Method and apparatus for processing bank branch business

Abstract

The present invention provides a method and apparatus for processing bank branch services, which are applied to the field of financial technology. The method includes: classifying accounts based on business data to obtain multiple account categories; for each account category, determining the corresponding business risk coefficient and corresponding business frequency; determining a first account category among the multiple account categories; for each bank branch, determining the corresponding first customer category; when the number of queuing customers at the bank branch is greater than a specified threshold, sending a request to the bank server to obtain customer information of the first customer category and receiving the first customer category of the bank branch; when the bank branch receives a business request from a customer, determining whether the customer belongs to the first customer category. If so, processing the business request of the customer; otherwise, sending the business request of the customer to the bank server and receiving the business processing result. The present invention can reduce risks when processing business for customers.

Description

Technical Field

[0001] The present invention relates to the field of financial technologies, and in particular, to a method and device for processing bank branch business. Background Art

[0002] Currently, all customer transaction processing and identity authentication in banks are carried out on bank servers. When the number of customers is relatively large, especially during peak transaction periods, it will lead to relatively long waiting times for customers and relatively high system pressure on bank servers. Therefore, there is a need for a method for processing bank branch business to reduce customer waiting times and system pressure on bank servers. Summary of the Invention

[0003] An embodiment of the present invention provides a method for processing bank branch business, which is used to reduce risks when processing business for customers. The method includes:

[0004] Obtain business data of accounts in a bank branch, classify the accounts based on the business data, and obtain multiple account categories;

[0005] For each account category, determine the corresponding business risk coefficient and corresponding business frequency according to the business data of the account category;

[0006] Determine a first account category among the multiple account categories according to the business risk coefficient and business frequency;

[0007] For each bank branch, determine the corresponding first customer category according to the first account category of the customers in the bank branch;

[0008] When the number of queuing customers in a bank branch is greater than a specified threshold, send a request to the bank server to obtain customer information of the first customer category of the bank branch among the queuing customers, and receive the first customer category of the bank branch fed back by the bank server;

[0009] When the bank branch receives a business request from a customer, determine whether the customer is of the first customer category. If so, process the business request of the customer based on the customer information of the customer stored in the bank branch; otherwise, send the business request of the customer to the bank server and receive the business processing result fed back by the bank server.

[0010] An embodiment of the present invention provides a device for processing bank branch business, which is used to reduce risks when processing business for customers. The device includes:

[0011] An account classification module, configured to obtain business data of accounts in a bank branch, classify the accounts based on the business data, and obtain multiple account categories;

[0012] A business analysis module, which is used to determine the business risk coefficient and corresponding business frequency corresponding to each account category according to the business data of the account category.

[0013] A first account category determination module, which is used to determine the first account category among multiple account categories according to the business risk coefficient and business frequency.

[0014] A first customer category determination module, which is used to determine the first customer category corresponding to each bank branch according to the first account category of the customers of the bank branch.

[0015] A request analysis module, which is used to send a request to the bank server to obtain the customer information of the customers of the first customer category among the queuing customers when the number of queuing customers at the bank branch is greater than a specified threshold, and receive the first customer category of the bank branch fed back by the bank server.

[0016] A business request processing module, which is used to determine whether the customer is of the first customer category when the bank branch receives a business request from the customer. If so, process the business request of the customer based on the customer information of the customer stored in the bank branch. Otherwise, send the business request of the customer to the bank server and receive the business processing result fed back by the bank server.

[0017] An embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned bank branch business processing method is implemented.

[0018] An embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned bank branch business processing method is implemented.

[0019] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the above-mentioned bank branch business processing method is implemented.

[0020] In an embodiment of the present invention, business data of accounts at bank branches is obtained, the accounts are classified based on the business data to obtain multiple account categories; for each account category, according to the business data of that account category, the corresponding business risk coefficient and the corresponding business frequency are determined; based on the business risk coefficient and the business frequency, the first account category among the multiple account categories is determined; for each bank branch, according to the first account category of the customers of that bank branch, the corresponding first customer category of that bank branch is determined; when the number of queuing customers at a bank branch is greater than a specified threshold, a request is sent to the bank server to obtain the customer information of the customers of the first customer category of that bank branch among the queuing customers, and the feedback of the first customer category of that bank branch from the bank server is received; when a bank branch receives a business request from a customer, it is determined whether the customer is of the first customer category, if so, based on the customer information of that customer stored at that bank branch, the business request of that customer is processed, otherwise, the business request of that customer is sent to the bank server, and the business processing result feedback from the bank server is received. In the above process, by analyzing the business data of the accounts, the first account category can be determined, and then the first customer category can be determined, so that when processing a business request, it is determined whether the customer is of the first customer category, if so, based on the customer information of that customer stored at that bank branch, the business request of that customer is processed, otherwise, the business request of that customer is sent to the bank server, and the business processing result feedback from the bank server is received, achieving the purpose of accurately processing business requests. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the drawings:

[0022] Figure 1 is the flow chart of the bank branch business processing method in the embodiment of the present invention Figure 1 ;

[0023] Figure 2 is the flow chart of classifying accounts in the embodiment of the present invention;

[0024] Figure 3 is the flow chart of conducting business analysis in the embodiment of the present invention;

[0025] Figure 4 is the flow chart of determining the first account category among multiple account categories in the embodiment of the present invention;

[0026] Figure 5Flowchart for selecting the first account category in the embodiments of the present invention;

[0027] Figure 6 Flowchart for determining the first customer category corresponding to a bank branch in the embodiments of the present invention;

[0028] Figure 7 Flow Figure 2 ;

[0029] Figure 8 Schematic Figure 1 ;

[0030] Figure 9 Schematic Figure 2 。 Detailed implementation manners

[0031] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer and more understandable, the following further describes the embodiments of the present invention in detail with reference to the drawings. Herein, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but not to limit the present invention.

[0032] In the description of this specification, the terms "include", "including", "have", "containing", etc. are all open-ended terms, that is, they are meant to include but not limited to. The descriptions with reference to terms such as "one embodiment", "one specific embodiment", "some embodiments", "for example", etc. mean that the specific features, structures or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. The step sequences involved in each embodiment are used to schematically illustrate the implementation of the present application, and the step sequences are not limited and can be adjusted appropriately as needed.

[0033] Figure 1 Flow Figure 1 ,such as Figure 1 shown, including:

[0034] Step 101: Obtain the business data of the accounts of the bank branch, classify the accounts based on the business data, and obtain multiple account categories;

[0035] Step 102: For each account category, determine the corresponding business risk coefficient and the corresponding business frequency according to the business data of the account category;

[0036] Step 103: Determine the first account category among multiple account categories according to the business risk coefficient and business frequency.

[0037] Step 104: For each bank branch, determine the first customer category corresponding to the bank branch according to the first account category of the customers of the bank branch.

[0038] Step 105: When the number of queuing customers at a bank branch is greater than the specified threshold, send a request to the bank server to obtain the customer information of the customers in the first customer category of the bank branch among the queuing customers, and receive the first customer category of the bank branch fed back by the bank server.

[0039] Step 106: When the bank branch receives a business request from a customer, determine whether the customer is in the first customer category. If so, process the business request of the customer based on the customer information of the customer stored in the bank branch; otherwise, send the business request of the customer to the bank server and receive the business processing result fed back by the bank server.

[0040] Specifically, customer information is used to support the bank branch in handling the business of customers, such as pre-stored face images, face matching thresholds, and various customer identifiers.

[0041] Figure 2 It is a flowchart for classifying accounts in an embodiment of the present invention. In one embodiment, business data of accounts at a bank branch is obtained, and the accounts are classified based on the business data to obtain multiple account categories, including:

[0042] Step 201: For each account number, use the business volume corresponding to each business in the historical business data of the account as the business volume of the account corresponding to the business.

[0043] Step 202: For each business, determine the function of the business, where the independent variable of the function is any two account numbers, and the corresponding function value is the difference in the business volume of the two account numbers corresponding to the business.

[0044] Step 203: Determine the distance function of the accounts according to the functions of each business.

[0045] Step 204: Classify the accounts of the bank according to the distance function of the accounts to obtain multiple account categories.

[0046] In one embodiment, determining the distance function of the accounts according to the functions of each business includes:

[0047] Determine the distance function of the accounts as the square root of the sum of the squares of the functions of each business.

[0048] In one embodiment, the bank accounts are classified according to the distance function of the accounts to obtain multiple account categories, including:

[0049] Select a clustering algorithm to cluster the bank accounts according to the distance function of the accounts to obtain multiple account categories;

[0050] Determine the risk level of each account in each obtained account category;

[0051] For each obtained account category, determine the maximum value of the proportion of the number of accounts corresponding to each risk level in this account category;

[0052] Loop through the following steps until the maximum value of the proportion of the number of accounts corresponding to each risk level in all account categories is greater than a consistent threshold:

[0053] Select an account category s from all account categories, where the proportion of the number of accounts corresponding to each risk level in this account category s is less than or equal to the consistent threshold;

[0054] Select a clustering algorithm to cluster all the accounts in the selected account category s according to the distance function of the accounts, and replace the selected account category s with the multiple new obtained account categories;

[0055] For each newly obtained account category, determine the maximum value of the proportion of the number of accounts corresponding to each risk level in this new account category.

[0056] Figure 3 This is the flowchart for business analysis in the embodiments of the present invention. In one embodiment, for each account category, according to the business data of this account category, determine the business risk coefficient and the corresponding business frequency of this account category, including:

[0057] Step 301, use the time range corresponding to the business data of this account category as the first time range;

[0058] Step 302, for each unit time (such as one day or one week) within the first time range, use the business data corresponding to this unit time in the business data of this account category as the sample business data of this account category;

[0059] Step 303, use the proportion of the number of risk-related businesses in each sample business data of this account category as the sample of the business risk coefficient corresponding to this account category, and use the business volume of each sample business data of this account category as the sample of the business frequency corresponding to this account category;

[0060] Step 304: Determine the business risk coefficient corresponding to the account category based on the business risk coefficient sample corresponding to the account category, and determine the business frequency corresponding to the account category based on the business frequency sample corresponding to the account category.

[0061] Note: For different account categories, the selection of the unit time is the same, so that there is comparability.

[0062] Figure 4 This is a flowchart for determining the first account category among multiple account categories in an embodiment of the present invention. In one embodiment, determining the first account category among multiple account categories based on the business risk coefficient and the business frequency includes:

[0063] Step 401: Determine the partial order of the account categories based on the business risk coefficient and the business frequency. Among them, for any two account categories among multiple account categories, when the business risk coefficient corresponding to the first account category among the two account categories is less than or equal to the business risk coefficient corresponding to the second account category among the two account categories, and the business frequency corresponding to the first account category is greater than or equal to the business frequency corresponding to the second account category, then it is determined that the first account category is superior to the second account category;

[0064] Step 402: Select the first account category from multiple account categories according to the partial order of the account categories.

[0065] Specifically, compared with the bank server, there are relatively large risks in directly processing customer transactions and identity authentication at bank branches. The business risk coefficient of the first account category selected through the partial order is relatively small, which can reduce the risks of processing transactions and identity authentication at bank branches. Selecting customers with relatively high business frequencies as the first account category can reduce the waiting time of customers.

[0066] Figure 5 This is a flowchart for selecting the first account category in an embodiment of the present invention. In one embodiment, selecting the first account category from multiple account categories according to the partial order of the account categories includes:

[0067] Step 501: Initialize the partial order maximum identifier corresponding to each account category among multiple account categories as undetermined, and initialize the comparison boolean value corresponding to each account category as yes;

[0068] Step 502: Add the account categories to the account category queue in ascending order of the corresponding business risk coefficients;

[0069] Step 503: Loop and execute the following steps until the account category queue is empty:

[0070] S1: Take out the first account category a at the head of the queue from the queue;

[0071] S2: If the partial order maximum flag corresponding to the account category a at the head of the queue is not pending, continue to execute step S1; if the partial order maximum flag corresponding to the account category a at the head of the queue is pending, sequentially execute steps S3 to S4:

[0072] S3: According to the partial order of the account categories, compare each account category b other than the account category a at the head of the queue in all account categories with a comparison boolean value of yes with the account category a at the head of the queue; if the account category b is superior to the account category a at the head of the queue, set the partial order maximum flag corresponding to the account category a to no, and then continue to execute step S1; if the account category a at the head of the queue is superior to the account category b, set the partial order maximum flag corresponding to the account category b to no, and use the account category b as the secondary account category of the account category a at the head of the queue; if the account category a at the head of the queue is not superior to the account category b and the account category b is not superior to the account category a at the head of the queue, the partial order maximum flags corresponding to the account category a at the head of the queue and the account category b remain unchanged;

[0073] S4: If it is confirmed that each account category other than the account category a at the head of the queue in all account categories with a comparison boolean value of yes is not superior to the account category a at the head of the queue, determine the account category a at the head of the queue as the first account category, and update the comparison boolean value of each secondary account category of the account category a at the head of the queue to no.

[0074] In one embodiment, determining the business risk coefficient corresponding to the account category according to the business risk coefficient sample corresponding to the account category, and determining the business frequency corresponding to the account category according to the business frequency sample corresponding to the account category, includes:

[0075] Set an acceptable business risk error threshold α and a business frequency error threshold β;

[0076] Based on the business risk coefficient sample corresponding to the account category, determine the variance θ and the coefficient sample number m of the business risk coefficient corresponding to the account category, and based on the business frequency sample corresponding to the account category, determine the variance of the business frequency corresponding to the account category and the frequency sample number n;

[0077] Set an acceptable first convergence probability p1 and a second convergence probability p2, where the first convergence probability represents the probability that the business risk error is greater than α, and the second convergence probability represents the probability that the business frequency error is greater than β;

[0078] If Or Then loop to execute the following steps until And

[0079] Obtain new business data for this account category, where there is no overlap in the time range between the new business data and the previously obtained business data for this account category;

[0080] For each unit of time (such as one day or one week) within the time range corresponding to the new business data of this account category, use the business data corresponding to this unit of time in the new business data of this account category as the sample business data for this account category;

[0081] Use the proportion of the number of risk-related businesses in each sample business data of this account category as the sample of the business risk coefficient corresponding to this account category, and use the business volume included in each sample business data of this account category as the sample of the business frequency corresponding to this account category;

[0082] Based on all the sample business risk coefficients corresponding to this account category, update the variance θ and the number of coefficient samples m of the business risk coefficient corresponding to this account category, and based on all the sample business frequencies corresponding to this account category, update the variance of the business frequency and the number of frequency samples n;

[0083] When and , determine the business risk coefficient corresponding to this account category as the mean of the sample business risk coefficients corresponding to this account category, and determine the business frequency corresponding to this account category as the mean of the sample business frequencies corresponding to this account category.

[0084] Figure 6 This is a flowchart for determining the first customer category corresponding to a bank branch in an embodiment of the present invention. In one embodiment, for each bank branch, determine the first customer category corresponding to this bank branch according to the first account category of the customers of this bank branch, including:

[0085] Step 601, obtain the customer set corresponding to the business data of this bank branch;

[0086] Step 602, for each customer in this customer set, if this customer has an account belonging to the first account category in the bank, add this customer to the first customer category corresponding to this bank branch.

[0087] Figure 7 This is the flowchart of the bank branch business processing method in an embodiment of the present invention Figure 2 , in one embodiment, the method further includes:

[0088] Step 701, use the maximum value of the business risk coefficients corresponding to all the first account categories as the business risk coefficient threshold, and use the minimum value of the business frequencies corresponding to all the first account categories as the business frequency threshold;

[0089] Step 702: For each of the multiple account categories, if the business risk coefficient corresponding to the account category is less than or equal to the business risk coefficient threshold and the business frequency corresponding to the account category is greater than or equal to the business frequency threshold, then regard this account category as the second account category;

[0090] Step 703: For each customer in the customer set corresponding to the business data of this bank branch, if this customer has an account belonging to the second account category in the bank, then add this customer to the second customer category of this bank branch.

[0091] In an embodiment, receiving the first customer category of this bank branch fed back by the bank server includes:

[0092] When the first customer category of this bank branch is empty, receive the second customer category of this bank branch fed back by the bank server;

[0093] When the bank branch receives a business request from a customer, determine whether this customer is in the first customer category or the second customer category. If so, based on the customer information of this customer stored in the bank branch, process the business request of this customer. Otherwise, send the business request of this customer to the bank server and receive the business processing result fed back by the bank server.

[0094] In an embodiment, the method further includes:

[0095] Based on the business handling data of the bank server, determine multiple business busy time intervals. For example, for each time interval, if the number of business handled by the bank server in this time interval is greater than the average value of the number of business handled by the bank server, then determine this time interval as a business busy time interval;

[0096] For each bank branch, based on the business handling data of this bank branch, determine the business risk probability corresponding to this bank branch;

[0097] Regard multiple bank branches with corresponding business risk probabilities less than the risk threshold as risk-controllable branches;

[0098] For risk-controllable branches, receive the customer information sent down by the bank server, where the customer information is the customer information of the first customer category (if not, then the second customer category) corresponding to each risk-controllable branch sent down by the bank server before this business busy time interval.

[0099] In summary, in the method proposed in the embodiment of the present invention, the business data of the accounts in the bank branch is obtained, the accounts are classified based on the business data to obtain multiple account categories; for each account category, according to the business data of this account category, the business risk coefficient and the corresponding business frequency corresponding to this account category are determined; based on the business risk coefficient and the business frequency, the first account category among the multiple account categories is determined; for each bank branch, according to the first account category of the customers of this bank branch, the first customer category corresponding to this bank branch is determined; when the number of queuing customers in the bank branch is greater than the specified threshold, a request is sent to the bank server to obtain the customer information of the customers of the first customer category of this bank branch among the queuing customers, and the customer information of the first customer category of this bank branch fed back by the bank server is received; when the bank branch receives a business request from a customer, it is judged whether the customer is of the first customer category, if so, based on the customer information of this customer stored in this bank branch, the business request of this customer is processed, otherwise, the business request of this customer is sent to the bank server, and the business processing result fed back by the bank server is received. In the above process, the first account category can be determined by analyzing the business data of the accounts, and then the first customer category can be determined, so that when processing the business request, it is judged whether the customer is of the first customer category, if so, based on the customer information of this customer stored in this bank branch, the business request of this customer is processed, otherwise, the business request of this customer is sent to the bank server, and the business processing result fed back by the bank server is received, so as to achieve the purpose of accurately processing the business request.

[0100] The embodiment of the present invention also proposes a bank branch business processing device, the principle of which is similar to that of the bank branch business processing method, and will not be elaborated here.

[0101] Figure 8 It is a schematic diagram of the bank branch business processing device in the embodiment of the present invention Figure 1 , including:

[0102] An account classification module 801, configured to obtain the business data of the accounts in the bank branch, and classify the accounts based on the business data to obtain multiple account categories;

[0103] A business analysis module 802, configured to, for each account category, determine the business risk coefficient and the corresponding business frequency corresponding to this account category according to the business data of this account category;

[0104] A first account category determination module 803, configured to determine the first account category among the multiple account categories according to the business risk coefficient and the business frequency;

[0105] A first customer category determination module 804, configured to, for each bank branch, determine the first customer category corresponding to this bank branch according to the first account category of the customers of this bank branch;

[0106] A request analysis module 805, configured to send a request to the bank server to obtain customer information of the first customer category of the bank branch among the queuing customers when the number of queuing customers at the bank branch is greater than a specified threshold, and receive the first customer category of the bank branch fed back by the bank server.

[0107] A service request processing module 806, configured to determine whether the customer is of the first customer category when the bank branch receives a service request from the customer. If so, process the service request of the customer based on the customer information of the customer stored in the bank branch; otherwise, send the service request of the customer to the bank server and receive the service processing result fed back by the bank server.

[0108] In one embodiment, the account classification module is specifically configured to:

[0109] For each account, use the transaction volume corresponding to each transaction in the historical transaction data of the account as the transaction volume of the account corresponding to the transaction.

[0110] For each transaction, determine a function of the transaction, where the independent variable of the function is any two accounts, and the corresponding function value is the difference in the transaction volume of the two accounts corresponding to the transaction.

[0111] Determine the distance function of the accounts according to the functions of each transaction.

[0112] Classify the accounts of the bank according to the distance function of the accounts to obtain multiple account categories.

[0113] In one embodiment, the service analysis module is specifically configured to:

[0114] Use the time range corresponding to the service data of the account category as the first time range.

[0115] For each unit time within the first time range, use the service data corresponding to the unit time in the service data of the account category as the sample service data of the account category.

[0116] Use the proportion of the number of risk-involved services in the services included in each sample service data of the account category as the sample business risk coefficient corresponding to the account category, and use the transaction volume included in each sample service data of the account category as the sample business frequency corresponding to the account category.

[0117] Determine the business risk coefficient corresponding to the account category according to the sample business risk coefficient corresponding to the account category, and determine the business frequency corresponding to the account category according to the sample business frequency corresponding to the account category.

[0118] In one embodiment, the first account category determination module is specifically configured to:

[0119] Determine the partial order of account categories based on the business risk coefficient and business frequency. Among any two account categories in multiple account categories, when the business risk coefficient corresponding to the first account category in the two account categories is less than or equal to the business risk coefficient corresponding to the second account category in the two account categories, and the business frequency corresponding to the first account category is greater than or equal to the business frequency corresponding to the second account category, it is determined that the first account category is superior to the second account category;

[0120] Select the first account category from multiple account categories according to the partial order of account categories.

[0121] In one embodiment, the first account category determination module is specifically configured to:

[0122] Initialize the partial order maximum flag corresponding to each account category in multiple account categories to pending, and initialize the comparison boolean value corresponding to each account category to yes;

[0123] Add account categories to the account category queue in ascending order of the corresponding business risk coefficients;

[0124] Loop through the following steps until the account category queue is empty:

[0125] S1: Take out the head account category a from the queue;

[0126] S2: If the partial order maximum flag corresponding to the head account category a is not pending, continue to execute step S1. If the partial order maximum flag corresponding to the head account category a is pending, sequentially execute steps S3 to S4:

[0127] S3: According to the partial order of account categories, compare each account category b other than the head account category a among all account categories with a comparison boolean value of yes with the head account category a in turn; if account category b is superior to the head account category a, set the partial order maximum flag corresponding to account category a to no, and then continue to execute step S1; if the head account category a is superior to account category b, set the partial order maximum flag corresponding to account category b to no, and use this account category b as the secondary account category of the head account category a; if the head account category a is not superior to account category b and account category b is not superior to the head account category a, the partial order maximum flags corresponding to the head account category a and account category b remain unchanged;

[0128] S4: If, among all the account categories for which the corresponding comparison boolean value is confirmed as "yes", each account category other than the leading account category a is not superior to the leading account category a, then determine the leading account category a as the first account category, and update the comparison boolean value of each sub-account category of the leading account category a to "no".

[0129] In one embodiment, the first customer category determination module is specifically configured to:

[0130] Obtain the customer set corresponding to the business data of the bank branch;

[0131] For each customer in the customer set, if the customer has an account belonging to the first account category in the bank, add the customer to the first customer category corresponding to the bank branch.

[0132] Figure 9 Schematic diagram of the bank branch business processing device in the embodiment of the present invention Figure 2 In one embodiment, the device further includes a second customer category determination module 901, configured to:

[0133] Take the maximum value of the business risk coefficients corresponding to all the first account categories as the business risk coefficient threshold, and take the minimum value of the business frequencies corresponding to all the first account categories as the business frequency threshold;

[0134] For each account category among the multiple account categories, if the business risk coefficient corresponding to the account category is less than or equal to the business risk coefficient threshold, and the business frequency corresponding to the account category is greater than or equal to the business frequency threshold, then take the account category as the second account category;

[0135] For each customer in the customer set corresponding to the business data of the bank branch, if the customer has an account belonging to the second account category in the bank, add the customer to the second customer category of the bank branch.

[0136] In one embodiment, the request analysis module is specifically configured to: when the first customer category of the bank branch is empty, receive the second customer category of the bank branch fed back by the bank server;

[0137] The business request processing module is specifically configured to: when the bank branch receives a business request from a customer, determine whether the customer is a first customer category or a second customer category. If so, process the business request of the customer based on the customer information of the customer stored in the bank branch. Otherwise, send the business request of the customer to the bank server and receive the business processing result fed back by the bank server.

[0138] In summary, in the device proposed in the embodiment of the present invention, the business data of the accounts of the bank branches is obtained, the accounts are classified based on the business data to obtain multiple account categories; for each account category, according to the business data of this account category, the business risk coefficient and the corresponding business frequency corresponding to this account category are determined; according to the business risk coefficient and the business frequency, the first account category among the multiple account categories is determined; for each bank branch, according to the first account category of the customers of this bank branch, the first customer category corresponding to this bank branch is determined; when the number of queuing customers in the bank branch is greater than the specified threshold, a request is sent to the bank server to obtain the customer information of the customers of the first customer category of this bank branch among the queuing customers, and the first customer category of this bank branch fed back by the bank server is received; when the bank branch receives a business request from a customer, it is judged whether the customer is of the first customer category, if so, based on the customer information of this customer stored in this bank branch, the business request of this customer is processed, otherwise, the business request of this customer is sent to the bank server, and the business processing result fed back by the bank server is received. In the above process, the first account category can be determined by analyzing the business data of the accounts, and then the first customer category can be determined, so that when processing the business request, it is judged whether the customer is of the first customer category, if so, based on the customer information of this customer stored in this bank branch, the business request of this customer is processed, otherwise, the business request of this customer is sent to the bank server, and the business processing result fed back by the bank server is received, so as to achieve the purpose of accurately processing the business request.

[0139] The embodiment of the invention also provides a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned bank branch business processing method is implemented.

[0140] The embodiment of the present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned bank branch business processing method is implemented.

[0141] The embodiment of the present invention also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the above-mentioned bank branch business processing method is implemented.

[0142] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program business system. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program business system implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0143] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program business systems according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows 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 the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0144] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implement the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0145] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0146] The specific embodiments described above further elaborate on the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for processing bank branch business, characterized in that, Including: Obtain the business data of the accounts of the bank branches, classify the accounts based on the business data, and obtain multiple account categories; For each account category, determine the corresponding business risk coefficient and the corresponding business frequency according to the business data of this account category; Determine the first account category among the multiple account categories according to the business risk coefficient and the business frequency; For each bank branch, determine the corresponding first customer category of this bank branch according to the first account category of the customers of this bank branch; When the number of queuing customers at a bank branch is greater than the specified threshold, send a request to the bank server to obtain the customer information of the customers of the first customer category of this bank branch among the queuing customers, and receive the first customer category of this bank branch fed back by the bank server; When the bank branch receives a business request from a customer, determine whether the customer is of the first customer category. If so, process the business request of the customer based on the customer information of the customer stored in this bank branch. Otherwise, send the business request of the customer to the bank server and receive the business processing result fed back by the bank server.

2. The method according to claim 1, characterized in that, Obtain the business data of the accounts of the bank branches, classify the accounts based on the business data, and obtain multiple account categories, including: For each account, use the business volume corresponding to each business in the historical business data of this account as the business volume of this account corresponding to this business; For each business, determine the function of this business, where the independent variable of this function is any two accounts, and the corresponding function value is the difference in the business volume of these two accounts corresponding to this business; Determine the distance function of the accounts according to the functions of each business; Classify the accounts of the bank according to the distance function of the accounts to obtain multiple account categories.

3. The method according to claim 1, wherein For each account category, determine the corresponding business risk coefficient and the corresponding business frequency according to the business data of this account category, including: Use the time range corresponding to the business data of this account category as the first time range; For each unit time within the first time range, use the business data corresponding to this unit time in the business data of this account category as the sample business data of this account category; Use the proportion of the number of risk-involved businesses in the businesses included in each sample business data of this account category as the sample of the business risk coefficient corresponding to this account category, and use the business volume included in each sample business data of this account category as the sample of the business frequency corresponding to this account category; Determine the business risk coefficient corresponding to this account category according to the sample of the business risk coefficient corresponding to this account category, and determine the business frequency corresponding to this account category according to the sample of the business frequency corresponding to this account category.

4. The method according to claim 1, characterized in that Determine the first account category among the multiple account categories according to the business risk coefficient and the business frequency, including: Determine the partial order of account categories based on the business risk coefficient and business frequency. Among them, for any two account categories in multiple account categories, when the business risk coefficient corresponding to the first account category in the two account categories is less than or equal to the business risk coefficient corresponding to the second account category in the two account categories, and the business frequency corresponding to the first account category is greater than or equal to the business frequency corresponding to the second account category, then determine that the first account category is superior to the second account category; Select the first account category from multiple account categories according to the partial order of account categories.

5. The method according to claim 4, characterized in that, Select the first account category from multiple account categories according to the partial order of account categories, including: Initialize the partial order maximum flag corresponding to each account category in multiple account categories to pending, and initialize the comparison boolean value corresponding to each account category to yes; Add account categories to the account category queue in ascending order of the corresponding business risk coefficients; Loop through the following steps until the account category queue is empty: S1: Take out the head account category a from the queue; S2: If the partial order maximum flag corresponding to the head account category a is not pending, continue to execute step S1. If the partial order maximum flag corresponding to the head account category a is pending, sequentially execute steps S3 to S4: S3: According to the partial order of account categories, compare each account category b other than the head account category a in all account categories with the comparison boolean value of yes with the head account category a in turn; if the account category b is superior to the head account category a, set the partial order maximum flag corresponding to the account category a to no, and then continue to execute step S1; if the head account category a is superior to the account category b, set the partial order maximum flag corresponding to the account category b to no, and use the account category b as the secondary account category of the head account category a; if the head account category a is not superior to the account category b and the account category b is not superior to the head account category a, the partial order maximum flags corresponding to the head account category a and the account category b remain unchanged; S4: If it is confirmed that each account category other than the head account category a in all account categories with the comparison boolean value of yes is not superior to the head account category a, determine the head account category a as the first account category, and update the comparison boolean value of each secondary account category of the head account category a to no.

6. The method according to claim 1, wherein [[ID= ​ ​ 7. The method according to claim 1, characterized in that, ​ ​ For each of multiple account categories, if the business risk coefficient corresponding to the account category is less than or equal to the business risk coefficient threshold, and the business frequency corresponding to the account category is greater than or equal to the business frequency threshold, then the account category is taken as the second account category; For each customer in the customer set corresponding to the business data of the bank branch, if the customer has an account belonging to the second account category in the bank, then the customer is added to the second customer category of the bank branch.

8. The method according to claim 7, wherein Receive the first customer category of the bank branch fed back by the bank server, including: When the first customer category of the bank branch is empty, receive the second customer category of the bank branch fed back by the bank server; When the bank branch receives a business request from a customer, determine whether the customer is the first customer category or the second customer category. If so, based on the customer information of the customer stored in the bank branch, process the business request of the customer. Otherwise, send the business request of the customer to the bank server and receive the business processing result fed back by the bank server.

9. A bank branch business processing device, characterized in that, Including: An account classification module, configured to obtain the business data of the accounts of the bank branch, classify the accounts based on the business data, and obtain multiple account categories; A business analysis module, configured to, for each account category, determine the business risk coefficient corresponding to the account category and the corresponding business frequency according to the business data of the account category; A first account category determination module, configured to determine the first account category among multiple account categories according to the business risk coefficient and the business frequency; A first customer category determination module, configured to, for each bank branch, determine the first customer category corresponding to the bank branch according to the first account category of the customers of the bank branch; A request analysis module, configured to, when the number of queuing customers in the bank branch is greater than the specified threshold, send a request to the bank server to obtain the customer information of the first customer category of the bank branch among the queuing customers, and receive the first customer category of the bank branch fed back by the bank server; A business request processing module, configured to, when the bank branch receives a business request from a customer, determine whether the customer is the first customer category. If so, based on the customer information of the customer stored in the bank branch, process the business request of the customer. Otherwise, send the business request of the customer to the bank server and receive the business processing result fed back by the bank server.

10. The device according to claim 9, characterized in that, The account classification module is specifically configured to: For each account number, take the business volume corresponding to each business in the historical business data of the account as the business volume of the account corresponding to the business; For each business, determine the function of the business, where the independent variable of the function is any two account numbers, and the corresponding function value is the difference between the business volumes of the two account numbers corresponding to the business; Determine the distance function of the account according to the functions of each business; Classify the accounts of the bank according to the distance function of the account to obtain multiple account categories.

11. The device according to claim 9, characterized in that The business analysis module is specifically configured to: Take the time range corresponding to the business data of the account category as the first time range; For each unit of time within the first time range, use the business data corresponding to the unit of time in the business data of this account category as the sample business data of this account category; Use the proportion of the number of risk-involved businesses in each sample business data of this account category as the sample of the business risk coefficient corresponding to this account category, and use the business volume included in each sample business data of this account category as the sample of the business frequency corresponding to this account category; Determine the business risk coefficient corresponding to this account category based on the sample of the business risk coefficient corresponding to this account category, and determine the business frequency corresponding to this account category based on the sample of the business frequency corresponding to this account category.

12. The device according to claim 9, characterized in that, The first account category determination module is specifically used for: Determine the partial order of account categories based on the business risk coefficient and business frequency. Among them, for any two account categories in multiple account categories, when the business risk coefficient corresponding to the first account category among the two account categories is less than or equal to the business risk coefficient corresponding to the second account category among the two account categories, and the business frequency corresponding to the first account category is greater than or equal to the business frequency corresponding to the second account category, then determine that the first account category is superior to the second account category; Select the first account category from multiple account categories according to the partial order of account categories.

13. The device according to claim 12, characterized in that, The first account category determination module is specifically used for: Initialize the partial order maximum flag corresponding to each account category in multiple account categories to pending, and initialize the comparison boolean value corresponding to each account category to yes; Add account categories to the account category queue in ascending order of the corresponding business risk coefficients; Loop through the following steps until the account category queue is empty: S1: Take out the head account category a from the queue; S2: If the partial order maximum flag corresponding to the head account category a is not pending, continue to execute step S1. If the partial order maximum flag corresponding to the head account category a is pending, sequentially execute steps S3 to S4: S3: According to the partial order of account categories, compare each account category b other than the head account category a in all account categories with the comparison boolean value of yes with the head account category a in turn; if the account category b is superior to the head account category a, set the partial order maximum flag corresponding to the account category a to no, and then continue to execute step S1; If the head account category a is superior to the account category b, set the partial order maximum flag corresponding to the account category b to no, and use the account category b as the secondary account category of the head account category a; If the head account category a is not superior to the account category b and the account category b is not superior to the head account category a, the partial order maximum flags corresponding to the head account category a and the account category b remain unchanged; S4: If it is confirmed that each account category other than the head account category a in all account categories with the comparison boolean value of yes is not superior to the head account category a, determine the head account category a as the first account category, and update the comparison boolean value of each secondary account category of the head account category a to no.

14. The device according to claim 9, characterized in that, The first customer category determination module is specifically used for: Obtain the customer set corresponding to the business data of the bank branch; For each customer in the customer set, if the customer has an account number belonging to the first account category in the bank, add the customer to the first customer category corresponding to the bank branch.

15. The device according to claim 9, characterized in that, It further includes a second customer category determination module for: Take the maximum value of the business risk coefficients corresponding to all the first account categories as the business risk coefficient threshold, and take the minimum value of the business frequencies corresponding to all the first account categories as the business frequency threshold; For each account category among multiple account categories, if the business risk coefficient corresponding to the account category is less than or equal to the business risk coefficient threshold and the business frequency corresponding to the account category is greater than or equal to the business frequency threshold, then take the account category as the second account category; For each customer in the customer set corresponding to the business data of the bank branch, if the customer has an account number belonging to the second account category in the bank, add the customer to the second customer category corresponding to the bank branch.

16. The device according to claim 15, characterized in that, The request analysis module is specifically used for: When the first customer category of the bank branch is empty, receive the second customer category of the bank branch fed back by the bank server.

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

18. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, it implements the method according to any one of claims 1 to 8.

19. A computer program product, characterized in that, The computer program product includes a computer program, and when the computer program is executed by the processor, it implements the method according to any one of claims 1 to 8.

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