Blockchain-based intelligent reconciliation method, system and electronic device

Abstract

This invention proposes a blockchain-based intelligent reconciliation method, system, and electronic device, relating to the field of blockchain technology. It includes defining reconciliation rules for multi-participant collaboration and a dynamic blockchain sharding strategy; storing the parameters of the reconciliation rules and dynamic sharding strategy in a smart contract; deploying the smart contract to the blockchain; acquiring the reconciliation data from multiple participants; obtaining the number of shards based on the dynamic sharding strategy; sharding the reconciliation data from each participant; calculating the hash value of each shard; and uploading the shard hash value to the blockchain. Based on preset trigger conditions, the smart contract is triggered to retrieve the corresponding shard hash value from the blockchain for comparison, completing the reconciliation process and obtaining a structured reconciliation result. This invention achieves efficient reconciliation among multiple transaction participants, significantly improving reconciliation efficiency, data reliability, and audit transparency, and solving the efficiency bottlenecks and trust issues in traditional reconciliation.

Description

Technical Field

[0001] This invention belongs to the field of blockchain technology, and in particular relates to a blockchain-based intelligent reconciliation method, system, and electronic device. Background Technology

[0002] Reconciliation is a core step in ensuring transaction consistency and enhancing fund security and business credibility. In multi-party collaborative transaction scenarios such as finance, supply chain, cross-border trade, and the sharing economy, accounts receivable and accounts payable are generated. To ensure the consistency and accuracy of accounts receivable and accounts payable, multi-party reconciliation is necessary. However, traditional reconciliation models heavily rely on manual verification and decentralized system operations, often resulting in the following problems:

[0003] 1. Inefficiency and waste of resources.

[0004] In the traditional model, the same transaction needs to be entered into separate systems by both the buyer and seller, and verification is completed through manual export, email transmission, and table comparison. This process is highly repetitive, has a low degree of automation, and consumes a lot of manpower and time, especially during the peak business periods at the beginning and end of the month, which can easily become a bottleneck restricting the overall operational efficiency of the enterprise.

[0005] 2. Information silos and difficulties in collaboration.

[0006] The data of each participating party is stored in a local system, lacking a unified, real-time data synchronization mechanism, resulting in serious information silos. Once discrepancies arise, repeated communication and verification across departments and enterprises are required, making tracing difficult, dispute resolution timelines lengthy, and severely impacting trust in cooperation and the efficiency of business progress.

[0007] 3. Weak risk control capabilities.

[0008] Relying on manual operations not only easily introduces risks such as misoperation, data omission, or tampering, but also makes it difficult to achieve end-to-end audit traceability. In complex business structures or high-concurrency transaction environments, traditional methods cannot guarantee the integrity, consistency, and security of data, resulting in significant potential financial and compliance risks. Summary of the Invention

[0009] To overcome the shortcomings of the existing technologies, this invention provides a blockchain-based intelligent reconciliation method, system, and electronic device. Based on blockchain technology, it enables efficient reconciliation among multiple transaction participants, significantly improving reconciliation efficiency, data reliability, and audit transparency, and solving the efficiency bottlenecks and trust problems in traditional reconciliation.

[0010] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0011] The first aspect of this invention provides a blockchain-based intelligent reconciliation method.

[0012] The blockchain-based smart reconciliation method includes the following steps:

[0013] Define reconciliation rules and dynamic sharding strategies for multi-participant collaboration, and store the parameters of the reconciliation rules and dynamic sharding strategies in smart contracts;

[0014] Deploying smart contracts to the blockchain;

[0015] Obtain the reconciliation data of multiple participants, obtain the number of shards based on the blockchain dynamic sharding strategy, shard the reconciliation data of each participant, calculate the hash value of each shard, and upload the shard hash value to the blockchain.

[0016] The smart contract is triggered according to the preset trigger conditions. The corresponding shard hash values ​​of each participant are obtained from the blockchain for comparison, the reconciliation process is completed and a structured reconciliation result is obtained.

[0017] A second aspect of the present invention provides a blockchain-based intelligent reconciliation system.

[0018] A blockchain-based intelligent reconciliation system includes:

[0019] The smart contract definition module is configured to: define reconciliation rules for multi-participant collaboration and blockchain dynamic sharding strategy, and store the parameters of the reconciliation rules and blockchain dynamic sharding strategy in the smart contract;

[0020] The smart contract deployment module is configured to deploy smart contracts to the blockchain;

[0021] The sharding hash calculation module is configured to: obtain the reconciliation data of multiple participants, obtain the number of shards based on the blockchain dynamic sharding strategy, shard the reconciliation data of each participant, calculate the hash value of each shard, and upload the sharding hash value to the blockchain.

[0022] The comparison module is configured to: trigger a smart contract based on preset trigger conditions, obtain the corresponding shard hash values ​​of each participant from the blockchain for comparison, complete the reconciliation process, and obtain a structured reconciliation result.

[0023] A third aspect of the present invention provides an electronic device including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the steps of the blockchain-based smart reconciliation method as described in the first aspect of the present invention.

[0024] The above one or more technical solutions have the following beneficial effects:

[0025] This invention provides a blockchain-based intelligent reconciliation method, system, and electronic device. It achieves automated and reliable reconciliation management of multi-party transaction data, breaking down data silos among multiple participants, significantly improving reconciliation efficiency and accuracy, and thoroughly reducing the risks of errors and disputes caused by information asymmetry and manual operation. Based on the application of blockchain smart contracts, cryptographic evidence storage technology, and artificial intelligence, this invention possesses high reliability, auditability, and strong trust characteristics, making it suitable for various business scenarios requiring multi-party collaborative reconciliation.

[0026] This invention, by introducing blockchain technology in conjunction with artificial intelligence, constructs a distributed, trusted, collaborative reconciliation architecture. This architecture enables the coded, automated execution of reconciliation rules and the immutable storage of transaction data, significantly improving the system's automation level and business credibility. Simultaneously, through the design of sophisticated discrepancy handling and arbitration mechanisms, combined with fully traceable audit logs, the fairness, transparency, and verifiability of the reconciliation process are ensured, further enhancing the system's robustness, security, and maintainability.

[0027] This invention uses a dynamic sharding strategy to determine the number of data shards. It shards the reconciliation data from each participant, calculates the hash value of each shard, and uploads these hash values ​​to the blockchain. When the amount of data to be reconciled exceeds an upper threshold, the sharding interval is reduced and the number of shards is increased; conversely, when the amount of data is less than a lower threshold, the sharding interval is increased and the number of shards is decreased. This dynamic sharding strategy allows for rapid identification of shards with discrepancies when dealing with large datasets, reducing unnecessary detailed comparisons. Conversely, when dealing with small datasets, shards are merged to reduce on-chain hash comparisons, thereby lowering network load and gas consumption.

[0028] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0029] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0030] Figure 1 This is a flowchart of the method in Example 1.

[0031] Figure 2 This is a flowchart of the blockchain dynamic sharding strategy in Example 1. Detailed Implementation

[0032] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0033] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0034] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0035] Example 1

[0036] Traditional reconciliation methods rely on manual verification. For the same transaction, the buyer and seller enter accounts receivable and accounts payable into different systems for entry and verification. This process is repetitive, labor-intensive, and easily leads to information silos. Furthermore, monthly reconciliation is often concentrated at the beginning or end of the month. If discrepancies occur, extensive communication and complex approval processes are required, impacting the speed of accounting processing.

[0037] To address this issue, this embodiment leverages blockchain technology to provide an efficient and reliable solution. By fundamentally reconstructing the reconciliation model, it introduces smart contracts and cryptographic evidence storage mechanisms into distributed ledger technology, constructing a multi-party collaborative automated reconciliation system. This significantly improves reconciliation efficiency, data reliability, and audit transparency, not only solving the efficiency bottlenecks and trust issues in traditional reconciliation but also creating new business value through technological empowerment. It enables efficient reconciliation among multiple transaction participants while ensuring low cost and low risk.

[0038] like Figure 1 As shown, the blockchain-based smart reconciliation method includes the following steps:

[0039] Define reconciliation rules and dynamic sharding strategies for multi-participant collaboration, and store the parameters of the reconciliation rules and dynamic sharding strategies in smart contracts;

[0040] Deploying smart contracts to the blockchain;

[0041] Obtain the reconciliation data of multiple participants, obtain the number of shards based on the blockchain dynamic sharding strategy, shard the reconciliation data of each participant, calculate the hash value of each shard, and upload the shard hash value to the blockchain.

[0042] The smart contract is triggered according to the preset trigger conditions. The corresponding shard hash values ​​of each participant are obtained from the blockchain for comparison, the reconciliation process is completed and a structured reconciliation result is obtained.

[0043] This embodiment discloses a blockchain-based intelligent reconciliation method. By utilizing blockchain technology and its characteristics, combined with the specific needs of financial data processing, it achieves automated reconciliation, improves the efficiency and accuracy of financial data processing, and thus meets the requirements of modern enterprises for accounting accuracy and compliance.

[0044] The technical solution of this embodiment will now be explained in detail.

[0045] (i) Smart contract-based reconciliation rules.

[0046] The parties involved in the reconciliation jointly define the reconciliation rules, which include the reconciliation cycle, data format standards, hash algorithms, tolerance ranges, etc. The reconciliation rules are then coded into smart contracts and deployed to the blockchain network.

[0047] To ensure efficient reconciliation, this embodiment adopts a dynamic blockchain sharding strategy to achieve dynamic blockchain sharding based on the amount of reconciliation data.

[0048] Blockchain dynamic sharding strategies specifically include:

[0049] Pre-set the upper and lower thresholds for the amount of data to be reconciled;

[0050] When the amount of data to be reconciled exceeds the upper limit threshold, reduce the sharding interval and increase the number of shards;

[0051] When the amount of data to be reconciled is less than the lower threshold, increase the sharding interval and reduce the number of shards;

[0052] When the amount of data to be reconciled is between the lower and upper thresholds, maintain the current number of shards.

[0053] like Figure 2 As shown, after obtaining the data to be reconciled, the data volume and transaction time are read, and dynamic sharding parameters are calculated. When determining the specific number of shards, if the data volume to be reconciled is greater than the upper threshold, the sharding interval needs to be reduced and the number of shards increased until the data volume to be reconciled is between the lower and upper thresholds. If the data volume to be reconciled is less than the lower threshold, the sharding interval needs to be increased and the number of shards decreased until the data volume to be reconciled is between the lower and upper thresholds. When the data volume to be reconciled is between the lower and upper thresholds, the current number of shards is maintained.

[0054] Once the number of shards is determined, the sharding and hash calculation process begins: the data to be reconciled is sharded according to the number of shards determined by the dynamic sharding strategy; the data within each shard is sorted based on the transaction ID or timestamp; and the hash value of each allocation is calculated after sorting.

[0055] Finally, the shard hash value is uploaded to the blockchain.

[0056] In ERP systems, transaction volumes vary significantly across different business operations, making a fixed sharding strategy unsuitable for all scenarios. This embodiment employs a dynamic sharding strategy. When dealing with large datasets, increasing the number of shards quickly identifies the shards where discrepancies exist, reducing unnecessary detailed comparisons. When dealing with small datasets, shards are merged to reduce the number of on-chain hash comparisons, thereby lowering network load and gas consumption.

[0057] The smart contract not only stores the reconciliation logic but also the current dynamic sharding strategy parameters. Among them:

[0058] The reconciliation logic is as follows: the reconciliation data for the corresponding multiple parties is sharded, the hash value of each shard is calculated, and then the hash values ​​of the corresponding shards are compared.

[0059] For example, reconciliation between Party A and Party B requires obtaining the transaction data between them. For ease of description, the obtained data is named Party A's pending reconciliation data and Party B's pending reconciliation data, respectively. Based on the blockchain's dynamic sharding strategy, the sharding time interval and the number of shards for Party A's and Party B's pending reconciliation data are determined. It can be understood that the sharding time interval and the number of shards for Party A's and Party B's pending reconciliation data are the same. Next, the pending reconciliation data for Party A and Party B is sharded, and the hash value of each shard is calculated. During the comparison, the hash values ​​of the corresponding shard data in Party A's and Party B's pending reconciliation data need to be compared.

[0060] The parameters of the blockchain dynamic sharding strategy include the upper and lower thresholds of the amount of data to be reconciled, as well as the currently valid time interval and number of shards.

[0061] When fluctuations in data volume lead to adjustments in the dynamic sharding strategy, the smart contract needs to compare the new hash value generated according to the new sharding rules to ensure the consistency of the comparison basis.

[0062] (ii) Transaction data is stored on the blockchain.

[0063] In this embodiment, the reconciliation data for multiple parties originates from the data generated during the transaction. The specific method for obtaining this reconciliation data is as follows:

[0064] When a transaction occurs, the business systems of each participating party extract key data, generate standardized data messages, and obtain the data to be reconciled.

[0065] The key data includes transaction ID, amount, timestamp, and participant identifier, and the participant's business system includes ERP and financial software.

[0066] When a transaction occurs, each party's business system (such as ERP and financial software) extracts key data (such as transaction ID, amount, timestamp, and participant identifier), generates standardized data messages, and calculates their hash values.

[0067] Therefore, in this embodiment, the hash value is broadcast to the blockchain network for evidence storage, while the original data remains locally, which not only ensures data privacy but also ensures data integrity and non-repudiation through cryptographic means.

[0068] Protecting confidential data is crucial during the on-chain data storage and verification process. Traditional on-chain data storage methods often neglect effective protection of confidential data, potentially leading to data leaks and severe losses for data owners. This embodiment introduces zero-knowledge proof technology. In the blockchain verification process, zero-knowledge proof plays a vital role in scenarios where it is necessary to prove the compliance of data without disclosing confidential information. For example, when proving the legality of a transaction, the transacting parties can use zero-knowledge proofs to convince the verifier that the transaction is legal and compliant without revealing confidential information such as the specific amount or counterparty. The verifier can confirm the validity of the data but cannot access any confidential data content.

[0069] The specific process of zero-knowledge proof includes:

[0070] 1. Proof generation:

[0071] When a transaction occurs, in addition to generating standardized transaction data messages, the participants (proof providers) also use a zero-knowledge proof protocol to generate a "compliance proof" for the transaction. This proof can reliably verify that "the transaction data I submitted, the content of which (such as amount and participants) meets the predefined business rules in the smart contract (e.g., the amount does not exceed the limit, and the transacting parties are on the whitelist)" without revealing the specific values ​​of these contents.

[0072] 2. Proof on-chain and verification:

[0073] This "proof of compliance," along with the hash of the transaction data, is submitted to the blockchain. Smart contracts or any authorized validators can then use this proof for verification.

[0074] 3. Verification process: The verifier runs the corresponding zero-knowledge proof verification algorithm.

[0075] The verification result has only two possibilities: "proven valid" (i.e., the transaction is indeed compliant) or "proven invalid". Throughout the entire verification process, the verifier will not have access to any sensitive information such as the specific amount of the transaction or the identifier of the transaction counterparty.

[0076] (III) Smart contract triggering and automatic reconciliation.

[0077] The smart contract automatically initiates the reconciliation process based on preset trigger conditions, retrieving the transaction hash values ​​stored by all parties on the blockchain. The preset trigger conditions can be timed or event-driven.

[0078] By comparing the consistency of hash values ​​of the same transaction across different participating systems, the system automatically determines whether the transaction status is normal or abnormal and generates structured reconciliation results.

[0079] The reconciliation process involves retrieving the corresponding shard hash values ​​of each participant from the blockchain, comparing them, and obtaining a structured reconciliation result, which specifically includes:

[0080] When the hash values ​​of the corresponding shards of each participant are consistent, the reconciliation result is determined to be that the transaction status is normal.

[0081] When at least one participant's corresponding shard hash value is inconsistent with that of other participants, the reconciliation result is determined to be an abnormal transaction status.

[0082] The smart contract automatically flags data with abnormal transaction status and generates a discrepancy report, notifying all participants.

[0083] (iv) Difference handling and arbitration mechanism.

[0084] Based on the reconciliation results, if an abnormal transaction status is detected, the next step is to proceed to the AI ​​arbitration stage.

[0085] Traditional blockchain arbitration often relies on human judgment and adjudication of disputes. In complex reconciliation scenarios involving massive amounts of data and multiple rules, manual processing is not only time-consuming and labor-intensive, but also prone to inconsistencies and unfairness in the rulings due to differences in human subjective perception. For example, in cross-border e-commerce transaction reconciliation disputes involving multiple parties, manual arbitration requires a significant amount of time to analyze transaction data, logistics data, and payment data. Different arbitrators may have differing understandings and applications of the same rules, thus affecting the impartiality of the ruling.

[0086] To address these issues, this embodiment introduces an artificial intelligence (AI) processing mechanism. First, leveraging the powerful data analysis capabilities of AI, it rapidly mines and analyzes the vast amount of reconciliation data stored on the blockchain. AI algorithms can automatically identify patterns, anomalies, and correlations in the data, providing objective data evidence for arbitration. For example, by learning from historical reconciliation data and dispute cases, AI can quickly determine whether the current dispute is similar to historical cases and identify possible solutions.

[0087] 1. AI arbitration data preparation.

[0088] Arbitration data from all parties involved is obtained from the blockchain, including data to be reconciled, smart contract execution records, and related metadata. The arbitration data is then preprocessed and features are extracted.

[0089] (1) Data collection:

[0090] The blockchain records all transaction data involved in reconciliation, smart contract execution records, and related metadata. The AI ​​agent collects this data in real time through an interface with the blockchain nodes.

[0091] For example, in e-commerce reconciliation scenarios, data is collected from various stages such as order creation, payment completion, and product delivery, as well as the status information of smart contracts at different stages of execution.

[0092] (2) Data preprocessing:

[0093] The collected data may contain issues such as inconsistent formats and noisy data. The AI ​​agent first cleans the data, removing duplicates, errors, and invalid data. Then, it standardizes the data, converting data from different formats into a unified format for subsequent analysis. For example, order data from different e-commerce platforms can be converted into a standardized format, including fields such as order number, transaction time, amount, and product information.

[0094] (3) Feature extraction:

[0095] Based on the needs of arbitration, key features are extracted from the preprocessed data. For example, in reconciliation disputes caused by data inconsistencies, features such as the data source, modification records, and relationships with other data are extracted. These features will serve as important bases for artificial intelligence analysis and decision-making.

[0096] 2. AI Arbitration Analysis and Decision Making.

[0097] By training the AI ​​agent with historical dispute cases, the AI ​​agent is equipped with the ability to identify typical data patterns of different types of disputes. Then, the trained AI agent can identify the type of dispute to which the current arbitration data belongs.

[0098] (1) Pattern recognition:

[0099] Artificial intelligence systems utilize machine learning algorithms to perform pattern recognition on extracted features. By learning from a large number of historical dispute cases, AI can identify typical data patterns in different types of disputes. For example, in common disputes involving discrepancies between payment amounts and order amounts, AI can identify specific patterns in data changes during the payment process, thereby quickly determining the type of dispute.

[0100] (2) Intelligent reasoning:

[0101] A pre-set knowledge graph is provided, which contains business rules, logical relationships between data, and historical case information. Based on the dispute type to which the current arbitration data belongs, the AI ​​agent traverses and reasons through the knowledge graph to arrive at the arbitration result.

[0102] After determining the dispute type to which the current arbitration data belongs, artificial intelligence (AI) performs intelligent reasoning based on a pre-defined knowledge graph. The knowledge graph contains information such as business rules, logical relationships between data, and historical cases. When a new dispute arises, AI traverses and reasons through the knowledge graph, combining this with the data characteristics of the current dispute to arrive at an arbitration conclusion. For example, if the knowledge graph stipulates that the payer is liable when payment data and order data are inconsistent and there are anomalies in the payment data modification records, AI can find that the current dispute data conforms to this rule and thus draw the corresponding conclusion.

[0103] (3) Decision generation:

[0104] Based on the reasoning results, artificial intelligence generates specific arbitration decision recommendations. These recommendations include liability determination, compensation calculation, and solutions. For example, after determining that one party has made a reconciliation error, the system calculates the amount of compensation due according to relevant rules and proposes specific steps to restore data consistency.

[0105] 3. Demonstration of explainable artificial intelligence.

[0106] (1) Process visualization:

[0107] To help all parties involved in arbitration understand the decision-making process of artificial intelligence (AI), visualization technology is used to demonstrate the AI's analytical process. For example, a graphical interface shows how AI extracts features from raw data, identifies data patterns, and performs reasoning within a knowledge graph, allowing users to intuitively see the data and rules upon which AI makes its decisions.

[0108] (2) Based on the explanation:

[0109] Beyond the visualization process, AI also provides detailed explanations of the decision-making basis. For each arbitration recommendation generated, AI lists the rules upon which it is based, data characteristics, and historical cases. For example, when determining that a merchant on an e-commerce platform has made a reconciliation error and needs to pay a certain amount of compensation, AI will explain that it is based on the platform's transaction rules regarding the consistency between order amount and payment amount, as well as the results of similar cases.

[0110] 4. Arbitration results are uploaded to the blockchain and updated.

[0111] (1) Results Recording:

[0112] The arbitration results generated by artificial intelligence are recorded on the blockchain via a blockchain interface. The results include detailed information such as liability determination, compensation amount, and settlement plan, while also recording the AI's decision-making process and basis. This information is stored on the blockchain in encrypted form to ensure its immutability and security.

[0113] (2) Data update:

[0114] If the arbitration result involves adjustments or modifications to data, such as correcting erroneous reconciliation data or updating the state of smart contracts, the relevant operations will be updated on the blockchain. Simultaneously, the update record will also be recorded on the blockchain as part of the arbitration process, ensuring the integrity and traceability of the entire arbitration process.

[0115] 5. On-chain recording of reconciliation results and audit tracking.

[0116] All reconciliation results (including success records, discrepancy reports, and arbitration conclusions) are written into the blockchain distributed ledger, forming an immutable audit trail chain.

[0117] Authorized parties can check historical reconciliation records at any time, supporting thorough auditing and compliance checks.

[0118] Through the above methods, this invention achieves automated and reliable reconciliation management of multi-party transaction data, significantly improving reconciliation efficiency and accuracy, and thoroughly reducing the risks of errors and disputes caused by information asymmetry and manual operation. Based on the application of blockchain smart contracts, cryptographic evidence storage technology, and artificial intelligence, this invention possesses high reliability, auditability, and strong trust characteristics, making it suitable for various business scenarios requiring multi-party collaborative reconciliation, including but not limited to supply chain finance, cross-border payments, insurance claims, and profit sharing in the sharing economy.

[0119] The core innovation of this invention lies in the introduction of blockchain technology combined with artificial intelligence to construct a distributed, trusted, collaborative reconciliation architecture. This architecture enables the coded, automated execution of reconciliation rules and the immutable storage of transaction data, significantly improving the system's automation level and business credibility. Simultaneously, by designing sophisticated discrepancy handling and arbitration mechanisms, and combining them with fully traceable audit logs, the fairness, transparency, and verifiability of the reconciliation process are ensured, further enhancing the system's robustness, security, and maintainability.

[0120] Example 2

[0121] This embodiment discloses a blockchain-based intelligent reconciliation system.

[0122] A blockchain-based intelligent reconciliation system includes:

[0123] The smart contract definition module is configured to: define reconciliation rules for multi-participant collaboration and blockchain dynamic sharding strategy, and store the parameters of the reconciliation rules and blockchain dynamic sharding strategy in the smart contract;

[0124] The smart contract deployment module is configured to deploy smart contracts to the blockchain;

[0125] The sharding hash calculation module is configured to: obtain the reconciliation data of multiple participants, obtain the number of shards based on the blockchain dynamic sharding strategy, shard the reconciliation data of each participant, calculate the hash value of each shard, and upload the sharding hash value to the blockchain.

[0126] The comparison module is configured to: trigger a smart contract based on preset trigger conditions, obtain the corresponding shard hash values ​​of each participant from the blockchain for comparison, complete the reconciliation process, and obtain a structured reconciliation result.

[0127] Example 3

[0128] The purpose of this embodiment is to provide an electronic device.

[0129] An electronic device includes a memory, a processor, and a program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps in the blockchain-based smart reconciliation method as described in Embodiment 1 of this disclosure.

[0130] The steps and methods involved in the apparatuses of Embodiments 2 and 3 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0131] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0132] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A blockchain-based intelligent reconciliation method, characterized in that, Includes the following steps: Define reconciliation rules and dynamic sharding strategies for multi-participant collaboration, and store the parameters of the reconciliation rules and dynamic sharding strategies in smart contracts; Deploying smart contracts to the blockchain; The system obtains the reconciliation data of multiple participants, obtains the number of shards based on the blockchain dynamic sharding strategy, shards the reconciliation data of each participant, calculates the hash value of each shard, uploads the shard hash value to the blockchain, and confirms the validity of the data through zero-knowledge proof. The smart contract is triggered according to the preset trigger conditions, and the corresponding shard hash values ​​of each participant are obtained from the blockchain for comparison, thus completing the reconciliation process and obtaining a structured reconciliation result. When an abnormal transaction status is detected, the process proceeds to the AI ​​arbitration stage: Arbitration data from all parties involved is obtained from the blockchain, including data to be reconciled and smart contract execution records. The arbitration data is then preprocessed and features are extracted. By training the AI ​​agent with historical dispute cases, the AI ​​agent is equipped with the ability to identify typical data patterns of different types of disputes. Then, the trained AI agent can identify the type of dispute to which the current arbitration data belongs. A pre-set knowledge graph is provided, which includes business rules, logical relationships between data, and historical case information. Based on the dispute type of the current arbitration data, the AI ​​agent traverses and reasons through the knowledge graph to arrive at the arbitration result; Based on the arbitration results, generate arbitration decision recommendations; The arbitration results generated by the AI ​​agent are recorded on the blockchain through a blockchain interface. The arbitration results include liability determination, compensation amount and handling plan. At the same time, the decision-making process and basis of the AI ​​agent are recorded. All reconciliation operation results are written into the blockchain distributed ledger to form an immutable audit trace chain.

2. The blockchain-based smart reconciliation method as described in claim 1, characterized in that, The reconciliation rules for multi-party collaboration include reconciliation cycle, data format standards, hash algorithms, and tolerance ranges.

3. The blockchain-based smart reconciliation method as described in claim 1, characterized in that, Blockchain dynamic sharding strategies specifically include: Pre-set the upper and lower thresholds for the amount of data to be reconciled; When the amount of data to be reconciled exceeds the upper limit threshold, reduce the sharding interval and increase the number of shards; When the amount of data to be reconciled is less than the lower threshold, increase the sharding interval and reduce the number of shards; When the amount of data to be reconciled is between the lower and upper thresholds, maintain the current number of shards.

4. The blockchain-based smart reconciliation method as described in claim 1, characterized in that, The specific method for obtaining the reconciliation data for multiple parties is as follows: When a transaction occurs, the business systems of each participating party extract key data, generate standardized data messages, and obtain the data to be reconciled. The key data includes transaction ID, amount, timestamp, and participant identifier, and the participant's business system includes ERP and financial software.

5. The blockchain-based smart reconciliation method as described in claim 4, characterized in that, Before calculating the hash value of each shard, the data within each shard is also sorted by transaction ID or timestamp.

6. The blockchain-based smart reconciliation method as described in claim 1, characterized in that, The reconciliation process involves retrieving the corresponding shard hash values ​​of each participant from the blockchain, comparing them, and obtaining a structured reconciliation result, which specifically includes: When the hash values ​​of the corresponding shards of each participant are consistent, the reconciliation result is determined to be that the transaction status is normal. When at least one participant's corresponding shard hash value is inconsistent with that of other participants, the reconciliation result is determined to be an abnormal transaction status. The smart contract automatically flags data with abnormal transaction status and generates a discrepancy report, notifying all participants.

7. The blockchain-based smart reconciliation method as described in claim 1, characterized in that, Also includes: The analysis process of the AI ​​agent is displayed using visualization technology; The generated arbitration decision recommendations should be explained in terms of the basis for the decision. The arbitration result is updated on the blockchain, and the update process is recorded on the blockchain as part of the arbitration process.

8. A blockchain-based intelligent reconciliation system, characterized in that, include: The smart contract definition module is configured to: define reconciliation rules for multi-participant collaboration and blockchain dynamic sharding strategy, and store the parameters of the reconciliation rules and blockchain dynamic sharding strategy in the smart contract; The smart contract deployment module is configured to deploy smart contracts to the blockchain; The sharding hash calculation module is configured to: obtain the reconciliation data of multiple participants, obtain the number of shards based on the blockchain dynamic sharding strategy, shard the reconciliation data of each participant, calculate the hash value of each shard, upload the sharding hash value to the blockchain, and confirm the validity of the data through zero-knowledge proof. The comparison module is configured to: trigger a smart contract based on preset trigger conditions, obtain the corresponding shard hash values ​​of each participant from the blockchain for comparison, complete the reconciliation process, and obtain a structured reconciliation result; When an abnormal transaction status is detected, the process proceeds to the AI ​​arbitration stage: Arbitration data from all parties involved is obtained from the blockchain, including data to be reconciled and smart contract execution records. The arbitration data is then preprocessed and features are extracted. By training the AI ​​agent with historical dispute cases, the AI ​​agent is equipped with the ability to identify typical data patterns of different types of disputes. Then, the trained AI agent can identify the type of dispute to which the current arbitration data belongs. A pre-set knowledge graph is provided, which includes business rules, logical relationships between data, and historical case information. Based on the dispute type of the current arbitration data, the AI ​​agent traverses and reasons through the knowledge graph to arrive at the arbitration result; Based on the arbitration results, generate arbitration decision recommendations; The arbitration results generated by the AI ​​agent are recorded on the blockchain through a blockchain interface. The arbitration results include liability determination, compensation amount and handling plan. At the same time, the decision-making process and basis of the AI ​​agent are recorded. All reconciliation operation results are written into the blockchain distributed ledger to form an immutable audit trace chain.

9. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the blockchain-based smart reconciliation method as described in any one of claims 1-7.

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