Digital certificate traceability and cancel-after-verification method and system based on creditor and debt atlas

Abstract

The invention is suitable for the technical field of digital certificate traceability and verification, and particularly relates to a digital certificate traceability and verification method and system based on a creditor and debt atlas, and the method comprises the steps: constructing a creditor and debt relation database, extracting a relation main body and a corresponding creditor and debt relation, and taking the relation main body as a node, the creditor and debt relation is a directed edge, the nodes are connected through the directed edge, a creditor and debt atlas is generated, and the directed edge points to a creditor from a debtor; attribute data of the digital certificate is collected, the attribute data at least comprises certificate identification, debt amount, expiration time and current debt state, the incidence relation between the directed edge and the attribute data is established, and the creditor and debt atlas is inserted into the creditor and debt relation database. By generating the verification suggestion, high-risk debt can be preferentially solved, the overall debt cost can be reduced, the debt resource allocation can be optimized, scientific debt can be realized, and the debt progress and the debt quality can be remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of digital voucher traceability and verification technology, and in particular to a method and system for digital voucher traceability and verification based on a debt and credit map. Background Technology

[0002] In debt management, digital certificates are electronic records of claims or debts, which can be understood as "digital debt instruments". Each debt or claim generates a corresponding certificate, which records information such as the debtor, creditor, amount, generation time and status. It is the basic unit of the entire debt map.

[0003] Existing debt management systems are mostly built on relational database ledgers, where each debt or digital voucher is recorded and stored independently. However, they are difficult to intuitively express and efficiently traverse the complex network of relationships between entities. They cannot identify debts that should be prioritized for write-off based on the global network, nor can they assess the potential impact of write-off operations on the debt status of upstream and downstream related companies.

[0004] Therefore, "how to identify the upstream and downstream relationships of digital vouchers" is the technical problem that this invention needs to solve. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for tracing and verifying digital vouchers based on a debt-creditor graph, in order to solve the problem of "how to identify the upstream and downstream relationships of digital vouchers" mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for tracing and verifying digital vouchers based on a debt-creditor graph, the method comprising:

[0008] Construct a database of creditor-debtor relationships, extract the subjects of the relationship and the corresponding creditor-debtor relationships, take the subjects of the relationship as nodes and the creditor-debtor relationships as directed edges, connect the nodes with the directed edges to generate a creditor-debtor graph, wherein the directed edges point from the debtor to the creditor;

[0009] Collect attribute data of digital vouchers, wherein the attribute data includes at least: voucher identifier, debt amount, due date and current debt status, establish the association relationship between directed edges and attribute data, and insert the debt graph into the debt relationship database;

[0010] Upon receiving a query request from a user containing a digital certificate, the system locates the corresponding digital certificate and activates a pre-edited two-way traceability mechanism, which includes an upstream backtracking mechanism and a downstream tracing mechanism.

[0011] The upstream backtracking mechanism includes: using a graph traversal algorithm to query the creditor-debtor relationship database, locate the source node, integrate digital certificates and source nodes, and generate a tracing path;

[0012] The downstream traceability mechanism includes: identifying changes in the status of creditor-debtor relationships by pointing to, defining as associated nodes and associated edges, querying pre-edited multi-dimensional write-off strategies, generating write-off suggestions, and sending them to preset terminals.

[0013] Furthermore, the method also includes:

[0014] The multidimensional write-off strategy is clustered into several write-off preferences, which include at least: prioritizing the write-off of high-interest debt items, prioritizing the write-off of debt items nearing maturity, and prioritizing the write-off of critical path items;

[0015] Create applicable conditions that correspond one-to-one with redemption preferences, determine target preferences, generate several recommendation sequences, and write them into a preset template to generate redemption suggestions.

[0016] Furthermore, the steps of constructing a creditor-debtor relationship database and extracting the relevant parties and their corresponding creditor-debtor relationships include:

[0017] Determine the data sources for the creditor-debtor relationship database, wherein the data sources include at least: the financial system and the supply chain system;

[0018] The creditor-debtor relationship database is updated based on the data source.

[0019] Furthermore, the step of extracting the relational entities and corresponding creditor-debtor relationships, with the relational entities as nodes and the creditor-debtor relationships as directed edges, includes:

[0020] Obtain the status information of each creditor-debtor relationship and establish the link between the status information and the directed edges.

[0021] Furthermore, the step of establishing the association between directed edges and attribute data, and inserting the debt-creditor graph into the debt-creditor relationship database, includes:

[0022] Insert several relation edges into the aforementioned debt-creditor graph, wherein the relation edges include at least: guarantee relation edges and transaction dependency edges;

[0023] Create identifier colors that correspond one-to-one with the relationship edges, and label the creditor-debtor graph to obtain a composite debt network.

[0024] Furthermore, the step of querying the pre-edited multi-dimensional reconciliation strategy, generating reconciliation suggestions, and sending them to the preset terminal includes:

[0025] Receive user feedback data regarding reimbursement suggestions, switch the multi-dimensional reimbursement strategy, and update the reimbursement suggestions;

[0026] Summarize reconciliation suggestions and feedback data, generate versions, and establish a mapping between query requests and versions.

[0027] Furthermore, the system includes:

[0028] The construction module is used to build a database of creditor-debtor relationships, extract the subjects of the relationship and the corresponding creditor-debtor relationships, take the subjects of the relationship as nodes and the creditor-debtor relationships as directed edges, and use the directed edges to connect the nodes to generate a creditor-debtor graph, wherein the directed edges point from the debtor to the creditor.

[0029] The data acquisition module is used to collect attribute data of digital vouchers, wherein the attribute data includes at least: voucher identifier, debt amount, due date and current debt status, establish the association relationship between directed edges and attribute data, and insert the debt graph into the debt relationship database;

[0030] The activation module is used to find the corresponding digital voucher after receiving a query request from a user containing a digital voucher, and activate a pre-edited two-way traceability mechanism. The two-way traceability mechanism includes an upstream backtracking mechanism and a downstream tracing mechanism. The upstream backtracking mechanism includes: using a graph traversal algorithm to query the creditor-debtor relationship database, locating the source node, integrating the digital voucher and the source node, and generating a traceability path. The downstream tracing mechanism includes: identifying changes in the state of the creditor-debtor relationship by defining associated nodes and associated edges, querying a pre-edited multi-dimensional write-off strategy, generating write-off suggestions, and sending them to preset terminals.

[0031] Furthermore, the building module includes:

[0032] A determining unit is used to determine the data source of the creditor-debtor relationship database, wherein the data source includes at least: financial systems and supply chain systems;

[0033] An update unit is used to update the creditor-debtor relationship database via the data source;

[0034] Establish a unit to obtain the status information of each creditor-debtor relationship and establish the link between the status information and the directed edges.

[0035] Furthermore, the acquisition module includes:

[0036] An insertion unit is used to insert a number of relationship edges into the debt-creditor graph, wherein the relationship edges include at least: guarantee relationship edges and transaction dependency edges;

[0037] The annotation unit is used to create a color that corresponds one-to-one with the relation edges, and to annotate the debt graph to obtain a composite debt network.

[0038] Furthermore, the activation module includes:

[0039] The switching unit is used to receive user feedback data on reimbursement suggestions, switch the multi-dimensional reimbursement strategy, and update the reimbursement suggestions;

[0040] The summary unit is used to summarize reconciliation suggestions and feedback data, generate versions, and establish a mapping between query requests and versions.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] By constructing a debt graph based on creditor-debtor relationships, global traceability of debt management can be achieved, enabling managers to quickly grasp all debt relationships. By building a two-way traceability mechanism, combined with graph traversal algorithms and multi-dimensional write-off strategies, it is possible to quickly trace the source of digital vouchers, verify the debt transfer path, and analyze the potential impact on upstream and downstream related enterprises, significantly improving the efficiency of traceability analysis. By generating write-off suggestions, high-risk debts can be resolved first, reducing overall debt costs, optimizing the allocation of debt resolution resources, achieving scientific debt resolution, and significantly improving the progress and quality of debt resolution. Attached Figure Description

[0043] Figure 1 A flowchart illustrating the digital certificate tracing and write-off method based on a debt-creditor graph provided in this embodiment of the invention;

[0044] Figure 2 This is a first sub-flowchart of the digital certificate tracing and write-off method based on a debt-credit graph provided in an embodiment of the present invention;

[0045] Figure 3 This is a second sub-flow flowchart of the digital certificate tracing and write-off method based on the debt-credit graph provided in an embodiment of the present invention;

[0046] Figure 4 The third sub-flow flowchart of the digital certificate tracing and write-off method based on the creditor-debtor graph provided in the embodiments of the present invention;

[0047] Figure 5 This is a block diagram of the digital voucher traceability and verification system based on a debt-creditor graph provided in an embodiment of the present invention;

[0048] Figure 6 A block diagram of the components of the construction module in the digital certificate traceability and write-off system based on the creditor-debtor graph provided in the embodiments of the present invention;

[0049] Figure 7 A block diagram of the data acquisition module in the digital voucher tracing and verification system based on a debt and creditor graph provided in this embodiment of the invention;

[0050] Figure 8 This is a block diagram of the activation module in the digital certificate tracing and verification system based on a debt and credit graph provided in an embodiment of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the 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 merely illustrative and not intended to limit the invention.

[0052] In Example 1, Figure 1 The implementation flow of the digital certificate tracing and reversal method based on the debt-claim graph provided in this embodiment of the invention is illustrated below in detail:

[0053] S100: Construct a database of creditor-debtor relationships, extract the subjects of the relationship and the corresponding creditor-debtor relationships, take the subjects of the relationship as nodes and the creditor-debtor relationships as directed edges, connect the nodes with the directed edges to generate a creditor-debtor graph, wherein the directed edges point from the debtor to the creditor.

[0054] This process involves acquiring user-uploaded creditor-debtor relationships to build a database. Various types of creditor-debtor data are processed uniformly, extracting creditors and debtors from contract texts, digital vouchers, settlement records, and ledger information. The creditor-debtor relationships between these entities are then defined. Using these entities as nodes, the creditor-debtor relationships reflecting the direction of fund or right-obligation transfers are abstracted as directed edges, with each edge pointing from the debtor to the creditor. Connecting these directed edges to their corresponding nodes generates a comprehensive creditor-debtor graph structure. Attribute information of the creditor-debtor relationships, including amount, formation time, maturity date, and current status, is collected and linked to the directed edges. The advantage of this method is its ability to intuitively express and systematically store multi-entity, multi-level creditor-debtor relationships, facilitating subsequent relationship queries, risk analysis, and source tracing calculations.

[0055] S200: Collect attribute data of digital vouchers, wherein the attribute data includes at least: voucher identifier, debt amount, due date and current debt status, establish the association relationship between directed edges and attribute data, and insert the debt graph into the debt relationship database.

[0056] For each set of creditor-debtor relationships, a corresponding digital certificate should be created. The specific coding rules for the digital certificate should be pre-defined by professionals. Attribute data of the digital certificate should be collected, including: certificate identifier, debt amount representing the scale of the claim, maturity date reflecting the performance period, and current debt status. A one-to-one association between directed edges and their corresponding attribute data should be established, ensuring that each directed edge carries complete and traceable creditor-debtor information. The completed creditor-debtor graph should be written into a creditor-debtor relationship database for centralized storage and management. This achieves the association and maintenance of creditor-debtor relationships with the attribute data of digital certificates, providing a data foundation for subsequent analysis, tracing, and risk identification.

[0057] S300: Upon receiving a query request from a user containing digital credentials, the system locates the corresponding digital credentials and activates a pre-edited two-way traceability mechanism. This mechanism includes an upstream backtracking mechanism and a downstream tracing mechanism. The upstream backtracking mechanism involves using a graph traversal algorithm to query the debt-creditor relationship database, locate the source node, integrate the digital credentials and the source node, and generate a traceability path. The downstream tracing mechanism involves identifying changes in the debt-creditor relationship by defining associated nodes and edges, querying a pre-edited multi-dimensional write-off strategy, generating write-off suggestions, and sending them to a preset terminal.

[0058] Upon receiving a user-uploaded query request, the system parses the request, extracts the digital certificate, and locates the corresponding digital certificate in the debt-creditor relationship database. It then activates a pre-edited two-way tracing mechanism. This mechanism involves traversing the debt-creditor relationship along both the forward and reverse directions, starting from the node and directed edge of the target digital certificate within the debt-creditor graph. The two-way tracing mechanism includes an upstream backtracking mechanism for analyzing the source and formation path of the debt, and a downstream tracing mechanism for analyzing the destination and subsequent flow of the debt. The upstream backtracking mechanism traces back level by level along the reverse directed edge connected to the target digital certificate, while the downstream tracing mechanism traces back level by level along the forward direction of the directed edge to identify subsequent related debtors. The advantage of this approach is that it enables comprehensive tracking and analysis of the source and destination of the digital certificate within the overall debt-creditor graph.

[0059] Based on the debt-creditor graph, a graph traversal algorithm is used to query the debt-creditor relationship database. Utilizing an upstream backtracking mechanism, the source node is identified, and the source node is integrated with associated digital vouchers to construct a complete and continuous traceability path. This path clearly presents the formation chain and source of responsibility for the debt-creditor relationship. The downstream tracing mechanism includes: identifying nodes and edges directly or indirectly connected to the target node along the direction of directed edges; defining the nodes and edges to be monitored as associated nodes and edges, respectively; monitoring the state changes of the debt-creditor relationship at associated nodes and edges in real time; and, upon detecting a state update, invoking a pre-edited multi-dimensional write-off strategy. This strategy comprehensively evaluates the debt-creditor relationship from multiple dimensions and generates write-off recommendations. These recommendations are written into a preset template to generate write-off suggestions, which are then distributed to a preset terminal (e.g., a financial management personnel terminal) where a write-off plan is selected and the debt-creditor relationship is automatically written off.

[0060] In Embodiment 2, unlike Embodiment 1, the method further includes:

[0061] The multidimensional write-off strategy is clustered into several write-off preferences, which include at least: prioritizing the write-off of high-interest debt items, prioritizing the write-off of debt items nearing maturity, and prioritizing the write-off of critical path items;

[0062] Create applicable conditions that correspond one-to-one with redemption preferences, determine target preferences, generate several recommendation sequences, and write them into a preset template to generate redemption suggestions.

[0063] The pre-constructed multi-dimensional write-off strategies are categorized according to dimensions such as risk characteristics, return impact, and time constraints, generating several representative write-off preferences. These preferences include: prioritizing the write-off of high-interest debt items to reduce financial costs; prioritizing the write-off of debt items nearing maturity to avoid default risk; and prioritizing the write-off of critical path items in the debt-credit graph to reduce transmission risk. Applicable conditions are created for each write-off preference. Based on the write-off preferences determined by the user, the debt items in the debt-credit graph are sorted and combined to generate several executable write-off recommendation sequences, which are then written into a preset template to generate write-off suggestions.

[0064] In Example 3, Figure 2 The first sub-process flowchart of the digital certificate tracing and cancellation method based on the creditor-debtor graph provided by the present invention is shown below. The steps of constructing the creditor-debtor relationship database and extracting the relationship subjects and corresponding creditor-debtor relationships are described in detail below:

[0065] S101: Determine the data sources of the creditor-debtor relationship database, wherein the data sources include at least: financial systems and supply chain systems.

[0066] The data sources for the creditor-debtor relationship database are determined. These sources include financial systems and supply chain systems. Financial systems can provide data such as loans, bills, accounts receivable and payable, settlement records, and digital vouchers, which can accurately reflect fund flows and debt repayment status. Supply chain systems can provide data such as order information, contractual relationships, delivery and receipt records, and reconciliation results, which can depict the business sources and upstream and downstream relationships that form creditor-debtor relationships.

[0067] S102: Update the creditor-debtor relationship database via the data source.

[0068] The creditor-debtor relationship database is updated regularly using newly added data from data sources.

[0069] In Example 4, Figure 2 The first sub-process flowchart of the digital certificate tracing and reversal method based on a debt-credit graph provided by an embodiment of the present invention is shown below. The steps of extracting the relational subjects and corresponding debt-credit relationships, with the relational subjects as nodes and the debt-credit relationships as directed edges, are described in detail below:

[0070] S103: Obtain the status information of each creditor-debtor relationship and establish the link between the status information and the directed edges.

[0071] The status information of creditor-debtor relationships is updated to accurately depict the changes in the status of creditor-debtor relationships over time without changing the graph structure. This enables continuous tracking and unified management of creditor-debtor relationships. The link between status information and directed edges is established, and the directed edges are updated synchronously when the status information changes.

[0072] In Example 5, Figure 3 The second sub-process flowchart of the digital certificate tracing and reversal method based on a debt-credit graph provided in this embodiment of the invention is shown. The following details the steps of establishing the association between directed edges and attribute data, and inserting the debt-credit graph into the debt-credit relationship database:

[0073] S201: Insert several relation edges into the debt-creditor graph, wherein the relation edges include at least: guarantee relation edges and transaction dependency edges.

[0074] Based on the existing debt and credit graph, several additional relationship edges are inserted into the debt and credit graph. These relationship edges are used to show additional connections beyond direct debt relationships. The relationship edges include: guarantee relationship edges and transaction dependency edges. Guarantee relationship edges can reflect the guarantee obligations between debtor entities, while transaction dependency edges are used to represent the dependency relationship between debtor entities in business transactions or fund transfers.

[0075] S202: Create identifier colors that correspond one-to-one with the relationship edges, and label the creditor-debtor graph to obtain a composite debt network.

[0076] Create a unique identifier color for each relationship edge, establish a mapping relationship between the identifier color and the relationship type, and annotate the newly added relationship edges in the debt graph to generate a composite debt network. The composite debt network can realize the visualization of multi-dimensional relationships such as direct debt, guarantee obligations, and transaction dependencies.

[0077] In Example 6, Figure 4 The diagram illustrates the third sub-process flowchart of the digital certificate tracing and reversal method based on a debt-creditor graph provided in this embodiment of the invention. The following details the steps of querying a pre-edited multi-dimensional reversal strategy, generating reversal suggestions, and sending them to a preset terminal:

[0078] S301: Receive user feedback data regarding reimbursement suggestions, switch the multi-dimensional reimbursement strategy, and update the reimbursement suggestions.

[0079] The system receives user feedback on previous reconciliation suggestions. This feedback includes comments and suggestions for improvement regarding the reconciliation amount, order, or method. Based on this feedback, the system adjusts the existing multi-dimensional reconciliation strategy, recalculates the reconciliation plan, and updates the reconciliation suggestions accordingly.

[0080] S302: Summarize reconciliation suggestions and feedback data, generate versions, and establish a mapping between query requests and versions.

[0081] The updated reimbursement suggestions are integrated and summarized with user feedback data, and recorded using a version system. Each user query request generates a reimbursement suggestion, and each reimbursement suggestion corresponds to a version. In this way, a mapping relationship between user query requests and versions is established, so that every user query can be accurately recorded.

[0082] Figure 5 This diagram illustrates the structural block diagram of a digital certificate traceability and verification system based on a debt-claims graph provided in an embodiment of the present invention. The digital certificate traceability and verification system 1 based on a debt-claims graph includes:

[0083] Module 11 is used to construct a database of creditor-debtor relationships, extract the subjects of the relationship and the corresponding creditor-debtor relationships, take the subjects of the relationship as nodes and the creditor-debtor relationships as directed edges, connect the nodes with the directed edges to generate a creditor-debtor graph, wherein the directed edges point from the debtor to the creditor.

[0084] The data acquisition module 12 is used to collect attribute data of digital vouchers, wherein the attribute data includes at least: voucher identifier, debt amount, due date and current debt status, establish the association relationship between directed edges and attribute data, and insert the debt graph into the debt relationship database;

[0085] Activation module 13 is used to find the corresponding digital certificate after receiving a query request from a user containing a digital certificate, and activate a pre-edited two-way traceability mechanism. The two-way traceability mechanism includes an upstream backtracking mechanism and a downstream tracing mechanism. The upstream backtracking mechanism includes: using a graph traversal algorithm to query the creditor-debtor relationship database, locating the source node, integrating the digital certificate and the source node, and generating a traceability path. The downstream tracing mechanism includes: identifying the state changes of the creditor-debtor relationship by defining the associated nodes and associated edges through pointers, querying the pre-edited multi-dimensional write-off strategy, generating write-off suggestions, and sending them to a preset terminal.

[0086] Figure 6 This diagram illustrates the composition of module 11 in the digital voucher tracing and verification system based on a debt-creditor graph provided in an embodiment of the present invention. Module 11 includes:

[0087] Determining unit 111 is used to determine the data source of the creditor-debtor relationship database, wherein the data source includes at least: financial system and supply chain system;

[0088] Update unit 112 is used to update the creditor-debtor relationship database via the data source;

[0089] Unit 113 is established to obtain the status information of each creditor-debtor relationship and establish the link between the status information and the directed edges.

[0090] Figure 7 This diagram illustrates the structural composition of the data acquisition module 12 in the digital voucher tracing and verification system based on a debt-creditor graph provided in an embodiment of the present invention. The data acquisition module 12 includes:

[0091] Insertion unit 121 is used to insert a number of relationship edges into the debt-creditor graph, wherein the relationship edges include at least: guarantee relationship edges and transaction dependency edges;

[0092] The annotation unit 122 is used to create an identifier color that corresponds one-to-one with the relation edges, and to annotate the creditor-debtor graph to obtain a composite debt network.

[0093] Figure 8 This diagram illustrates the structural composition of the activation module 13 in the digital certificate tracing and verification system based on a debt-creditor graph provided in an embodiment of the present invention. The activation module 13 includes:

[0094] The switching unit 131 is used to receive user feedback data on reimbursement suggestions, switch the multi-dimensional reimbursement strategy, and update the reimbursement suggestions;

[0095] Summary unit 132 is used to summarize reconciliation suggestions and feedback data, generate versions, and establish a mapping between query requests and versions.

[0096] The construction module 11 is mainly used to complete step S100, the acquisition module 12 is mainly used to complete step S200, and the activation module 13 is mainly used to complete step S300.

[0097] The determining unit 111 is mainly used to complete step S101, the updating unit 112 is mainly used to complete step S102, and the establishing unit 113 is mainly used to complete step S103.

[0098] Insertion unit 121 is mainly used to complete step S201, and annotation unit 122 is mainly used to complete step S202;

[0099] The switching unit 131 is mainly used to complete step S301, and the summarizing unit 132 is mainly used to complete step S302.

[0100] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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, they should be considered to be within the scope of this specification.

[0101] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0102] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for tracing and verifying digital vouchers based on a debt-creditor graph, characterized in that, The method includes: Construct a database of creditor-debtor relationships, extract the subjects of the relationship and the corresponding creditor-debtor relationships, take the subjects of the relationship as nodes and the creditor-debtor relationships as directed edges, connect the nodes with the directed edges to generate a creditor-debtor graph, wherein the directed edges point from the debtor to the creditor; Collect attribute data of digital vouchers, wherein the attribute data includes at least: voucher identifier, debt amount, due date and current debt status, establish the association relationship between directed edges and attribute data, and insert the debt graph into the debt relationship database; Upon receiving a query request from a user containing a digital certificate, the system locates the corresponding digital certificate and activates a pre-edited two-way traceability mechanism, which includes an upstream backtracking mechanism and a downstream tracing mechanism. The upstream backtracking mechanism includes: using a graph traversal algorithm to query the creditor-debtor relationship database, locate the source node, integrate digital certificates and source nodes, and generate a tracing path; The downstream traceability mechanism includes: identifying changes in the status of creditor-debtor relationships by pointing to, defining as associated nodes and associated edges, querying pre-edited multi-dimensional write-off strategies, generating write-off suggestions, and sending them to preset terminals.

2. The method for tracing and verifying digital vouchers based on a debt-creditor graph according to claim 1, characterized in that, The method further includes: The multidimensional write-off strategy is clustered into several write-off preferences, which include at least: prioritizing the write-off of high-interest debt items, prioritizing the write-off of debt items nearing maturity, and prioritizing the write-off of critical path items; Create applicable conditions that correspond one-to-one with redemption preferences, determine target preferences, generate several recommendation sequences, and write them into a preset template to generate redemption suggestions.

3. The method for tracing and verifying digital vouchers based on a debt-creditor graph according to claim 1, characterized in that, The steps of constructing a database of creditor-debtor relationships and extracting the relevant parties and their corresponding creditor-debtor relationships include: Determine the data sources for the creditor-debtor relationship database, wherein the data sources include at least: the financial system and the supply chain system; The creditor-debtor relationship database is updated based on the data source.

4. The method for tracing and verifying digital vouchers based on a debt-creditor graph according to claim 3, characterized in that, The step of extracting the relational entities and corresponding creditor-debtor relationships, with the relational entities as nodes and the creditor-debtor relationships as directed edges, includes: Obtain the status information of each creditor-debtor relationship and establish the link between the status information and the directed edges.

5. The method for tracing and verifying digital vouchers based on a debt-creditor graph according to claim 1, characterized in that, The steps of establishing the association between directed edges and attribute data, and inserting the debt-credit graph into the debt-credit relationship database, include: Insert several relation edges into the aforementioned debt-creditor graph, wherein the relation edges include at least: guarantee relation edges and transaction dependency edges; Create identifier colors that correspond one-to-one with the relationship edges, and label the creditor-debtor graph to obtain a composite debt network.

6. The method for tracing and verifying digital vouchers based on a debt-creditor graph according to claim 2, characterized in that, The steps of querying the pre-edited multi-dimensional reconciliation strategy, generating reconciliation suggestions, and sending them to preset terminals include: Receive user feedback data regarding reimbursement suggestions, switch the multi-dimensional reimbursement strategy, and update the reimbursement suggestions; Summarize reconciliation suggestions and feedback data, generate versions, and establish a mapping between query requests and versions.

7. A digital voucher traceability and verification system based on a debt-creditor graph, characterized in that, The system includes: The construction module is used to build a database of creditor-debtor relationships, extract the subjects of the relationship and the corresponding creditor-debtor relationships, take the subjects of the relationship as nodes and the creditor-debtor relationships as directed edges, and use the directed edges to connect the nodes to generate a creditor-debtor graph, wherein the directed edges point from the debtor to the creditor. The data acquisition module is used to collect attribute data of digital vouchers, wherein the attribute data includes at least: voucher identifier, debt amount, due date and current debt status, establish the association relationship between directed edges and attribute data, and insert the debt graph into the debt relationship database; The activation module is used to find the corresponding digital voucher after receiving a query request from a user containing a digital voucher, and activate a pre-edited two-way traceability mechanism. The two-way traceability mechanism includes an upstream backtracking mechanism and a downstream tracing mechanism. The upstream backtracking mechanism includes: using a graph traversal algorithm to query the creditor-debtor relationship database, locating the source node, integrating the digital voucher and the source node, and generating a traceability path. The downstream tracing mechanism includes: identifying changes in the state of the creditor-debtor relationship by defining associated nodes and associated edges, querying a pre-edited multi-dimensional write-off strategy, generating write-off suggestions, and sending them to preset terminals.

8. The digital certificate traceability and verification system based on a debt-creditor graph as described in claim 7, characterized in that, The building module includes: A determining unit is used to determine the data source of the creditor-debtor relationship database, wherein the data source includes at least: financial systems and supply chain systems; An update unit is used to update the creditor-debtor relationship database via the data source; Establish a unit to obtain the status information of each creditor-debtor relationship and establish the link between the status information and the directed edges.

9. The digital certificate traceability and verification system based on a debt-creditor graph as described in claim 7, characterized in that, The acquisition module includes: An insertion unit is used to insert a number of relationship edges into the debt-creditor graph, wherein the relationship edges include at least: guarantee relationship edges and transaction dependency edges; The annotation unit is used to create a color that corresponds one-to-one with the relation edges, and to annotate the debt graph to obtain a composite debt network.

10. The digital certificate traceability and verification system based on a debt-creditor graph according to claim 7, characterized in that, The activation module includes: The switching unit is used to receive user feedback data on reimbursement suggestions, switch the multi-dimensional reimbursement strategy, and update the reimbursement suggestions; The summary unit is used to summarize reconciliation suggestions and feedback data, generate versions, and establish a mapping between query requests and versions.

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