Bank branch operation time management method and system

Abstract

The present invention proposes a management method and system for bank branch operation time, which relates to the technical field of financial data processing. The method comprises: obtaining customer data of all bank branches within a preset range, performing cluster analysis on all bank branches according to the customer data, and obtaining multiple bank branch subsets; selecting multiple bank branches with the highest management efficiency, and determining the service customer time and the corresponding environmental payment transaction volume of each bank branch according to the customer data of each selected bank branch; determining the corresponding relationship between the service customer time and the environmental payment transaction volume according to the selected bank branch; for each unselected bank branch, determining the optimal service time of the unselected bank branch according to the bank branch subset to which it belongs; constructing a transaction volume change curve of the unselected bank branch; and determining the main rest time of the bank branch according to the transaction volume change curve and the optimal service time of the unselected bank branch.

Description

Technical Field

[0001] The present invention relates to the technical field of financial data processing, and in particular to a method and system for managing the operating hours of bank outlets. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the invention recited in the claims. No admission is made that the description herein is prior art by inclusion in this section.

[0003] At present, the working hours of bank branches are fixed. When there are many customer services, the bank will be busy, and when there are few customer services, it will waste bank resources.

[0004] In summary, there is an urgent need for a technical solution that can overcome the above-mentioned defects, improve the utilization rate of bank resources and reduce resource waste. Summary of the invention

[0005] In order to solve the problems existing in the prior art, the present invention proposes a method and system for managing the operating hours of bank outlets, which can reasonably arrange the resource allocation of bank outlets and the working hours of staff, thereby improving resource utilization.

[0006] In a first aspect of an embodiment of the present invention, a method for managing bank branch operating hours is proposed, comprising:

[0007] Obtain customer data of all bank branches within a preset range, perform cluster analysis on all bank branches based on the customer data, and obtain multiple bank branch subsets;

[0008] For each subset of bank outlets, multiple bank outlets with the highest management efficiency are selected, and based on the customer data of each selected bank outlet, the service customer time and the corresponding environmental payment transaction volume of each bank outlet are determined;

[0009] For each subset of bank outlets, determine the correspondence between the service customer time and the environmental payment transaction volume based on the selected bank outlets;

[0010] For each bank branch that is not selected, determine the optimal service time of the bank branch that is not selected according to the bank branch subset to which it belongs;

[0011] For each bank branch that is not selected, construct a transaction volume change curve of the bank branch that is not selected;

[0012] According to the transaction volume variation curve and optimal service duration of the bank branch that was not selected, the main rest time of the bank branch is determined.

[0013] In a second aspect of an embodiment of the present invention, a management system for bank branch operating hours is provided, comprising:

[0014] A cluster analysis module is used to obtain customer data of all bank outlets within a preset range, perform cluster analysis on all bank outlets based on the customer data, and obtain multiple bank outlet subsets;

[0015] A bank branch data processing module is used to select multiple bank branches with the highest management efficiency for each bank branch subset, and determine the service customer time and corresponding environmental payment transaction volume of each bank branch based on the customer data of each selected bank branch;

[0016] A bank branch subset data processing module is used to determine the corresponding relationship between the service customer time and the environmental payment transaction volume for each bank branch subset according to the selected bank branch;

[0017] The optimal service time determination module is used to determine the optimal service time of each unselected bank branch according to the bank branch subset to which it belongs;

[0018] A transaction volume change curve construction module is used to construct a transaction volume change curve of each unselected bank branch;

[0019] The main rest time determination module is used to determine the main rest time of the bank branch according to the transaction volume change curve and the optimal service time of the unselected bank branch.

[0020] In a third aspect of an embodiment of the present invention, a computer device is proposed, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements a method for managing the operating hours of bank branches when executing the computer program.

[0021] In a fourth aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, a method for managing the operating hours of bank branches is implemented.

[0022] In a fifth aspect of an embodiment of the present invention, a computer program product is proposed. The computer program product includes a computer program. When the computer program is executed by a processor, a method for managing the operating hours of bank branches is implemented.

[0023] The bank branch operation time management method and system proposed in the present invention obtains customer data of all bank branches within a preset range, performs cluster analysis on all bank branches according to the customer data, and obtains multiple bank branch subsets; for each bank branch subset, selects multiple bank branches with the highest management efficiency, and determines the service customer time and the corresponding environmental payment transaction volume of each bank branch according to the customer data of each selected bank branch; for each bank branch subset, determines the corresponding relationship between the service customer time and the environmental payment transaction volume according to the selected bank branch; for each unselected bank branch, determines the optimal service time of the unselected bank branch according to the bank branch subset to which it belongs; for each unselected bank branch, constructs a transaction volume change curve of the unselected bank branch; and The transaction volume change curve and the optimal service time are used to determine the main rest time of the bank branch, which can effectively overcome the problem that the working hours of bank branches are fixed. When there are more customer businesses, the bank business will be busy, and when the customer business is scarce, it will cause waste of bank resources. The present invention analyzes the relationship between bank branches through customer data, and then obtains the optimal service time of relevant bank branches based on data such as the service customer time and environmental payment volume of the bank branches. Then, the main rest time of the bank branch is determined by analyzing the transaction volume change curve and the optimal service time, so as to reasonably arrange the working hours of the bank branches, increase bank resources during busy times, and reduce bank resources during idle times. The resources of bank branches are managed according to data, which can effectively improve the operating efficiency of bank branches, improve resource utilization, and reduce waste of bank resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 The present invention is a flowchart of a method for managing bank branch operating hours according to an embodiment of the present invention.

[0026] Figure 2 It is a flowchart of determining the service customer time of each bank branch and the corresponding environmental payment transaction volume according to an embodiment of the present invention.

[0027] Figure 3 It is a flow chart of determining the correspondence between the service customer time and the environmental payment transaction volume according to an embodiment of the present invention.

[0028] Figure 4It is a schematic diagram of a process of determining the optimal service time of unselected bank outlets according to an embodiment of the present invention.

[0029] Figure 5 It is a schematic diagram of a process of constructing a transaction volume variation curve of unselected bank outlets according to an embodiment of the present invention.

[0030] Figure 6 The present invention is a schematic diagram of a process for determining the main rest time of a bank branch according to an embodiment of the present invention.

[0031] Figure 7 It is a schematic diagram of the relationship between time intervals according to an embodiment of the present invention.

[0032] Figure 8 It is a flowchart of determining the main rest time of a bank branch according to another embodiment of the present invention.

[0033] Fig. 9 The present invention is a schematic diagram of a management system architecture for bank branch operating hours according to an embodiment of the present invention.

[0034] Fig.10 It is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present invention, and are not intended to limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0036] Those skilled in the art will appreciate that the embodiments of the present invention may be implemented as a system, device, apparatus, method or computer program product. Therefore, the present disclosure may be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0037] According to an embodiment of the present invention, a method and system for managing the operating hours of bank outlets are proposed, which relate to the technical field of financial data processing.

[0038] The principle and spirit of the present invention are explained in detail below with reference to several representative embodiments of the present invention.

[0039] Figure 1 FIG. 1 is a flow chart of a method for managing bank branch operating hours according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0040] S1, obtaining customer data of all bank outlets within a preset range, performing cluster analysis on all bank outlets based on the customer data, and obtaining multiple bank outlet subsets;

[0041] S2, for each subset of bank outlets, select multiple bank outlets with the highest management efficiency, and determine the service customer time and corresponding environmental payment transaction volume of each bank outlet based on the customer data of each selected bank outlet;

[0042] S3, for each bank branch subset, determine the corresponding relationship between the service customer time and the environmental payment transaction volume according to the selected bank branches;

[0043] S4, for each bank branch that is not selected, determine the optimal service time of the bank branch that is not selected according to the bank branch subset to which it belongs;

[0044] S5, for each bank branch that is not selected, construct a transaction volume change curve of the bank branch that is not selected;

[0045] S6, determining the main rest time of the bank branch according to the transaction volume change curve and the optimal service time of the bank branch that is not selected.

[0046] In order to explain more clearly the above-mentioned management method of bank branch operating hours, each step is explained in detail below.

[0047] In S1, customer data of all bank branches within a preset range are obtained, and cluster analysis is performed on all bank branches based on the customer data to obtain multiple bank branch subsets.

[0048] In actual application scenarios, different bank branches serve different customer groups, and the correspondence between the length of time they serve customers and the amount of environmental payment transactions is different. However, since the data of one bank branch is too little, it cannot be used to predict the correspondence of other bank branches, and the correspondence of all bank branches is definitely not consistent. In this regard, the present invention clusters bank branches based on customer data to solve the above problem. In this way, it can be ensured that the correspondence of each bank branch in the same bank branch subset is roughly consistent, and the data is sufficient to obtain more accurate results; and the correspondence of bank branch subsets can also be predicted based on the similarity of clustering connotations.

[0049] Specifically, for each bank branch, based on the customer data of the bank branch, the data of the bank branch in multiple dimensions are determined, and the multiple dimensions include: number of customers, average transaction volume, average payment amount, cash demand, and non-cash re-empty demand. The main transaction category of the bank branch can also be determined, and the main transaction category is the transaction category with the largest transaction volume of the bank branch. The transaction volume refers to the number of transactions, not the amount of the transaction.

[0050] For each of the multiple dimensions, a distance function of the dimension can be set, and the distance function can calculate the distance between any two values ​​of the dimension. In this way, the distance function corresponding to the bank branch can be determined according to the distance function of each dimension. For example, the distance function corresponding to the bank branch is set to the Pth root of the weighted sum of the Pth power of the distance function of each dimension, where P is a positive integer, for example, P is selected to be equal to 2.

[0051] According to the distance function corresponding to the bank outlets, the bank outlets are clustered and analyzed to obtain multiple bank outlet subsets. The clustering algorithm may be K-means.

[0052] It is also possible to perform cluster analysis on bank branches using learning vector quantization based on the distance function corresponding to the bank branches and taking the main transaction categories as category identifiers to obtain multiple bank branch subsets.

[0053] Clustering can also be performed in the following way. Specifically, the specific process of a method for clustering analysis of all bank branches is as follows:

[0054] S101, selecting a plurality of bank outlets from the bank outlets as cluster centers, each cluster center corresponds to a bank outlet subset, and the initial elements of the bank outlet subset only include the bank outlets corresponding to the corresponding cluster center;

[0055] S102, for each bank branch, perform the following steps:

[0056] According to the customer data of the bank branch, multiple cluster centers that are consistent with the main transaction category of the bank branch are selected from all the cluster centers, and the distance between each selected cluster center and the bank branch is calculated based on the distance function corresponding to the bank branch. Then, the minimum value is selected from the multiple distances as the minimum distance of the same category corresponding to the bank branch, and the bank branch subset corresponding to the minimum value is used as the first bank branch subset corresponding to the bank branch; for each cluster center selected that is consistent with the main transaction category of the bank branch, the distance between each bank branch of the bank branch subset corresponding to the cluster center and the bank branch is calculated based on the distance function corresponding to the bank branch, and the minimum value of the distance is determined as the boundary distance between the cluster center and the bank branch; then, the minimum value is selected from the multiple boundary distances corresponding to the bank branch and the selected multiple cluster centers that are consistent with the main transaction category of the bank branch as the minimum boundary distance of the same category corresponding to the bank branch, and the bank branch subset corresponding to the cluster center corresponding to the minimum value is used as the second bank branch subset corresponding to the bank branch;

[0057] Select multiple cluster centers that are inconsistent with the main transaction category of the bank branch from all cluster centers, calculate the distance between each selected cluster center and the bank branch based on the distance function corresponding to the bank branch, and then select the minimum value from the multiple distances as the minimum distance of different categories corresponding to the bank branch; for each selected cluster center that is inconsistent with the main transaction category of the bank branch, calculate the distance between each bank branch of the bank branch subset corresponding to the cluster center and the bank branch based on the distance function corresponding to the bank branch, and determine the minimum value of the distance as the boundary distance between the cluster center and the bank branch; then select the minimum value from the multiple boundary distances corresponding to the bank branch and the selected multiple cluster centers that are inconsistent with the main transaction category of the bank branch as the minimum boundary distance of different categories corresponding to the bank branch;

[0058] If the absolute value of the difference between the corresponding minimum distance of the same category and the corresponding minimum distance of different categories is greater than or equal to the absolute value of the difference between the corresponding minimum boundary distance of the same category and the corresponding minimum boundary distance of different categories, and the corresponding minimum boundary distance of the same category is less than the corresponding minimum boundary distance of different categories, then the bank branch is classified into the second bank branch subset corresponding to the bank branch;

[0059] If the absolute value of the difference between the corresponding minimum distance of the same category and the corresponding minimum distance of different categories is smaller than the absolute value of the difference between the corresponding minimum boundary distance of the same category and the corresponding minimum boundary distance of different categories, and the corresponding minimum distance of the same category is smaller than the corresponding minimum distance of different categories, the bank branch is classified into the first bank branch subset corresponding to the bank branch;

[0060] Otherwise, a new cluster center is created based on the bank branch, the new cluster center corresponds to a new bank branch subset, and the initial elements of the new bank branch subset only include the bank branch corresponding to the corresponding cluster center (that is, the bank branch);

[0061] S103, after executing the above step (S102) for all bank outlets, for each bank outlet subset, based on the data and main transaction categories of all bank outlets in the bank outlet subset in multiple dimensions, determine the data and main transaction categories of the mean center corresponding to the bank outlet subset in multiple dimensions, as well as the change value corresponding to the bank outlet subset; wherein the change value corresponding to the bank outlet subset is determined based on the cluster center corresponding to the bank outlet subset and the mean center corresponding to the bank outlet subset;

[0062] S104, if there is a bank branch subset whose corresponding change value is greater than the preset threshold, multiple cluster centers are newly set based on the mean center obtained in the above steps, each newly set cluster center corresponds to a new bank branch subset, and the initial elements of the new bank branch subset only include the corresponding newly set cluster center; then, based on the newly set cluster center and the new bank branch subset, the above steps (S102) are continued to be performed for each bank branch, and the data and main transaction categories of the mean center corresponding to each bank branch subset in multiple dimensions, as well as the change value corresponding to each bank branch subset (S103) are determined, until the change values ​​corresponding to all bank branch subsets are less than or equal to the preset threshold;

[0063] S105: If the change values ​​corresponding to all bank branch subsets are less than or equal to a preset threshold, the cluster analysis of the bank branches is stopped, thereby obtaining a plurality of bank branch subsets.

[0064] In actual application scenarios, for each subset of bank outlets, based on the data and main transaction categories of all bank outlets in the subset of bank outlets in multiple dimensions, the data and main transaction categories of the cluster center corresponding to the subset of bank outlets in multiple dimensions, as well as the change value corresponding to the subset of bank outlets are determined. Specifically, the following steps can be followed: for each dimension of the multiple dimensions, the mean of the data values ​​of all bank outlets in the subset of bank outlets in the dimension can be used as the data value of the cluster center corresponding to the subset of bank outlets in the dimension; for the main transaction category, the data value with the largest number among the main transaction categories of all bank outlets in the subset of bank outlets can be used as the main transaction category of the cluster center corresponding to the subset of bank outlets; for each dimension of the multiple dimensions, the difference between the two values ​​corresponding to the dimension between the cluster center corresponding to the subset of bank outlets and the corresponding mean center is determined, the difference is used as the difference value corresponding to the dimension, and the square root of the weighted sum of the squares of the differences corresponding to all dimensions is used as the change value corresponding to the subset of bank outlets.

[0065] Among them, the main transaction category is the transaction type with the largest number of transactions in a bank branch. The main transaction category is directly related to the needs of the bank branch. In the classification of bank branches, the needs of the bank branches are essential. The above clustering method can make the main transaction categories of the bank branches that are assigned to the same bank branch subset the same. By ensuring that the main transaction categories of the bank branches in the same bank branch subset are the same, the accuracy of clustering can be improved, that is, the bank branches assigned to the same bank branch subset are roughly the same.

[0066] In S2, reference Figure 2 For each bank branch subset, multiple bank branches with the highest management efficiency are selected. According to the customer data of each selected bank branch, the specific process of determining the service customer time of each bank branch and the corresponding environmental payment transaction volume includes:

[0067] S201, selecting a plurality of bank outlets with the highest management efficiency; wherein, according to the management data of each bank outlet, determining the proportion of abnormal management data corresponding to the bank outlet, and taking the bank outlet whose corresponding proportion of abnormal management data is less than a first threshold as the bank outlet with the highest management efficiency;

[0068] S202, for each selected bank branch, determining the service time data of the bank branch in a certain period of time, and taking the average of the service time as the service time of the bank branch;

[0069] S203, for each selected bank branch, obtaining payment transaction data of multiple payment locations within a set distance range of the bank branch within a certain time range, and taking the average of the payment transaction volume within the time range as the environmental payment transaction volume of the bank branch.

[0070] In this embodiment, the payment transaction volume refers to the number of transactions.

[0071] It should be noted that if the service time of a bank branch is too long and it is idle for a long time, or if the service time is too short and customers have to wait too long, these can be reflected in the abnormal management data in the management data of the bank branch. The smaller the proportion of abnormal management data in the management data of the bank branch, the more reasonable the setting of the service time of the bank branch is.

[0072] In one embodiment, based on the management data of each bank branch, the proportion of abnormal management data corresponding to the bank branch can be determined according to the following method: obtain the management data of the bank branch in a first period, and for each day in the first period, determine the ratio of the amount of abnormal management data to the amount of management data in the management data of the bank branch on that day, and use the ratio as the proportion of abnormal management data of the bank branch on that day; determine the variance σ based on the proportion of abnormal management data of all days of the bank branch in the first period (the proportion of abnormal management data of each day in the first period is regarded as a sample); and set a second threshold value according to the variance σ Where ε is an acceptable error threshold for the proportion of abnormal management data, and P is the probability that the acceptable error for the proportion of abnormal management data is greater than ε; select a second period so that the number of days included in the second period is greater than the second threshold; for each day in the second period, determine the proportion of the amount of abnormal management data to the amount of management data in the management data of the bank branch on that day, and use this proportion as the proportion of abnormal management data of the bank branch on that day; use the average of the proportion of abnormal management data of the bank branch on all days in the second period as the proportion of abnormal management data corresponding to the bank branch.

[0073] According to the law of large numbers, the more data there is, the more accurate the calculation of the proportion of abnormal management data is, so the number of days corresponding to the management data is required to be greater than the second threshold.

[0074] In S3, reference Figure 3 ,For each bank outlet subset, the specific process of determining the correspondence between the service customer time and the environmental payment transaction volume according to the selected bank outlets includes:

[0075] S301, establishing a relationship sample corresponding to each selected bank branch according to the service customer time and the corresponding environmental payment transaction volume of the bank branch; wherein the relationship sample is a point in a two-dimensional coordinate system, the horizontal axis is the service customer time, and the vertical axis is the environmental payment transaction volume;

[0076] S302: Perform function fitting based on the relationship sample to obtain a relationship function between the customer service time and the environmental payment transaction volume.

[0077] It should be noted that the financial transaction data of the customer group within the preset range includes: payment transactions around bank outlets, and transaction data at bank outlets. Both types of transaction data are external manifestations of the internal needs of the customer group, and there is a connection between them, that is, there is a relationship between the two types of transaction data.

[0078] In S4, ref. Figure 4 For each bank branch that is not selected, the specific process of determining the optimal service time of the bank branch that is not selected according to the bank branch subset to which it belongs includes:

[0079] S401, obtaining the environmental payment transaction volume of the unselected bank outlets;

[0080] S402, determining the customer service time corresponding to the payment transaction volume in the environment according to the correspondence between the bank branch subsets to which the unselected bank branch belongs, and using the customer service time as the optimal service time of the unselected bank branch.

[0081] In S5, ref. Figure 5 , for each bank branch that is not selected, the specific process of constructing the transaction volume change curve of the bank branch that is not selected includes:

[0082] S501, selecting multiple discrete moments;

[0083] S502, for each discrete moment, obtaining the historical transaction data of the unselected bank branch at the discrete moment, and using the average transaction volume of the historical transaction data as the transaction volume corresponding to the discrete moment;

[0084] S503, establish a plane coordinate system, wherein the horizontal axis is time and the vertical axis is transaction volume; each discrete moment corresponds to a point in the plane coordinate system, and all points are continuous to obtain a transaction volume change curve of the unselected bank branch.

[0085] In S6, reference Figure 6 , according to the transaction volume change curve and optimal service time of the unselected bank branch, the specific process of determining the main rest time of the bank branch includes:

[0086] S601, subtract the best service time from the business hours of the unselected bank branch to obtain the main rest time;

[0087] S602, marking multiple minimum value points of the transaction volume change curve in the transaction volume change curve, and selecting a first transaction volume so as to meet the following conditions: marking the first transaction volume in the transaction volume change curve, and determining the time point corresponding to the first transaction volume; constructing time intervals of two adjacent time points according to the time point corresponding to the first transaction volume, the business start time and the business end time of the bank branch, and selecting multiple time intervals containing the time of the marked minimum value point and the transaction volume corresponding to the minimum value point is less than or equal to the first transaction volume from all the constructed time intervals, and the total duration of the multiple time intervals is equal to the main rest duration;

[0088] S603, from all time intervals constructed from the time point corresponding to the first transaction volume and two adjacent time points of the bank branch's business start time and business end time, select multiple time intervals that include the time corresponding to the minimum point and the transaction volume corresponding to the minimum point is less than or equal to the first transaction volume, and use the multiple time intervals as the main rest time of the bank branch that was not selected.

[0089] It should be noted that the main rest time is the rest time for most employees of the bank branch, not the closing time of the bank branch.

[0090] In this embodiment, the minimum value is a minimum point of a function curve, and the function value of this point is less than or equal to the function value of the points around this point. Through the minimum point, we want to find the time interval when the corresponding transaction volume is less than or equal to the transaction volume. In fact, any point in this time can be found, but the minimum point has obvious characteristics and is easier to find.

[0091] Specifically, refer to Figure 7 The relationship diagram is shown; in this trading volume change curve, four minimum points can be marked.

[0092] Based on the transaction volume change curve, the first transaction volume is selected so as to satisfy the following conditions:

[0093] like Figure 7 As shown, a straight line corresponding to the first trading volume is drawn in the trading volume change curve (the straight line is parallel to the time axis, and the corresponding trading volume is the first trading volume).

[0094] Based on the straight line, multiple intersection points between the straight line and the trading volume change curve can be obtained; the multiple intersection points are the first trading volume marked in the trading volume change curve, and then based on the multiple intersection points, the time point corresponding to the first trading volume is determined.

[0095] According to the time points, business start time, and business end time corresponding to the multiple intersection points, multiple time intervals of adjacent time points, namely, interval AI, are constructed respectively.

[0096] From all constructed time intervals, multiple time intervals (intervals A, C, E, G, I) are selected that contain the time of the marked minimum point and the trading volume corresponding to the minimum point is less than or equal to the first trading volume, and the total duration of the multiple time intervals is equal to the main rest duration.

[0097] Further, based on the determined first transaction volume, multiple time intervals including the time corresponding to the minimum point and the transaction volume corresponding to the minimum point is selected from all time intervals composed of the intersection of the determined first transaction volume and the transaction volume change curve, and the multiple time intervals are used as the main rest time of the unselected bank branch, that is, intervals A, C, E, G, and I are used as the main rest time of the unselected bank branch.

[0098] In another embodiment of the present invention, another method of determining the main rest time of a bank branch according to the transaction volume change curve of the unselected bank branch and the optimal service time (same as above, the main rest time is equal to the difference between the business hours of the unselected bank branch and the optimal service time) is described in detail. Figure 8 .like Figure 8 As shown, the method includes:

[0099] S81, determining the minimum and maximum points of the trading volume change curve;

[0100] S82, for each minimum point or maximum point, determine the time points corresponding to all intersections of the straight line corresponding to the trading volume corresponding to the extreme point and the trading volume change curve, construct a corresponding time interval for every two adjacent time points, and from all the constructed time intervals, select multiple time intervals in which the function value of the trading volume change curve corresponding to the corresponding time point is less than or equal to the trading volume corresponding to the extreme point, and calculate the duration of the selected multiple time intervals, and use the duration as the duration corresponding to the extreme point.

[0101] S83, from all the minimum value points or maximum value points, find multiple extreme value points whose corresponding duration is less than or equal to the main rest duration, find the extreme value point with the largest corresponding duration from the multiple extreme value points, and use the transaction volume corresponding to the extreme value point as the left endpoint of the main rest duration;

[0102] S84, from all the minimum value points or maximum value points, find multiple extreme value points whose corresponding duration is greater than or equal to the main rest duration, find the extreme value point with the smallest corresponding duration from the multiple extreme value points, and use the transaction volume corresponding to the extreme value point as the right endpoint of the main rest duration;

[0103] S85, the left endpoint and the right endpoint of the main rest time constitute an interval, and the interval is discretized to obtain multiple discrete transaction volumes.

[0104] S86, for each discrete trading volume, determine the time points corresponding to all the intersections of the straight line corresponding to the discrete trading volume and the trading volume change curve, construct a corresponding time interval for every two adjacent time points, and from all the constructed time intervals, select multiple time intervals whose function values ​​of the corresponding time points corresponding to the trading volume change curve are less than or equal to the discrete trading volume, use the selected multiple time intervals as the time intervals corresponding to the discrete trading volume, and calculate the duration of the selected multiple time intervals, and use the duration as the duration corresponding to the discrete trading volume.

[0105] S87, from all discrete trading volumes, find multiple discrete trading volumes whose corresponding duration is less than or equal to the main rest duration, find the discrete trading volume with the largest corresponding duration from the multiple discrete trading volumes, and use the discrete trading volume as the lower bound discrete trading volume of the main rest duration;

[0106] S88, from all discrete trading volumes, find multiple discrete trading volumes whose corresponding duration is greater than or equal to the main rest duration, find the discrete trading volume with the smallest corresponding duration from the multiple discrete trading volumes, and use the discrete trading volume as the upper bound discrete trading volume of the main rest duration;

[0107] S89, determining the main rest time of the bank branch according to the time interval corresponding to the lower limit discrete transaction volume of the main rest time and the time interval corresponding to the upper limit discrete transaction volume.

[0108] It should be noted that, although the operations of the method of the present invention are described in a specific order in the above embodiments and the accompanying drawings, this does not require or imply that the operations must be performed in the specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0109] After introducing the method of the exemplary embodiment of the present invention, next, refer to Fig. 9 A management system for bank branch operating hours according to an exemplary embodiment of the present invention is introduced.

[0110] The implementation of the management system of bank branch operation time can refer to the implementation of the above method, and the repeated parts will not be repeated. The term "module" or "unit" used below can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware is also possible and conceived.

[0111] Based on the same inventive concept, the present invention also proposes a management system for bank branch operation hours, such as Fig. 9 As shown, the system includes:

[0112] Cluster analysis module 110, used to obtain customer data of all bank outlets within a preset range, perform cluster analysis on all bank outlets according to the customer data, and obtain multiple bank outlet subsets;

[0113] The bank branch data processing module 120 is used to select a plurality of bank branches with the highest management efficiency for each bank branch subset, and determine the service customer time and corresponding environmental payment transaction volume of each bank branch according to the customer data of each selected bank branch;

[0114] The bank branch subset data processing module 130 is used to determine the corresponding relationship between the service customer time and the environmental payment transaction volume for each bank branch subset according to the selected bank branch;

[0115] The best service duration determination module 140 is used to determine the best service duration of each unselected bank branch according to the bank branch subset to which it belongs;

[0116] A transaction volume change curve construction module 150 is used to construct a transaction volume change curve of each unselected bank branch;

[0117] The main rest time determination module 160 is used to determine the main rest time of the bank branch according to the transaction volume change curve and the optimal service duration of the unselected bank branch.

[0118] In one embodiment, the bank branch data processing module 120 is specifically used for:

[0119] Selecting multiple bank branches with the highest management efficiency; wherein, according to the management data of each bank branch, determining the proportion of abnormal management data corresponding to the bank branch, and taking the bank branch whose corresponding abnormal management data proportion is less than a first threshold as the bank branch with the highest management efficiency;

[0120] For each selected bank branch, determine the service time data of the bank branch in a certain period of time, and take the average service time as the service time of the bank branch;

[0121] For each selected bank branch, payment transaction data of multiple payment locations within a set distance range of the bank branch within a certain time range is obtained, and the average of the payment transaction volume within the time range is used as the environmental payment transaction volume of the bank branch.

[0122] In one embodiment, the bank branch subset data processing module 130 is specifically used for:

[0123] According to the service customer time and the corresponding environmental payment transaction volume of each selected bank branch, a relationship sample corresponding to the bank branch is established; wherein the relationship sample is a point in a two-dimensional coordinate system, the horizontal axis is the service customer time, and the vertical axis is the environmental payment transaction volume;

[0124] Function fitting is performed based on the relationship samples to obtain a relationship function between the customer service time and the environmental payment transaction volume.

[0125] In one embodiment, the optimal service duration determination module 140 is specifically used to:

[0126] Obtain the environmental payment transaction volume of the unselected bank branch;

[0127] According to the correspondence between the bank branch subsets to which the unselected bank branch belongs, the customer service time corresponding to the payment transaction volume in the environment is determined, and the customer service time is used as the optimal service time of the unselected bank branch.

[0128] In one embodiment, the transaction volume change curve construction module 150 is specifically used for:

[0129] Select multiple discrete moments;

[0130] For each discrete moment, the historical transaction data of the unselected bank branch at the discrete moment is obtained, and the average transaction volume of the historical transaction data is used as the transaction volume corresponding to the discrete moment;

[0131] A plane coordinate system is established, wherein the horizontal axis is time and the vertical axis is transaction volume; each discrete moment corresponds to a point in the plane coordinate system, and all points are made continuous to obtain a transaction volume change curve of the unselected bank branch.

[0132] In one embodiment, the main rest time determination module 160 is specifically used to:

[0133] Subtract the best service time from the business hours of the unselected bank branch to obtain the main rest time;

[0134] Marking multiple minimum points of the transaction volume change curve in the transaction volume change curve, and selecting the first transaction volume so as to meet the following conditions: marking the first transaction volume in the transaction volume change curve, and determining the time point corresponding to the first transaction volume; constructing time intervals of two adjacent time points according to the time point corresponding to the first transaction volume, the business start time and the business end time of the bank branch, and selecting multiple time intervals containing the time of the marked minimum point and the transaction volume corresponding to the minimum point is less than or equal to the first transaction volume from all the constructed time intervals, and the total duration of the multiple time intervals is equal to the main rest duration;

[0135] From all time intervals constructed from the time point corresponding to the first transaction volume and two adjacent time points of the bank branch's business start and end, select multiple time intervals that include the time corresponding to the minimum point and whose transaction volume corresponding to the minimum point is less than or equal to the first transaction volume, and use the multiple time intervals as the main rest time of the unselected bank branch.

[0136] It should be noted that, although several modules of the management system of bank branch operation hours are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules described above can be embodied in one module. Conversely, the features and functions of one module described above can be further divided into multiple modules to be embodied.

[0137] Based on the above invention concept, Fig.10 As shown, the present invention also proposes a computer device 1000, including a memory 1010, a processor 1020, and a computer program 1030 stored in the memory 1010 and executable on the processor 1020, wherein the processor 1020 implements the aforementioned method for managing the operating hours of bank branches when executing the computer program 1030.

[0138] Based on the aforementioned inventive concept, the present invention proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the aforementioned method for managing the operating hours of bank outlets is implemented.

[0139] Based on the aforementioned inventive concept, the present invention proposes a computer program product, which includes a computer program, and when the computer program is executed by a processor, a method for managing the operating hours of bank branches is implemented.

[0140] The bank branch operation time management method and system proposed in the present invention obtains customer data of all bank branches within a preset range, performs cluster analysis on all bank branches according to the customer data, and obtains multiple bank branch subsets; for each bank branch subset, selects multiple bank branches with the highest management efficiency, and determines the service customer time and the corresponding environmental payment transaction volume of each bank branch according to the customer data of each selected bank branch; for each bank branch subset, determines the corresponding relationship between the service customer time and the environmental payment transaction volume according to the selected bank branch; for each unselected bank branch, determines the optimal service time of the unselected bank branch according to the bank branch subset to which it belongs; for each unselected bank branch, constructs a transaction volume change curve of the unselected bank branch; and The transaction volume change curve and the optimal service time are used to determine the main rest time of the bank branch, which can effectively overcome the problem that the working hours of bank branches are fixed. When there are more customer businesses, the bank business will be busy, and when the customer business is scarce, it will cause waste of bank resources. The present invention analyzes the relationship between bank branches through customer data, and then obtains the optimal service time of relevant bank branches based on data such as the service customer time and environmental payment volume of the bank branches. Then, the main rest time of the bank branch is determined by analyzing the transaction volume change curve and the optimal service time, so as to reasonably arrange the working hours of the bank branches, increase bank resources during busy times, and reduce bank resources during idle times. The resources of bank branches are managed according to data, which can effectively improve the operating efficiency of bank branches, improve resource utilization, and reduce waste of bank resources.

[0141] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0142] The present invention is described with reference to flowcharts and / or block diagrams of methods and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0143] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0144] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0145] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for managing the operating hours of bank outlets, characterized in that: include: Obtain customer data of all bank branches within a preset range, perform cluster analysis on all bank branches based on the customer data, and obtain multiple bank branch subsets; For each subset of bank outlets, multiple bank outlets with the highest management efficiency are selected, and based on the customer data of each selected bank outlet, the service customer time and the corresponding environmental payment transaction volume of each bank outlet are determined; For each subset of bank outlets, determine the correspondence between the service customer time and the environmental payment transaction volume based on the selected bank outlets; For each bank branch that is not selected, determine the optimal service time of the bank branch that is not selected according to the bank branch subset to which it belongs; For each bank branch that is not selected, construct a transaction volume change curve of the bank branch that is not selected; Determine the main rest time of the bank branch based on the transaction volume change curve and optimal service time of the bank branch that was not selected; Among them, according to the transaction volume change curve and the optimal service time of the bank branch that was not selected, the main rest time of the bank branch is determined, including: Subtract the best service time from the business hours of the unselected bank branch to obtain the main rest time; Marking multiple minimum points of the transaction volume change curve in the transaction volume change curve, and selecting the first transaction volume so as to meet the following conditions: marking the first transaction volume in the transaction volume change curve, and determining the time point corresponding to the first transaction volume; constructing time intervals of two adjacent time points according to the time point corresponding to the first transaction volume, the business start time and the business end time of the bank branch, and selecting multiple time intervals containing the time of the marked minimum point and the transaction volume corresponding to the minimum point is less than or equal to the first transaction volume from all the constructed time intervals, and the total duration of the multiple time intervals is equal to the main rest duration; From all time intervals constructed from the time point corresponding to the first transaction volume and two adjacent time points of the bank branch's business start and end, select multiple time intervals that include the time corresponding to the minimum point and whose transaction volume corresponding to the minimum point is less than or equal to the first transaction volume, and use the multiple time intervals as the main rest time of the unselected bank branch.

2. The method according to claim 1, characterized in that For each bank branch subset, multiple bank branches with the highest management efficiency are selected, and based on the customer data of each selected bank branch, the service customer time and the corresponding environmental payment transaction volume of each bank branch are determined, including: Selecting multiple bank branches with the highest management efficiency; wherein, according to the management data of each bank branch, determining the proportion of abnormal management data corresponding to the bank branch, and taking the bank branch whose corresponding abnormal management data proportion is less than a first threshold as the bank branch with the highest management efficiency; For each selected bank branch, determine the service time data of the bank branch in a certain period of time, and take the average service time as the service time of the bank branch; For each selected bank branch, payment transaction data of multiple payment locations within a set distance range of the bank branch within a certain time range is obtained, and the average of the payment transaction volume within the time range is used as the environmental payment transaction volume of the bank branch.

3. The method according to claim 1, characterized in that For each bank branch subset, the corresponding relationship between the service customer time and the environmental payment transaction volume is determined according to the selected bank branches, including: According to the service customer time and the corresponding environmental payment transaction volume of each selected bank branch, a relationship sample corresponding to the bank branch is established; wherein the relationship sample is a point in a two-dimensional coordinate system, the horizontal axis is the service customer time, and the vertical axis is the environmental payment transaction volume; Function fitting is performed based on the relationship samples to obtain a relationship function between the customer service time and the environmental payment transaction volume.

4. The method according to claim 2, characterized in that: For each bank branch that is not selected, the optimal service time of the bank branch that is not selected is determined according to the bank branch subset to which it belongs, including: Obtain the environmental payment transaction volume of the unselected bank branch; According to the correspondence between the bank branch subsets to which the unselected bank branch belongs, the customer service time corresponding to the payment transaction volume in the environment is determined, and the customer service time is used as the optimal service time of the unselected bank branch.

5. The method according to claim 1, characterized in that For each bank branch that is not selected, a transaction volume change curve of the bank branch that is not selected is constructed, including: Select multiple discrete moments; For each discrete moment, the historical transaction data of the unselected bank branch at the discrete moment is obtained, and the average transaction volume of the historical transaction data is used as the transaction volume corresponding to the discrete moment; A plane coordinate system is established, wherein the horizontal axis is time and the vertical axis is transaction volume; each discrete moment corresponds to a point in the plane coordinate system, and all points are made continuous to obtain a transaction volume change curve of the unselected bank branch.

6. A bank branch operation time management system, characterized in that: include: A cluster analysis module is used to obtain customer data of all bank outlets within a preset range, perform cluster analysis on all bank outlets based on the customer data, and obtain multiple bank outlet subsets; A bank branch data processing module is used to select multiple bank branches with the highest management efficiency for each bank branch subset, and determine the service customer time and corresponding environmental payment transaction volume of each bank branch based on the customer data of each selected bank branch; A bank branch subset data processing module is used to determine the corresponding relationship between the service customer time and the environmental payment transaction volume for each bank branch subset according to the selected bank branch; The optimal service time determination module is used to determine the optimal service time of each unselected bank branch according to the bank branch subset to which it belongs; A transaction volume change curve construction module is used to construct a transaction volume change curve of each unselected bank branch; A main rest time determination module, used to determine the main rest time of the bank branch according to the transaction volume change curve and the optimal service time of the unselected bank branch; Wherein, the main rest time determination module is specifically used for: Subtract the best service time from the business hours of the unselected bank branch to obtain the main rest time; Marking multiple minimum points of the transaction volume change curve in the transaction volume change curve, and selecting the first transaction volume so as to meet the following conditions: marking the first transaction volume in the transaction volume change curve, and determining the time point corresponding to the first transaction volume; constructing time intervals of two adjacent time points according to the time point corresponding to the first transaction volume, the business start time and the business end time of the bank branch, and selecting multiple time intervals containing the time of the marked minimum point and the transaction volume corresponding to the minimum point is less than or equal to the first transaction volume from all the constructed time intervals, and the total duration of the multiple time intervals is equal to the main rest duration; From all time intervals constructed from the time point corresponding to the first transaction volume and two adjacent time points of the bank branch's business start and end, select multiple time intervals that include the time corresponding to the minimum point and whose transaction volume corresponding to the minimum point is less than or equal to the first transaction volume, and use the multiple time intervals as the main rest time of the unselected bank branch.

7. The system according to claim 6, characterized in that The bank branch data processing module is specifically used for: Selecting multiple bank branches with the highest management efficiency; wherein, according to the management data of each bank branch, determining the proportion of abnormal management data corresponding to the bank branch, and taking the bank branch whose corresponding abnormal management data proportion is less than a first threshold as the bank branch with the highest management efficiency; For each selected bank branch, determine the service time data of the bank branch in a certain period of time, and take the average service time as the service time of the bank branch; For each selected bank branch, payment transaction data of multiple payment locations within a set distance range of the bank branch within a certain time range is obtained, and the average of the payment transaction volume within the time range is used as the environmental payment transaction volume of the bank branch.

8. The system according to claim 6, characterized in that The bank branch subset data processing module is specifically used for: According to the service customer time and the corresponding environmental payment transaction volume of each selected bank branch, a relationship sample corresponding to the bank branch is established; wherein the relationship sample is a point in a two-dimensional coordinate system, the horizontal axis is the service customer time, and the vertical axis is the environmental payment transaction volume; Function fitting is performed based on the relationship samples to obtain a relationship function between the customer service time and the environmental payment transaction volume.

9. The system according to claim 7, characterized in that The optimal service duration determination module is specifically used for: Obtain the environmental payment transaction volume of the unselected bank branch; According to the correspondence between the bank branch subsets to which the unselected bank branch belongs, the customer service time corresponding to the payment transaction volume in the environment is determined, and the customer service time is used as the optimal service time of the unselected bank branch.

10. The system according to claim 6, characterized in that The transaction volume change curve construction module is specifically used for: Select multiple discrete moments; For each discrete moment, the historical transaction data of the unselected bank branch at the discrete moment is obtained, and the average transaction volume of the historical transaction data is used as the transaction volume corresponding to the discrete moment; A plane coordinate system is established, wherein the horizontal axis is time and the vertical axis is transaction volume; each discrete moment corresponds to a point in the plane coordinate system, and all points are made continuous to obtain a transaction volume change curve of the unselected bank branch.

11. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

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

13. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

Images