Risk management and control method for business ticket cashing platform, and storage medium

Abstract

The invention relates to the technical field of business ticket cashing management and control, and discloses a risk management and control method for a business ticket cashing platform, and the method comprises the steps: fusing an enterprise identification code and a hierarchical code to form a composite identification, and building a group hierarchical identification system; performing hierarchical storage on the enterprise data according to hierarchical codes based on a distributed database; establishing a hierarchical index tree for the stored data according to hierarchical codes; performing statistics on change data of each hierarchy through a hierarchy increment statistical algorithm, and automatically generating a hierarchy summary result in combination with historical baseline data of each hierarchy; different permission levels are given to the users according to the level codes, and the high-level users can call the data of the low-level users. According to the scheme, the business ticket cashing risk management and control efficiency is improved, the user operation complexity is reduced, and the use experience is optimized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of commercial bill redemption management and control, and particularly relates to a risk management and control method for a commercial bill redemption platform and a storage medium. BACKGROUND

[0002] At present, the commercial bill redemption platform is designed for a single enterprise, and only uses a unified social credit code as the unique identifier, without considering the hierarchical management needs of the group enterprise headquarters, subsidiaries and grandsons, and cannot realize hierarchical screening, aggregation and control, for example, the headquarters checks the redemption default rate of a regional subsidiary. At the same time, the existing big data processing scheme only solves the efficiency problem of single enterprise full data, and does not design a distributed index for hierarchical data, resulting in the need to traverse all subsidiary data when performing group full hierarchical statistics, causing system lag. When the group enterprise level is complex and the bill data volume exceeds ten million, the traditional full statistics needs to take several hours or even longer, which cannot meet the real-time risk control needs. The existing technology lacks a standardized hierarchical coding system, and the subsidiary data changes cannot be automatically synchronized to the upper level, resulting in lag or deviation of the group headquarters data.

[0003] From the above, it can be seen that how to improve the efficiency of commercial bill redemption management for group enterprises, improve the efficiency of risk checking, simplify the operation difficulty of users and improve the user experience have become technical problems to be solved by the technical personnel in the field.

[0004] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present application, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] In order to have a basic understanding of some aspects of the disclosed embodiments, the following is a simple summary. The summary is not a general review, nor is it intended to determine the key / important components or delineate the scope of protection of these embodiments, but as a prelude to the detailed description below.

[0006] The embodiments of the present disclosure provide a risk management and control method and system for a commercial bill redemption platform, which can give reasonable decision suggestions according to the identification features and risk assessment results of the commercial bill data, so that the decision maker can intuitively select the decision suggestions, reduce the energy consumed by the decision maker, and the given decision suggestions are more comprehensive and accurate, reducing the loss of the enterprise.

[0007] In some embodiments, the risk management and control method for the commercial bill redemption platform comprises: fusing the enterprise identification code and the hierarchical coding to form a composite identifier, and establishing a group hierarchical identification system; based on a distributed database, storing enterprise data in stages according to the hierarchical coding; According to the hierarchical coding, a hierarchical index tree is established for the stored data; Through the hierarchical incremental statistical algorithm, the change data of each level is counted, and a hierarchical summary result is automatically generated in combination with historical baseline data of each level. According to the hierarchical coding, different levels of permissions are given to users, and users at a high level can call data of users at a low level.

[0008] Optionally, in the group hierarchical identification system, the length of the hierarchical coding is 4 bits, the first 2 bits represent the level, and the last 2 bits represent the enterprise serial number in the same level.

[0009] Optionally, the distributed database is an HBase database, and the specific way of hierarchical storage is: partitioning according to the first 2 bits of the hierarchical coding, and distributing enterprise data of the same level to the same partition, and the maximum data volume of each partition is limited to 5-10 million.

[0010] Optionally, the root node of the hierarchical index tree is associated with the composite identifier of the group headquarters and the corresponding data partition address, the first-level node is associated with the composite identifier of the first-level subsidiary and the corresponding data partition address, and each first-level node only points to the leaf node of the subordinate second-level subsidiary.

[0011] Optionally, in the hierarchical incremental statistical algorithm, the historical baseline data includes the total number of bills, the number of bills already redeemed, the number of overdue bills, and the number of high-risk commercial bills of each level, and the historical baseline data is automatically updated once every preset time interval.

[0012] Optionally, through the hierarchical incremental statistical algorithm, the step of counting the change data of each level includes: Receive bill status change information and extract the composite identifier of the level to which the change data belongs; According to the hierarchical coding in the composite identifier, determine the upper level chain of the level; Synchronously add the incremental value in the change data to the incremental buffer area of itself and the upper level.

[0013] Optionally, the permission level includes three levels: The first-level permission can only call the bill data of its own level; The second-level permission can call the bill data of itself and all subordinate companies; The third-level permission can call the bill data of all levels.

[0014] Optionally, the hierarchical summary result includes the bill balance, redemption rate, overdue rate, and high-risk commercial bill proportion of each level, and the summary result is synchronized in real time to the group hierarchical visualization management and control platform, supporting graphical display and abnormal early warning.

[0015] Optionally, the risk control method for the commercial bill redemption platform further includes: Periodically compare the summary results of each level with the original data in the distributed database. If the deviation rate exceeds 0.1%, automatically trigger the baseline data re-initialization and incremental data backtracking calculation.

[0016] The risk control method for the commercial bill redemption platform provided by the embodiments of the present disclosure can achieve the following technical effects: By constructing a group identification system based on four-level coding, the limitations of traditional single enterprise identification in group cross-level penetration management are overcome. The system supports the headquarters to monitor key indicators such as default rate of regional subsidiaries in real time, and improves the data retrieval efficiency by 3-5 times through the optimized hierarchical index tree structure. The distributed database partitioning strategy based on the first two levels of hierarchical coding is adopted, combined with the directional association mechanism of the root node and the child node of the hierarchical index tree, so that the full amount of massive bill data statistics is reduced from several hours to minutes. The hierarchical incremental calculation algorithm adopts an incremental buffer zone accumulation mode, and periodically updates the historical baseline data, which realizes automatic synchronization of subsidiary data changes to the upper level, effectively eliminating the time efficiency bottleneck of more than 24 hours of data lag in the traditional scheme. Through the design of a differentiated permission system, different permission users can complete data retrieval operations without writing complex query statements, significantly reducing the operation steps. This scheme improves the efficiency of commercial bill redemption risk control while reducing user operation complexity and optimizing user experience.

[0017] The foregoing general description and the following description are only exemplary and explanatory, and are not intended to limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0018] One or more embodiments are exemplarily illustrated by corresponding drawings, which do not constitute limitations on the embodiments, elements with the same reference numerals in the drawings are shown as similar elements, the drawings do not constitute proportional limits, and wherein: Figure 1 is a schematic diagram of a risk control method for a commercial bill redemption platform provided by an embodiment of the present disclosure; Figure 2 is a schematic diagram of another risk control method for a commercial bill redemption platform provided by an embodiment of the present disclosure; Figure 3 is a schematic diagram of another risk control method for a commercial bill redemption platform provided by an embodiment of the present disclosure; Figure 4 is a schematic diagram of another risk control method for a commercial bill redemption platform provided by an embodiment of the present disclosure; Figure 5 is a schematic diagram of a risk control system for a commercial bill redemption platform provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0019] In order to enable a more detailed understanding of the features and technical content of the embodiments of the present disclosure, the implementation of the embodiments of the present disclosure is described in detail below, and the attached drawings are used for reference only and do not limit the embodiments of the present disclosure. In the following technical description, in order to facilitate explanation, through multiple details, a sufficient understanding of the disclosed embodiments is provided. However, one or more embodiments can still be implemented without these details. In other cases, in order to simplify the drawings, well-known structures and devices can be simplified.

[0020] The terms "first", "second", and the like in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances in order to describe the embodiments of the present disclosure. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion.

[0021] Unless otherwise specified, the term "a plurality of" means two or more.

[0022] The term "corresponding" can refer to an association or binding relationship. A and B correspond to each other means that there is an association or binding relationship between A and B.

[0023] In combination Figure 1 As shown, in some embodiments, the risk control method for the commercial bill redemption platform includes: S01, fusion enterprise identification code and hierarchical coding to form a composite identification, and establish a group hierarchical identification system; S02, based on a distributed database, the enterprise data is stored according to the hierarchical coding; S03, according to the hierarchical coding, the stored data is established as a hierarchical index tree; S04, through the hierarchical incremental statistical algorithm, the change data of each level is counted, and the hierarchical summary result is automatically generated in combination with the historical baseline data of each level; S05, according to the hierarchical coding, different permission levels are given to users, and the data of the users of the lower level can be called by the users of the higher level.

[0024] The risk control method for the commercial bill redemption platform provided by the embodiment of the present disclosure overcomes the limitations of traditional single enterprise identification in group cross-level penetration management by constructing a group identification system based on four-level coding. The system supports the headquarters to monitor key indicators such as the redemption default rate of regional subsidiaries in real time, and improves the data retrieval efficiency by 3-5 times through an optimized hierarchical index tree structure. The distributed database partitioning strategy based on the first two levels of hierarchical coding, combined with the directional association mechanism of the root node and the child nodes of the hierarchical index tree, reduces the time consumption of full statistics of massive bill data from several hours to minutes. The hierarchical incremental calculation algorithm adopts an incremental buffer zone accumulation mode, and periodically updates the historical baseline data, which realizes automatic synchronization of the data of the subsidiary to the upper level after the data of the subsidiary is changed, and effectively eliminates the time efficiency bottleneck of the headquarters data lagging more than 24 hours in the traditional scheme. Through the design of a differentiated permission system, different permission users can complete data retrieval operations without writing complex query statements, significantly reducing the operation steps. The scheme improves the efficiency of risk control of commercial bill redemption, reduces the complexity of user operation, and optimizes the user experience.

[0025] Optionally, the enterprise identification code is an enterprise credit code, or a non-repeated username automatically generated by the platform.

[0026] Optionally, in the group hierarchical identification system, the length of the hierarchical coding is 4 bits, the first 2 bits represent the hierarchical level, and the last 2 bits represent the enterprise sequence in the same hierarchical level. In this way, the first two codes are used to distinguish the management levels of the headquarters, regional companies, city branch companies and stores, and the last two codes are used to identify different enterprise entities in the same hierarchical level, ensuring that the codes are unique and scalable. Through the four-bit coding structure, the system can accurately identify and associate cross-level enterprise relationships, and realize efficient routing and filtering in data query and permission control, providing a standardized data basis for subsequent risk analysis and decision support.

[0027] Optionally, the distributed database is an HBase database, and the specific way of hierarchical storage is: partitioning according to the first 2 bits of the hierarchical coding, distributing the enterprise data of the same hierarchical level to the same partition, and limiting the maximum data volume of each partition to 5-10 million. In this way, the logical isolation of data is realized through the first two codes. The columnar storage feature of HBase further improves the separation efficiency of new and old data. The root node of the hierarchical index tree is stored in an independent namespace, and the child nodes are distributed in the corresponding partitions according to the coding path, reducing cross-zone scanning during query. The incremental calculation algorithm collects the change logs of each node every minute, and updates the summary layer after compression and merging, ensuring the consistency of hierarchical data.

[0028] Optionally, the data volume of each partition is monitored in real time to ensure that it does not exceed the set limit of 5-10 million. When the partition data volume approaches the upper limit, automatic partition splitting is triggered to keep the partition data volume within a reasonable range. Where the data volume approaches the upper limit means that the data volume reaches 95% of the set total data volume.

[0029] Optionally, the automatic triggering of partition splitting means that one partition is split into two partitions corresponding to the same hierarchical coding. When the data volume of a certain partition approaches the set threshold, automatic secondary splitting is performed according to the last two bits of the hierarchical coding (e.g., 00 is split into 00A / 00B).

[0030] In some embodiments, the operation and maintenance strategy of the HBase database includes: Region division rules and pre-partitioning strategy; HexStringSplit algorithm is used for pre-partitioning, and four partitions are pre-built according to the first two bits of the hierarchical coding. Each partition corresponds to a hierarchical level, 00 corresponds to the headquarters level, 01 corresponds to the first-level subsidiary, 02 corresponds to the second-level subsidiary, and 03 corresponds to the last-level institution; four split keys are set according to 00|01|02|03, and when writing, the first two bits of the composite identifier are automatically routed to the corresponding Region; Among them, the column family division standard in the HBase database includes: CF1 (BaseInfo): stores the face basis information (drawer, amount, due date), enables Snappy compression, and retains 3 maximum version numbers; CF2 (Circulation): stores the circulation record (endorser, endorsed, circulation time), and enables DATA_BLOCK_ENCODING encoding optimization; CF3 (Status): stores the status information (not redeemed / already redeemed / overdue), and sets the TTL to 180 days, which is the validity period of the bill; CF4 (Blockchain): stores the blockchain storage hash value and timestamp, and is set as a read-only column family.

[0031] Optionally, the root node of the hierarchical index tree is associated with the composite identifier of the group headquarters and the corresponding data partition address, the first-level node is associated with the composite identifier of the first-level subsidiary and the corresponding data partition address, and each first-level node only points to the leaf node of the subordinate second-level subsidiary. In this way, the root node and each level of the child node form a strict parent-child mapping relationship, ensuring that the data path is unique and traceable. When the data of the subsidiary changes, the system automatically triggers multi-level summary update according to the coding level to ensure that the headquarters view can be quickly synchronized. While supporting millions of bills, good scalability and consistency are maintained, facilitating global risk monitoring by the group.

[0032] Optionally, in the tiered incremental statistical algorithm, historical baseline data includes the total number of bills, the number of bills already redeemed, the number of overdue bills, and the number of high-risk commercial bills at each tier. This historical baseline data is automatically updated at preset intervals. This regular updating of historical baseline data ensures the timeliness and accuracy of risk indicators, providing dynamic monitoring data for management at all levels. Through the fusion analysis of baseline and real-time data, the group's ability to predict and respond to commercial bill redemption risks is improved.

[0033] Optionally, by combining real-time incremental change logs, key indicators such as overdue rates, repayment completion rates, and risk concentration at each level are calculated. An abnormal fluctuation warning is automatically triggered when any key indicator fluctuates above a preset value. This allows the system to instantly push warning information to the relevant management level, enabling timely handling of potential risks and preventing further losses. Furthermore, the warning information can include the degree of abnormality of the indicator, the scope of subsidiaries involved, and a list of related invoices, supporting management in quickly locating the source of the problem and activating contingency plans.

[0034] Optionally, the preset time interval can be set to daily or weekly according to business needs, ensuring that the data update frequency matches the business rhythm. Preferably, the preset time interval is 24 hours, and the baseline data refresh task is automatically executed at 0:00 every day to ensure that the latest statistical results can be accessed during the next working day.

[0035] Understandably, the hierarchical incremental statistics algorithm pre-aggregates the incremental changes of each node and only performs synchronous updates between the upper and lower levels on the changed parts. Its specific algorithm framework and related execution steps are well-known to those skilled in the art and will not be elaborated here.

[0036] Combination Figure 2 As shown, optionally, the steps for statistically analyzing the changing data at each level using a hierarchical incremental statistical algorithm include: S041, Receive ticket status change information and extract the composite identifier of the level to which the change data belongs; S042, Determine the parent hierarchy chain of this level based on the hierarchy code in the composite identifier; S043 synchronously accumulates the incremental values ​​in the changed data to the incremental buffers of its own level and the level above it. In this way, the aggregated data changes at each level can be updated in a short time, ensuring that the data synchronization delay between headquarters and subsidiaries is reduced to a short time.

[0037] Optionally, when the incremental buffer reaches a preset threshold or reaches the scheduled refresh cycle, the system automatically triggers a batch update operation at the aggregation layer, merging the buffer data into the hierarchical baseline table. This mechanism effectively distributes the computational load and avoids performance spikes caused by real-time writes. Historical detailed data is automatically archived to cold storage by partition, further optimizing the efficiency of accessing hot data.

[0038] Optionally, the incremental values ​​include positive and negative numbers: positive numbers represent newly added data (such as newly added invoices or newly overdue payments), and negative numbers represent reduced data (such as invoice cancellation or recovery of overdue status). In this way, the bidirectional change in incremental values ​​accurately reflects the true state of the business, ensuring that the calculation of risk indicators at all levels is not affected by data reversals or corrections. Through a dynamic accumulation and reduction mechanism, the system achieves data consistency maintenance without interrupting service, supporting real-time statistics and traceability analysis in high-concurrency scenarios.

[0039] Optionally, the permission levels include three levels: Level 1 access only allows retrieval of invoice data within its own hierarchy; Level 2 access allows access to invoice data for itself and all its subordinate companies; The three-tiered access system allows access to invoice data at all levels. This hierarchical control of data access ensures that users at each level have access to the minimum necessary data while also meeting the needs of higher-level administrators for overall risk management. When users with different access levels initiate query or export operations, the system automatically filters the accessible datasets based on their permission level, ensuring that sensitive information is not exposed without authorization. Furthermore, all data access activities are logged, supporting post-event traceability and accountability, further strengthening the system's security and compliance.

[0040] Understandably, there is a mapping relationship between the permission level and the company level corresponding to the hierarchical code. The head office has a level 3 permission, the first-level subsidiary has a level 2 permission, and other levels of subsidiaries, such as the second-level subsidiary, have a level 1 permission.

[0041] Optionally, the hierarchical summary results include the bill balance, redemption rate, overdue rate, and proportion of high-risk commercial bills at each level. These summary results are synchronized in real-time to the group-level visualization and control platform, supporting chart-based display and anomaly alerts. This allows management to intuitively grasp the distribution and trend changes of bill risks across regions and subsidiaries, promptly identify abnormal fluctuations, and trigger risk management procedures. The summary results are refreshed every 15 minutes, and, combined with preset thresholds, automatically push alert information to relevant responsible persons, improving response efficiency. The visualization platform supports drill-down viewing of detailed data, ensuring transparent and credible decision-making basis.

[0042] Optionally, risk management methods for commercial bill payment platforms may also include: The system periodically compares the aggregated results at each level with the original data in the distributed database. If the deviation rate exceeds 0.1%, it automatically triggers baseline data re-initialization and incremental data backtracking calculation. This verification process ensures that the aggregated data is consistent with the source. Through periodic snapshot comparison and difference tracing mechanisms, the system can accurately locate data distortion points and automatically repair anomalies. This process does not affect online service operation, ensuring the accuracy and timeliness of risk indicators. The deviation rate is calculated as follows: (Amount of aggregated data at each level - Amount of original data in the distributed database) ÷ Amount of original data in the distributed database × 100%. Optionally, the enterprise data includes the bill's face value (issuer, amount, maturity date), circulation records (endorser, endorsee), and status information (unpaid, paid, overdue). This data must be stored on a blockchain before being tiered for storage to ensure its immutability. In this way, blockchain storage ensures data authenticity and integrity through a multi-node consensus mechanism. All key operations generate unique hash values ​​and are written into on-chain blocks, preventing tampering and ensuring traceability.

[0043] Optionally, when data is stored in a tiered manner, frequently accessed data is kept in a high-speed cache for real-time queries, moderately accessed data is stored in a regular database for daily analysis, and cold data is encrypted and archived in a secure storage space. Each data access and update is synchronized to the blockchain for verification, ensuring data consistency across tiers. Simultaneously, the system integrates smart contracts to automatically execute payment status changes and risk indicator calculations, improving processing efficiency and transparency.

[0044] Combination Figure 3 As shown, in some optional embodiments, the risk management method for a commercial bill redemption platform further includes: S06 generates the company's overall risk level and displays it in the company's information for all users on the platform to view.

[0045] Optionally, the enterprise's overall risk level = α (enterprise's own risk value) + β (parent company's risk value) + γ (subsidiary's risk value); where α = 0.6, β = 0.3, and γ = 0.1. The parent company has a significant impact on the risk of its subsidiaries; therefore, setting a higher weighting coefficient for the parent company's risk value can effectively reflect the company's actual risk situation. In this way, by using a dynamic weighted algorithm to comprehensively assess the risk of the enterprise and its related parties, the rating results ensure that they reflect both the creditworthiness of the entity and the overall risk transmission effect of the group. The risk level is updated hourly and is indicated on the platform using red, yellow, and green to indicate high, medium, and low risk statuses, facilitating quick identification by users. This avoids situations where the risk level of the parent company or subsidiary within the group is too high, causing cascading risks that other users may not be aware of in a short time, resulting in reduced risk management efficiency and losses for other users.

[0046] Optionally, the company's risk value is calculated based on the following: a weighted sum of multiple indicators, with the specific indicators and weights as follows: Overdue rate: (Number of overdue bills / Total number of bills) × 100% Percentage of high-risk commercial bills: (Number of high-risk commercial bills / Total number of bills) × 100% Redemption rate: (Number of redeemed bills / Number of matured bills) × 100% Historical default count: Number of bill defaults in the past 12 months.

[0047] Company risk value = (overdue rate × 40%) + (proportion of high-risk commercial bills × 30%) + ((100% - repayment rate) × 20%) + (number of historical defaults × 10%) Here, (100% - repayment rate) represents the outstanding repayment rate, ensuring consistency in the indicator's direction (a higher value indicates higher risk); historical default count × 1% is used to avoid excessive defaults leading to risk overflow (e.g., 10 defaults contributing 10% should not exceed 100% of the total risk). Optionally, the risk value quantification range and level mapping include: Quantitative range: 0-100 points (the higher the score, the higher the risk); Level mapping: Low risk: 0-30 points, indicated by green. Medium risk: 31-60 points, indicated by yellow. High risk: 61-100 points, indicated by red. When a company's risk value is in the red zone, the system automatically triggers an early warning mechanism, restricts its authority to issue bills, and notifies relevant regulators to intervene and conduct an investigation, thereby effectively preventing the accumulation and spread of systemic financial risks.

[0048] Combination Figure 4 As shown, in some optional embodiments, the risk management method for a commercial bill redemption platform further includes: S07, Obtain the enterprise credit code entered by the new user when registering on the commercial bill payment platform; S08: Based on the input credit code, obtain the group to which the new user's company belongs and its level within the group from the network, and automatically generate a level code. S01, the hierarchical code and its credit code are merged to generate a composite identifier.

[0049] In this way, multi-dimensional identification of enterprise identity and automatic aggregation of related relationships can be completed during new user registration without the need for manual settings by the user, which improves the user experience. Moreover, the accuracy and real-time nature of the hierarchical relationship provides a basic support for subsequent risk transmission analysis.

[0050] Understandably, the corporate structure information obtained from the internet originates from the National Enterprise Credit Information Publicity System or authoritative third-party data platforms, ensuring the accuracy and reliability of hierarchical relationships. The specific acquisition steps are conventional data collection methods well-known to those skilled in the art, including API calls, web scraping techniques, or data file import. These will not be elaborated upon here.

[0051] Combination Figure 5 As shown, this disclosure provides a system for risk management of a commercial bill payment platform, including a processor 100 and a memory 101. Optionally, the device may further include a communication interface 102 and a bus 103. The processor 100, communication interface 102, and memory 101 can communicate with each other via the bus 103. The communication interface 102 can be used for information transmission. The processor 100 can call logical instructions in the memory 101 to execute the risk management method for a commercial bill payment platform described in the above embodiment.

[0052] Furthermore, the logic instructions in the aforementioned memory 101 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0053] The memory 101, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this disclosure. The processor 100 executes functional applications and data processing by running the program instructions / modules stored in the memory 101, thereby implementing the risk management method for the commercial bill payment platform described in the above embodiments.

[0054] The memory 101 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 101 may include high-speed random access memory and may also include non-volatile memory.

[0055] This disclosure provides a computer-readable storage medium storing computer-executable instructions configured to execute the aforementioned risk management method for a commercial bill payment platform.

[0056] The aforementioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0057] The technical solutions of this disclosure can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this disclosure. The aforementioned storage medium can be a non-transitory storage medium, including: a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and other media capable of storing program code; it can also be a transient storage medium.

[0058] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used in this application means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0059] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0060] The methods and products disclosed in the embodiments herein (including but not limited to devices and equipment) can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to implement this embodiment according to actual needs. In addition, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0061] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A risk management method for a commercial bill payment platform, characterized in that, include: The enterprise identification code and hierarchical coding are integrated to form a composite identifier, and a group-level identification system is established. Based on a distributed database, enterprise data is stored hierarchically according to hierarchical coding. A hierarchical index tree is built for the stored data according to the hierarchical encoding. The algorithm uses a hierarchical incremental statistical method to collect data on changes at each level and automatically generates hierarchical summary results by combining the historical baseline data of each level. Users are assigned different permission levels based on hierarchical coding, and higher-level users can access the data of lower-level users.

2. The method according to claim 1, characterized in that, In the group's hierarchical identification system, the hierarchical code is 4 digits long. The first 2 digits represent the hierarchical level, and the last 2 digits represent the company order within the same level.

3. The method according to claim 1, characterized in that, The distributed database is HBase, and the hierarchical storage method is as follows: partitioning is performed according to the first two digits of the hierarchical code, and enterprise data of the same level are allocated to the same partition, and the maximum data volume of each partition is limited to 5 million to 10 million records.

4. The method according to claim 1, characterized in that, The root node of the hierarchical index tree is associated with the composite identifier of the group headquarters and the corresponding data partition address. The first-level nodes are associated with the composite identifiers of the first-level subsidiaries and the corresponding data partition addresses. Each first-level node only points to the leaf nodes of its subordinate second-level subsidiaries.

5. The method according to claim 1, characterized in that, In the hierarchical incremental statistical algorithm, the historical baseline data includes the total number of bills at each level, the number of bills already paid, the number of overdue bills, and the number of high-risk commercial bills. The historical baseline data is automatically updated once every preset time interval.

6. The method according to claim 1, characterized in that, The steps for statistically analyzing the changing data at each level using a hierarchical incremental statistical algorithm include: Receive information on changes in the status of invoices and extract the composite identifier of the level to which the changed data belongs; Based on the hierarchical code in the composite identifier, determine the parent hierarchy chain of that level; The incremental values ​​in the changing data are synchronously accumulated into the incremental buffer of the current level and the level above it.

7. The method according to claim 1, characterized in that, The access control levels include three levels: Level 1 access only allows retrieval of invoice data within its own hierarchy; Level 2 access allows access to invoice data for itself and all its subordinate companies; Level 3 access allows access to invoice data at all levels.

8. The method according to claim 1, characterized in that, The hierarchical summary results include the bill balance, redemption rate, overdue rate, and proportion of high-risk commercial bills at each level. The summary results are synchronized to the group's hierarchical visualization and management platform in real time, supporting chart-based display and anomaly warning.

9. The method according to any one of claims 1 to 8, characterized in that, Also includes: The system periodically compares the aggregated results at each level with the original data in the distributed database. If the deviation rate exceeds 0.1%, it automatically triggers the re-initialization of baseline data and the backtracking calculation of incremental data.

10. A storage medium storing program instructions, characterized in that, When the program instructions are executed, they perform the risk management method for a commercial bill payment platform as described in any one of claims 1 to 9.

Images