CN113535822B - Bank line number matching method and device, storage medium and equipment - Google Patents
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Abstract
The invention discloses a matching method of bank line numbers, a matching device, a storage medium and equipment thereof. The matching method comprises the following steps: the method comprises the steps of obtaining a constructed data statistics model and remittance information filled by a client, wherein the data statistics model comprises a first mapping relation between a bank line number and a bank card number and a second mapping relation between the bank line number and a bank name, and remittance data comprises a payee account number and a payee bank fuzzy name; matching according to the account number of the payee and the first mapping relation to obtain a plurality of candidate bank line numbers; matching according to the candidate bank serial numbers and the second mapping relation to obtain candidate bank names; calculating fuzzy matching score values of each candidate bank name according to the fuzzy names of the collection bank and the candidate bank names; and taking the candidate bank name with the highest fuzzy matching score value as the accurate name of the receiving bank, thereby determining the accurate bank line number. The method can improve the input efficiency of the bank names and the bank linkage numbers and reduce the workload.
Description
Technical Field
The invention belongs to the technical field of machine learning, and particularly relates to a matching method and device for bank line numbers, a computer readable storage medium and computer equipment.
Background
In the cross-bank transfer business, a customer usually fills three elements (a payee account number, a payee name and a payee line name), and in a transfer passage of a people bank, a collection line number needs to be filled, each business website of each bank of the people bank has a unique bank line number, and a specific branch of a bank can be rapidly positioned according to the number so as to transfer money.
At present, the manual mode of the counter is adopted to carry out supplementary record on the bank line numbers, and the traditional manual inquiry and input line number working mode of the counter has the following obvious defects: 1) The workload is large, and the work content is repeated and time-consuming. 2) Some specific money transfer scenarios cannot be automated, increasing labor costs. 3) Without a verification mechanism, manual complement is easy to generate errors, the probability of reexchange refunds is increased, the working efficiency is reduced, and the remittance period is increased, so that the customer satisfaction is reduced. 4) In the existing operation flow, the mode of manual inquiry and supplementary recording of the joint line numbers not only makes the whole operation flow more complicated, a large number of non-intelligent operations bring inconvenience and waste of a large amount of time to customers and banking workers, but also the imprecise line name data provided by the customers increases the difficulty of manual searching.
Disclosure of Invention
First, the present invention solves the problems
How to improve the matching efficiency and the automatic input degree of the bank line numbers.
(II) the technical proposal adopted by the invention
A matching method of bank line numbers, the matching method comprising:
The method comprises the steps of obtaining a constructed data statistics model and remittance information filled by a customer, wherein the data statistics model comprises a first mapping relation between a bank line number and a bank card number and a second mapping relation between the bank line number and a bank name, and remittance data comprises a payee account number and a payee bank fuzzy name;
matching according to the payee account number and the first mapping relation to obtain a plurality of candidate bank linkage numbers;
matching according to the candidate bank serial numbers and the second mapping relation to obtain a plurality of candidate bank names;
calculating fuzzy matching score values of each candidate bank name according to the fuzzy names of the collection bank and the candidate bank names;
and taking the candidate bank name with the highest fuzzy matching score value as the accurate name of the receiving bank, and determining the accurate bank linkage number according to the accurate name of the receiving bank.
Preferably, the first mapping relation is a mapping relation between nine digits of a prefix of the bank parallel number and six digits of a prefix of the bank card number; the method for matching and obtaining a plurality of candidate bank serial numbers according to the payee account number and the first mapping relation comprises the following steps: and obtaining nine prefix digits of the candidate bank line numbers according to the six prefix digits of the payee account number and the first mapping relation.
Preferably, the second mapping relationship is a mapping relationship between a nine-bit prefix of the bank serial number and a bank name; the method for obtaining the candidate bank names by matching according to the candidate bank serial numbers and the second mapping relation comprises the following steps: and obtaining a plurality of candidate bank names according to the nine prefix digits of the plurality of candidate bank linkage numbers and the second mapping relation.
Preferably, the data statistics model further includes a third mapping relation between three digits of a prefix of the bank line number and the bank names, and after the plurality of candidate bank line numbers are obtained by matching according to the plurality of candidate bank line numbers and the second mapping relation, the matching method further includes:
Determining bank characteristic information according to the third mapping relation and the fuzzy name of the collection bank;
and screening part of candidate bank names from the candidate bank names according to the bank characteristic information to serve as candidate bank names.
Preferably, the method for calculating the fuzzy matching score value of each candidate bank name according to the fuzzy name of the receiving bank and the candidate bank names comprises the following steps:
Removing the fuzzy names of the collection banks and the regional information and the bank characteristic values in the names of the banks to be selected, and respectively obtaining collection bank abbreviations corresponding to the fuzzy names of the collection banks and the names of the banks to be selected;
and according to a fuzzy matching algorithm, carrying out fuzzy matching on the collection bank abbreviations and each candidate bank abbreviation one by one to obtain a fuzzy matching score value of each candidate bank abbreviation.
Preferably, the matching method further comprises:
Judging whether the highest fuzzy matching score value is a preset score value or not;
if not, generating a manual operation instruction which is used for prompting an operator to input the name of the money receiving bank.
Preferably, the matching method further comprises:
generating a new first mapping relation according to nine digits of a prefix of a bank linkage number corresponding to the name of the collection bank and six digits of a prefix of the account number of the collection person, which are input by an operator, and adding the new first mapping relation to a data statistics model.
The invention also discloses a matching device of the bank line number, which comprises:
The system comprises an acquisition unit, a client and a data statistics module, wherein the acquisition unit is used for acquiring a constructed data statistics model and remittance information filled by the client, the data statistics model comprises a first mapping relation between a bank line number and a bank card number and a second mapping relation between the bank line number and a bank name, and the remittance data comprises a payee account number and a fuzzy name of a payee bank;
The first matching unit is used for matching a plurality of candidate bank linkage numbers according to the payee account number and the first mapping relation;
The second matching unit is used for matching the plurality of candidate bank serial numbers and the second mapping relation to obtain a plurality of candidate bank names;
The fuzzy score calculating unit is used for calculating the fuzzy matching score value of each candidate bank name according to the fuzzy name of the collection bank and the candidate bank names;
and the determining unit is used for taking the candidate bank name with the highest fuzzy matching score value as the accurate name of the receiving bank and determining an accurate bank linkage number according to the accurate name of the receiving bank.
The invention also discloses a computer readable storage medium which stores a matching program of the bank serial number, and the matching method of the bank serial number is realized when the matching program of the bank serial number is executed by a processor.
The invention also discloses a computer device, which comprises a computer readable storage medium, a processor and a matching program of the bank serial number stored in the computer readable storage medium, wherein the matching program of the bank serial number realizes the matching method of the bank serial number when being executed by the processor.
(III) beneficial effects
The invention discloses a matching method of bank line numbers, which has the following technical effects compared with the traditional method:
According to the scheme, an accurate payee account number and a pre-built data statistics model are adopted to screen out a plurality of candidate bank names, a fuzzy matching algorithm is further adopted to match the fuzzy names of the money receiving bank with the candidate bank names one by one, so that the accurate bank names are obtained, and the bank line number is determined.
Drawings
Fig. 1 is a flowchart of a matching method of bank line numbers according to a first embodiment of the present invention;
fig. 2 is a detailed schematic diagram of steps of a matching method of bank serial numbers according to a first embodiment of the present invention;
fig. 3 is a flowchart of a matching method of bank serial numbers according to a second embodiment of the present invention;
fig. 4 is a schematic block diagram of a matching device for bank line numbers according to a third embodiment of the present invention;
Fig. 5 is a schematic block diagram of a computer device according to a fifth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Before describing in detail various embodiments of the present application, the inventive concepts of the present application are briefly described first: when transferring money across banks through a people bank channel, a collection line number needs to be filled in, in the prior art, the bank line number is subjected to supplementary recording in a manual mode, and meanwhile, line name data provided by customers are generally inaccurate, so that the difficulty of manual searching and the workload of manual supplementary recording are increased. According to the scheme, an accurate payee account number and a pre-built data statistics model are adopted to screen out a plurality of candidate bank names, a fuzzy matching algorithm is further adopted to match the fuzzy names of the money receiving bank with the candidate bank names one by one, so that the accurate bank names are obtained, and the bank line number is determined.
Specifically, as shown in fig. 1 and 2, the matching method of the bank line number of the first embodiment includes the following steps:
Step S10: the method comprises the steps of obtaining a constructed data statistics model and remittance information filled by a customer, wherein the data statistics model comprises a first mapping relation between a bank line number and a bank card number and a second mapping relation between the bank line number and a bank name, and remittance data comprises a payee account number and a payee bank fuzzy name;
step S20: matching according to the payee account number and the first mapping relation to obtain a plurality of candidate bank linkage numbers;
Step S30: matching according to the candidate bank serial numbers and the second mapping relation to obtain a plurality of candidate bank names;
step S40: calculating fuzzy matching score values of each candidate bank name according to the fuzzy names of the collection bank and the candidate bank names;
step S50: and taking the candidate bank name with the highest fuzzy matching score value as the accurate name of the receiving bank, and determining the accurate bank linkage number according to the accurate name of the receiving bank. .
Specifically, in step S10, the remittance information filled in by the customer mainly includes the account number of the payee, the name of the payee, the fuzzy name of the payee bank, the account number of the payee and the name of the payee as precise information, there is no error, and the name of the payee may have the inaccuracy problems of irregular writing format, shorthand, missed writing, wrong writing and the like, so the remittance information is defined as the fuzzy name of the payee bank. In banking business handling, after a teller adopts a manual input mode to carry out supplementary recording, the data statistical model is dynamically updated so as to continuously increase the statistical data of the data statistical model. Illustratively, the first mapping relationship is a mapping relationship between nine digits of a prefix of the bank serial number and six digits of a prefix of the bank card number, and the data example of the first mapping relationship is as follows: 427020&:102581099;427020&:102584000;427020&:102581000;427020&:102581001....... The second mapping relation is the mapping relation between the nine digits of the prefix of the bank serial number and the bank name, and the data example of the second mapping relation is as follows: 102581000&:102581000546&: china industry and commerce Bank shares Limited company Guangzhou five mountain branch &:102100099996&:5810&: guangzhou &: guangzhou &: guangdong. 402829507&:402829507042&: gansu Lintao rural cooperative banks eight-lining branch line &:402821000015&:8295&: lintao &: setting &: gansu. 402372700&:402372700171&: tang set branch of rural commercial banking stock limited company of Mongolian Anhui, and-: 402361018886&:3727&: mongolian &: bozhou &: an emblem.
In another embodiment, the data statistics model further includes a third mapping relationship between three digits of the prefix of the bank binding number and the name of the bank, and the data example of the third mapping relationship is as follows: 102&: china industry and commerce banking stock Co., ltd; 102&: china industry and commerce bank stock Limited company; 102&: china industry and commerce stock Co., ltd; 102&: china business banking; 102&: a Chinese business; 102&: an industrial and commercial bank; 102&: industry.
In step S20, the method for matching to obtain a plurality of candidate bank parallel numbers according to the payee account number and the first mapping relationship includes: and obtaining nine prefix digits of the candidate bank line numbers according to the six prefix digits of the payee account number and the first mapping relation. The approximate bank linkage number candidate range is matched in advance according to the account number of the payee filled by the client.
In step S30, the method for obtaining the plurality of candidate bank names according to the plurality of candidate bank serial numbers and the second mapping relation by matching includes: and obtaining a plurality of candidate bank names according to the nine prefix digits of the plurality of candidate bank linkage numbers and the second mapping relation. That is, a rough bank name candidate range is further determined from the bank combination number candidate range determined in step S20.
In step S40, the specific step of calculating the fuzzy matching score value of each candidate bank name according to the fuzzy name of the receiving bank and the plurality of candidate bank names includes: removing the fuzzy names of the collection banks and the regional information and the bank characteristic values in the candidate bank names to respectively obtain collection bank abbreviations corresponding to the fuzzy names of the collection banks and candidate bank abbreviations corresponding to the candidate bank names; and according to a fuzzy matching algorithm, carrying out fuzzy matching on the collection bank abbreviations and each candidate bank abbreviation one by one to obtain a fuzzy matching score value of each candidate bank abbreviation.
Illustratively, if the fuzzy name of the collection bank filled by the customer is five mountain branches in Guangzhou city, removing the regional information Guangzhou city, and removing the bank characteristic value worker to obtain the collection bank short for five mountain branches. And removing the regional information Guangzhou market if the candidate bank name is the five mountain branch of the China industry and commerce bank stock limited company, and removing the bank characteristic value China industry and commerce bank stock limited company to obtain the five mountain branch of the collection bank. Thus, the complexity of the matching field can be reduced, the calculated amount is reduced, and the matching speed is improved.
Further, fuzzy matching is carried out on the collection bank abbreviations and each candidate bank abbreviation one by one, and fuzzy matching score values of each candidate bank abbreviation are obtained. For example, the score of "five mountain branches" and "five mountain branches" is 100.00 points, and the score of "Beijing middle voyage oil branches" and "five mountain branches" is 28.57 points.
Further, in step S50, the candidate bank name with the highest fuzzy matching score is taken as the accurate name of the receiving bank, and the accurate bank line number is determined according to the accurate name of the receiving bank, so as to complete the intelligent matching of the bank name and the bank line number.
Specifically, the matching method further comprises: judging whether the highest fuzzy matching score value is a preset score value or not; if not, generating a manual operation instruction which is used for prompting an operator to input the name of the money receiving bank. If yes, the matching is ended. For example, when the preset score is 100 and the highest fuzzy matching score is 100, it is indicated that the fuzzy name of the collection bank is identical to the accurate name of the collection bank obtained by automatic matching. When the highest fuzzy match score value is not 100, for example 98 points, then manual entry by the teller or manual selection of the correct bank name and bank serial number from the existing list is required.
Further, the matching method further comprises: generating a new first mapping relation according to nine digits of a bank linkage number prefix corresponding to the name of the collection bank and six digits of a prefix of the account number of the collection person, which are input by an operator, and adding the new first mapping relation to the data statistical model, so that the data statistical model is dynamically updated.
In a second embodiment, as shown in fig. 3, the matching method of the bank line number includes the following steps:
Step S10: the method comprises the steps of obtaining a constructed data statistics model and remittance information filled by a customer, wherein the data statistics model comprises a first mapping relation between a bank line number and a bank card number and a second mapping relation between the bank line number and a bank name, and remittance data comprises a payee account number and a payee bank fuzzy name;
step S20: matching according to the payee account number and the first mapping relation to obtain a plurality of candidate bank linkage numbers;
Step S30: matching according to the candidate bank serial numbers and the second mapping relation to obtain a plurality of candidate bank names;
Step S41: determining bank characteristic information according to the third mapping relation and the fuzzy name of the collection bank;
step S42: and screening part of candidate bank names from the candidate bank names according to the bank characteristic information to serve as candidate bank names.
Step S51: and calculating the fuzzy matching score value of each candidate bank name according to the fuzzy name of the receiving bank and the plurality of candidate bank names.
Step S52: and taking the name of the candidate bank with the highest fuzzy matching score as the accurate name of the receiving bank, and determining the accurate bank linkage number according to the accurate name of the receiving bank.
Specifically, the specific processes of step S10, step S20 and step S30 in the second embodiment are the same as those of step S10, step S20 and step S30 in the first embodiment, and will not be described here again.
Further, in step S41, the data statistics model constructs a third mapping relationship between three digits of the prefix of the bank coupling number and the bank name in advance, and the fuzzy name of the collection bank filled in by the customer has various possible forms, such as business bank behavior example, the corresponding bank characteristic information is determined to be 102, which may be a China industry and commerce bank stock limit company, a China industry and commerce bank, and an industry and commerce. In practice, the three digits of the bank combination number prefix of each bank are unique, for example, the three digits of the bank combination number prefix of China industry and commerce banks, china construction banks, china agriculture banks and the like are different.
After the bank characteristic information is determined, the bank characteristic information is compared with the candidate bank joint line number one, and the joint line number with the prefix three digits of the candidate bank joint line number identical to the bank characteristic information is reserved, so that part of candidate bank names are further screened out from the plurality of candidate bank names to serve as candidate bank names, and the candidate bank names correspond to the reserved candidate bank joint line number.
Illustratively, in step S30, the obtained candidate bank serial numbers are 102100009, 102121000, 102581000, 105584001215, 105584000021 and 105584000005, and in step S41, the bank characteristic information is 102, and in step S42, the candidate bank serial numbers are reserved 102100009, 102121000 and 102581000, so as to screen out the corresponding candidate bank names. The number of candidate bank names is less than the number of candidate bank names. In this way, in the subsequent step S51 and step S52, the calculation amount can be further reduced, and the matching efficiency can be improved.
As shown in fig. 4, in the third embodiment, the matching apparatus of the bank join line number includes an acquisition unit 100, a first matching unit 200, a second matching unit 300, a blur score calculation unit 400, and a determination unit 500. The obtaining unit 100 is configured to obtain a constructed data statistics model and remittance information filled by a customer, where the data statistics model includes a first mapping relationship between a bank line number and a bank card number and a second mapping relationship between the bank line number and a bank name, and the remittance data includes a payee account number and a fuzzy name of a payee bank. The first matching unit 200 is configured to obtain a plurality of candidate bank parallel numbers according to the payee account number and the first mapping relationship. The second matching unit 300 is configured to obtain a plurality of candidate bank names according to the plurality of candidate bank serial numbers and the second mapping relationship. The fuzzy score calculating unit 400 is configured to calculate a fuzzy match score value of each candidate bank name according to the fuzzy name of the receiving bank and the plurality of candidate bank names. The determining unit 500 is configured to take a candidate bank name with the highest fuzzy matching score value as an accurate name of the receiving bank, and determine an accurate bank serial number according to the accurate name of the receiving bank. The specific processing procedures of the acquiring unit 100, the first matching unit 200, the second matching unit 300, the blur score calculating unit 400, and the determining unit 500 refer to the descriptions of the first embodiment and the second embodiment, and are not described herein.
Further, in another embodiment, the matching device further includes a third matching unit 301, where the third matching unit 301 is configured to determine bank characteristic information according to the third mapping relationship and the fuzzy name of the collection bank; and screening part of candidate bank names from the candidate bank names according to the bank characteristic information to serve as candidate bank names. The specific processing procedure of the third matching unit 301 can be referred to the related description of the second embodiment, and will not be described herein.
Further, the fuzzy score calculating unit 400 is further configured to calculate a fuzzy match score value of each candidate bank name according to the fuzzy name of the receiving bank and the plurality of candidate bank names. The determining unit 500 is further configured to use the selected bank name with the highest fuzzy matching score value as the accurate name of the receiving bank, and determine an accurate bank serial number according to the accurate name of the receiving bank.
The fourth embodiment also discloses a computer readable storage medium, wherein the computer readable storage medium stores a matching program of the bank serial number, and the matching method of the bank serial number is realized when the matching program of the bank serial number is executed by a processor.
Further, the fifth embodiment also discloses a computer device, which includes, at the hardware level, as shown in fig. 5, a processor 12, an internal bus 13, a network interface 14, and a computer readable storage medium 11. The processor 12 reads the corresponding computer program from the computer-readable storage medium and then runs to form the request processing means at a logic level. Of course, in addition to software implementation, one or more embodiments of the present disclosure do not exclude other implementation manners, such as a logic device or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but may also be hardware or a logic device. The computer readable storage medium 11 stores a matching program of the bank serial number, and the matching program of the bank serial number realizes the matching method of the bank serial number when being executed by a processor.
Computer-readable storage media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer-readable 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 disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic disk storage, quantum memory, graphene-based storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device.
While certain embodiments have been shown and described, it would be appreciated by those skilled in the art that changes and modifications may be made without departing from the principles and spirit of the invention, the scope of which is defined in the claims and their equivalents.
Claims (10)
1. The matching method of the bank line number is characterized by comprising the following steps:
The method comprises the steps of obtaining a constructed data statistics model and remittance information filled by a customer, wherein the data statistics model comprises a first mapping relation between a bank line number and a bank card number and a second mapping relation between the bank line number and a bank name, and the remittance information comprises a payee account number and a payee bank fuzzy name;
matching according to the payee account number and the first mapping relation to obtain a plurality of candidate bank linkage numbers;
matching according to the candidate bank serial numbers and the second mapping relation to obtain a plurality of candidate bank names;
calculating fuzzy matching score values of each candidate bank name according to the fuzzy names of the collection bank and the candidate bank names;
and taking the candidate bank name with the highest fuzzy matching score value as the accurate name of the receiving bank, and determining the accurate bank linkage number according to the accurate name of the receiving bank.
2. The method for matching bank serial numbers according to claim 1, wherein the first mapping relationship is a mapping relationship between nine digits of a prefix of a bank serial number and six digits of a prefix of a bank card number; the method for matching and obtaining a plurality of candidate bank serial numbers according to the payee account number and the first mapping relation comprises the following steps: and obtaining nine prefix digits of the candidate bank line numbers according to the six prefix digits of the payee account number and the first mapping relation.
3. The method for matching bank serial numbers according to claim 2, wherein the second mapping relationship is a mapping relationship between a prefix nine digits of the bank serial number and a bank name; the method for obtaining the candidate bank names by matching according to the candidate bank serial numbers and the second mapping relation comprises the following steps: and obtaining a plurality of candidate bank names according to the nine prefix digits of the plurality of candidate bank linkage numbers and the second mapping relation.
4. The method for matching bank serial numbers according to claim 3, wherein the data statistics model further comprises a third mapping relation between three digits of a prefix of the bank serial number and a bank name, and after matching the plurality of candidate bank serial numbers and the second mapping relation to obtain a plurality of candidate bank names, the matching method further comprises:
Determining bank characteristic information according to the third mapping relation and the fuzzy name of the collection bank;
and screening part of candidate bank names from the candidate bank names according to the bank characteristic information to serve as candidate bank names.
5. The method of claim 4, wherein calculating a fuzzy match score value for each candidate bank name based on the collection bank fuzzy name and the plurality of candidate bank names comprises:
Removing the fuzzy names of the collection banks and the regional information and the bank characteristic values in the names of the banks to be selected, and respectively obtaining collection bank abbreviations corresponding to the fuzzy names of the collection banks and the names of the banks to be selected;
and according to a fuzzy matching algorithm, carrying out fuzzy matching on the collection bank abbreviations and each candidate bank abbreviation one by one to obtain a fuzzy matching score value of each candidate bank abbreviation.
6. The method for matching bank line numbers according to claim 2, wherein the matching method further comprises:
Judging whether the highest fuzzy matching score value is a preset score value or not;
if not, generating a manual operation instruction which is used for prompting an operator to input the name of the money receiving bank.
7. The method for matching bank line numbers according to claim 6, wherein the matching method further comprises:
generating a new first mapping relation according to nine digits of a prefix of a bank linkage number corresponding to the name of the collection bank and six digits of a prefix of the account number of the collection person, which are input by an operator, and adding the new first mapping relation to a data statistics model.
8. A matching device for bank line numbers, the matching device comprising:
The system comprises an acquisition unit, a client and a data statistics module, wherein the acquisition unit is used for acquiring a constructed data statistics model and remittance information filled by the client, the data statistics model comprises a first mapping relation between a bank line number and a bank card number and a second mapping relation between the bank line number and a bank name, and the remittance information comprises a payee account number and a fuzzy name of a payee bank;
The first matching unit is used for matching a plurality of candidate bank linkage numbers according to the payee account number and the first mapping relation;
The second matching unit is used for matching the plurality of candidate bank serial numbers and the second mapping relation to obtain a plurality of candidate bank names;
The fuzzy score calculating unit is used for calculating the fuzzy matching score value of each candidate bank name according to the fuzzy name of the collection bank and the candidate bank names;
and the determining unit is used for taking the candidate bank name with the highest fuzzy matching score value as the accurate name of the receiving bank and determining an accurate bank linkage number according to the accurate name of the receiving bank.
9. A computer-readable storage medium, wherein the computer-readable storage medium stores a matching program of bank join numbers, which when executed by a processor, implements the matching method of bank join numbers according to any one of claims 1 to 7.
10. A computer device comprising a computer readable storage medium, a processor and a matching program for bank join numbers stored in the computer readable storage medium, which when executed by the processor, implements the matching method for bank join numbers according to any one of claims 1 to 7.
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