Automatic fund clearing method and device, storage medium and electronic equipment

Abstract

The invention provides an automatic fund clearing method and device, a storage medium and electronic equipment, and the method comprises the steps: monitoring the fund data transmitted by an entrusting party in real time through employing a finite-state machine, and obtaining the to-be-cleared data; according to the liquidation service information of the entrusting party, a liquidation rule is determined, grouping processing is automatically carried out on the to-be-liquidated data according to the liquidation rule, multiple liquidation batches are obtained, and one liquidation batch comprises multiple pieces of to-be-liquidated data; and determining an initial task sequence corresponding to each liquidation batch according to the liquidation scene corresponding to each liquidation batch, and processing tasks corresponding to all the initial task sequences in parallel by adopting a finite-state machine to obtain a final liquidation result. According to the method, automatic accounting can be carried out, the to-be-cleared data of the entrusting party can be grouped, the clearing task batch corresponding to the entrusting party is generated, tedious manual operation is avoided, the clearing task can be automatically processed, background business logic codes do not need to be repeatedly constructed, and the processing efficiency and accuracy are improved.

Description

Technical Field

[0001] The present application relates to the technical field of money fund settlement, and in particular to a method for automated fund clearing, an apparatus for automated fund clearing, a computer-readable storage medium, and an electronic device. Background Art

[0002] During the fund clearing process, the agent bank needs to interact with different entrusting parties and clearing parties through system interaction. However, due to the differences in the implementation of different entrusting parties, clearing parties and various financial systems, the fund clearing process cannot be fully synchronized. In addition, different entrusting parties have their own unique processes and clearing order rules, which leads to a limited proportion of system clearing automation processing, and a large number of manual confirmation and accounting steps are still required. At the same time, due to the different clearing roles of the agent bank, the operating steps of the business personnel in the clearing scenario are also different. Although the background code for clearing execution is actually the same set of business logic, the execution order of certain steps in the entire clearing process is different.

[0003] Since the fund clearing process varies among the client, clearing party and various financial institutions, and the amount of clearing funds involved is huge, the clearing scenario is very complex. Even for clearing processes with cleared business rules, business personnel still need to manually clear and group orders and check funds, making it difficult to ensure complete synchronization of the fund clearing process, resulting in a limited proportion of system clearing automation processing, which consumes a lot of time and manpower costs.

[0004] Since different entrusting parties have their own unique processes, as well as differences in clearing and order consolidation rules and business logic, once the entrusting party's needs change, a large amount of background code needs to be modified, and system iteration cannot be achieved through simple modifications, which increases the system's maintenance costs and iteration risks, and reduces the system's maintainability and scalability.

[0005] When the backend clearing step fails, the system simply echoes the error to the frontend, and the frontend business personnel locate and repair it by themselves. The system does not self-repair identifiable common anomalies, which causes business personnel to spend a lot of time locating and handling abnormal problems, increasing the time cost of clearing. This is not only not conducive to the effectiveness of fund clearing, but also affects the maintenance of the system. Summary of the invention

[0006] The main purpose of the present application is to provide a method for automated fund clearing, an apparatus for automated fund clearing, a computer-readable storage medium and an electronic device, so as to at least solve the problem in the prior art that the level of automated fund clearing is low, it is difficult to adapt to the clearing and consolidation rules of different entrusting parties and financial institutions, and the clearing scenarios that are compatible with special clearing steps.

[0007] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for automated fund clearing is provided, comprising: using a finite state machine to monitor the fund data sent by the entrusting party in real time to obtain data to be cleared; determining clearing rules based on the clearing business information of the entrusting party, and automatically grouping and processing the data to be cleared according to the clearing rules to obtain multiple clearing batches, wherein one clearing batch includes multiple data to be cleared; determining an initial task sequence corresponding to each clearing batch according to the clearing scenario corresponding to each clearing batch, and using the finite state machine to process all tasks corresponding to the initial task sequence in parallel to obtain a final clearing result.

[0008] Optionally, the finite state machine is used to process all tasks corresponding to the initial task sequence in parallel to obtain a final liquidation result, including: determining the task units corresponding to the initial task sequence and the execution order of the task units according to the initial task sequence, the initial task sequence including at least one task unit; executing the tasks in the task units in sequence according to the task units and the execution order of the task units to obtain a single batch liquidation result of the initial task sequence; when all the initial task sequences are completed, determining the set of single batch liquidation results of all the initial task sequences as the final liquidation result.

[0009] Optionally, according to the task units and the execution order of the task units, the tasks in the task units are executed in sequence to obtain a single batch clearing result of the initial task sequence, including: determining the execution status of the currently executed task of the initial task sequence, the currently executed task being the task in the task unit being executed at the current moment; according to the execution status of the currently executed task, using the finite state machine to update the initial task sequence in real time to obtain an updated task sequence, wherein the execution status of the currently executed task includes successful execution and abnormal execution; using the finite state machine to continue executing the tasks in the task unit according to the updated task sequence to obtain a single batch clearing result of the initial task sequence.

[0010] Optionally, according to the task units and the execution order of the task units, the tasks in the task units are executed in sequence to obtain a single batch clearing result of the initial task sequence, including: when the execution status of the currently executed task is successful execution, continue to execute the task corresponding to the next task unit; when the execution status of the currently executed task is an execution exception, perform an abnormal correction on the currently executed task to obtain a correction result, and when the correction result is a successful correction, continue to execute the task corresponding to the next task unit.

[0011] Optionally, when the execution status of the currently executed task is an execution exception, the currently executed task is subjected to an exception correction to obtain a correction result, including: when the execution status of the currently executed task is an execution exception, determining the cause of the exception of the currently executed task; according to the cause of the exception of the currently executed task, performing an exception correction on the currently executed task to obtain an initial correction task; repeatedly executing the initial correction task; when the initial correction task is successfully executed, determining the initial correction task as an update correction task, and determining that the correction result is a successful correction; when the initial correction task is repeatedly executed for a preset number of times and the initial correction task always fails to execute, correcting the initial correction task using a manual correction method to obtain the update correction task, and determining that the correction result is a successful correction.

[0012] Optionally, before using a finite state machine to monitor the fund data sent by the client in real time and obtaining the data to be cleared, the method includes: obtaining multiple historical business scenarios and historical clearing tasks corresponding to each of the historical business scenarios, the historical business scenarios are clearing business scenarios at historical moments, and the historical clearing tasks are historical execution tasks corresponding to the historical business scenarios and the execution order of each of the historical execution tasks; modeling is performed according to the multiple historical business scenarios and the historical clearing tasks corresponding to each of the historical business scenarios, defining an execution condition between each of the historical execution tasks corresponding to the historical clearing task, and obtaining the finite state machine.

[0013] Optionally, determining the clearing rules based on the clearing business information of the entrusting party includes: determining the user information of the entrusting party, the user information including at least the user type and user identification information; determining the clearing business scenario, the clearing business scenario including at least the required data type of the data to be cleared and the clearing target; determining the clearing rules based at least on the user information of the entrusting party and the clearing business scenario.

[0014] According to another aspect of the present application, a device for automated fund clearing is provided, comprising: a first processing unit, for using a finite state machine to monitor in real time the fund data sent by the entrusting party to obtain data to be cleared; a first determination unit, for determining clearing rules according to the clearing business information of the entrusting party, and automatically grouping and processing the data to be cleared according to the clearing rules to obtain multiple clearing batches, wherein one clearing batch includes multiple data to be cleared; a second determination unit, for determining an initial task sequence corresponding to each clearing batch according to the clearing scenario corresponding to each clearing batch, and using the finite state machine to process in parallel all tasks corresponding to the initial task sequence to obtain a final clearing result.

[0015] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods for automated fund clearing.

[0016] According to another aspect of the present application, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for executing any one of the described automated funds clearing methods.

[0017] Applying the technical solution of the present application, the above-mentioned method of automated fund clearing first uses a finite state machine to monitor the fund data sent by the entrusting party in real time to obtain the data to be cleared; then, according to the clearing business information of the entrusting party, the clearing rules are determined, and the data to be cleared is automatically grouped and processed according to the clearing rules to obtain multiple clearing batches, and one clearing batch includes multiple data to be cleared; finally, according to the clearing scenarios corresponding to each clearing batch, the initial task sequence corresponding to each clearing batch is determined, and the finite state machine is used to process the tasks corresponding to all the initial task sequences in parallel to obtain the final clearing result. This method can automatically calculate and group the data to be cleared by the entrusting party, generate the clearing task batches corresponding to the entrusting party, avoid tedious manual operations, automatically process clearing tasks, and do not need to repeatedly build background business logic code, improve processing efficiency and accuracy, and solve the problem that the level of fund clearing automation in the prior art is low, and it is difficult to adapt to the clearing and order rules of different entrusting parties and financial institutions and the clearing scenarios of compatible special clearing steps. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 A hardware structure block diagram of a mobile terminal for performing a method for automatic fund clearing provided in an embodiment of the present application is shown;

[0020] Figure 2 A schematic diagram of a flow chart of a method for automatic fund clearing provided according to an embodiment of the present application is shown;

[0021] Figure 3 A schematic diagram showing a flow chart of another method for automatic fund clearing provided according to an embodiment of the present application;

[0022] Figure 4A schematic diagram of a flow chart of an automatic processing process of a liquidation task based on a finite state machine according to an embodiment of the present application is shown;

[0023] Figure 5 A structural block diagram of a device for automatic fund clearing provided according to an embodiment of the present application is shown.

[0024] The above drawings include the following reference numerals:

[0025] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0026] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0027] 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 drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] As introduced in the background technology, in the existing technology, the clearing scenarios are very complex due to the differences in the fund clearing processes among the entrusting party, the clearing party and various financial institutions, and the huge amount of clearing funds involved; and the flexibility and scalability are insufficient, resulting in high system maintenance costs; and there is also a lack of a complete exception handling mechanism.

[0030] In order to solve the problem that the level of automation of funds clearing in the prior art is low, and it is difficult to adapt to the clearing and consolidation rules of different entrusting parties and financial institutions and the clearing scenarios with compatible special clearing steps, the embodiments of the present application provide a method for automated funds clearing, an apparatus for automated funds clearing, a computer-readable storage medium and an electronic device.

[0031] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0032] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a mobile terminal for a method for automatic fund clearing according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0033] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the method for automatic fund clearing in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned specific examples of the network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0034] In this embodiment, a method for automated fund clearing running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0035] Figure 2 Flowchart of the method for automatic fund clearing according to the embodiment of the present application. Figure 2 As shown, the method comprises the following steps:

[0036] Step S201, using a finite state machine to monitor the fund data sent by the entrusting party in real time to obtain the data to be cleared;

[0037] Specifically, the finite state machine monitors the client's pending data in real time. Once the client's pending data is obtained, the data state is updated to the pending data group state. The client may include multiple users, each of whom has different user attributes and user needs. The clearing rules are determined according to the user attributes and user needs of different users. For example, the pending data with the same user attributes are grouped together, or the pending data with the same user needs are grouped together.

[0038] Step S202, determining a clearing rule according to the clearing business information of the client, and automatically grouping the data to be cleared according to the clearing rule to obtain multiple clearing batches, wherein one clearing batch includes multiple data to be cleared;

[0039] Specifically, the clearing rules are related to business needs. The clearing rules can be to group the data to be cleared corresponding to a certain type of user attributes, or to group the data to be cleared with the same user needs. In the clearing grouping process, the data to be cleared is input into the clearing model established based on the finite state machine. According to the configured clearing parameters, the system will automatically group the clearing data according to the clearing and ordering rules corresponding to different entrusting parties, and generate the corresponding clearing and ordering grouping batch information. At the same time, the system will also initialize the task execution sequence of the clearing batch, avoiding tedious manual query and screening grouping operations. In addition, when the clearing rules of the entrusting party change, the system can flexibly adapt to the changes in the ordering rules by adjusting the configuration information, and reduce operational risks. This intelligent clearing grouping method can improve the efficiency and accuracy of clearing processing, reduce manual intervention, and bring a higher level of automation to the clearing process.

[0040] Automatically calculate and group the client's pending clearing data, generate the client's corresponding clearing task batches, and initialize the clearing task execution sequence without manual intervention by business personnel. Compared with traditional manual query and screening grouping operations, this processing method quickly and accurately completes the generation of clearing batches, avoids tedious manual operations, and improves processing efficiency and accuracy. At the same time, automated processing can also reduce the operational burden of business personnel and provide more efficient and accurate clearing services for the client.

[0041] Wherein, determining the clearing rules according to the clearing business information of the client includes the following steps:

[0042] Step S2021, determining the user information of the client, wherein the user information at least includes the user type and user identification information;

[0043] Step S2022, determining a clearing business scenario, wherein the clearing business scenario at least includes the required data type of the data to be cleared and a clearing target;

[0044] Step S2023: determining the settlement rules at least according to the user information of the entrusting party and the settlement business scenario.

[0045] Specifically, when the finite state machine detects data to be cleared, the clearing model automatically groups the client's data to be cleared according to the configured clearing parameters and generates different clearing batches, and predicts the execution sequence of clearing tasks. When the client's clearing and clearing rules or clearing parameters change, the configuration information can be flexibly adjusted to adapt to the new clearing process, without the need for business personnel to repeatedly query and filter groups.

[0046] Step S203, determining the initial task sequence corresponding to each of the liquidation batches according to the liquidation scenarios corresponding to each of the liquidation batches, and using the finite state machine to process in parallel all the tasks corresponding to the initial task sequence to obtain a final liquidation result.

[0047] Specifically, the clearing scenarios corresponding to each clearing batch in the group are determined, and the initial task sequence is determined according to the clearing scenario. During the clearing process, the clearing model automatically executes and detects the task status of each clearing group batch, and continuously corrects the next clearing step according to the execution results of the task unit until the clearing is completed. This automated clearing process further reduces the steps of manual operations and improves the efficiency and accuracy of clearing. At the same time, when the client or the clearing party proposes new business requirements or special clearing processing steps, the system can quickly iterate by supplementing the state trigger mode of the finite state machine, quickly respond to the business changes of the client, and avoid the duplication of the background business logic code. This flexible system design improves the scalability of the system, is compatible with the client's characteristic and personalized clearing business scenarios, and brings a higher level of intelligence to the clearing process of the local financial system.

[0048] Wherein, before using a finite state machine to monitor the fund data sent by the entrusting party in real time and obtaining the data to be cleared, the method includes the following steps:

[0049] Step S301, obtaining multiple historical business scenarios and historical settlement tasks corresponding to each of the historical business scenarios, wherein the historical business scenarios are settlement business scenarios at historical moments, and the historical settlement tasks are historical execution tasks corresponding to the historical business scenarios and the execution order of each of the historical execution tasks;

[0050] Step S302 , modeling is performed according to the multiple historical business scenarios and the historical settlement tasks corresponding to the historical business scenarios, defining an execution condition between the historical execution tasks corresponding to the historical settlement task, and obtaining the finite state machine.

[0051] Among them, based on the established finite state machine, the task status of the client's unfinished liquidation is monitored in real time. Among them, the finite state machine is to monitor and control the liquidation task status by modeling the liquidation business scenario and defining the transition conditions between states. The transition conditions between states are the execution conditions between the historical execution tasks corresponding to the historical liquidation tasks, for example: after the execution of task A is completed, task B is executed, and after the execution of task A fails, the abnormal recovery task is started.

[0052] The finite state machine is used to process all tasks corresponding to the initial task sequence in parallel to obtain a final settlement result, including the following steps:

[0053] Step S401, determining the task units corresponding to the initial task sequence and the execution order of the task units according to the initial task sequence, wherein the initial task sequence includes at least one task unit;

[0054] Step S402, executing the tasks in the task units in sequence according to the task units and the execution order of the task units, and obtaining a single batch clearing result of the initial task sequence;

[0055] According to the task units and the execution order of the task units, the tasks in the task units are executed in sequence to obtain a single batch clearing result of the initial task sequence, including the following steps:

[0056] Step S501, determining the execution status of the currently executed task of the initial task sequence, wherein the currently executed task is a task in the task unit being executed at the current moment;

[0057] Step S502, according to the execution status of the currently executed task, the finite state machine is used to update the initial task sequence in real time to obtain an updated task sequence, wherein the execution status of the currently executed task includes successful execution and abnormal execution;

[0058] Step S503: Using the finite state machine to continue executing the tasks in the task unit according to the updated task sequence, to obtain a single batch clearing result of the initial task sequence.

[0059] Specifically, according to the obtained liquidation task status, the liquidation task unit corresponding to the corresponding status is executed. During the execution process, the system will automatically select the appropriate liquidation task unit for processing according to the type of task unit and the specific liquidation scenario to ensure the efficient completion of the liquidation task.

[0060] The output result of the task unit execution is converted into a new liquidation task state, and the next task unit is executed according to the new state. During the state conversion process between task units, the system will automatically convert the state according to the current state and liquidation scenario, and trigger the execution of the next task unit. At the same time, the system will automatically identify and repair abnormal situations according to the execution results of the task unit to ensure the high-quality completion of the liquidation task.

[0061] For example, after task A is executed successfully, the update task sequence will be updated to "A:S", where A represents task A and S represents the successful execution of task A. At this time, task B can be continued to be executed. After task A is executed abnormally, the update task sequence will be updated to "A:G", where A represents task A and G represents that task A is not executed successfully, that is, the execution is abnormal. At this time, it is necessary to execute the abnormal correction steps of task A until task A is executed successfully, that is, the update task sequence is updated to "A:S", and then task B can be continued to be executed.

[0062] The finite state machine liquidation model detects the state changes of liquidation batches in real time based on the predicted execution sequence of liquidation tasks, automatically schedules the circulation of each liquidation task unit, and continuously modifies the next liquidation task based on the execution results of the task unit until the liquidation task is completed. In addition, when the client proposes new business needs and special liquidation scenarios, the state control mode of the supplementary state machine can be quickly iterated to expand the business scenarios and quickly respond to the client's business changes. Through this finite state machine-based approach, we can realize the automatic execution of liquidation tasks, enhance the scalability and flexibility of the system, thereby saving time and labor costs, reducing the risks of manual operations, and reducing the complexity of system maintenance.

[0063] According to the task units and the execution order of the task units, the tasks in the task units are executed in sequence to obtain a single batch clearing result of the initial task sequence, including the following steps:

[0064] Step S601, when the execution status of the currently executed task is successful, continue to execute the task corresponding to the next task unit;

[0065] Step S602, when the execution status of the currently executed task is an execution exception, the currently executed task is abnormally corrected to obtain a correction result, and when the correction result is a successful correction, the task corresponding to the next task unit is continued to be executed.

[0066] Specifically, in order to deal with abnormal situations that may occur during the liquidation process, an exception handling mechanism is set in the liquidation model, the liquidation exception status code is defined in the liquidation model, and a repair strategy for known exceptions is preset. When the liquidation task of the finite state machine liquidation model triggers an exception, the system will automatically identify the exception and enter the exception repair unit, waiting for the exception to be handled before entering the next liquidation task unit. This exception handling mechanism can quickly locate the system exceptions faced by the liquidation task and solve them in a timely manner, improving the stability and reliability of the liquidation process, and providing better protection for the automatic liquidation process of the local fiscal system.

[0067] Wherein, when the execution status of the currently executed task is an execution exception, performing an abnormal correction on the currently executed task to obtain a correction result includes the following steps:

[0068] Step S6021, when the execution status of the currently executed task is abnormal, determining the abnormal reason of the currently executed task;

[0069] Step S6022, according to the abnormal reason of the currently executed task, performing abnormal correction on the currently executed task to obtain an initial corrected task;

[0070] The initial correction task may be an automatically executed correction task. If the abnormal reason of the currently executed task is a reason that the machine cannot recover, the initial correction task may also be a manually executed correction task. If the initial correction task is a manually executed correction task and the correction is successful, the correction program is manually updated, and the abnormal reason and the correction task are edited into a program and stored, so that the machine can automatically correct the abnormal reason the next time it is encountered.

[0071] Step S6023, repeatedly executing the initial correction task;

[0072] Step S6024, when the initial correction task is successfully executed, determining the initial correction task as an updated correction task, and determining the correction result as a correction success;

[0073] Step S6025, when the initial correction task is repeatedly executed for a preset number of times and the initial correction task always fails, the initial correction task is corrected by manual correction to obtain the updated correction task, and the correction result is determined to be a successful correction.

[0074] Specifically, in the liquidation model, the liquidation exception status code is defined, and the repair strategy for known exceptions is preset. When the liquidation task of the finite state machine liquidation model triggers an exception, the system will automatically identify the exception and enter the exception repair unit, waiting for the exception to be processed before entering the next liquidation task unit. In this way, the system can quickly locate the system exceptions faced by the liquidation task and solve them in time, improve the stability and reliability of automatic liquidation processing, and ensure the smooth completion of the liquidation task.

[0075] By defining known exception status codes, presetting known exception repair strategies, and establishing an open mapping relationship, when an exception occurs during the execution of a liquidation task in a finite state machine, the liquidation model automatically identifies the exception and enters the exception repair unit, and enters the next liquidation task unit after the exception processing is completed. At the same time, the present invention enables the client to establish the mapping relationship between known exceptions, exception status codes, and exception repair strategies on its own, thereby achieving the scalability of the exception handling process and enhancing the automated processing capabilities of the liquidation model.

[0076] Step S403: when all the initial task sequences are executed, a collection of single-batch clearing results of all the initial task sequences is determined as the final clearing result.

[0077] Specifically, the clearing model monitors and processes the clearing batch process, continuously amends the next clearing step according to the execution results of the task unit, and automatically processes the clearing task. This processing method supports the state trigger mode of the fast iteration finite state machine to quickly respond to the business changes of the client without repeatedly building the background business logic code. At the same time, the system realizes the scalability of the clearing task state sequence, is compatible with characteristic and personalized clearing business scenarios, improves the efficiency of fund clearing, and reduces the pressure of system maintenance. In this way, the system can quickly adapt to the personalized needs of different clients, improve the efficiency of fund clearing, and reduce the pressure of system maintenance.

[0078] The above-mentioned method of automatic fund clearing of the present application first uses a finite state machine to monitor the fund data sent by the entrusting party in real time to obtain the data to be cleared; then, according to the clearing business information of the entrusting party, the clearing rules are determined, and the data to be cleared is automatically grouped and processed according to the clearing rules to obtain multiple clearing batches, and one clearing batch includes multiple data to be cleared; finally, according to the clearing scenarios corresponding to each clearing batch, the initial task sequence corresponding to each clearing batch is determined, and the finite state machine is used to process the tasks corresponding to all the initial task sequences in parallel to obtain the final clearing result. This method can automatically calculate and group the data to be cleared of the entrusting party, generate the clearing task batches corresponding to the entrusting party, avoid tedious manual operations, automatically process clearing tasks, and do not need to repeatedly build background business logic codes, thereby improving processing efficiency and accuracy, and solving the problems in the prior art that the level of fund clearing automation is low, and it is difficult to adapt to the clearing and order rules of different entrusting parties and financial institutions and the clearing scenarios of compatible special clearing steps.

[0079] In some instances, such as Figure 3 As shown, it includes two steps, namely, clearing batch grouping and clearing batch processing.

[0080] Among them, the first link (clearing batch grouping) mainly implements an automated clearing batch generation mechanism. This mechanism can automatically group the client's clearing data according to different clearing order rules, and obtain the clearing batch tasks and preset task execution sequences under various clearing scenarios. It specifically includes the following steps:

[0081] 1) The finite state machine monitors the client's pending data in real time. Once the client's pending data is obtained, the data status is updated to the pending data group status;

[0082] 2) Obtain the clearing parameter information corresponding to the client of the data to be cleared, parse the clearing rules, group the data to be cleared according to the order consolidation rules and generate clearing batches;

[0083] 3) Determine the liquidation scenarios corresponding to each liquidation batch in the group, and initialize the liquidation task execution sequence in sequence;

[0084] 4) After the liquidation batch is initialized, register the background database and update the liquidation task execution status so that the finite state machine can automatically process the liquidation batch.

[0085] Link 2 (liquidation batch processing) mainly realizes the automatic processing of liquidation batch tasks, concurrently monitors the sequence and task execution status of each liquidation task batch, and flows to different task events. The processing process of the liquidation model has efficient concurrent processing capabilities and a complete exception handling mechanism to ensure the timeliness and accuracy of liquidation tasks.

[0086] Among them, the automatic generation of liquidation batches and automatic processing of liquidation tasks are implemented based on finite state machines, such as Figure 4 As shown, the specific steps include:

[0087] 1) Based on the established finite state machine, the status of the unfinished liquidation tasks of the client is monitored in real time. The finite state machine is used to model the liquidation business scenario and define the transition conditions between states to achieve monitoring and control of the liquidation task status;

[0088] 2) According to the obtained liquidation task status, execute the liquidation task unit corresponding to the corresponding status. During the execution process, the system will automatically select the appropriate liquidation task unit for processing according to the type of task unit and the specific liquidation scenario to ensure the efficient completion of the liquidation task;

[0089] 3) Convert the output results of the task unit execution into a new liquidation task state, and switch to the execution of the next task unit according to the new state. During the state transition between task units, the system will automatically perform state transitions and trigger the execution of the next task unit according to the current state and liquidation scenario. At the same time, the system will automatically identify and repair abnormal situations based on the execution results of the task unit to ensure the high-quality completion of the liquidation task.

[0090] Clearing batch processing is the main link of fund clearing, involving complex interactions between the client, the clearing party and various financial institutions. In this process, the finite state machine monitors the processing status of the clearing batch tasks in real time, and converts the clearing batch task sequence according to the task status and scenario, thereby triggering the automatic execution of the next task unit. The finite state machine plays a key role in this process, covering all situations in various clearing scenarios and execution steps, and extracting common abnormal problems according to the situation, so that the abnormalities and adaptive flow of task units can be repaired by themselves during the execution of the clearing model. Through the finite state machine, the system opens up the ability to orchestrate task state sequences, so that the client can establish special processes through the execution combination and execution status of the task sequence according to the needs of its own clearing scenario, and store and maintain them, realizing the scalability of the clearing task node sequence and being compatible with special and personalized clearing business scenarios.

[0091] The above embodiment includes the following advantages:

[0092] 1) According to the clearing parameters configured by the client, the system background automatically checks and groups the clearing data, and initializes the clearing task execution sequence according to the clearing configuration information, thereby obtaining the batch clearing grouping results. Compared with the traditional manual query and screening of clearing data, this method does not require manual intervention by business personnel, can effectively optimize the clearing process, improve clearing efficiency, and reduce the burden of operation and maintenance work, providing the client with more efficient and accurate clearing services.

[0093] 2) Use the finite state machine to monitor the changes in the task status of the liquidation batch in real time, and execute the liquidation batch tasks concurrently according to the changes. After each task is executed, the system will update the liquidation task sequence, determine the task unit satisfied by the latest task status, and automatically execute the next step of the liquidation scenario. In addition, when the client proposes new business needs or special liquidation scenarios, the client can establish special processes based on the needs of its own liquidation scenarios through the execution combination and execution status of the task sequence, and store and maintain them in the library. By supplementing the state control mode of the state machine, the client can quickly iterate, expand business scenarios, and quickly respond to changes in the client's business, so as to realize the scalability of the liquidation task node sequence and be compatible with special and personalized liquidation business scenarios. This method can improve liquidation efficiency, reduce the burden of operation and maintenance, and meet the personalized needs of different clients.

[0094] 3) The clearing model defines common clearing exception status codes that may occur, and presets repair strategies for known exceptions. When the clearing task of the finite state machine clearing model triggers an exception, the system will automatically identify it and enter the exception repair unit for processing. After the processing is completed, the clearing model will continue to monitor the execution of the clearing task sequence. This mechanism can effectively handle abnormal situations in the clearing process, ensure the accuracy and stability of clearing, and improve the quality and stability of the system's automatic clearing service.

[0095] The present application embodiment also provides a device for automatic fund clearing. It should be noted that the device for automatic fund clearing of the present application embodiment can be used to execute the method for automatic fund clearing provided by the present application embodiment. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and those that have been described will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware is also possible and conceived.

[0096] The following is an introduction to the device for automated fund clearing provided in the embodiments of the present application.

[0097] Figure 5 Schematic diagram of an apparatus for automatic fund clearing according to an embodiment of the present application. Figure 5As shown, the device includes a first processing unit 10, a first determining unit 20 and a second determining unit 30. The first processing unit 10 is used to use a finite state machine to monitor the fund data sent by the entrusting party in real time to obtain the data to be cleared; the first determining unit 20 is used to determine the clearing rules according to the clearing business information of the entrusting party, and automatically group the data to be cleared according to the clearing rules to obtain multiple clearing batches, and one clearing batch includes multiple data to be cleared; the second determining unit 30 is used to determine the initial task sequence corresponding to each clearing batch according to the clearing scenario corresponding to each clearing batch, and use the finite state machine to parallelly process all the tasks corresponding to the initial task sequence to obtain the final clearing result.

[0098] The above-mentioned automatic fund clearing device of the present application includes a first processing unit, a first determining unit and a second determining unit. The first processing unit is used to first use a finite state machine to monitor the fund data sent by the entrusting party in real time to obtain the data to be cleared; the first determining unit is used to determine the clearing rules according to the clearing business information of the entrusting party, and automatically group the clearing data according to the clearing rules to obtain multiple clearing batches, and a clearing batch includes multiple data to be cleared; the second determining unit is used to determine the initial task sequence corresponding to each clearing batch according to the clearing scene corresponding to each clearing batch, and use a finite state machine to parallelly process the tasks corresponding to all the initial task sequences to obtain the final clearing result. The device can automatically calculate and group the data to be cleared of the entrusting party, generate the clearing task batch corresponding to the entrusting party, avoid tedious manual operations, automatically process clearing tasks, and do not need to repeatedly build the background business logic code, improve processing efficiency and accuracy, and solve the problem that the level of fund clearing automation in the prior art is low, it is difficult to adapt to the clearing and order rules of different entrusting parties and financial institutions, and the clearing scene of compatible special clearing steps.

[0099] In some instances, the second determination unit includes a first determination module, a first execution module, and a second determination module. The first determination module is used to determine the task units corresponding to the initial task sequence and the execution order of the task units according to the initial task sequence, and the initial task sequence includes at least one task unit; the first execution module is used to execute the tasks in the task units in sequence according to the task units and the execution order of the task units to obtain a single batch settlement result of the initial task sequence; the second determination module is used to determine the set of single batch settlement results of all the initial task sequences as the final settlement result when all the initial task sequences are completed. The scalability of the settlement task state sequence is achieved, and it is compatible with characteristic and personalized settlement business scenarios, which improves the efficiency of fund settlement and reduces the pressure of system maintenance.

[0100] In some examples, the first execution module includes a second determination module, an update module, and a second execution module, wherein the second determination module is used to determine the execution status of the currently executed task of the initial task sequence, wherein the currently executed task is the task in the task unit being executed at the current moment; the update module is used to use the finite state machine to update the initial task sequence in real time according to the execution status of the currently executed task, and obtain an updated task sequence, wherein the execution status of the currently executed task includes successful execution and abnormal execution; the second execution module is used to use the finite state machine to continue to execute the tasks in the task unit according to the updated task sequence, and obtain a single batch clearing result of the initial task sequence. The system will automatically select the appropriate clearing task unit for processing according to the type of task unit and the specific clearing scenario to ensure the efficient completion of the clearing task.

[0101] In some examples, the first execution module includes a first execution submodule and a second execution submodule. The first execution submodule is used to continue to execute the task corresponding to the next task unit when the execution status of the current execution task is successful; the second execution submodule is used to perform abnormal correction on the current execution task when the execution status of the current execution task is abnormal, obtain the correction result, and continue to execute the task corresponding to the next task unit when the correction result is successful. The system anomalies faced by the liquidation task can be quickly located and resolved in time, which improves the stability and reliability of the liquidation process and provides better protection for the automatic liquidation process of the agent local financial system.

[0102] In this embodiment, the second execution submodule includes a third determination module, a first correction module, a third execution submodule, a fourth determination module, and a second correction module. The third determination module is used to determine the abnormal cause of the current execution task when the execution state of the current execution task is abnormal execution; the first correction module is used to perform abnormal correction on the current execution task according to the abnormal cause of the current execution task to obtain an initial correction task; the third execution submodule is used to repeatedly execute the initial correction task; the fourth determination module is used to determine the initial correction task as an updated correction task when the initial correction task is successfully executed, and determine that the correction result is a successful correction; the second correction module is used to correct the initial correction task by manual correction when the initial correction task is repeatedly executed for a preset number of times and the initial correction task always fails to execute, obtain the updated correction task, and determine that the correction result is a successful correction. The system anomalies faced by the liquidation task can be quickly located and solved in time, the stability and reliability of the automatic liquidation processing are improved, and the smooth completion of the liquidation task is ensured.

[0103] An optional solution, the device includes a first acquisition module and a construction module, the first acquisition module is used to acquire multiple historical business scenarios and historical settlement tasks corresponding to each of the historical business scenarios, the historical business scenarios are settlement business scenarios at historical moments, the historical settlement tasks are historical execution tasks corresponding to the historical business scenarios and the execution order of each of the historical execution tasks; the construction module is used to model according to the multiple historical business scenarios and the historical settlement tasks corresponding to each of the historical business scenarios, define an execution condition between each of the historical execution tasks corresponding to the historical settlement task, and obtain the finite state machine. Based on the established finite state machine, the task status of the client's unfinished settlement is monitored in real time.

[0104] As an optional solution, the first determination unit includes a fifth determination module, a sixth determination module and a seventh determination module, wherein the fifth determination module is used to determine the user information of the client, wherein the user information includes at least the user type and user identification information; the sixth determination module is used to determine the clearing business scenario, wherein the clearing business scenario includes at least the required data type of the data to be cleared and the clearing target; and the seventh determination module is used to determine the clearing rules based at least on the user information of the client and the clearing business scenario. The configuration information can be flexibly adjusted to adapt to the new clearing process, without the need for business personnel to repeatedly query and filter groups.

[0105] The device for automatic fund clearing includes a processor and a memory, and the first processing unit and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions. The modules are all located in the same processor; or, the modules are located in different processors in any combination.

[0106] The processor includes a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and the kernel parameters can be adjusted to solve the problem of low automation level of fund settlement in the prior art, difficulty in adapting to the settlement rules of different entrusting parties and financial institutions, and the settlement scenarios compatible with special settlement steps.

[0107] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0108] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method for automated fund clearing.

[0109] An embodiment of the present invention provides a processor, which is used to run a program, wherein the method for automatic fund clearing is executed when the program is running.

[0110] The embodiment of the present invention provides a device, the device includes a processor, a memory, and a program stored in the memory and executable on the processor, and the processor implements at least the steps of the method for automatic fund clearing when executing the program. The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0111] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing at least the following method steps for automatic fund clearing.

[0112] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0113] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0114] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0115] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0116] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0117] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0118] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0119] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0120] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0121] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0122] 1) The above-mentioned method of automatic fund clearing of the present application first uses a finite state machine to monitor the fund data sent by the entrusting party in real time to obtain the data to be cleared; then, the clearing rules are determined according to the clearing business information of the entrusting party, and the clearing data is automatically grouped and processed according to the clearing rules to obtain multiple clearing batches, and one clearing batch includes multiple data to be cleared; finally, according to the clearing scenarios corresponding to each clearing batch, the initial task sequence corresponding to each clearing batch is determined, and the finite state machine is used to process the tasks corresponding to all the initial task sequences in parallel to obtain the final clearing result. This method can automatically calculate and group the data to be cleared by the entrusting party, generate the clearing task batches corresponding to the entrusting party, avoid tedious manual operations, automatically process clearing tasks, and do not need to repeatedly build background business logic codes, thereby improving processing efficiency and accuracy, and solving the problems in the prior art of low level of fund clearing automation, difficulty in adapting to the clearing and consolidation rules of different entrusting parties and financial institutions, and compatible clearing scenarios of special clearing steps.

[0123] 2) The above-mentioned automatic fund clearing device of the present application includes a first processing unit, a first determining unit and a second determining unit. The first processing unit is used to first use a finite state machine to monitor the fund data sent by the entrusting party in real time to obtain the data to be cleared; the first determining unit is used to determine the clearing rules according to the clearing business information of the entrusting party, and automatically group the clearing data according to the clearing rules to obtain multiple clearing batches, and a clearing batch includes multiple data to be cleared; the second determining unit is used to determine the initial task sequence corresponding to each clearing batch according to the clearing scene corresponding to each clearing batch, and use a finite state machine to parallelly process the tasks corresponding to all the initial task sequences to obtain the final clearing result. The device can automatically calculate and group the data to be cleared of the entrusting party, generate the clearing task batch corresponding to the entrusting party, avoid tedious manual operations, automatically process clearing tasks, and do not need to repeatedly build the background business logic code, improve processing efficiency and accuracy, and solve the problem of low level of fund clearing automation in the prior art, and difficulty in adapting to the clearing and order rules of different entrusting parties and financial institutions and the clearing scene of compatible special clearing steps.

[0124] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for automatic fund clearing, characterized in that: include: Use finite state machine to monitor the fund data sent by the client in real time and obtain the data to be cleared; Determine a clearing rule according to the clearing business information of the client, and automatically group the data to be cleared according to the clearing rule to obtain multiple clearing batches, wherein one clearing batch includes multiple data to be cleared; According to the liquidation scenarios corresponding to the liquidation batches, the initial task sequences corresponding to the liquidation batches are determined, and the finite state machine is used to process all the tasks corresponding to the initial task sequences in parallel to obtain a final liquidation result.

2. The method according to claim 1, characterized in that: The finite state machine is used to process all tasks corresponding to the initial task sequence in parallel to obtain a final settlement result, including: According to the initial task sequence, determining the task units corresponding to the initial task sequence and the execution order of the task units, wherein the initial task sequence includes at least one of the task units; According to the task units and the execution order of the task units, the tasks in the task units are executed in sequence to obtain a single batch clearing result of the initial task sequence; When all the initial task sequences are executed, a collection of single-batch clearing results of all the initial task sequences is determined as the final clearing result.

3. The method according to claim 2, characterized in that According to the task units and the execution order of the task units, the tasks in the task units are executed in sequence to obtain a single batch clearing result of the initial task sequence, including: Determine the execution status of the currently executed task of the initial task sequence, wherein the currently executed task is a task in the task unit being executed at the current moment; According to the execution status of the currently executed task, the initial task sequence is updated in real time using the finite state machine to obtain an updated task sequence, wherein the execution status of the currently executed task includes successful execution and abnormal execution; The finite state machine is used to continue executing the tasks in the task unit according to the updated task sequence to obtain a single batch clearing result of the initial task sequence.

4. The method according to claim 2, characterized in that: According to the task units and the execution order of the task units, the tasks in the task units are executed in sequence to obtain a single batch clearing result of the initial task sequence, including: When the execution status of the currently executed task is successful, continue to execute the task corresponding to the next task unit; When the execution status of the currently executed task is an execution exception, the currently executed task is abnormally corrected to obtain a correction result, and when the correction result is a successful correction, the task corresponding to the next task unit is continued to be executed.

5. The method according to claim 4, characterized in that When the execution state of the currently executed task is abnormal, performing abnormal correction on the currently executed task to obtain a correction result includes: When the execution status of the currently executed task is an execution exception, determining the abnormal cause of the currently executed task; According to the abnormal reason of the currently executed task, the currently executed task is abnormally corrected to obtain an initial corrected task; Repeating the initial correction task; In the case where the initial correction task is successfully executed, determining the initial correction task as an updated correction task, and determining the correction result as a successful correction; When the initial correction task is repeatedly executed for a preset number of times and the initial correction task always fails to execute, the initial correction task is corrected by manual correction to obtain the updated correction task, and the correction result is determined to be a successful correction.

6. The method according to claim 1, characterized in that Before using a finite state machine to monitor the fund data sent by the client in real time and obtaining the data to be cleared, the method includes: Acquire multiple historical business scenarios and historical clearing tasks corresponding to each of the historical business scenarios, wherein the historical business scenarios are clearing business scenarios at historical moments, and the historical clearing tasks are historical execution tasks corresponding to the historical business scenarios and the execution order of each of the historical execution tasks; Modeling is performed according to the multiple historical business scenarios and the historical settlement tasks corresponding to the historical business scenarios, and an execution condition between the historical execution tasks corresponding to the historical settlement task is defined to obtain the finite state machine.

7. The method according to any one of claims 1 to 6, characterized in that Determine the clearing rules based on the clearing business information of the client, including: Determining user information of the client, wherein the user information includes at least user type and user identification information; Determine a clearing business scenario, where the clearing business scenario at least includes the required data type of the data to be cleared and a clearing target; The clearing rule is determined at least according to the user information of the entrusting party and the clearing business scenario.

8. A device for automatic fund clearing, characterized in that: include: The first processing unit is used to use a finite state machine to monitor the fund data sent by the entrusting party in real time to obtain the data to be cleared; A first determining unit is used to determine a clearing rule according to the clearing business information of the client, and automatically group the data to be cleared according to the clearing rule to obtain a plurality of clearing batches, wherein one clearing batch includes a plurality of the data to be cleared; The second determining unit is used to determine the initial task sequence corresponding to each of the liquidation batches according to the liquidation scenarios corresponding to each of the liquidation batches, and use the finite state machine to parallelly process all the tasks corresponding to the initial task sequence to obtain a final liquidation result.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method for automated fund clearing as described in any one of claims 1 to 7.

10. An electronic device, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for executing the automated clearing of funds as described in any one of claims 1 to 7.

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