Payment exception processing method and device, computer equipment and storage medium
By obtaining payment chain information and identifying exception payment nodes, and using pre-trained models to perform exception processing, the problem of inefficient payment exception handling in traditional methods is solved, and payment security is improved.
Patent Information
- Application Number
- CN202411188314.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-28
- Publication Date
- 2024-12-24
AI Technical Summary
When traditional methods deal with payment exceptions, it is difficult to accurately and effectively locate the abnormal payment node and obtain detailed abnormal node information, resulting in low processing efficiency and error-proneness.
By obtaining payment chain information, identifying abnormal payment nodes, and inputting abnormal node information into the pre-trained exception recognition model for identification, the corresponding payment processing steps are called for exception processing.
Accurate identification and handling of payment abnormalities is achieved, payment risks are reduced, and payment security is improved.
Smart Images
Figure CN119180658A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data processing technology, specifically to the field of financial technology, and in particular to a payment exception processing method, device, computer equipment and storage medium. Background Art
[0002] In the field of financial technology, especially in the field of financial business systems, with the complexity of payment systems and the surge in transaction volume, ensuring the smoothness and security of payment processes has become a key challenge. In current technology, the acquisition and analysis of payment chain information is the basis for monitoring payment anomalies. By analyzing the data of each link in the payment chain, potential payment problems can be preliminarily identified.
[0003] However, traditional methods often rely on manual review or simple rule matching when handling payment anomalies, which makes it difficult to efficiently and accurately locate abnormal payment nodes and obtain detailed abnormal node information. In addition, for identified payment anomalies, there is a lack of intelligent identification mechanisms and automated processing procedures, resulting in low processing efficiency and prone to errors. Summary of the invention
[0004] The purpose of the embodiments of the present application is to provide a payment exception processing method, apparatus, computer equipment and storage medium to solve the problem of being unable to accurately and effectively handle payment exceptions.
[0005] In order to solve the above technical problems, the present application embodiment provides a payment exception processing method, which adopts the following technical solutions:
[0006] Get payment chain information;
[0007] Acquiring payment exception information based on the payment chain information, and identifying abnormal payment nodes according to the payment exception information;
[0008] Acquire abnormal node information according to the abnormal payment node;
[0009] Inputting the abnormal node information and the payment abnormality information into a pre-trained abnormality recognition model for recognition to obtain an abnormal payment result;
[0010] The corresponding payment processing steps are called according to the abnormal payment result to perform payment exception processing.
[0011] Furthermore, the step of obtaining payment chain information specifically includes:
[0012] Acquire first request information, access the first transaction object to extract information according to the first request information, and obtain first transaction information;
[0013] Acquire second request information, access the second transaction object according to the second request information to extract information, and obtain second transaction information;
[0014] Perform a transaction record query based on the first transaction information and the second transaction information to obtain transaction record information;
[0015] Sequentially sorting the transaction record information to obtain transaction record sequence information;
[0016] Payment chain information is generated according to the first transaction information, the second transaction information, and the transaction record sequence information.
[0017] Furthermore, the step of obtaining payment exception information based on the payment chain information and identifying abnormal payment nodes according to the payment exception information specifically includes:
[0018] Verifying the payment chain information to obtain the payment exception information;
[0019] Determine the corresponding payment node according to the payment exception information;
[0020] The payment node is marked with an abnormal type and an abnormal level to obtain the abnormal payment node.
[0021] Furthermore, the step of verifying the payment chain information to obtain the payment exception information specifically includes:
[0022] Performing information integrity verification on the payment chain information to obtain valid payment chain information;
[0023] Acquire historical payment chain information, compare the valid payment chain information with the historical payment chain information, and obtain payment difference information;
[0024] The payment difference information is input into a preset exception acquisition model to obtain payment exception information.
[0025] Furthermore, the step of obtaining abnormal node information according to the abnormal payment node specifically includes:
[0026] Determine a process payment node according to the abnormal payment node;
[0027] Obtaining process node information corresponding to the process payment node;
[0028] Determine node relevance based on the abnormal payment node and the process node information;
[0029] The node association is added to the process node information to obtain the abnormal node information.
[0030] Furthermore, the step of calling a corresponding payment processing step to perform payment exception processing according to the abnormal payment result specifically includes:
[0031] Acquire processing request information, and extract an abnormal payment processing mapping table from a database according to the processing request information;
[0032] Query the abnormal payment processing mapping table according to the abnormal payment result to obtain an abnormal payment processing solution;
[0033] Extracting the payment processing steps from a database according to the abnormal payment processing scheme;
[0034] Execute the payment processing steps and generate a payment processing record and save it to a preset processing record table.
[0035] Furthermore, after the step of executing the payment processing step and generating a payment processing record and saving it in a preset processing record table, the following steps are also included:
[0036] Re-obtain processed payment chain information;
[0037] Identify whether there is a new abnormal payment node in the processed payment chain information;
[0038] If the processed payment chain information contains the new abnormal payment node, then the new abnormal node information is obtained according to the new abnormal payment node, and the new abnormal node information is input into the pre-trained abnormal recognition model for identification to obtain a new abnormal payment result, and the corresponding payment processing step is called according to the new abnormal payment result to perform payment abnormality processing, and the steps from obtaining new abnormal node information to performing payment abnormality processing are continuously repeated until the processed payment chain information does not contain the new abnormal payment node. In order to solve the above technical problems, the embodiment of the present application also provides a payment abnormality processing device, which adopts the following technical solution:
[0039] A first information acquisition module, used to acquire payment chain information;
[0040] A node identification module, used to obtain payment anomaly information based on the payment chain information, and identify abnormal payment nodes according to the payment anomaly information;
[0041] A second information acquisition module, used to acquire abnormal node information according to the abnormal payment node;
[0042] A result acquisition module, used for inputting the abnormal node information and the payment abnormality information into a pre-trained abnormality recognition model for recognition, and obtaining an abnormal payment result;
[0043] The exception handling module is used to call the corresponding payment processing steps to perform payment exception handling according to the abnormal payment result.
[0044] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:
[0045] A computer device comprises a memory and a processor, wherein the memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, the steps of the payment exception processing method as described in any one of the above items are implemented.
[0046] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:
[0047] A computer-readable storage medium having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by a processor, implement the steps of any of the above payment exception processing methods.
[0048] Compared with the prior art, the embodiment of the present application has the following beneficial effects: the embodiment obtains payment chain information; obtains payment exception information based on the payment chain information, and identifies abnormal payment nodes according to the payment exception information; obtains abnormal node information according to the abnormal payment node; inputs the abnormal node information and the payment exception information into a pre-trained abnormal recognition model for recognition to obtain an abnormal payment result; and calls the corresponding payment processing steps to process the payment exception according to the abnormal payment result. This effectively realizes the identification and processing of abnormal situations occurring during payment, so as to reduce the risk during payment and improve the security of payment. BRIEF DESCRIPTION OF THE DRAWINGS
[0049] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0050] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;
[0051] Figure 2 A flowchart of an embodiment of a payment exception processing method according to the present application;
[0052] Figure 3 yes Figure 2 A flowchart of a specific implementation of step S10;
[0053] Figure 4 yes Figure 2 A flowchart of a specific implementation of step S20;
[0054] Figure 5 yes Figure 4 A flowchart of a specific implementation of step S201;
[0055] Figure 6 yes Figure 2 A flowchart of a specific implementation of step S30;
[0056] Figure 7 yes Figure 2 A flowchart of a specific implementation of step S50;
[0057] Figure 8 It is a structural schematic diagram of an embodiment of a payment exception processing device according to the present application;
[0058] Fig. 9 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION
[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.
[0060] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor does it refer to non-related or alternative embodiments that are mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.
[0061] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.
[0062] like Figure 1As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.
[0063] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.
[0064] Terminal devices 101, 102, 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 (Moving Picture Experts Group Audio Layer IV) players, laptop computers, desktop computers, etc.
[0065] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .
[0066] It should be noted that the payment exception processing method provided in the embodiment of the present application is generally executed by a server, and accordingly, the payment exception processing device is generally set in the server.
[0067] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.
[0068] Continue to refer Figure 2 , shows a flow chart of an embodiment of a method for handling payment exceptions according to the present application. The payment exception handling method comprises the following steps:
[0069] Step S10, obtaining payment chain information;
[0070] In this embodiment, the payment chain information refers to the information included in the process from the user end to the payment system end, from the transaction payment initiated by the user end to the payment system end, and then processed, verified, and the result returned by the payment system. By obtaining the payment chain information, the global transaction can be effectively viewed to facilitate finding the abnormal part from the global transaction.
[0071] Step S20, obtaining payment exception information based on the payment chain information, and identifying abnormal payment nodes according to the payment exception information;
[0072] In this embodiment, the abnormal payment node refers to the payment process node where an abnormality occurs. The payment chain information includes several payment process nodes, such as login node, user verification node, transaction initiation node, transaction verification node, transaction return node, etc. By identifying the abnormal payment node where an abnormality occurs in the payment chain information, the abnormal part can be effectively found, providing an effective basis for subsequent abnormal situation identification.
[0073] Step S30, obtaining abnormal node information according to the abnormal payment node;
[0074] In this embodiment, abnormal node information refers to detailed information related to abnormal payment nodes, such as transaction history of the user side, account activity records, user behavior data, verification rules of the payment system side, payment response speed, etc. By obtaining abnormal node information, it is convenient for subsequent models to conduct effective analysis to comprehensively determine the cause and result of payment anomalies.
[0075] Step S40, inputting the abnormal node information and the payment abnormality information into a pre-trained abnormality recognition model for recognition to obtain an abnormal payment result;
[0076] In this embodiment, the pre-trained anomaly recognition model can adopt a logistic regression model. Logistic regression is a widely used classification algorithm. Although it is essentially a linear model, it can handle binary classification problems through the sigmoid function. In payment anomaly detection, it can be used to effectively determine whether the payment behavior corresponding to the abnormal node information belongs to the category of abnormal payment; the pre-trained model can also adopt a decision tree model. The decision tree makes decisions through a tree structure. Each internal node represents a test on an attribute, each branch represents a test output, and each leaf node represents a category. In payment anomaly detection, the judgment process can be intuitively displayed, and the nonlinear relationship between abnormal node information and abnormal payment results can be processed. The above-mentioned logistic regression model is suitable for situations where the relationship between features is relatively simple and the boundary between abnormal and normal payment behaviors is relatively clear, while the decision tree model is suitable for scenarios that require better explanation of abnormal payments. In specific implementation, the above-mentioned pre-trained model can be selected from both, or other models with feature learning and result judgment, such as neural networks or random forests, can be selected according to actual conditions to obtain better recognition results.
[0077] Step S50, calling the corresponding payment processing step to perform payment exception processing according to the abnormal payment result.
[0078] In this embodiment, the abnormal payment result refers to the judgment of abnormal payment, such as dangerous payment by user, repeated payment by user, system error processing, etc. The abnormal payment results are respectively provided with different payment processing steps for repair processing. Payment abnormality processing refers to the repair processing performed on the user side or the payment system side, including immediately blocking transactions, freezing related accounts, notifying law enforcement agencies, repairing system vulnerabilities, etc. By calling the payment processing steps corresponding to the abnormal payment results to perform payment abnormality processing, the risk during payment is effectively reduced to improve the security of payment.
[0079] This embodiment obtains payment chain information; obtains payment exception information based on the payment chain information, and identifies abnormal payment nodes according to the payment exception information; obtains abnormal node information according to the abnormal payment node; inputs the abnormal node information and the payment exception information into a pre-trained abnormal recognition model for identification to obtain an abnormal payment result; and calls the corresponding payment processing step to perform payment exception processing according to the abnormal payment result. This effectively realizes the identification and processing of abnormal situations occurring during payment, so as to reduce the risks during payment and improve the security of payment. The embodiment of the present application can be applied to payment systems in the financial industry, especially insurance payment systems, by identifying abnormal situations occurring during insurance payment and effectively adjusting and processing them accordingly, thereby reducing the risks faced by insurance payment, improving the security of insurance payment, and being beneficial to the development of the financial industry.
[0080] Continue to refer Figure 3 In some optional implementations of this embodiment, step S10 includes the following steps:
[0081] Step S101, obtaining first request information, accessing a first transaction object according to the first request information to extract information, and obtaining first transaction information;
[0082] In this embodiment, the first transaction object refers to the user terminal, which corresponds to the user's personal account, the first request information is an access request directed to the user terminal, and the first transaction information refers to the information recorded by the user terminal, which includes user account information, transaction history records, etc. In this embodiment, the user terminal refers to a user account on a certain business system, such as an insurance business system, which is generally used for insurance payment, insurance subscription, and insurance business information query on the insurance business system, and the first request information is an access request directed to the user account of the insurance business system.
[0083] Step S102, obtaining second request information, accessing the second transaction object according to the second request information to extract information, and obtaining second transaction information;
[0084] In this embodiment, the second request object refers to the business system end, which corresponds to the business system. The business system records business data for business information feedback, business handling, business processing, etc. The second transaction information refers to payment vouchers, payment records, payment business information, etc. In this embodiment, the business system end refers to a business system, such as an insurance business system, which records various insurance businesses and corresponding data, and can order insurance business or pay and renew insurance business by querying insurance business.
[0085] Step S103, querying transaction records according to the first transaction information and the second transaction information to obtain transaction record information;
[0086] In this embodiment, querying the transaction record based on the first transaction information and the second transaction information is a process of associating and corresponding the first transaction information and the second transaction information, for example, associating and corresponding the transaction history record in the first transaction information and the payment voucher, payment record, and payment business information of the second transaction information, thereby obtaining transaction record information in a logical order.
[0087] Step S104, sequentially sorting the transaction record information to obtain transaction record sequence information;
[0088] In this embodiment, the sequential combing of transaction record information is sequential combing in chronological order. The transaction record sequence information refers to the transaction record information sorted in chronological order. The transaction record sequence information may be a transaction record sequence table. In this embodiment, the transaction record information may include multiple transactions, which may be initiated simultaneously or at short intervals. The above situation may occur when the page of the business system cannot be redirected and refreshed in time due to network conditions, and transactions are repeatedly initiated. By sequentially combing the transaction record information, transaction records that conform to the chronological order are obtained.
[0089] Step S105: Generate payment chain information according to the first transaction information, the second transaction information, and the transaction record sequence information.
[0090] In this embodiment, by associating the first transaction information, the second transaction information and the transaction record information, the payment chain information of the response of the user end and the business system end to the transaction can be obtained, so as to facilitate the subsequent identification and processing of abnormal payment nodes.
[0091] In this embodiment, in addition to the first transaction object and the second transaction object, a third transaction object may also appear. If a third-party payment institution appears in the payment process, the third-party payment institution serves as the third transaction object. At this time, the third request information can be obtained, and the third transaction object can be accessed according to the third request information to extract information, and the third transaction information can be obtained. Then, the transaction record query is performed based on the first transaction information, the second transaction information and the third transaction information, so as to obtain the transaction record information.
[0092] This embodiment obtains the first transaction information by obtaining the first request information, accessing the first transaction object according to the first request information to extract information, and obtaining the first transaction information; obtains the second request information, accesses the second transaction object according to the second request information to extract information, and obtains the second transaction information; performs transaction record query according to the first transaction information and the second transaction information to obtain transaction record information; sequentially combs the transaction record information to obtain transaction record sequence information; generates payment chain information according to the first transaction information, the second transaction information, and the transaction record sequence information. In this way, the payment chain information associated with the first transaction object, the second transaction object, and the transaction record is effectively obtained to facilitate the subsequent abnormal payment node identification and processing.
[0093] Continue to refer Figure 4 In some optional implementations of this embodiment, step S20 includes the following steps:
[0094] Step S201, verifying the payment chain information to obtain the payment exception information;
[0095] In this embodiment, the verification process includes checking the integrity of the payment chain (such as checking whether there are signs of tampering), consistency (such as checking whether the transaction amount, timestamp, etc. are consistent in all relevant records), and compliance (such as checking whether the transaction complies with specific business rules or laws and regulations). If any inconsistency, violation or suspicious behavior is found during the verification process, the system will record these situations as payment exception information, which includes abnormal transaction ID, abnormal transaction amount, abnormal timestamp, payment nodes involved, etc.
[0096] Step S202, determining a corresponding payment node according to the payment exception information;
[0097] In this embodiment, the payment node may represent participants at different stages of the transaction process, such as the user side, payment system side, bank, third-party payment platform, etc. By analyzing the transaction ID, timestamp, participant identification and other information in the payment exception information, the system can track the specific payment nodes and determine the position and role of these nodes in the payment process.
[0098] Step S203, marking the payment node with an abnormal type and an abnormal level to obtain the abnormal payment node.
[0099] In this embodiment, the exception type and exception level are preset content information, such as fraudulent transactions, technical failures, network delays, etc., and the exception levels include minor, medium, severe, etc. By adding the exception type and exception level to the payment node with marking information, an abnormal payment node is obtained.
[0100] This embodiment obtains the payment exception information by verifying the payment chain information; determines the corresponding payment node according to the payment exception information; and marks the payment node with an exception type and an exception level, thereby obtaining an abnormal payment node showing the exception type and an exception level, so as to facilitate the subsequent rapid acquisition of abnormal node information according to the abnormal payment node.
[0101] Continue to refer Figure 5 In some optional implementations of this embodiment, step S201 includes the following steps:
[0102] Step S2011, verifying the integrity of the payment chain information to obtain valid payment chain information;
[0103] In this embodiment, information integrity verification is a verification step to check whether each part of the payment chain information is complete enough, and whether the association and dependency between each part are correct. For example, it can be verified whether the digital signature in the payment chain information is valid, or whether the timestamp is continuous to determine whether the payment chain information is valid information. After the information integrity verification of the payment chain information is completed, the payment chain information is saved as valid payment chain information. When it is verified that each part of the payment chain information is incomplete or the association and dependency between each part is incorrect, the payment chain information needs to be re-acquired to ensure that the information integrity of the payment chain information meets the requirements.
[0104] Step S2012, obtaining historical payment chain information, comparing the valid payment chain information with the historical payment chain information, and obtaining payment difference information;
[0105] In this embodiment, the user end corresponding to the historical payment chain information is the same as the user end corresponding to the valid payment information, which is used to characterize the user's payment operation habits. The historical payment chain information is stored in the database of the business system and can be extracted from the database through the information extraction identifier corresponding to the historical payment chain information. By comparing the valid payment chain information and the historical payment chain information in detail to compare the transaction amount, transaction time, transaction object, transaction status and other aspects, the difference points that are inconsistent with the historical payment chain are identified and used as payment difference information.
[0106] Step S2013, inputting the payment difference information into a preset exception acquisition model to obtain payment exception information.
[0107] In this embodiment, the preset anomaly acquisition model can adopt a logistic regression model, which is a widely used classification algorithm. The correspondence between payment difference information and payment anomaly information is sorted out through the logistic regression model, so that the payment anomaly information can be effectively obtained based on the payment difference information. In specific implementation, the above preset model can select other models with feature learning and result judgment according to actual conditions, such as decision trees, neural networks, random forests, etc., to obtain better recognition results.
[0108] This embodiment obtains valid payment chain information by verifying the integrity of the payment chain information; obtains historical payment chain information, compares the valid payment chain information with the historical payment chain information, and obtains payment difference information; inputs the payment difference information into a preset model, thereby effectively obtaining payment anomaly information that identifies differences based on the historical payment chain.
[0109] Continue to refer Figure 6 In some optional implementations of this embodiment, step S30 includes the following steps:
[0110] Step S301, determining a process payment node according to the abnormal payment node;
[0111] In this embodiment, the process payment node refers to a node that interacts with the abnormal payment node. For example, the previous node and the next node corresponding to the abnormal payment node in the payment chain information may be the user end, the business system end, and the third-party payment institution. The process payment node represents different stages or steps in the payment process, such as order generation, payment request, payment processing, payment confirmation, etc. After determining the process payment node, the process payment node can be recorded by adding a mark to clarify the stage at which the abnormality in the payment process occurs.
[0112] Step S302, obtaining the process node information corresponding to the process payment node;
[0113] In this embodiment, the process node information includes the node status, processing time, processing results, related data, etc. By obtaining the process node information, it is convenient to analyze the payment anomaly information occurring at the abnormal payment node later.
[0114] Step S303, determining node relevance according to the abnormal payment node and the process node information;
[0115] In this embodiment, the correlation between abnormal payment nodes and process node information can be analyzed based on data dependencies and business logic, so as to effectively determine the node correlation, so as to facilitate the subsequent understanding of how abnormal payment nodes are generated in the payment process, thereby effectively evaluating the impact of abnormal payment nodes and determining the reasons for the occurrence of abnormal payment nodes.
[0116] Step S304: adding the node association to the process node information to obtain the abnormal node information.
[0117] This embodiment determines the process payment node according to the abnormal payment node; obtains the process node information corresponding to the process payment node; determines the node association according to the abnormal payment node and the process node information; and adds the node association to the process node information, thereby effectively obtaining the abnormal node information that is associated with the abnormal payment node in the payment chain process.
[0118] Continue to refer Figure 7 In some optional implementations of this embodiment, step S50 includes the following steps:
[0119] Step S501, obtaining processing request information, and extracting an abnormal payment processing mapping table from a database according to the processing request information;
[0120] In this embodiment, the processing request information is information generated after obtaining the abnormal payment result. The information identifier contained in the processing request information corresponds to the abnormal payment processing mapping table. By setting the corresponding processing event, the processing event detects in real time whether the pre-trained model outputs the abnormal payment result. When the processing event detects that the model outputs the abnormal payment result, the processing request information is generated, and the processing request information is used to extract data from the database, so as to conveniently and quickly obtain the abnormal payment processing mapping table.
[0121] Step S502, querying the abnormal payment processing mapping table according to the abnormal payment result to obtain an abnormal payment processing solution;
[0122] In this embodiment, the abnormal payment processing mapping table includes several abnormal payment processing solutions, which are processing solutions formulated based on historical abnormal payment information. The abnormal payment processing solutions correspond to abnormal payment results one by one.
[0123] Step S503, extracting the payment processing steps from the database according to the abnormal payment processing solution;
[0124] In this embodiment, the abnormal payment processing scheme and the payment processing steps have the same information identifier. In this embodiment, in order to reduce the content byte size of the abnormal payment processing mapping table to facilitate quick extraction, the abnormal payment processing mapping table and the payment processing steps are respectively stored in the database. In the specific implementation, the payment processing steps corresponding to the abnormal payment processing scheme can also be associated and added to the abnormal payment processing mapping table to quickly and accurately execute the steps.
[0125] Step S504, execute the payment processing steps, and generate a payment processing record and save it to a preset processing record table.
[0126] In this embodiment, the payment processing record refers to the processing record of the successful or failed execution of the payment processing step. When the payment processing step fails to be effectively executed, the payment processing step that fails to be effectively executed is deemed to have failed processing. When the payment processing step is effectively executed, the payment processing step that is effectively executed is deemed to have succeeded processing. After the above-mentioned processing failure or success, a corresponding payment processing record is generated, and the payment processing record is sent to the storage location of a preset processing record table. When the preset processing record table receives the payment processing record, it will update the record table according to the payment processing record to complete the effective record of the execution of the payment processing step.
[0127] This embodiment obtains processing request information, extracts an abnormal payment processing mapping table from a database according to the processing request information; searches the abnormal payment processing mapping table according to the abnormal payment result to obtain an abnormal payment processing solution; extracts the payment processing steps from a database according to the abnormal payment processing solution; executes the payment processing steps, and generates a payment processing record and saves it in a preset processing record table. Thus, the corresponding payment processing steps are effectively executed according to the abnormal payment result to solve the payment abnormality problem.
[0128] In some optional implementations of this embodiment, after step S504, the following steps are further included:
[0129] Re-obtain processed payment chain information;
[0130] In this embodiment, a verification event can be preset to detect in real time whether the payment processing step is completed for the first time. When the payment processing step is completed for the first time, a verification request is generated, and the processed payment chain information is obtained according to the verification request. The processed payment chain information refers to the payment chain information of the next completion of the complete payment process after the payment processing step is completed for the first time.
[0131] Identify whether there is a new abnormal payment node in the processed payment chain information;
[0132] If the processed payment chain information contains the new abnormal payment node, new abnormal node information is obtained according to the new abnormal payment node, the new abnormal node information is input into the pre-trained abnormal recognition model for recognition, and a new abnormal payment result is obtained. According to the new abnormal payment result, the corresponding payment processing step is called to perform payment abnormality processing, and the steps from obtaining new abnormal node information to performing payment abnormality processing are continuously repeated until the processed payment chain information does not contain the new abnormal payment node;
[0133] If the processed payment chain information does not contain the new abnormal payment node, processing completion information is generated and sent to the processing record table for registration.
[0134] In this embodiment, the processing completion information is sent to the storage location of the preset processing record table. When the preset processing record table receives the processing completion information, the record table is updated according to the processing completion information to complete the effective record of the execution status of the verification step.
[0135] This embodiment reacquires the processed payment chain information; identifies whether there is a new abnormal payment node in the processed payment chain information; if there is the new abnormal payment node in the processed payment chain information, then acquires new abnormal node information according to the new abnormal payment node, inputs the new abnormal node information into the pre-trained model for identification, obtains a new abnormal payment result, calls the corresponding payment processing step according to the new abnormal payment result to perform payment abnormality processing, and continuously repeats the steps from acquiring new abnormal node information to performing payment abnormality processing until there is no new abnormal payment node in the processed payment chain information; if there is no new abnormal payment node in the processed payment chain information, then generates processing completion information and sends it to the processing record table for registration. This effectively completes the verification of whether the payment processing step is effective after execution, so as to improve the effectiveness of the method.
[0136] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).
[0137] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.
[0138] Further references Figure 8 , as a response to the above Figure 1 The present application provides an embodiment of a payment exception processing device, and the device embodiment is similar to Figure 1 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.
[0139] like Figure 8As shown, the payment exception processing device 600 described in this embodiment includes: a first information acquisition module 601, a node identification module 602, a second information acquisition module 603, a result acquisition module 604, and an exception processing module 605. Among them:
[0140] The first information acquisition module 601 is used to acquire payment chain information;
[0141] A node identification module 602 is used to obtain payment anomaly information based on the payment chain information, and identify abnormal payment nodes according to the payment anomaly information;
[0142] The second information acquisition module 603 is used to acquire abnormal node information according to the abnormal payment node;
[0143] A result acquisition module 604 is used to input the abnormal node information and the payment abnormality information into a pre-trained abnormality recognition model for recognition to obtain an abnormal payment result;
[0144] The exception handling module 605 is used to call the corresponding payment processing steps to perform payment exception handling according to the abnormal payment result.
[0145] This embodiment, by adopting the above-mentioned payment exception processing device, can obtain payment chain information; obtain payment exception information based on the payment chain information, and identify abnormal payment nodes according to the payment exception information; obtain abnormal node information according to the abnormal payment node; input the abnormal node information and the payment exception information into a pre-trained abnormal recognition model for identification to obtain an abnormal payment result; call the corresponding payment processing step according to the abnormal payment result to perform payment exception processing. Thereby, the abnormal situations occurring during payment can be effectively identified and processed to reduce the risks during payment and improve the security of payment. The embodiment of the present application can be applied to the payment system of the financial industry, especially the insurance payment system, by identifying the abnormal situations occurring during insurance payment and effectively adjusting and processing them accordingly, thereby reducing the risks faced by insurance payment, improving the security of insurance payment, and being beneficial to the development of the financial industry.
[0146] To solve the above technical problems, the present application also provides a computer device. Fig. 9 , Fig. 9 This is a basic structural block diagram of the computer device in this embodiment.
[0147] The computer device 7 includes a memory 71, a processor 72, and a network interface 73 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 7 with components 71-73, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.
[0148] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.
[0149] The memory 71 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 71 can be an internal storage unit of the computer device 7, such as a hard disk or memory of the computer device 7. In other embodiments, the memory 71 can also be an external storage device of the computer device 7, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. equipped on the computer device 7. Of course, the memory 71 can also include both the internal storage unit of the computer device 7 and its external storage device. In this embodiment, the memory 71 is generally used to store the operating system and various application software installed on the computer device 7, such as computer-readable instructions of the payment exception processing method, etc. In addition, the memory 71 can also be used to temporarily store various types of data that have been output or are to be output.
[0150] The processor 72 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 72 is generally used to control the overall operation of the computer device 7. In this embodiment, the processor 72 is used to run computer-readable instructions or process data stored in the memory 71, such as computer-readable instructions for running the payment exception processing method.
[0151] The network interface 73 may include a wireless network interface or a wired network interface. The network interface 73 is generally used to establish a communication connection between the computer device 7 and other electronic devices.
[0152] By adopting the above-mentioned computer equipment, this embodiment can obtain payment chain information; obtain payment exception information based on the payment chain information, and identify abnormal payment nodes according to the payment exception information; obtain abnormal node information according to the abnormal payment node; input the abnormal node information and the payment exception information into the pre-trained abnormal recognition model for identification to obtain abnormal payment results; call the corresponding payment processing steps according to the abnormal payment results to perform payment exception processing. Thereby, the abnormal situations occurring during payment can be effectively identified and processed to reduce the risks during payment and improve the security of payment. The embodiment of the present application can be applied to the payment system of the financial industry, especially the insurance payment system, by identifying the abnormal situations occurring during insurance payment and effectively adjusting and processing them accordingly, thereby reducing the risks faced by insurance payment, improving the security of insurance payment, and being beneficial to the development of the financial industry.
[0153] The present application also provides another implementation, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the payment exception processing method as described above.
[0154] This embodiment, by adopting the above-mentioned computer-readable storage medium, can obtain payment chain information; obtain payment exception information based on the payment chain information, and identify abnormal payment nodes according to the payment exception information; obtain abnormal node information according to the abnormal payment node; input the abnormal node information and the payment exception information into a pre-trained abnormal recognition model for identification to obtain an abnormal payment result; call the corresponding payment processing step according to the abnormal payment result to perform payment exception processing. Thereby, it is possible to effectively identify and process abnormal situations that occur during payment, so as to reduce the risks during payment and improve the security of payment. The embodiment of the present application can be applied to payment systems in the financial industry, especially insurance payment systems, by identifying abnormal situations generated during insurance payment, so as to effectively adjust and process them accordingly, thereby reducing the risks faced by insurance payment, improving the security of insurance payment, and being beneficial to the development of the financial industry.
[0155] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.
[0156] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.
Claims
1. A payment exception processing method, characterized in that: The steps include: Get payment chain information; Acquiring payment exception information based on the payment chain information, and identifying abnormal payment nodes according to the payment exception information; Acquire abnormal node information according to the abnormal payment node; Inputting the abnormal node information and the payment abnormality information into a pre-trained abnormality recognition model for recognition to obtain an abnormal payment result; The corresponding payment processing steps are called according to the abnormal payment result to perform payment exception processing.
2. The payment exception processing method according to claim 1, characterized in that: The step of obtaining payment chain information specifically includes: Acquire first request information, access the first transaction object to extract information according to the first request information, and obtain first transaction information; Acquire second request information, access the second transaction object according to the second request information to extract information, and obtain second transaction information; Perform a transaction record query based on the first transaction information and the second transaction information to obtain transaction record information; Sequentially sorting the transaction record information to obtain transaction record sequence information; Payment chain information is generated according to the first transaction information, the second transaction information, and the transaction record sequence information.
3. The payment exception processing method according to claim 1, characterized in that: The step of acquiring payment exception information based on the payment chain information and identifying abnormal payment nodes according to the payment exception information specifically includes: Verifying the payment chain information to obtain the payment exception information; Determine the corresponding payment node according to the payment exception information; The payment node is marked with an abnormal type and an abnormal level to obtain the abnormal payment node.
4. The payment exception processing method according to claim 3, characterized in that: The step of verifying the payment chain information to obtain the payment exception information specifically includes: Performing information integrity verification on the payment chain information to obtain valid payment chain information; Acquire historical payment chain information, compare the valid payment chain information with the historical payment chain information, and obtain payment difference information; The payment difference information is input into a preset exception acquisition model to obtain payment exception information.
5. The payment exception processing method according to claim 1, characterized in that: The step of obtaining abnormal node information according to the abnormal payment node specifically includes: Determine a process payment node according to the abnormal payment node; Obtaining process node information corresponding to the process payment node; Determine node relevance based on the abnormal payment node and the process node information; The node association is added to the process node information to obtain the abnormal node information.
6. The payment exception processing method according to claim 1, characterized in that: The step of calling the corresponding payment processing step to perform payment exception processing according to the abnormal payment result specifically includes: Acquire processing request information, and extract an abnormal payment processing mapping table from a database according to the processing request information; Query the abnormal payment processing mapping table according to the abnormal payment result to obtain an abnormal payment processing solution; Extracting the payment processing steps from a database according to the abnormal payment processing scheme; Execute the payment processing steps and generate a payment processing record and save it to a preset processing record table.
7. The payment exception processing method according to claim 6, characterized in that: After the step of executing the payment processing step and generating a payment processing record and saving it in a preset processing record table, the following steps are also included: Re-obtain processed payment chain information; Identify whether there is a new abnormal payment node in the processed payment chain information; If the processed payment chain information contains the new abnormal payment node, new abnormal node information is obtained according to the new abnormal payment node, and the new abnormal node information is input into the pre-trained abnormal recognition model for recognition to obtain a new abnormal payment result, and the corresponding payment processing steps are called according to the new abnormal payment result to perform payment exception processing, and the steps from obtaining new abnormal node information to performing payment exception processing are continuously repeated until the processed payment chain information does not contain the new abnormal payment node.
8. A payment exception processing device, characterized in that: include: A first information acquisition module, used to acquire payment chain information; A node identification module, used to obtain payment anomaly information based on the payment chain information, and identify abnormal payment nodes according to the payment anomaly information; A second information acquisition module, used to acquire abnormal node information according to the abnormal payment node; A result acquisition module, used for inputting the abnormal node information and the payment abnormality information into a pre-trained abnormality recognition model for recognition, and obtaining an abnormal payment result; The exception handling module is used to call the corresponding payment processing steps to perform payment exception handling according to the abnormal payment result.
9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the payment exception processing method as claimed in any one of claims 1 to 7 when executing the computer-readable instructions.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps of the payment exception processing method according to any one of claims 1 to 7 are implemented.