain rules are bypassed, mark the fund application and the approval chain as abnormal, specifically including:

[0040] Real-time track the progress of each fund application in the approval chain, including: whether it progresses step by step according to the approval chain rules, and whether each level of approval operation is completed on time;

[0041] Record the detailed information of each approval operation, and verify the compliance of each level of approval according to the approval chain rules preset by the smart contract;

[0042] Based on the anomaly detection model established by the anomaly detection rules, monitor potential problems in the approval chain;

[0043] Generate an anomaly mark for the detected abnormal fund application.

[0044] As a further aspect of the present invention, the monitoring of potential problems in the approval chain specifically includes:

[0045]

[0046] where D is the anomaly score, x is the data point of the funding application to be detected and approved, and x i are the k nearest neighbors in the approval history dataset closest to it, and d(x, x i ) represents the similarity distance between data points;

[0047] Set a marking threshold for the anomaly score. If the anomaly score of the funding application exceeds the marking threshold, mark the funding application as an anomaly and generate an anomaly mark.

[0048] As a further solution of the present invention, conduct a retrospective review on the funding applications with anomaly marks, track the complete flow path of the abnormal application, extract all relevant transaction records, and conduct a correlation analysis to generate an integrated analysis report of abnormal funds, specifically including:

[0049] Extract the funding application data with anomaly marks from the blockchain, and set corresponding retrospective analysis strategies according to the anomaly types, including:

[0050] For anomalies of the approval chain skipping type, analyze the skipped links and relevant records in the approval chain;

[0051] For anomalies of the amount exceeding limit type, analyze the historical fund flow records related to the application amount;

[0052] For anomalies of the associated project type, analyze the historical transactions between the application and the supplier;

[0053] Through the blockchain records, track the complete flow path of the abnormal funds and identify the abnormal nodes in the fund flow path;

[0054] Define association rules, and extract historical transaction records related to the current abnormal funds according to the association rules;

[0055] The association rules include: all funding applications submitted by the same applicant, all historical transaction records with the same fund flow direction as the current abnormal funds, historical records with the same project ID as the current application, and funding applications approved by the same group of approvers;

[0056] Screen the funding applications and their approval records that meet the association rules from the blockchain, and construct an association graph of abnormal funds based on the fund flow records and historical transaction records;

[0057] Conduct a quantitative analysis on the extracted records and calculate the association strength with the current funds:

[0058]

[0059]

[0060] Set an intensity threshold, and identify potential associated anomalies based on the association intensity and abnormal distribution;

[0061] Summarize the flow path of abnormal funds, historical transaction records, and the results of correlation analysis into a report.

[0062] Another object of the present invention is to provide a financial audit system based on blockchain technology, and the system includes:

[0063] An intelligent contract rule setting module, which is used to preset intelligent contract rules according to enterprise financial management policies and rules, including fund approval chain rules, fund flow rules, anomaly detection rules, and dynamic update rules, and deploy the created intelligent contracts on the blockchain, recording the unique identifier;

[0064] A distributed identity generation module, which is used to automatically generate a unique distributed identity for each applicant and business-related party according to personnel data, bind a permission level to each distributed identity according to the applicant's position and responsibilities, and write it into the blockchain;

[0065] A fund application record verification module, which is used to record the applicant's distributed identity and application information when the applicant issues a fund application, generate a unique application ID, automatically write the application data into the blockchain, trigger intelligent contract verification at the same time, enter the approval process, and add an anomaly mark to the fund application with verification anomalies;

[0066] An approval chain matching and updating module, which is used to identify the approval chain corresponding to the fund application, match the approvers who meet the permission level, record the distributed identity, operation time, and approval opinion of the approver for each approval operation, and update the blockchain record;

[0067] An approval chain integrity verification module, which is used to continuously verify the integrity of the approval chain during the approval process. If one level of approval is not completed, the current transaction is suspended; if the approval chain rules are bypassed, an anomaly mark is added to the fund application and the approval chain;

[0068] An abnormal fund backtracking analysis module, which is used to conduct a backtracking review of the fund application with an anomaly mark, track the complete flow path of the abnormal application, extract all relevant transaction records, and conduct a correlation analysis to generate a combined analysis report of abnormal funds.

[0069] The beneficial effects of the present invention are:

[0070] By presetting anomaly detection rules through smart contracts, the system can trigger anomaly markings in real time and, combined with the immutable distributed records of the blockchain, ensure the discovery of potential risks in fund applications at the first time. This mechanism avoids the delays and omissions in traditional financial audits due to manual reviews, especially has a strong ability to identify hidden anomalies in complex audit scenarios. At the same time, this method is not limited to the identification of current anomalies, but also mines historical transaction records associated with anomalous funds through the backtracking review function, expanding the anomaly location to the level of correlation analysis;

[0071] This method enhances the transparency of fund flows and the traceability of audits. Since all fund applications, approval records, anomaly markings, and backtracking review results are recorded through the blockchain, the system has a powerful traceability ability. Enterprises can track the flow of funds, the compliance of the approval chain, and the detailed information of anomaly markings at any time, ensuring that all fund operations are carried out within a clear rule framework. The immutability of the blockchain also provides credible evidence support for audit results, which not only improves the transparency of internal fund management in enterprises but also provides a reliable compliance basis for enterprises to respond to external audits and supervision. Brief Description of the Drawings

[0072] Figure 1 It is a flowchart of a financial audit method based on blockchain technology provided by an embodiment of the present invention;

[0073] Figure 2 It is a flowchart of presetting smart contract rules according to enterprise financial management policies and rules provided by an embodiment of the present invention;

[0074] Figure 3 It is a flowchart of binding permission levels to each distributed identity provided by an embodiment of the present invention;

[0075] Figure 4 It is a flowchart of adding anomaly markings to verified anomalous fund applications provided by an embodiment of the present invention;

[0076] Figure 5 It is a flowchart of identifying the approval chain corresponding to a fund application and matching approvers who meet the permission levels provided by an embodiment of the present invention;

[0077] Figure 6 It is a flowchart of continuously verifying the integrity of the approval chain during the approval process provided by an embodiment of the present invention;

[0078] Figure 7 It is a flowchart of conducting a backtracking review of fund applications with anomaly markings provided by an embodiment of the present invention;

[0079] Figure 8 It is a structural block diagram of a financial audit system based on blockchain technology provided by an embodiment of the present invention. Detailed implementation manners

[0080] To make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0081] It can be understood that the terms "first", "second", etc. used in the present application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of the present application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0082] Figure 1 The flowchart of a financial audit method based on blockchain technology provided by an embodiment of the present invention is as Figure 1 shown, and the method includes:

[0083] S100, preset smart contract rules according to enterprise financial management policies and rules, including fund approval chain rules, fund flow rules, anomaly detection rules and dynamic update rules, and deploy the created smart contract on the blockchain, recording the unique identifier;

[0084] This step needs to classify the types of enterprise fund applications, such as large-amount funds, small-amount funds and special funds, and design corresponding fund approval chain rules based on the characteristics of each type of fund application. These rules clearly define the levels of the approval process, the scope of authority of the approvers, and the order of approval, ensuring the compliance and transparency of the approval process.

[0085] Secondly, it is necessary to set the fund flow rules, define the upper limit amount of a single fund application, and at the same time, according to the specific needs of departments, projects or cost centers within the enterprise, set different fund thresholds and flow frequency limits to avoid the risks brought by the abuse of funds or overly frequent fund flows.

[0086] Thirdly, it is necessary to define the anomaly detection rules. This link is based on the policy requirements and risk predictions of the enterprise, and identifies potential abnormal behaviors, such as abnormal large-amount fund flows and non-compliant approval chain operations, by establishing an anomaly detection model.

[0087] In addition, it is also necessary to add dynamic update rules. By using the historical fund flow data and anomaly detection data stored in the blockchain, regularly analyze the applicability of these rules, and optimize and update the rules according to the changes in the enterprise development and risk environment to ensure that the rules always adapt to the actual needs.

[0088] Finally, compile all the designed rules into smart contract code and deploy it to the blockchain network. At the same time, record the unique identifier of each smart contract for quick invocation and verification in subsequent processes.

[0089] By presetting the fund approval chain rules and flow rules, the standardization and automation of the fund application and approval process can be achieved, which not only improves efficiency but also significantly reduces the possibility of manual intervention, thus reducing problems caused by human negligence or operational errors. Secondly, the introduction of anomaly detection rules makes the entire financial audit process more accurate and efficient. Based on the immutability and transparency characteristics of the blockchain, the anomaly detection model can quickly identify potential risks and automatically trigger subsequent processing processes through smart contracts, greatly enhancing the risk management ability. In addition, the design of dynamic update rules ensures the flexibility and continuous improvement ability of the system. The business environment and risk characteristics of enterprises change over time, and dynamic update rules can ensure that the rule system can keep up with the times, continuously optimize, and always maintain high efficiency and adaptability. Finally, the deployment of smart contracts and the recording of unique identifiers further strengthen the enforceability and traceability of the rules. The distributed ledger feature of the blockchain ensures that the execution process of smart contracts is open, transparent, and tamper-proof, thus greatly enhancing the credibility and compliance of enterprise financial management.

[0090] Such as Figure 2 As shown, presetting smart contract rules according to enterprise financial management policies and rules, including fund approval chain rules, fund flow rules, anomaly detection rules, and dynamic update rules, and deploying the created smart contracts on the blockchain and recording unique identifiers specifically include:

[0091] S110. Design fund approval chain rules for each type of fund application according to the type, amount, and risk level of the fund application, including large amounts of funds, small amounts of funds, and special funds, and define the approval process and levels required for the fund application.

[0092] S120. Set fund flow rules, define the upper limit of the amount for a single fund application, set different thresholds according to different departments, projects, or cost centers, and set the maximum frequency of fund flow.

[0093] S130. Define anomaly detection rules, define types of abnormal behaviors according to enterprise policies and risk predictions, and establish an anomaly detection model based on blockchain transaction data.

[0094] S140. Add dynamic update rules, use the blockchain to store historical fund flow and anomaly detection data, and regularly analyze the applicability of all established rules.

[0095] S150. Compile the fund approval chain rules, fund flow rules, and anomaly detection rules into executable smart contract code, and deploy the smart contract to the blockchain network, recording the unique identifier.

[0096] S200. Automatically generate a unique distributed identity for each applicant and business-related party based on personnel data, bind the permission level to each distributed identity according to the applicant's position and responsibilities, and write it into the blockchain;

[0097] In this step, the basic information of applicants and business-related parties, including data such as name, position, department, and responsibilities, is first extracted from the enterprise's internal personnel system, and a unique distributed identity is generated for each person based on this information. This distributed identity is created based on blockchain technology, and its characteristics include uniqueness and immutability, thus ensuring the authenticity and security of the identity. Then, according to the generated distributed identity, the system will automatically bind the permission scope of each identity. The permission scope is divided into fund application permission, approval permission, and query permission. The specific binding method is based on the applicant's position, responsibilities, and department to ensure that the permission division of each identity complies with the enterprise's internal management specifications. In addition, to adapt to the dynamically changing business needs, the system also presets a dynamic adjustment mechanism for permissions. Through this mechanism, the permission scope can change in real time according to time limits (such as temporary authorization) or behavior records (such as the compliance of historical approval behaviors), thus enhancing the flexibility and adaptability of the system.

[0098] The establishment of the approval chain rules and the binding of the permission levels of the distributed identities are important contents of this link. The approval chain rules clarify which distributed identities are required to participate in the approval of different types of transactions and the order of participation in the approval. These rules not only improve the efficiency of the fund approval process but also ensure the rigor and transparency of the review. According to the approval chain rules, each distributed identity will be bound to the corresponding approval chain permission level, which means that the system will automatically screen the approval identities that meet the permission level during the approval process, avoiding process interruptions caused by permission conflicts or non-compliance with approval requirements.

[0099] Finally, all the generated distributed identities and their bound permission scopes, permission levels, and related rules will be written into the blockchain. The distributed storage and immutability of the blockchain ensure the security of identity and permission information and provide reliable technical support for identity verification and permission invocation in subsequent processes.

[0100] An efficient and secure identity management system is constructed through the generation of distributed identities and the binding of permissions. The uniqueness of each identity and the precise division of permissions can effectively avoid problems such as incorrect permission settings or duplications that may occur in manual management, ensuring the compliance and security of the fund application and approval process. Secondly, the introduction of a dynamic adjustment mechanism significantly improves the flexibility and dynamic adaptability of the system. The business requirements of an enterprise may change over time and with the environment. By dynamically adjusting the permission scope, new requirements can be quickly responded to, cumbersome manual configuration work can be reduced, and management costs can be lowered at the same time. In addition, the setting of approval chain rules and the binding of permission levels further optimize the approval process. Based on the transparency of the blockchain and the automation characteristics of smart contracts, approvers can quickly process fund applications that meet the permissions, effectively reducing the approval time and avoiding approval errors or delays caused by human factors. Finally, all distributed identities and their permission information are written into the blockchain, ensuring the security, immutability, and traceability of the data. It is not only possible to quickly query and verify identity permission information during subsequent audits but also provides a solid technical guarantee for the entire financial audit process.

[0101] As Figure 3 shown, automatically generating a unique distributed identity for each applicant and business-related party according to personnel data, binding a permission level to each distributed identity according to the applicant's position and responsibilities, and writing it into the blockchain specifically includes:

[0102] S210, extracting the basic information of the applicant and the information of the business-related party from the personnel system, and generating a unique blockchain-based distributed identity for each applicant and business-related party based on this;

[0103] S220, automatically binding a permission scope to each distributed identity according to the applicant's position, responsibilities, and department, including fund application permissions, approval permissions, and query permissions. When binding permissions, a dynamic adjustment mechanism is preset to allow the permissions to change in real time according to time limits and behavior records;

[0104] S230, establishing approval chain rules and binding each distributed identity to the corresponding approval chain permission level. The approval chain rules are used to screen which distributed identities are required to participate in the approval of different types of transactions and the approval order of different distributed identities, and based on this, the approval chain permission level of the distributed identity is defined;

[0105] S240, writing each distributed identity and its bound permission level into the blockchain.

[0106] S300: When the applicant submits a funding application, record the applicant's distributed identity and application information, generate a unique application ID, automatically write the application data into the blockchain, trigger the verification of the smart contract at the same time, enter the approval process, and add an exception mark to the funding application with abnormal verification.

[0107] In this step, after receiving the funding application sent by the applicant, the system will immediately extract key information such as the applicant's distributed identity, application timestamp, and purpose of funds, and use this information to generate a unique application ID. Since the application ID is generated based on blockchain technology, it has uniqueness and immutability, which provides a solid technical guarantee for subsequent tracking and auditing of fund flows. Then, the system will perform an integrity check on the funding application information to ensure that all necessary information (such as the application amount, purpose of funds, reason for application, etc.) is complete and accurate, and write the detailed record of the funding application into the blockchain. The distributed ledger feature of the blockchain ensures the transparency and immutability of these records, providing a reliable basis for the review of funding applications.

[0108] Subsequently, the system will call the smart contract to automatically verify the compliance of the funding application according to the preset rules of the funding approval chain and the rules of fund flow. The rules of the funding approval chain ensure that the funding application complies with the established approval process and authority requirements, and the rules of fund flow prevent the occurrence of over-limit applications or unreasonable fund flows by controlling parameters such as the application amount and fund flow direction. If the system identifies an abnormality in the funding application during the verification process (such as the amount exceeding the specified limit, the approval chain being incomplete, the purpose of funds being unclear, etc.), the system will automatically add an exception mark to the funding application and write the exception mark into the blockchain together with the application record. While completing the above operations, the system will also automatically generate an audit log for each funding application. The audit log contains key information such as the applicant's distributed identity, application amount, purpose of funds, and application priority to ensure the integrity and traceability of subsequent audits and data analysis.

[0109] This step realizes the full - process recording and verification of fund applications through blockchain technology. The whole process from application reception to anomaly marking is transparent and traceable, which not only effectively improves the transparency of fund management, but also provides a comprehensive data basis for subsequent fund flow tracking and anomaly backtracking. Secondly, the automated verification based on smart contracts significantly improves the efficiency and accuracy of approval. Smart contracts can quickly and unbiasedly conduct compliance reviews on fund applications according to preset rules, avoiding subjectivity and errors that may occur in traditional manual reviews, thus significantly reducing the risk of approval errors. In addition, in step S300, through the generation of a unique application ID and the automatic creation of audit logs, a detailed electronic file is established for each fund application. The existence of audit logs not only facilitates subsequent internal audits and compliance checks, but also provides important objective evidence for enterprises in the face of external supervision or disputes.

[0110] The introduction of the anomaly marking mechanism fully reflects the advantages of this step in risk management. When the system identifies an anomaly in a fund application, it can quickly mark and record it in the blockchain. This real - time marking and recording method can not only prevent abnormal applications from continuing to enter the approval process and causing risk expansion, but also provides key clues for subsequent anomaly backtracking reviews. In addition, due to the immutability of blockchain data, anomaly marks and application records always remain true and reliable, establishing an efficient risk prevention and control and traceability system for enterprises.

[0111] As Figure 4 shown, when the applicant issues a fund application, the distributed identity and application information of the applicant are recorded, a unique application ID is generated, and the application data is automatically written into the blockchain. At the same time, the smart contract verification is triggered, entering the approval process, and an anomaly mark is added to the fund application with verification anomalies, specifically including:

[0112] S310, when receiving the fund application issued by the applicant, obtain the information of the fund application, and generate a unique application ID based on the applicant's distributed identity, application timestamp, and fund usage;

[0113] S320, verify the integrity of the information of the fund application, and write the complete record of the fund application into the blockchain;

[0114] S330, call the smart contract, verify the compliance of the application according to the fund approval chain rules and fund flow rules, and when it is identified that there is an anomaly in this fund application, add an anomaly mark to this fund application and write it into the blockchain;

[0115] S340, automatically generate an audit log for each fund application, including the applicant's distributed identity, application amount, usage, and priority.

[0116] The S400 identifies the approval chain corresponding to the fund application, matches the approvers who meet the permission level, records the distributed identity, operation time, and approval opinion of the approver for each approval operation, and updates the blockchain record.

[0117] This step reads the fund application data from the blockchain, including key information such as the distributed identity of the applicant, the application amount, the application purpose, and the application ID, and matches the corresponding approval chain rules based on this information. The approval chain rules are designed according to the enterprise's preset fund approval policies, which clarify the approval levels and approval sequences required for different types of fund applications. The process of matching the approval chain rules is systematic and automated to ensure that each fund application can be accurately corresponded to a specific type of approval chain.

[0118] After the matching is completed, the system screens the eligible approvers according to the approval chain rules. The screening of approvers is strictly based on the permission level and scope of responsibilities bound in their distributed identities, and only the approvers whose permissions fully meet the requirements can be selected to participate in the approval. The system then sends an approval request to the matched approvers, and the approval request will include the key information of the fund application (such as the applicant's identity, application amount, purpose, and priority, etc.) to help the approvers quickly understand the specific situation of the fund application and make decisions. During the approval process, the system will record each approval operation in detail, including the distributed identity of the approver, the approval time, the approval opinion (such as approval or rejection), and the specific operation data of the approval. These records will be updated to the blockchain in real time to form a traceable approval log.

[0119] After each approval is completed, the system will automatically check the integrity of the approval chain. An important part of the integrity check is to verify whether the approval is completed strictly in accordance with the preset approval chain rules, specifically including: whether the approval is carried out step by step in the prescribed order, whether there are any approval levels skipped or bypassed, and whether all approvers meet the permission requirements, etc. If the system detects any behavior that does not conform to the rules in the approval process (such as the approval order is disrupted, the approver's permission is insufficient, etc.), it will immediately mark the corresponding fund application and approval chain as abnormal and record the abnormal information for subsequent auditing and processing. When the system confirms that the approval chain is complete and all approvals conform to the rules, the status of the fund application will be updated to "approved" and automatically enter the fund appropriation process to ensure that the subsequent fund flow can be carried out in a timely manner.

[0120] Through the approval process management based on the blockchain, the transparency and automation of the approval operation are realized. Each step of the approval process is recorded in the blockchain, forming an immutable and publicly transparent approval log, which not only improves the credibility of the approval process but also provides a reliable basis for the enterprise's internal audit and external supervision. Secondly, the automatic matching of approvers and approval chain rules significantly improves the approval efficiency.

[0121] By strictly examining each level of operation in the approval chain, the system can effectively prevent irregularities in the approval process, including situations where the approval order is randomly changed and unauthorized personnel participate in the approval. This verification mechanism not only ensures the compliance of the approval chain but also greatly reduces the financial risks caused by opaque or irregular approval processes. At the same time, when the system detects approval anomalies, it can add anomaly marks in real-time and record the anomaly information, providing important clues for subsequent anomaly tracking and responsibility division.

[0122] As Figure 5 shown, the approval chain corresponding to the identified fund application is matched with approvers who meet the permission levels. Each approval operation records the distributed identity of the approver, the operation time, and the approval opinion, and updates the blockchain record, specifically including:

[0123] S410, Read the fund application data and match the corresponding approval chain rules for this fund application data;

[0124] S420, According to the approval chain rules, screen out the approvers who meet the conditions and send approval requests to each matched approver;

[0125] S430, Record the approver information and approval process information for each approval;

[0126] S440, After each approval is completed, automatically check whether the approval chain is completed according to the rules, and the rules include:

[0127] Whether to approve step by step according to the approval chain order;

[0128] Whether any approval levels are skipped or bypassed;

[0129] Whether all approvers meet the permission requirements;

[0130] If there is incomplete approval according to the rules, automatically mark and record the anomaly;

[0131] If all approvals are completed, update the fund application status to approved and enter the fund disbursement process.

[0132] S500, Continuously verify the integrity of the approval chain during the approval process. If one level of approval is not completed, suspend the current transaction; if the approval chain rules are bypassed, mark the fund application and the approval chain as anomalies;

[0133] This step uses blockchain technology to track the status of each fund application in the approval chain in real time, including whether the approval progresses strictly in accordance with the preset approval chain rules step by step, whether there are situations where approval levels are skipped or bypassed, and whether each level of approval operation is completed on time. By tracking the progress of the approval chain, the system can accurately grasp the current status of each fund application and take suspension or rectification measures in a timely manner when necessary.

[0134] During the approval process, the system records the detailed information of each approval operation, including the distributed identity of the approver, approval time, approval opinion, and approval level, etc. This information is written into the blockchain in real time and verified step by step by the smart contract according to the preset approval chain rules. The automated verification function of the smart contract can quickly identify whether each level of approval meets the rule requirements, such as whether the approver has sufficient authority, whether the operation time exceeds the limit, whether the approval opinion is clear, etc., so as to ensure the integrity and compliance of the approval chain.

[0135] This step analyzes the historical data in the approval chain through an anomaly detection model and uses algorithms to dynamically monitor the current approval event. For example, the model can calculate the similarity distance between the approval event to be detected and the historical dataset to obtain an anomaly score. If this score exceeds the preset anomaly score threshold, it indicates that there may be problems with this approval event. The system will immediately mark it as an anomaly and generate an anomaly mark record. This anomaly detection method based on similarity calculation can effectively identify complex problems in the approval chain that are not easily discovered by traditional rules, such as abnormal approval time, contradictory approval opinions, and obvious deviation of approval behavior from historical patterns.

[0136] Once an anomaly mark is generated, the system will record the relevant data in the blockchain as the basis for subsequent retrospective review and responsibility tracing. In addition, for the fund applications marked as anomalies, the system will suspend their current transaction processes to prevent potential risks from further expanding. For the approval events marked as anomalies, a notification mechanism will be triggered when necessary to feedback the anomaly information to the relevant administrators or risk control departments for timely manual intervention.

[0137] By tracking the progress of the approval chain in real time, this step enables the system to conduct full-process dynamic monitoring of the status of fund applications, so as to take prevention and control measures at the first time when problems occur, significantly reducing the possibility of risk spread. Secondly, the smart contract greatly improves the efficiency and accuracy of verifying the approval chain rules. Compared with manual review, the smart contract can quickly execute complex rule checks to ensure that the approval process strictly follows the preset rules, while reducing delays or omissions that may occur in the traditional manual process.

[0138] Using the historical data of the approval chain and the similarity analysis algorithm, the system can identify non-intuitive abnormal situations that are difficult to detect by traditional rules. This intelligent anomaly detection method greatly improves the risk management ability of the system. In addition, the anomaly marking mechanism and the immutability of the records further enhance the transparency of the audit and the traceability of responsibilities. Each anomaly marking record will be written into the blockchain to ensure that the whole process of abnormal behavior is traceable, laying a technical foundation for subsequent retrospective analysis and responsibility division.

[0139] As Figure 6 shown, the integrity of the approval chain is continuously verified during the approval process. If one level of approval is not completed, the current transaction is suspended; if the approval chain rules are bypassed, the fund application and the approval chain are marked as abnormal, specifically including:

[0140] S510, Real-time track the progress of each fund application in the approval chain, including: whether it progresses step by step according to the approval chain rules, and whether each level of approval operation is completed on time;

[0141] S520, Record the detailed information of each approval operation, and verify the compliance of each level of approval according to the approval chain rules preset by the smart contract;

[0142] S530, Based on the anomaly detection model established by the anomaly detection rules, monitor potential problems in the approval chain;

[0143] S540, Generate an anomaly mark for the detected abnormal fund application.

[0144] In this step, the monitoring of potential problems in the approval chain specifically means:

[0145]

[0146] Where D is the anomaly score, x is the data point of the approval event to be detected, x i is the k nearest neighbors in the approval history dataset that are closest to it, and d(x, x i ) represents the similarity distance between data points;

[0147] Set the marking threshold of the anomaly score. If the anomaly score of the fund application exceeds the marking threshold, the fund application is marked as abnormal and an anomaly mark is generated.

[0148] S600, Conduct a retrospective review of the fund applications with anomaly marks, track the complete flow path of the abnormal application, extract all relevant transaction records, and conduct a correlation analysis to generate a combined analysis report of abnormal funds.

[0149] This step will extract all fund application records marked as abnormal from the blockchain, and formulate corresponding retrospective analysis strategies according to the abnormality type. For example, for approval chain skipping abnormalities, the system will focus on analyzing the skipped links in the approval chain and their related approval records; for amount exceeding limit abnormalities, the system will focus on the historical fund flow related to the application amount; and for related project abnormalities, the system will dig deep into the project ID or supplier's historical transactions related to the application funds to fully restore the background and flow of abnormal funds.

[0150] The complete flow path of abnormal funds is tracked through blockchain records, and possible abnormal nodes in the process of fund flow are identified. These nodes may include abnormal outflow of funds, inflow time, flow account and other characteristics. By tracking, a logical chain of abnormal behavior can be constructed. At the same time, the system screens historical transaction records closely related to the current abnormal funds according to the preset association rules. Association rules include but are not limited to the following: all fund applications submitted by the same applicant, historical transactions with consistent fund flows, historical transactions with the same project ID, and other fund applications approved by the same approver or approval group. The setting of these rules can fully cover the abnormal association dimensions that may exist in fund applications, and provide a multi-level perspective for abnormal analysis.

[0151] After extracting relevant records, a correlation diagram of abnormal funds is constructed through blockchain records to show the correlation between abnormal funds and other fund applications and transaction records. In order to further quantify and evaluate the risks of abnormal funds, the system conducts quantitative analysis on the extracted records and calculates the correlation strength with current funds. For example, the intensity of capital flow can be measured by the ratio of abnormal capital inflows to the total inflows, and the approval intensity can be reflected by the ratio of abnormal approvals to the total approvals. This quantitative analysis provides intuitive data support for the correlation of abnormal funds. Combined with the preset strength threshold, the system can accurately identify potential correlation anomalies and file these anomalies into specific risk categories.

[0152] The retrospective review based on blockchain technology ensures the reliability and traceability of data. Since blockchain is tamper-proof, all fund flows and transaction records can be traced. The system can accurately restore the flow path of abnormal funds and, on this basis, dig out hidden risk nodes to ensure the comprehensiveness of abnormal analysis.

[0153] Secondly, the flexibility of association rules significantly improves the intelligence level of anomaly analysis. By filtering related records of the same applicant, consistent capital flow, and the same project ID through rules, the system can dig deep into hidden abnormal funds and transaction behaviors from multiple angles. This multi-dimensional analysis method avoids the omission problem caused by the single perspective in traditional anomaly detection methods and comprehensively explores potential abnormal associations.

[0154] In addition, quantitative analysis makes the assessment of abnormal correlations more scientific and intuitive. Through correlation indicators such as the intensity of capital flow and approval intensity, the system can accurately measure the tightness of the connection between abnormal funds and other transactions, and identify high-risk transactions by combining intensity thresholds. This data-driven quantitative method not only improves the accuracy of abnormal analysis but also provides an objective basis for enterprises to conduct risk assessments.

[0155] As Figure 7 shown, the backtracking review of the funds application with abnormal marks is carried out to trace the complete flow path of the abnormal application, extract all relevant transaction records, and conduct correlation analysis to generate a combined analysis report of abnormal funds, specifically including:

[0156] S610, Extract the funds application data with abnormal marks from the blockchain, and set corresponding backtracking analysis strategies according to the abnormal types, including:

[0157] For the abnormal situation of skipping the approval chain, analyze the skipped links and relevant records in the approval chain;

[0158] For the abnormal situation of exceeding the amount limit, analyze the historical capital flow records related to the application amount;

[0159] For the abnormal situation of related projects, analyze the historical transactions between the application and the supplier;

[0160] S620, Through the blockchain records, trace the complete flow path of the abnormal funds, and identify the abnormal nodes in the funds flow path;

[0161] S630, Define the association rules, and extract the historical transaction records related to the current abnormal funds according to the association rules;

[0162] The association rules include: all funds applications submitted by the same applicant, all historical transaction records with the same flow direction as the current abnormal funds, historical records with the same project ID as the current application, and funds applications approved by the same group of approvers;

[0163] S640, Screen the funds applications and their approval records that meet the association rules from the blockchain, and construct an association graph of abnormal funds based on the funds flow records and historical transaction records;

[0164] Conduct quantitative analysis on the extracted records, and calculate the association intensity with the current funds:

[0165]

[0166] S650, Set the intensity threshold, and identify potential associated anomalies according to the association intensity and abnormal distribution;

[0167] S660, Summarize the flow path of abnormal funds, historical transaction records, and correlation analysis results into a report.

[0168] Figure 8 The structural block diagram of a financial audit system based on blockchain technology provided by an embodiment of the present invention, as Figure 8 shown, the system includes:

[0169] The smart contract rule setting module 100 is used to preset smart contract rules according to enterprise financial management policies and rules, including fund approval chain rules, fund flow rules, anomaly detection rules and dynamic update rules, and deploy the created smart contracts on the blockchain, recording the unique identifier;

[0170] The distributed identity generation module 200 is used to automatically generate a unique distributed identity for each applicant and business-related party according to personnel data, bind a permission level to each distributed identity according to the applicant's position and responsibilities, and write it into the blockchain;

[0171] The fund application record verification module 300 is used to record the applicant's distributed identity and application information when the applicant issues a fund application, generate a unique application ID, automatically write the application data into the blockchain, trigger smart contract verification at the same time, enter the approval process, and add an anomaly mark to the fund application with verification anomalies;

[0172] The approval chain matching and updating module 400 is used to identify the approval chain corresponding to the fund application, match the approvers who meet the permission level, record the distributed identity, operation time and approval opinion of the approver for each approval operation, and update the blockchain record;

[0173] The approval chain integrity verification module 500 is used to continuously verify the integrity of the approval chain during the approval process. If one level of approval is not completed, the current transaction is suspended; if the approval chain rule is bypassed, an anomaly mark is added to the fund application and the approval chain;

[0174] The abnormal fund traceback analysis module 600 is used to conduct a retrospective review of the fund application with an anomaly mark, track the complete flow path of the abnormal application, extract all relevant transaction records, and conduct a correlation analysis to generate an abnormal fund joint analysis report.

[0175] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0176] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0177] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0178] The above-described embodiments merely represent several implementation manners of the present invention. Their descriptions are relatively specific and detailed, but they should not be construed as limitations on the scope of the patent for the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention shall be subject to the appended claims.

[0179] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A financial audit method based on blockchain technology, characterized in that: The method comprises: Preset smart contract rules according to the enterprise's financial management policies and rules, including fund approval chain rules, fund flow rules, anomaly detection rules and dynamic update rules, and deploy the created smart contract on the blockchain to record the unique identifier; Automatically generate a unique distributed identity for each applicant and business stakeholder based on personnel data, and bind a permission level to each distributed identity based on the applicant's position and responsibilities, and write it into the blockchain; When an applicant submits a funding application, the applicant’s distributed identity and application information are recorded, a unique application ID is generated, and the application data is automatically written into the blockchain. At the same time, smart contract verification is triggered, the approval process is entered, and an abnormal mark is added to the funding application with abnormal verification; Identify the approval chain corresponding to the funding application and match the approver with the required permission level. Each approval operation records the approver’s distributed identity, operation time, and approval opinion, and updates the blockchain record. During the approval process, the integrity of the approval chain is continuously verified. If one of the first-level approvals is not completed, the current transaction will be suspended. If the approval chain rules are bypassed, the funding application and the approval chain will be marked as abnormal. Conduct retrospective review of abnormally marked funding applications, track the complete flow path of the abnormal application, extract all relevant transaction records, conduct correlation analysis, and generate a joint analysis report on abnormal funds.

2. The method according to claim 1, characterized in that The smart contract rules are preset according to the enterprise financial management policies and rules, including fund approval chain rules, fund flow rules, anomaly detection rules and dynamic update rules, and the created smart contract is deployed on the blockchain to record the unique identifier, specifically including: Design funding approval chain rules for each type of funding application, including large-amount funding, small-amount funding and special funding, based on the type, amount and risk level of the funding application, and define the approval process and levels required for funding applications; Set fund flow rules, define the upper limit of the amount of a single fund application, set different thresholds for different departments, projects or cost centers, and set the maximum frequency of fund flow; Define anomaly detection rules, define abnormal behavior types according to enterprise policies and risk prediction, and establish anomaly detection models based on blockchain transaction data; Add dynamic update rules, use blockchain to store historical fund flow and anomaly detection data, and regularly analyze the applicability of all established rules; Compile the fund approval chain rules, fund flow rules and anomaly detection rules into executable smart contract code, deploy the smart contract to the blockchain network, and record the unique identification.

3. The method according to claim 2, characterized in that The method automatically generates a unique distributed identity for each applicant and business-related party based on personnel data, binds the permission level to each distributed identity based on the applicant's position and responsibilities, and writes it into the blockchain, including: Extract the basic information of applicants and business stakeholders from the personnel system, and generate a unique distributed identity based on blockchain for each applicant and business stakeholder; According to the applicant's position, responsibilities and department, each distributed identity is automatically bound to a range of permissions, including funding application permissions, approval permissions and query permissions. When binding permissions, a dynamic adjustment mechanism is preset to allow permissions to change in real time based on time limits and behavior records. Establish approval chain rules and bind each distributed identity to the corresponding approval chain authority level. The approval chain rules are used to screen which distributed identities are required to participate in the approval of different types of transactions, as well as the approval order of different distributed identities, and based on this, define the approval chain authority level of the distributed identity; Each distributed identity and its associated permission level are written into the blockchain.

4. The method according to claim 3, characterized in that When an applicant submits a funding application, the applicant’s distributed identity and application information are recorded, a unique application ID is generated, and the application data is automatically written into the blockchain. At the same time, the smart contract verification is triggered, the approval process is entered, and an abnormal mark is added to the funding application with abnormal verification, including: When receiving a funding application from an applicant, obtain the funding application information and generate a unique application ID based on the applicant's distributed identity, application timestamp, and funding purpose; Verify the integrity of funding applications and write the complete record of funding applications into the blockchain; Call the smart contract to verify the compliance of the application according to the fund approval chain rules and fund flow rules. When an abnormality is identified in the fund application, an abnormal mark is added to the fund application and written into the blockchain. An audit log is automatically generated for each funding application, including the applicant’s distributed identity, application amount, purpose, and priority.

5. The method according to claim 4, characterized in that The approval chain corresponding to the identified fund application is matched with the approver who meets the authority level. Each approval operation records the approver's distributed identity, operation time and approval opinion, and updates the blockchain record, including: Read the funding application data and match the corresponding approval chain rules for the funding application data; According to the approval chain rules, screen qualified approvers and send approval requests to each matching approver; Record the approver information and approval process information for each approval; After each approval is completed, it is automatically checked whether the approval chain is completed according to the rules. The rules include: Whether approval is carried out step by step according to the approval chain sequence; Whether any approval level is skipped or bypassed; Whether all approvers meet the authority requirements; If there is any failure to fully approve according to the rules, the exception will be automatically marked and recorded; If all approvals are completed, the funding application status will be updated to approved and the funding disbursement process will begin.

6. The method according to claim 4, characterized in that The integrity of the approval chain is continuously verified during the approval process. If one of the first-level approvals is not completed, the current transaction is suspended; if the approval chain rules are bypassed, the funding application and the approval chain are marked as abnormal, including: Real-time tracking of the progress of each funding application in the approval chain, including: whether it is advancing step by step according to the approval chain rules, and whether each level of approval operation is completed on time; Record the detailed information of each approval operation and verify the compliance of each level of approval according to the approval chain rules preset by the smart contract; Anomaly detection models built based on anomaly detection rules monitor potential problems in the approval chain; Generate an abnormal mark for any abnormal fund application detected.

7. The method according to claim 6, characterized in that The potential problems in the monitoring and approval chain are as follows: D is the anomaly score, x is the data point of the approval event to be detected, and x i is the k closest neighbors in the approval history dataset, d(x, x i ) represents the similarity distance between data points; A marking threshold for the anomaly score is set. If the anomaly score of the funding application exceeds the marking threshold, the funding application is marked as abnormal and an anomaly mark is generated.

8. The method according to claim 6, characterized in that The aforementioned retrospective review of the abnormally marked fund application, tracking the complete flow path of the abnormal application, extracting all relevant transaction records, and performing correlation analysis to generate an abnormal fund joint analysis report, specifically includes: Extract fund application data with abnormal marks from the blockchain, and set corresponding backtracking analysis strategies according to the abnormal type, including: For exceptions such as skipping the approval chain, analyze the skipped links and related records in the approval chain; For abnormal amounts exceeding the limit, analyze the historical fund flow records related to the application amount; For abnormalities in related projects, analyze the historical transactions between the application and the supplier; Through blockchain records, the complete flow path of abnormal funds can be tracked and abnormal nodes in the flow path of funds can be identified; Define association rules and extract historical transaction records related to current abnormal funds based on the association rules; The association rules include: all funding applications submitted by the same applicant, all historical transaction records with the same abnormal fund flow as the current one, historical records with the same project ID as the current application, and funding applications approved by the same group of approvers; Filter the fund applications and their approval records that meet the association rules from the blockchain, and build an association graph of abnormal funds based on fund flow records and historical transaction records; Perform quantitative analysis on the extracted records and calculate the correlation strength with the current funds: Set strength thresholds to identify potential association anomalies based on association strength and anomaly distribution; The abnormal funds flow path, historical transaction records, and correlation analysis results are summarized into a report.

9. A financial audit system based on blockchain technology, characterized in that: The system comprises: Smart contract rule setting module, which is used to preset smart contract rules according to the enterprise financial management policies and rules, including fund approval chain rules, fund flow rules, anomaly detection rules and dynamic update rules, and deploy the created smart contract on the blockchain to record the unique identification; Distributed identity generation module, which is used to automatically generate a unique distributed identity for each applicant and business stakeholder based on personnel data, and bind the permission level to each distributed identity based on the applicant's position and responsibilities, and write it into the blockchain; The fund application record verification module is used to record the applicant's distributed identity and application information when the applicant submits a fund application, generate a unique application ID, and automatically write the application data into the blockchain. At the same time, it triggers smart contract verification, enters the approval process, and adds an abnormal mark to the fund application with abnormal verification; The approval chain matching and updating module is used to identify the approval chain corresponding to the funding application and match the approvers who meet the permission level. Each approval operation records the approver's distributed identity, operation time and approval opinion, and updates the blockchain record; The approval chain integrity verification module is used to continuously verify the integrity of the approval chain during the approval process. If one of the first-level approvals is not completed, the current transaction will be suspended; if the approval chain rules are bypassed, the funding application and the approval chain will be marked as abnormal; The abnormal funds retrospective analysis module is used to conduct retrospective review of abnormally marked fund applications, track the complete flow path of the abnormal application, extract all relevant transaction records, perform correlation analysis, and generate an abnormal funds joint analysis report.

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