Top-up payment account checking abnormity detection method and device, electronic equipment and medium

Abstract

The invention relates to a recharge payment account checking anomaly detection method and device, electronic equipment and a medium, and the method comprises the steps: obtaining an account checking result of a target day, the account checking result comprising at least one payment channel and an original business rule corresponding to each payment channel; inputting the at least one payment channel into a pre-trained large model to obtain a target business rule corresponding to each payment channel; and for each payment channel, if the original business rule corresponding to the payment channel is not matched with the target business rule, judging that the account checking result corresponding to the payment channel is abnormal. According to the method, for the account checking result of the target day, the target business rule corresponding to each payment channel can be accurately determined based on the pre-trained large model, and then the original business rule corresponding to each payment channel is compared with the target business rule, so that abnormal detection of the account checking result is realized, wrong report and false report are avoided, and the user experience is improved. And higher operation efficiency and earnings are brought to operators.

Description

Technical Field

[0001] The present invention relates to the technical fields of telecommunication data processing and AI. Specifically, the present invention relates to a method, device, electronic device and medium for detecting anomalies in recharge and payment reconciliation. Background Art

[0002] With the rapid development of Internet technology, the business of the telecommunications industry has become more and more convenient and flexible. In order to improve the user experience and system stickiness, various convenient recharge and payment methods are provided for users, enabling users to conveniently complete the payment of telecommunications bills anytime and anywhere, and enhancing the user-friendliness.

[0003] The following technical defects exist in the prior art:

[0004] 1. Currently, there are a large number of recharge and payment channels, resulting in various interface protocols with each payment channel, bringing complex business logics to the system.

[0005] 2. Between each recharge and payment channel and the telecommunication core system, the processing flows are different. Each business process has many and long links, and various scenarios such as recharge and payment failures and duplicate payments emerge in an endless stream, posing a great challenge to the data consistency of the system.

[0006] 3. The business volumes of each recharge and payment channel vary greatly. Some have a large business volume on weekends, some on weekdays, and some have an irregular business volume time, etc., bringing great difficulties to the accurate alarm monitoring of the system.

[0007] 4. In view of the above situation, in order to ensure data consistency, a daily reconciliation mechanism is currently used to ensure it. However, if there is no business on the recharge and payment channel on a certain day during the reconciliation process, how to accurately determine whether there is an anomaly in the system has become a major problem. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to provide a method, device, electronic device and medium for detecting anomalies in recharge and payment reconciliation, aiming to solve at least one of the above technical problems.

[0009] In a first aspect, the technical solution of the present invention to solve the above technical problem is as follows: A method for detecting anomalies in recharge and payment reconciliation, the method includes:

[0010] Obtain the reconciliation result of the target day, where the reconciliation result includes at least one payment channel and the original business rule corresponding to each payment channel;

[0011] Input the at least one payment channel into a pre-trained large model to obtain the target business rule corresponding to each payment channel;

[0012] For each of the payment channels, if the original business rule corresponding to the payment channel does not match the target business rule, it is determined that there is an abnormality in the reconciliation result corresponding to the payment channel until the reconciliation detection result corresponding to each of the payment channels is obtained.

[0013] The beneficial effect of the present invention is that for the reconciliation result of the target date, the target business rule corresponding to each payment channel can be accurately determined based on the pre-trained large model, and then the original business rule corresponding to each payment channel is compared with the target business rule to realize the abnormal detection of the reconciliation result, avoid misreporting and false reporting, and bring higher operation efficiency and benefits to the operator.

[0014] On the basis of the above technical solution, the present invention can also be improved as follows.

[0015] Further, the reconciliation result also includes the original business processing flow corresponding to each payment channel, and the method further includes:

[0016] Input the at least one payment channel into the pre-trained large model to obtain the target business processing flow corresponding to each payment channel;

[0017] For each payment channel, if the original business processing flow corresponding to the payment channel does not match the target business processing flow, it is determined that there is an abnormality in the reconciliation result corresponding to the payment channel.

[0018] Further, when there is an abnormality in the reconciliation result corresponding to any one of the payment channels, the method further includes:

[0019] Give an alarm according to the reconciliation result with abnormality.

[0020] Further, the at least one payment channel includes at least two payment channels, and each payment channel corresponds to a recharge payment reconciliation data, and the method further includes:

[0021] Regularize the recharge payment reconciliation data corresponding to at least two payment channels according to a preset format to obtain the recharge payment reconciliation data in a unified format;

[0022] Generate a classification code for the recharge payment reconciliation data in the unified format corresponding to each payment channel;

[0023] Generate a payment record form according to the classification code corresponding to each payment channel and the recharge payment reconciliation data in the unified format corresponding to all payment channels.

[0024] Further, the method further includes:

[0025] Compare the data in the payment record form with the data in the external reconciliation file to obtain the reconciliation result corresponding to the target date.

[0026] In a second aspect, to solve the above technical problems, the present invention also provides a device for detecting abnormal reconciliation of recharge and payment, which device includes:

[0027] An acquisition module, configured to acquire the reconciliation result of the target day, where the reconciliation result includes at least one payment channel and the original business rule corresponding to each payment channel;

[0028] A target business rule determination module, configured to input the at least one payment channel into a pre-trained large model to obtain the target business rule corresponding to each payment channel;

[0029] An abnormal detection module, configured to, for each payment channel, if the original business rule corresponding to the payment channel does not match the target business rule, determine that the reconciliation result corresponding to the payment channel is abnormal until the reconciliation detection result corresponding to each payment channel is obtained.

[0030] In a third aspect, to solve the above technical problems, the present invention also provides an electronic device, which electronic device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the abnormal reconciliation detection method of the present application is implemented.

[0031] In a fourth aspect, to solve the above technical problems, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the abnormal reconciliation detection method of the present application is implemented.

[0032] Additional aspects and advantages of the present application will be given in part in the following description, and these will become apparent from the following description or be understood through the practice of the present application. Description of the Drawings

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments of the present invention.

[0034] Figure 1 A flowchart of an abnormal reconciliation detection method for recharge and payment provided by an embodiment of the present invention;

[0035] Figure 2 A flowchart of a process for obtaining recharge and payment reconciliation data based on a payment channel provided by an embodiment of the present invention;

[0036] Figure 3 A flowchart of another abnormal reconciliation detection method for recharge and payment provided by an embodiment of the present invention;

[0037] Figure 4 Schematic diagram of a recharge and payment reconciliation anomaly detection device provided by an embodiment of the present invention;

[0038] Figure 5 Schematic diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0039] The principles and features of the present invention are described below. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0040] The technical solution of the present invention and how the technical solution of the present invention solves the above technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below with reference to the accompanying drawings.

[0041] The solution provided by the embodiments of the present invention can be applied to any application scenario that needs to detect anomalies in the daily reconciliation results. The solution provided by the embodiments of the present invention can be executed by any electronic device. For example, it can be the user's terminal device, including at least one of the following: smart phone, tablet computer, laptop computer, desktop computer, smart speaker, smart watch, smart TV, smart vehicle-mounted device.

[0042] The embodiments of the present invention provide a possible implementation manner. As Figure 1 shown, a flowchart of a recharge and payment reconciliation anomaly detection method is provided. This solution can be executed by any electronic device. For example, it can be a terminal device, or jointly executed by a terminal device and a server. For the convenience of description, the method provided by the embodiments of the present invention will be described below with the terminal device as the execution subject. As Figure 1 shown in the flowchart, the method may include the following steps:

[0043] S10. Obtain the reconciliation result of the target day, where the reconciliation result includes at least one payment channel and the original business rule corresponding to each payment channel;

[0044] S20. Input the at least one payment channel into a pre-trained large model to obtain the target business rule corresponding to each payment channel;

[0045] S30. For each payment channel, if the original business rule corresponding to the payment channel does not match the target business rule, it is determined that the reconciliation result corresponding to the payment channel is abnormal until the reconciliation detection result corresponding to each payment channel is obtained.

[0046] Through the method of the present invention, for the reconciliation result of the target date, the target business rules corresponding to each payment channel can be accurately determined based on a pre-trained large model, and then the original business rules corresponding to each payment channel are compared with the target business rules to achieve anomaly detection of the reconciliation result, avoiding misreporting and false reporting, and bringing higher operation efficiency and benefits to the operator.

[0047] The following further illustrates the solution of the present invention in combination with the following specific embodiments. In this embodiment, a method for detecting abnormal recharge and payment reconciliation may include the following steps:

[0048] S10. Obtain the reconciliation result of the target date, where the reconciliation result includes at least one payment channel and the original business rules corresponding to each payment channel;

[0049] Among them, the target date refers to any day. One payment channel corresponds to one payment method. The original business rule refers to the business rule corresponding to the target date, reflecting the rule of the business volume corresponding to the real payment business on the target date. For example, the business volume is large on weekends and small on weekdays.

[0050] S20. Input the at least one payment channel into the pre-trained large model to obtain the target business rules corresponding to each payment channel;

[0051] Among them, for each payment channel, the target business rule corresponding to this payment channel represents the correct business rule of this payment channel.

[0052] The large model can be trained based on a large amount of recharge and payment historical data and business scenarios. Through this large model, the recharge and payment business rules and regulations of telecom operators can be fully learned.

[0053] The training process of the above large model may be as follows:

[0054] 1. According to the recharge and payment business scenarios in the telecom industry, select an AI large model. Based on a general large model, select a large model in the telecom industry domain.

[0055] 2. Sort out the business rules and business processing flows of various payment channels as the target business rules and target business processing flows. It is also necessary to sort out the recharge and payment reconciliation results corresponding to various payment channels as training data.

[0056] 3. Provide the historical business data (reconciliation results) of the recharge and payment channels over the years to the large model for training and learning, so that the large model can accurately identify the business rules and business processing flows of each payment channel and accurately portrait the business of each type of payment channel.

[0057] S30. For each of the payment channels, if the original business rule corresponding to the payment channel does not match the target business rule, it is determined that the reconciliation result corresponding to the payment channel is abnormal until the reconciliation detection result corresponding to each of the payment channels is obtained.

[0058] Among them, the fact that the original business rule corresponding to the payment channel does not match the target business rule means that the original business rule is different from the target business rule. For example, if the target day is a working day and the target business rule corresponding to the working day is low business volume, but the original business rule corresponding to the target day is high business volume, this situation is that the original business rule does not match the target business rule. Similarly, if the original business rule corresponding to the payment channel matches the target business rule, it is determined that the reconciliation result corresponding to the payment channel is not abnormal.

[0059] Among them, the reconciliation detection result is that the reconciliation result is abnormal or the reconciliation result is not abnormal.

[0060] Furthermore, when the reconciliation result corresponding to any one of the payment channels is abnormal, the method further includes:

[0061] According to the abnormal reconciliation result, an alarm is made. For example, if the business volume of a certain payment channel suddenly increases or decreases on the same day or does not conform to the previous business usage rule trend, a monitoring alarm is made.

[0062] Optionally, the reconciliation result further includes the original business processing flow corresponding to each of the payment channels, and the method further includes:

[0063] Input the at least one payment channel into a pre-trained large model to obtain the target business processing flow corresponding to each of the payment channels;

[0064] For each of the payment channels, if the original business processing flow corresponding to the payment channel does not match the target business processing flow, it is determined that the reconciliation result corresponding to the payment channel is abnormal.

[0065] Among them, the business processing flow corresponding to a payment channel usually does not change much. For each of the payment channels, the original business processing flow refers to the actual business processing flow corresponding to the payment channel, and the target business processing flow refers to the correct business processing flow corresponding to the payment channel. Then, when the original business processing flow corresponding to the payment channel does not match the target business processing flow, it can indicate that the reconciliation result corresponding to the payment channel is abnormal.

[0066] Similarly, when the original business processing flow corresponding to the payment channel matches the target business processing flow, it can indicate that the reconciliation result corresponding to the payment channel is not abnormal.

[0067] SeeFigure 3 , optionally, at least one of the above payment channels includes at least two payment channels, and each of the payment channels corresponds to a recharge and payment reconciliation data. The method further includes:

[0068] Regularize the recharge and payment reconciliation data corresponding to at least two of the payment channels (which may exist in the form of a reconciliation file) according to a preset format to obtain the recharge and payment reconciliation data in a unified format;

[0069] Generate a classification code for the recharge and payment reconciliation data in the unified format corresponding to each of the payment channels, and one classification code corresponds to one payment channel;

[0070] Generate a payment record form according to the classification code corresponding to each of the payment channels and the recharge and payment reconciliation data in the unified format corresponding to all the payment channels.

[0071] Among them, the processing processes between each payment channel and the telecom core system are different. There are many and long business process links, and various scenarios such as recharge and payment failures and duplicate payments emerge in an endless stream, bringing great challenges to the data consistency of the system. By recording the recharge and payment reconciliation data in the unified format corresponding to each payment channel in the payment record form, it can simplify the subsequent processing process of recharge and payment, reduce the business process links, and improve the payment success rate.

[0072] Further, the method further includes:

[0073] Compare the data in the payment record form with the external reconciliation file data to obtain the reconciliation result corresponding to the target date.

[0074] Among them, the external reconciliation file data refers to the correct recharge and payment reconciliation data, which may include the recharge and payment reconciliation data corresponding to the target date. Taking the external reconciliation file data as the standard and comparing it with the data in the payment record form, the reconciliation result corresponding to the target date can be obtained, which can also be called the recharge reconciliation result.

[0075] Further, the comparison execution strategies corresponding to different payment channels may be different. Then, for the data corresponding to each payment channel in the payment record form, based on the comparison execution strategy corresponding to the payment channel, compare the data corresponding to the payment channel with the external reconciliation file data to obtain the reconciliation result corresponding to the payment channel.

[0076] Optionally, the respective reconciliation results corresponding to the payment record form may be classified according to the payment channels. For example, the two sides are consistent, there are many channels, there are many accounts, and the recorded amounts on the two sides are inconsistent.

[0077] Optionally, in the solution of this application, Figure 2The payment system shown realizes full payment to obtain the recharge and payment reconciliation data corresponding to a payment channel on the target day. Through the payment system provided by this solution, the business processing flows corresponding to different payment channels and the interface protocols with the payment system can be unified, thereby simplifying the business logic.

[0078] Optionally, after obtaining the reconciliation result corresponding to each payment channel, the reconciliation result can also be displayed. For example, it can be displayed on the front-end interface according to the payment channel, specifically showing the reconciliation summary result and the difference details of each payment channel.

[0079] Optionally, the reconciliation results corresponding to each payment channel can also be used to generate report data in the background and push it to relevant personnel via email.

[0080] Optionally, for the reconciliation result corresponding to each said payment channel, if the reconciliation result corresponding to this payment channel is recorded in an external channel but not recorded on the accounting side, the background can automatically make up the payment. If other situations occur, the cause can be analyzed and then how to handle it can be determined.

[0081] Optionally, when adding a new payment channel (recharge reconciliation channel), it can be pre-configured in the payment system of this application.

[0082] Optionally, for abnormal data such as payment failure or duplicate payment, the abnormal data can be automatically repaired based on AI.

[0083] Through the solution of this application, the recharge and payment failure rate that users can actively perceive has dropped from one in ten thousand to 0. Achieving 100% success and accuracy of user recharge and payment.

[0084] Based on the same principle as the method shown in Figure 1 This embodiment of the present invention also provides a recharge and payment reconciliation anomaly detection device 20, as shown in Figure 4 This recharge and payment reconciliation anomaly detection device 20 may include an acquisition module 210, a target business rule determination module 220, and an anomaly detection module 230, where:

[0085] The acquisition module 210 is used to acquire the reconciliation result of the target day, and the reconciliation result includes at least one payment channel and the original business rule corresponding to each said payment channel;

[0086] The target business rule determination module 220 is used to input the at least one payment channel into a pre-trained large model to obtain the target business rule corresponding to each said payment channel;

[0087] Anomaly detection module 230 is used to, for each of the payment channels, if the original business rule corresponding to the payment channel does not match the target business rule, determine that there is an anomaly in the reconciliation result corresponding to the payment channel until the reconciliation detection result corresponding to each of the payment channels is obtained.

[0088] Optionally, the reconciliation result further includes the original business processing flow corresponding to each of the payment channels, and the anomaly detection module is further used to:

[0089] Input the at least one payment channel into a pre-trained large model to obtain the target business processing flow corresponding to each of the payment channels;

[0090] For each of the payment channels, if the original business processing flow corresponding to the payment channel does not match the target business processing flow, determine that there is an anomaly in the reconciliation result corresponding to the payment channel.

[0091] Optionally, when there is an anomaly in the reconciliation result corresponding to any one of the payment channels, the device further includes:

[0092] An alarm module for performing an alarm according to the reconciliation result with an anomaly.

[0093] Optionally, the at least one payment channel includes at least two payment channels, and each payment channel corresponds to a recharge and payment reconciliation data. The device further includes:

[0094] A payment record table generation module for:

[0095] Regularize the recharge and payment reconciliation data corresponding to at least two of the payment channels in a preset format to obtain the recharge and payment reconciliation data in a unified format;

[0096] Generate a classification code for the recharge and payment reconciliation data in the unified format corresponding to each of the payment channels;

[0097] Generate a payment record table according to the classification code corresponding to each of the payment channels and the recharge and payment reconciliation data in the unified format corresponding to all the payment channels.

[0098] Optionally, the device further includes:

[0099] A reconciliation result determination module for comparing the data in the payment record table with the external reconciliation file data to obtain the reconciliation result corresponding to the target date.

[0100] The recharge and payment reconciliation anomaly detection device according to the embodiments of the present invention can execute the recharge and payment reconciliation anomaly detection method provided by the embodiments of the present invention, and their implementation principles are similar. The actions performed by each module and unit in the recharge and payment reconciliation anomaly detection device in the embodiments of the present invention correspond to the steps in the recharge and payment reconciliation anomaly detection method in the embodiments of the present invention. For the detailed function descriptions of each module of the recharge and payment reconciliation anomaly detection device, reference can specifically be made to the descriptions in the corresponding recharge and payment reconciliation anomaly detection method shown above, and details are not described herein again.

[0101] Among them, the above-mentioned recharge and payment reconciliation anomaly detection device can be a computer program (including program code) running in a computer device. For example, the recharge and payment reconciliation anomaly detection device is an application software; this device can be used to execute the corresponding steps in the method provided by the embodiments of the present invention.

[0102] In some embodiments, the recharge and payment reconciliation anomaly detection device provided by the embodiments of the present invention can be implemented in a combination of software and hardware. As an example, the recharge and payment reconciliation anomaly detection device provided by the embodiments of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the recharge and payment reconciliation anomaly detection method provided by the embodiments of the present invention. For example, a processor in the form of a hardware decoding processor can adopt one or more application-specific integrated circuits (ASICs, Application Specific Integrated Circuits), DSPs, programmable logic devices (PLDs, Programmable Logic Devices), complex programmable logic devices (CPLDs, Complex Programmable Logic Devices), field-programmable gate arrays (FPGAs, Field-Programmable Gate Arrays) or other electronic components.

[0103] In other embodiments, the recharge and payment reconciliation anomaly detection device provided by the embodiments of the present invention can be implemented in a software manner. Figure 4 The figure shows the recharge and payment reconciliation anomaly detection device stored in the memory, which can be software in the form of a program and plug-ins, etc., and includes a series of modules, including an acquisition module 210, a target business rule determination module 220, and an anomaly detection module 230, for implementing the recharge and payment reconciliation anomaly detection method provided by the embodiments of the present invention.

[0104] The modules involved in the embodiments of the present invention can be implemented in a software manner or in a hardware manner. Among them, the name of the module does not constitute a limitation to the module itself in some cases.

[0105] Based on the same principle as the method shown in the embodiments of the present invention, embodiments of the present invention also provide an electronic device, which may include but is not limited to: a processor and a memory; the memory is used to store a computer program; the processor is used to execute the method shown in any embodiment of the present invention by calling the computer program.

[0106] In an alternative embodiment, an electronic device is provided, as Figure 5 shown Figure 5 The electronic device 4000 shown includes: a processor 4001 and a memory 4003. Among them, the processor 4001 and the memory 4003 are connected, such as connected through a bus 4002. Optionally, the electronic device 4000 may further include a transceiver 4004, and the transceiver 4004 may be used for data interaction between the electronic device and other electronic devices, such as data sending and / or data receiving, etc. It should be noted that in actual applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0107] The processor 4001 may be a CPU (Central Processing Unit, central processor), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), an ASIC (Application Specific Integrated Circuit, application-specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logic blocks, modules and circuits described in connection with the disclosure of the present invention. The processor 4001 may also be a combination that implements computing functions, such as a combination including one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0108] The bus 4002 may include a path for transmitting information between the above components. The bus 4002 may be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture, extended industry standard structure) bus, etc. The bus 4002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 only a thick line is shown in

[0109] The memory 4003 can be a ROM (Read Only Memory), or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory), or other types of dynamic storage devices that can store information and instructions. It can also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0110] The memory 4003 is used to store the application program code (computer program) for implementing the solution of the present invention and is controlled by the processor 4001 for execution. The processor 4001 is used to execute the application program code stored in the memory 4003 to implement the content shown in the foregoing method embodiments.

[0111] Among them, the electronic device can also be a terminal device. Figure 5 The electronic device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0112] The embodiments of the present invention provide a computer-readable storage medium, on which a computer program is stored. When it runs on a computer, it enables the computer to execute the corresponding content in the foregoing method embodiments.

[0113] According to another aspect of the present invention, there is also provided a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the above various implementation manners of the embodiments.

[0114] Computer program code for performing the operations of the present invention may be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0115] It should be understood that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0116] The computer-readable storage medium provided by the embodiments of the present invention may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0117] The above computer-readable storage medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to execute the method shown in the above embodiments.

[0118] The above description is only a preferred embodiment of the present invention and an explanation of the technical principles applied. Those skilled in the art should understand that the scope of disclosure involved in the present invention is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the present invention.

Claims

1. A recharge payment reconciliation anomaly detection method, characterized in that: The following steps are involved: Obtaining a reconciliation result on a target date, wherein the reconciliation result includes at least one payment channel and an original business rule corresponding to each payment channel; Inputting the at least one payment channel into the pre-trained large model to obtain the target business rules corresponding to each payment channel; For each of the payment channels, if the original business rules corresponding to the payment channel do not match the target business rules, it is determined that there is an abnormality in the reconciliation result corresponding to the payment channel, until the reconciliation detection result corresponding to each of the payment channels is obtained.

2. The method according to claim 1, characterized in that The reconciliation result also includes the original business processing flow corresponding to each payment channel, and the method further includes: Inputting the at least one payment channel into the pre-trained large model to obtain the target business processing flow corresponding to each payment channel; For each of the payment channels, if the original business processing flow corresponding to the payment channel does not match the target business processing flow, it is determined that there is an abnormality in the reconciliation result corresponding to the payment channel.

3. The method according to claim 1 or 2, characterized in that: When there is an abnormality in the reconciliation result corresponding to any of the payment channels, the method further includes: Issue an alarm based on abnormal reconciliation results.

4. The method according to claim 1, characterized in that The at least one payment channel includes at least two payment channels, each payment channel corresponds to a recharge payment reconciliation data, and the method further includes: According to a preset format, the recharge and payment reconciliation data corresponding to at least two of the payment channels are regularized to obtain recharge and payment reconciliation data in a unified format; Generate a classification code for the recharge payment reconciliation data in a unified format corresponding to each payment channel; A payment record table is generated based on the classification code corresponding to each payment channel and the recharge payment reconciliation data in a unified format corresponding to all payment channels.

5. The method according to claim 4, characterized in that The method further comprises: The data in the payment record table is compared with the data in the external reconciliation file to obtain the reconciliation result corresponding to the target date.

6. A device for detecting abnormality in recharging and payment, characterized in that: include: An acquisition module, used to acquire a reconciliation result on a target date, wherein the reconciliation result includes at least one payment channel and an original business rule corresponding to each payment channel; A target business rule determination module, used for inputting the at least one payment channel into a pre-trained large model to obtain a target business rule corresponding to each payment channel; The anomaly detection module is used to determine that there is an anomaly in the reconciliation result corresponding to each payment channel if the original business rule corresponding to the payment channel does not match the target business rule, until the reconciliation detection result corresponding to each payment channel is obtained.

7. The device according to claim 6, characterized in that The recharge and payment reconciliation data also includes the original business processing flow corresponding to each payment channel, and the anomaly detection module is also used to: Inputting the at least one payment channel into the pre-trained large model to obtain the target business processing flow corresponding to each payment channel; For each of the payment channels, if the original business processing flow corresponding to the payment channel does not match the target business processing flow, it is determined that there is an abnormality in the reconciliation result corresponding to the payment channel.

8. The device according to claim 6 or 7, characterized in that When there is an abnormality in the reconciliation result corresponding to any of the payment channels, the device further includes: The alarm module is used to issue alarms based on abnormal reconciliation results.

9. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 5 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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