Method and device for determining optimal remittance path for batch remittance

Abstract

The present invention provides a method and device for determining an optimal remittance path for batch remittances, which can be used in the field of artificial intelligence technology. The method comprises: receiving a batch payment instruction and a remittance path preference of a customer; determining remittance information of the customer's remittance according to the batch payment instruction, wherein the remittance information comprises account information, remittance amount and remittance time; obtaining an optimal remittance path according to the remittance information through an optimal path learning library and a preset remittance path selection model. The present invention can improve the processing efficiency of remittances while ensuring that the customer's remittances are remitted through the optimal path.

Description

Technical Field

[0001] The present invention relates to the technical field of batch remittances, in particular to the technical field of artificial intelligence, and in particular to a method and device for determining an optimal remittance path for batch remittances. Background Art

[0002] At present, the inter-bank remittance of batch payment of corporate online banking transfer remittance is mainly divided into the following four steps: 1. The customer prepares a batch payment file and submits a batch payment instruction in the corporate online banking system. Among them, the customer needs to enter the remittance path in the batch file template. 2. The corporate online banking system parses the file, sorts the remittance path, and selects the inter-bank instruction. 3. The corporate online banking system selects the inter-bank instruction and sends the remittance path entered by the customer to the inter-bank system. 4. The inter-bank system remits the remittance according to the path sent by the corporate online banking. Therefore, there are currently two problems with corporate online banking batch remittances: one is that the customer may not understand the entry specifications of the remittance path, resulting in entry errors. The other is that the customer may not understand the current opening status and rules of the remittance path, resulting in the inability to remit the funds in real time after selecting the wrong path.

[0003] At present, some banks help customers choose the best remittance path based on various remittance factors. However, for batch remittances, thousands of different remittances can be submitted at one time. If the best path is selected for each customer, each instruction must be screened one by one through the inter-bank interface, which will result in slow screening and low efficiency. Summary of the invention

[0004] One object of the present invention is to provide a method for determining an optimal remittance path for batch remittances, which improves the processing efficiency of remittances while ensuring that the remittances of customers are remitted through the optimal path. Another object of the present invention is to provide an apparatus for determining an optimal remittance path for batch remittances. Another object of the present invention is to provide a computer device. Another object of the present invention is to provide a readable medium.

[0005] In order to achieve the above objectives, the present invention discloses, on one hand, a method for determining an optimal remittance path for batch remittances, comprising:

[0006] Receive customers’ batch payment instructions and remittance routing preferences;

[0007] Determine the remittance information of the customer's remittance according to the batch payment instruction, the remittance information including account information, remittance amount and remittance time;

[0008] The optimal remittance path is obtained according to the remittance information through an optimal path learning library and a preset remittance path selection model.

[0009] Preferably, the remittance path preference includes fastest speed and lowest cost.

[0010] Preferably, the method further comprises the step of predetermining the optimal path learning library:

[0011] Determine the remittance path attributes of the preset multiple remittance paths, wherein the remittance path attributes include remittance speed, opening time period, supported amount, and remittance fee corresponding to the remittance amount;

[0012] Obtain historical remittance information, historical remittance routes and remittance route preferences of historical customer batch payment instructions;

[0013] The optimal path learning library is obtained by obtaining an optimal remittance path corresponding to the remittance information and the remittance path preference according to the historical remittance path, the remittance path preference and the remittance path attribute.

[0014] Preferably, the account information includes whether the payer's account supports online banking, whether the receiving bank supports online banking, the remittance amount and the remittance time;

[0015] The optimal path learning library includes a remittance path selection table corresponding to different remittance path preferences, and the remittance path selection table includes:

[0016] When the remittance time is a working day or a non-working day, the optimal remittance path corresponding to whether the payment account supports online banking interconnection, whether the receiving bank supports online banking interconnection, and whether the remittance amount is greater than the preset threshold.

[0017] Preferably, obtaining the optimal remittance path according to the remittance information through an optimal path learning library and a preset remittance path selection model specifically includes:

[0018] Obtain the customer's historical remittance information;

[0019] Determine, based on the customer information, batch payment instructions, and remittance path preference of the customer, whether there is target historical remittance information that is the same as the batch payment instructions and remittance path preference in the historical remittance information;

[0020] If so, the remittance path of the target historical remittance information is used as the optimal remittance path. If not, the optimal remittance path is obtained through the optimal path learning library and the preset remittance path selection model.

[0021] Preferably, further comprising:

[0022] Determining whether the operation status of the optimal remittance path is normal;

[0023] If not, the priorities of all remittance paths are obtained according to the batch payment instruction, the remittance path preference and the preset remittance path selection model, and the suboptimal remittance path with the highest priority after the optimal remittance path is determined as the optimal remittance path for executing the batch payment instruction.

[0024] Preferably, further comprising:

[0025] Feedback the optimal remittance path to the user so that the user can confirm whether to use the optimal remittance path for batch payment;

[0026] Receiving a confirmation instruction from a user and executing the batch payment instruction through the optimal remittance path;

[0027] The modification instruction of the user is received to redetermine the optimal remittance path, and the batch payment instruction is executed through the redetermined optimal remittance path.

[0028] The present invention also discloses a device for determining an optimal remittance path for batch remittances, comprising:

[0029] An information receiving module is used to receive customers' batch payment instructions and remittance path preferences;

[0030] An information parsing module, used to determine the remittance information of the customer's remittance according to the batch payment instruction, wherein the remittance information includes account information, remittance amount and remittance time;

[0031] The path matching module is used to obtain the optimal remittance path according to the remittance information through the optimal path learning library and the preset remittance path selection model.

[0032] The present invention also discloses a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor.

[0033] When the processor executes the program, the method described above is implemented.

[0034] The present invention also discloses a computer readable medium having a computer program stored thereon.

[0035] When the program is executed by a processor, the method described above is implemented.

[0036] The present invention considers the batch payment instructions of the customer and the remittance path preference of the customer, determines the remittance information of the customer's remittance according to the batch payment instructions, quickly determines the optimal remittance path through the optimal path learning library based on the remittance information and the remittance path preference, and adopts a preset remittance path selection model as a supplementary optimal remittance path determination means of the optimal path learning library to obtain the optimal remittance path for batch remittances. The present invention quickly determines the optimal remittance path based on the remittance information by establishing an optimal path learning library, and organically combines it with the single remittance optimal remittance path recommendation method of the preset remittance path selection model, thereby achieving the efficiency and matching accuracy of determining the optimal remittance path during large-scale remittances, and ensuring the stability of batch remittances. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 A structural diagram showing a specific embodiment of the system for determining the optimal remittance path for batch remittances of the present invention;

[0039] Figure 2 A flow chart showing a specific embodiment of the method for determining the optimal remittance path for batch remittances of the present invention;

[0040] Figure 3 A flow chart showing a specific embodiment S000 of the method for determining the optimal remittance path for batch remittances of the present invention;

[0041] Figure 4 One of the flow charts showing a specific embodiment S300 of the method for determining the optimal remittance path for batch remittances of the present invention;

[0042] Figure 5 A second flowchart of a specific embodiment S300 of the method for determining the optimal remittance path for batch remittances of the present invention is shown;

[0043] Figure 6 A flowchart showing a specific embodiment S400 of the method for determining the optimal remittance path for batch remittances of the present invention;

[0044] Figure 7 A structural diagram showing a specific embodiment of the device for determining the optimal remittance path for batch remittances of the present invention;

[0045] Figure 8 A schematic diagram showing the structure of a computer device suitable for implementing an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] It should be noted that the method and device for determining the optimal remittance path for batch remittances disclosed in the present application can be used in the field of artificial intelligence technology, and can also be used in any field other than the field of artificial intelligence technology. The application field of the method and device for determining the optimal remittance path for batch remittances disclosed in the present application is not limited.

[0048] In order to facilitate understanding of the technical solution provided by the present application, the relevant contents of the technical solution of the present application are described below. The method for determining the optimal remittance path for batch remittances provided by the embodiment of the present invention quickly determines the optimal remittance path based on remittance information by establishing an optimal path learning library, and organically combines the optimal remittance path recommendation method for a single remittance of a preset remittance path selection model, thereby achieving the efficiency and matching accuracy of determining the optimal remittance path for large-scale remittances, and ensuring the stability of batch remittances.

[0049] Figure 1 is a schematic diagram of the structure of a system for determining an optimal remittance path for batch remittances provided by an embodiment of the present invention. Figure 1 As shown, the system for determining the optimal remittance path for batch remittances provided by the embodiment of the present invention includes a client terminal 1 and an apparatus 2 for determining the optimal remittance path for batch remittances.

[0050] The client terminal 1 may receive the batch remittance operation of the client to form a batch remittance instruction, and transmit the batch remittance instruction to the device 2 for determining the optimal remittance path for batch remittance.

[0051] The device 2 for determining the optimal remittance path for batch remittance can receive the customer's batch payment instructions and remittance path preferences, determine the remittance information of the customer's remittance according to the batch payment instructions, and the remittance information includes account information, remittance amount and remittance time, and obtain the optimal remittance path according to the remittance information through the optimal path learning library and the preset remittance path selection model.

[0052] It should be noted that the optimal remittance path determination device 2 for batch remittances can be set up separately or integrated into the corporate online banking system. Those skilled in the art can set up the optimal remittance path determination device 2 for batch remittances according to actual needs, and the present invention is not limited to this.

[0053] The following takes the optimal remittance path determination device 2 for batch remittance as an example to illustrate the implementation process of the optimal remittance path determination method for batch remittance provided by the embodiment of the present invention. It is understandable that the execution subject of the optimal remittance path determination method for batch remittance provided by the embodiment of the present invention includes but is not limited to the optimal remittance path determination device for batch remittance.

[0054] According to one aspect of the present invention, this embodiment discloses a method for determining an optimal remittance path for batch remittances. Figure 2 As shown, in this embodiment, the method includes:

[0055] S100: Receive the customer's batch payment instructions and remittance path preference.

[0056] S200: Determine the remittance information of the customer's remittance according to the batch payment instruction, wherein the remittance information includes account information, remittance amount and remittance time.

[0057] S300: Obtaining an optimal remittance path according to the remittance information through an optimal path learning library and a preset remittance path selection model.

[0058] The present invention considers the batch payment instructions of the customer and the remittance path preference of the customer, determines the remittance information of the customer's remittance according to the batch payment instructions, quickly determines the optimal remittance path through the optimal path learning library based on the remittance information and the remittance path preference, and adopts a preset remittance path selection model as a supplementary optimal remittance path determination means of the optimal path learning library to obtain the optimal remittance path for batch remittances. The present invention quickly determines the optimal remittance path based on the remittance information by establishing an optimal path learning library, and organically combines it with the single remittance optimal remittance path recommendation method of the preset remittance path selection model, thereby achieving the efficiency and matching accuracy of determining the optimal remittance path during large-scale remittances, and ensuring the stability of batch remittances.

[0059] In a preferred embodiment, the remittance path preference includes the fastest speed and the lowest cost. Specifically, based on different remittance information such as remittance time and amount, customers have different requirements for batch remittances. Therefore, in this preferred embodiment, according to the customer's possible requirements for batch remittances, two remittance path preferences of the fastest speed and the lowest cost are preset, so that users can choose different remittance path preferences according to the security, timeliness and cost requirements of batch remittances. Therefore, the optimal remittance path determination device for batch remittances can select the corresponding optimal remittance path according to the user's remittance path preference.

[0060] In a preferred embodiment, Figure 3 As shown, the method further includes a step S000 of predetermining the optimal path learning library:

[0061] S010: Determine remittance path attributes of preset multiple remittance paths, where the remittance path attributes include remittance speed, opening time period, supported amount, and remittance fee corresponding to the remittance amount.

[0062] S020: Obtain historical remittance information, historical remittance routes and remittance route preferences of historical customer batch payment instructions.

[0063] S030: Obtaining the optimal remittance path corresponding to the remittance information and the remittance path preference according to the historical remittance path, the remittance path preference and the remittance path attribute to obtain the optimal path learning library.

[0064] Specifically, based on the habits and preferences in the customer's historical remittance information, an optimal path learning library can be established to store the optimal remittance paths corresponding to different remittance information, so as to quickly determine the corresponding optimal remittance path based on the user's remittance information and remittance path preferences.

[0065] In the preferred embodiment, the remittance path attributes of the various remittance paths that can be supported by the bank's interbank system are first determined, and the remittance path attributes at least include remittance speed, opening time period, and remittance fee corresponding to the opening time period. Then, a large number of historical remittance information, historical remittance paths, and remittance path preferences corresponding to batch payment instructions of historical customers are obtained, and the optimal path learning library is obtained by matching the remittance path preferences, historical remittance information, and historical remittance paths selected or finally remitted by a large number of customers with different remittance path attributes.

[0066] For example, in a specific example, a plurality of remittance paths are preset, including expedited interbank large-amount system remittance, ordinary interbank small-amount system remittance, and interbank quick remittance, that is, remittance by online banking interconnection system. In this specific example, the number 1 represents expedited interbank large-amount system remittance, the number 0 represents ordinary interbank small-amount system remittance, and the number 3 represents interbank quick remittance, that is, remittance by online banking interconnection system. In actual application, customers need to submit the numbers corresponding to the selected remittance paths on the corporate online banking, and if the customers are not familiar with the numbers corresponding to the various remittance paths, they are likely to fill in the numbers incorrectly, resulting in the failure of the customer's batch remittance. The present invention can quickly match the optimal remittance path corresponding to the remittance information by setting the optimal path learning library.

[0067] Among them, the expedited inter-bank large-amount system remittance supports both large-amount remittances of more than 1 million yuan and small-amount remittances. The opening time period is: the system is open during working hours and closed during non-working hours. The remittance fee corresponding to the remittance amount is: the fee is divided according to the remittance amount range, the fee for less than 10,000 yuan is 6 yuan, 10,000 to 100,000 yuan is 12 yuan, 100,000 to 500,000 yuan is 18 yuan, 500,000 to 1 million yuan is 24 yuan, and the fee rate for more than 1 million yuan is 0.0024%, with an upper limit of 200 yuan. The remittance speed is between the ordinary inter-bank small-amount system remittance and the inter-bank fast remittance and online banking interconnection system remittance.

[0068] The opening time period of ordinary instant interbank small amount system remittance is: divided into two states according to the transaction time: the upper limit of 1 million on weekdays and no upper limit on weekend scenarios. The remittance fee corresponding to the remittance amount is: its fee is the lowest among the three. According to the amount range, the fee is 5 yuan for less than 10,000, 10 yuan for 10,000 to 100,000, 15 yuan for 100,000 to 500,000, 20 yuan for 500,000 to 1 million, and the fee rate for more than 1 million is 0.002%, with an upper limit of 200 yuan. The remittance speed is the lowest among the three: expedited instant interbank large amount system remittance, ordinary instant interbank small amount system remittance and interbank fast remittance instant online banking interconnection system remittance.

[0069] The amount supported by inter-bank quick remittance via online banking interconnection system is: only remittances below 1 million yuan are supported, and some account types and banks do not support this remittance method. The opening time is: the system is open 7×24 hours. The remittance fee corresponding to the remittance amount is the same as that of the expedited inter-bank large-amount system remittance. The remittance speed is the fastest among the expedited inter-bank large-amount system remittance, the ordinary inter-bank small-amount system remittance and the inter-bank quick remittance via online banking interconnection system remittance.

[0070] In the historical batch remittance, the customer fills in the batch remittance file and submits the batch remittance instruction. The customer selects the remittance path preference, including the fastest speed and the lowest cost. Further, the batch remittance instructions submitted by the customer can be parsed, and the remittance path can be sorted to screen out the inter-bank instructions. According to the remittance path preference selected by the customer and the preset remittance path selection model, the current optimal path is screened and sent to the inter-bank system. Among them, the preset remittance path selection model first sorts the remittance path priority according to the customer's remittance path preference, and screens the remittance paths from high to low priority one by one according to whether the payer account of the remittance supports online banking interconnection, whether the receiving bank supports online banking interconnection, the remittance amount, the remittance time, and the current remittance path operation status, and finally selects the current optimal remittance path. The inter-bank system remits the instructions in real time according to the optimal remittance path selected by the remittance path selection model. Then, according to the historical remittance path, remittance path preference, remittance path attribute and remittance information of a large number of successful batch remittance instructions, continuous learning and training can be carried out to form a remittance path set to obtain the optimal path learning library.

[0071] In a preferred embodiment, the account information includes whether the payer's account supports online banking, whether the receiving bank supports online banking, the remittance amount and the remittance time.

[0072] The optimal path learning library includes a remittance path selection table corresponding to different remittance path preferences, and the remittance path selection table includes: when the remittance time is a working day and a non-working day, whether the payment account supports online banking interconnection, whether the receiving bank supports online banking interconnection, and whether the remittance amount is greater than a preset threshold, the corresponding optimal remittance path.

[0073] Specifically, for the above specific example, the optimal path selection library obtained through learning and training may include two remittance path selection tables in Table 1 and Table 2. Among them, Table 1 shows the correspondence between the remittance path attributes and remittance information and the optimal remittance path when the customer's remittance path preference is the fastest speed. Table 2 shows the correspondence between the remittance path attributes and remittance information and the optimal remittance path when the customer's remittance path preference is the lowest cost. Among them, in this specific example, the preset threshold is 1 million. Thus, after obtaining the remittance information of the customer's remittance through the customer's batch payment instruction, the optimal remittance path can be directly found from the corresponding remittance path selection table in combination with the remittance information and the remittance path preference. Tables 1 and 2 respectively show the optimal path learning library obtained by learning and training for this specific example.

[0074] Table 1 fastest

[0075]

[0076] Table 2 Lowest cost

[0077]

[0078]

[0079] For example, in a specific example, a customer fills in a batch remittance file and submits a batch remittance instruction. The customer selects a remittance path preference, including the fastest time and the lowest cost. Further, the batch remittance instructions submitted by the customer can be parsed, and the remittance path can be sorted to filter out inter-bank instructions. According to the customer's selection preferences, payment account, receiving bank, remittance amount, and remittance time, the inter-bank instructions are matched with the learning library remittance path, and the optimal remittance path obtained by matching is selected. Example 1: Assume that a customer remits RMB 100,000 to CCB using a current account, the payer's account type and the receiving bank both support online banking interconnection, and the remittance amount is less than RMB 1 million. If the customer prefers the fastest remittance speed, the path matching result is online banking interconnection; if the customer prefers the lowest handling fee, the path matching result is inter-bank small amount. At this time, the matching result is consistent whether the transaction time is a working day or a non-working day. Example 2: Assume that a customer remits RMB 1.7 million to BOC using an Anxin account, the payer's account type does not support online banking interconnection, and the remittance amount is greater than RMB 1 million. If the transaction time is during working hours, the large amount system is open and the small amount system has an upper limit of 1 million, the path matching result is inter-bank large amount; if the transaction time is a non-working day, the large amount system is closed and the small amount system has no upper limit, the path matching result is inter-bank small amount. In this case, the customer chooses the fastest speed or the lowest cost, and the matching result is consistent.

[0080] In a preferred embodiment, Figure 4 As shown, the step S300 obtains the optimal remittance path according to the remittance information through the optimal path learning library and the preset remittance path selection model, specifically including:

[0081] S310: Obtain the historical remittance information of the customer;

[0082] S320: Determine whether there is target historical remittance information that is the same as the batch payment instruction and the remittance path preference in the historical remittance information according to the customer information, the batch payment instruction and the remittance path preference of the customer;

[0083] S330: If yes, the remittance path of the target historical remittance information is used as the optimal remittance path; if no, the optimal remittance path is obtained through an optimal path learning library and a preset remittance path selection model.

[0084] Specifically, in this preferred embodiment, in order to further improve the efficiency of determining the optimal remittance path, after obtaining the remittance information according to the customer's batch payment instruction, the customer's historical remittance information can be obtained. The customer's historical remittance information is analyzed to determine whether there is a target historical remittance information in the customer's historical remittance information that is the same as the remittance information of the current batch remittance. If there is a target historical remittance information that is exactly the same as the current batch remittance, the corresponding remittance path can be directly extracted from the target historical remittance information as the optimal remittance path. Thus, in the batch remittance scenario, the customer is likely to submit a series of identical batch payment instructions, and the remittance path previously selected or finally remitted by the customer can be directly remitted as the optimal remittance path, avoiding the problem of low efficiency in determining the optimal remittance path for each batch payment instruction for a large number of identical batch payment instructions.

[0085] In a preferred embodiment, Figure 5 As shown, the S300 further includes:

[0086] S340: Determine whether the operation status of the optimal remittance path is normal.

[0087] S350: If not, obtain the priorities of all remittance paths according to the batch payment instruction, the remittance path preference and the preset remittance path selection model, and determine the suboptimal remittance path with the highest priority after the optimal remittance path as the optimal remittance path for executing the batch payment instruction.

[0088] Specifically, it can be understood that after the optimal remittance path is obtained through the optimal path learning library, the optimal remittance path may be in an unavailable state. Therefore, in this preferred embodiment, the operating state of the optimal remittance path obtained through the optimal path learning library can be determined. When the operating state of the optimal remittance path is abnormal, the optimal remittance path can be further re-determined according to the preset remittance path selection model. Among them, the preset remittance path selection model can prioritize all preset remittance paths according to the remittance information and the remittance path preference, and screen the remittance paths in order from high to low priority, and exclude the optimal remittance path with abnormal current operating state. The other highest priority remittance paths are used as the re-determined optimal remittance paths. Thus, in this preferred embodiment, while improving the recommendation efficiency of the optimal remittance path, the reliability of the optimal remittance path recommended to the customer is also taken into account, ensuring that the optimal remittance path recommended to the customer is available, and achieving the purpose of improving the efficiency and performance of the optimal remittance path recommendation.

[0089] For example, in a specific example, a customer fills out a batch remittance file and submits a batch remittance instruction. The customer selects a remittance path preference, including the fastest time and the lowest cost. Further, the batch remittance instructions submitted by the customer can be parsed, and the remittance paths can be sorted to filter out inter-bank instructions. The current optimal remittance path is filtered out based on the remittance path preference selected by the customer and the preset remittance path selection model. Check the operating status of the current optimal remittance path, and if it is normal, send the remittance information to the inter-bank system for remittance. If the current optimal remittance path is abnormal, the preset remittance path selection model is used to select the suboptimal remittance path and send it to the inter-bank system. The inter-bank system remits the remittance in real time according to the suboptimal remittance path sent, and sends the remittance path result back to the learning library.

[0090] In a preferred embodiment, Figure 6 As shown, the method further includes S400:

[0091] S410: Feedback the optimal remittance path to the user so that the user can confirm whether to use the optimal remittance path for batch payment.

[0092] S420: Receive the user's confirmation instruction and execute the batch payment instruction through the optimal remittance path.

[0093] S430: receiving a modification instruction from the user to redetermine the optimal remittance path, and executing the batch payment instruction through the redetermined optimal remittance path.

[0094] Specifically, in order to increase the accuracy and flexibility of the optimal remittance path recommendation, in this preferred embodiment, the optimal remittance path obtained through the optimal path learning library and the preset remittance path selection model can be fed back to the customer, so that the customer can modify and confirm the optimal remittance path. If the customer thinks that the current optimal remittance path is suitable, the remittance can be directly confirmed through the confirmation instruction to make a remittance through the current optimal remittance path. If the customer wishes to remit money through other remittance paths, the optimal remittance path can be modified through the modification instruction. Further, the optimal remittance path and remittance information modified by the customer can be recorded to obtain historical remittance information, and the optimal path learning library can be further trained through the historical remittance information, and the accuracy of the optimal remittance path recommendation of the optimal path learning library can be improved through continuous learning and training.

[0095] In summary, the present invention takes into full account the personalized needs of customers for timeliness and costs according to the selection conditions such as payment account type, receiving bank, and amount range previously input by customers, and gives priority to pre-screening the available optimal remittance path for customers in the remittance path learning library, and then ensures the matching of the optimal remittance path through the preset remittance path selection model. This patent effectively alleviates the processing pressure of matching the optimal path for large-scale transfer remittances, solves the performance problem of batch payment being difficult to load intelligent routing remittance methods, and ensures the smooth operation of the remittance system; at the same time, it simplifies the operating steps for customers to manually input multiple batch remittance information, greatly improving the remittance efficiency and user experience of customers.

[0096] Based on the same principle, this embodiment also discloses a device for determining the optimal remittance path for batch remittances. Figure 7 As shown, in this embodiment, the device includes an information receiving module 11, an information parsing module 12 and a path matching module 13.

[0097] The information receiving module 11 is used to receive the batch payment instructions and remittance path preferences of the customers.

[0098] The information analysis module 12 is used to determine the remittance information of the customer's remittance according to the batch payment instruction, and the remittance information includes account information, remittance amount and remittance time.

[0099] The path matching module 13 is used to obtain the optimal remittance path according to the remittance information through the optimal path learning library and the preset remittance path selection model.

[0100] The present invention considers the batch payment instructions of the customer and the remittance path preference of the customer, determines the remittance information of the customer's remittance according to the batch payment instructions, quickly determines the optimal remittance path through the optimal path learning library based on the remittance information and the remittance path preference, and adopts a preset remittance path selection model as a supplementary optimal remittance path determination means of the optimal path learning library to obtain the optimal remittance path for batch remittances. The present invention quickly determines the optimal remittance path based on the remittance information by establishing an optimal path learning library, and organically combines it with the single remittance optimal remittance path recommendation method of the preset remittance path selection model, thereby achieving the efficiency and matching accuracy of determining the optimal remittance path during large-scale remittances, and ensuring the stability of batch remittances.

[0101] Since the principle of solving the problem by the device is similar to that of the above method, the implementation of the device can refer to the implementation of the method and will not be repeated here.

[0102] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer device, and specifically, the computer device may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0103] In a typical example, the computer device specifically includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method executed by the client as described above is implemented; or, when the processor executes the program, the method executed by the server as described above is implemented.

[0104] Reference below Figure 8 , which shows a schematic diagram of the structure of a computer device 600 suitable for implementing an embodiment of the present application.

[0105] like Figure 8 As shown, the computer device 600 includes a central processing unit (CPU) 601, which can perform various appropriate operations and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 to a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The CPU 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0106] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal feedback device (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 606 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed as needed as the storage section 608.

[0107] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program tangibly contained on a machine-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 609, and / or installed from the removable medium 611.

[0108] 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, magnetic tape magnetic 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.

[0109] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0110] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks 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 produce 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.

[0111] 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 including 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.

[0112] 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 A step that specifies a function in one or more boxes.

[0113] 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.

[0114] 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 on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0115] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0116] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0117] The above is only an 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 changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for determining the optimal remittance path for batch remittance, characterized in that: include: Receive batch payment instructions and remittance path preferences from customers, wherein the remittance path preferences include fastest speed and lowest cost; Determine the remittance information of the customer's remittance according to the batch payment instruction, the remittance information including account information, remittance amount and remittance time; The optimal remittance path is obtained according to the remittance information through the optimal path learning library and the preset remittance path selection model, wherein the optimal path learning library includes a remittance path selection table when the customer's remittance path preference is the fastest speed and a remittance path selection table when the customer's remittance path preference is the lowest cost; after the remittance information of the customer's remittance is obtained through the customer's batch payment instruction, the optimal remittance path can be directly found from the corresponding remittance path selection table in combination with the remittance information and the remittance path preference; Among them, the preset remittance path selection model first sorts the remittance path priority according to the customer's remittance path preference, and screens the remittance paths from high to low priority one by one according to whether the payer's account of the remittance supports online banking interconnection, whether the receiving bank supports online banking interconnection, the remittance amount, the remittance time and the current remittance path operation status, and finally selects the optimal remittance path.

2. The method for determining the optimal remittance path for batch remittance according to claim 1, characterized in that: The method further comprises the step of predetermining the optimal path learning library: Determine the remittance path attributes of the preset multiple remittance paths, wherein the remittance path attributes include remittance speed, opening time period, supported amount, and remittance fee corresponding to the remittance amount; Obtain historical remittance information, historical remittance routes and remittance route preferences of historical customer batch payment instructions; The optimal path learning library is obtained by obtaining an optimal remittance path corresponding to the remittance information and the remittance path preference according to the historical remittance path, the remittance path preference and the remittance path attribute.

3. The method for determining the optimal remittance path for batch remittance according to claim 1, characterized in that: The account information includes whether the payer's account supports online banking, whether the receiving bank supports online banking, the remittance amount and the remittance time; The remittance path selection table includes: When the remittance time is a working day or a non-working day, the optimal remittance path corresponding to whether the payment account supports online banking interconnection, whether the receiving bank supports online banking interconnection, and whether the remittance amount is greater than the preset threshold.

4. The method for determining the optimal remittance path for batch remittance according to claim 1, characterized in that: The step of obtaining the optimal remittance path according to the remittance information through the optimal path learning library and the preset remittance path selection model specifically includes: Obtain the customer's historical remittance information; Determine, based on the customer information, batch payment instructions, and remittance path preference of the customer, whether there is target historical remittance information that is the same as the batch payment instructions and remittance path preference in the historical remittance information; If so, the remittance path of the target historical remittance information is used as the optimal remittance path. If not, the optimal remittance path is obtained through the optimal path learning library and the preset remittance path selection model.

5. The method for determining the optimal remittance path for batch remittance according to claim 4, characterized in that: Further including: Determining whether the operation status of the optimal remittance path is normal; If not, the priorities of all remittance paths are obtained according to the batch payment instruction, the remittance path preference and the preset remittance path selection model, and the suboptimal remittance path with the highest priority after the optimal remittance path is determined as the optimal remittance path for executing the batch payment instruction.

6. The method for determining the optimal remittance path for batch remittance according to claim 1, characterized in that: Further including: Feedback the optimal remittance path to the user so that the user can confirm whether to use the optimal remittance path for batch payment; Receiving a confirmation instruction from a user and executing the batch payment instruction through the optimal remittance path; The modification instruction of the user is received to redetermine the optimal remittance path, and the batch payment instruction is executed through the redetermined optimal remittance path.

7. A device for determining the optimal remittance path for batch remittance, characterized in that: include: An information receiving module, used to receive a customer's batch payment instruction and a remittance path preference, wherein the remittance path preference includes the fastest speed and the lowest cost; An information parsing module, used to determine the remittance information of the customer's remittance according to the batch payment instruction, wherein the remittance information includes account information, remittance amount and remittance time; A path matching module is used to obtain an optimal remittance path according to the remittance information through an optimal path learning library and a preset remittance path selection model; wherein the optimal path learning library includes a remittance path selection table when the customer's remittance path preference is the fastest speed and a remittance path selection table when the customer's remittance path preference is the lowest cost; after obtaining the remittance information of the customer's remittance through the customer's batch payment instruction, the optimal remittance path can be directly found from the corresponding remittance path selection table in combination with the remittance information and the remittance path preference; Among them, the preset remittance path selection model first sorts the remittance path priority according to the customer's remittance path preference, and screens the remittance paths from high to low priority one by one according to whether the payer's account of the remittance supports online banking interconnection, whether the receiving bank supports online banking interconnection, the remittance amount, the remittance time and the current remittance path operation status, and finally selects the optimal remittance path.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 6 is implemented.

9. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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