Method and device for processing bank customer's mobile phone number change

Abstract

The present invention proposes a method and device for processing mobile phone number changes of bank customers, which relate to the field of data processing technology. The method includes: obtaining customer mobile phone number change data stored in a bank server; for each customer mobile phone number change data, determining a first vector and a second vector corresponding to the customer mobile phone number change data based on the mobile phone number before the change and the mobile phone number after the change, respectively; clustering the customer mobile phone number change data based on the first vector and the second vector to obtain multiple change data subsets; for each change data subset, determining the risk index of each identity confirmation method in the change data subset; when a request for modifying the mobile phone number initiated by the first customer is obtained, determining the change data subset corresponding to this request based on the request data; and determining the identity confirmation method corresponding to this request based on the risk index of each identity confirmation method in the change data subset corresponding to this request.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method and device for processing changes in mobile phone numbers of bank customers. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. No statement herein is admitted to be prior art by virtue of its inclusion in this section.

[0003] In banking scenarios, customers are required to reserve their mobile phone number when establishing a bank account. This mobile phone number is important personal identification information and is used to receive bank notifications, account activity reminders, and other information. It also serves as an important identification basis when handling banking business. When customers need to change their reserved mobile phone number, they generally need to go to the bank counter to handle the process, which is time-consuming and labor-intensive, and results in a poor customer experience.

[0004] In summary, there is an urgent need for a technical solution that can overcome the above-mentioned defects and can change the customer's mobile phone number conveniently and quickly. Summary of the Invention

[0005] In order to solve the problems existing in the prior art, the present invention proposes a method and device for processing a change in the mobile phone number of a bank customer.

[0006] In a first aspect of an embodiment of the present invention, a method for processing a mobile phone number change of a bank customer is proposed, comprising:

[0007] Obtain customer mobile phone number change data stored on the bank server;

[0008] For each customer's mobile phone number change data, determine the first vector and the second vector corresponding to the customer's mobile phone number change data based on the mobile phone number before the change and the mobile phone number after the change respectively;

[0009] Clustering the customer's mobile phone number change data based on the first vector and the second vector to obtain multiple change data subsets;

[0010] For each subset of changed data, determine the risk indicators of each identity confirmation method in the subset of changed data;

[0011] When a request to modify a mobile phone number is received from the first customer, the change data subset corresponding to the request is determined based on the request data;

[0012] Determine the identity confirmation method corresponding to this request based on the risk indicators of each identity confirmation method in the change data subset corresponding to this request.

[0013] In a second aspect of an embodiment of the present invention, a device for processing a mobile phone number change of a bank customer is provided, comprising:

[0014] A data acquisition module is used to obtain customer mobile phone number change data stored in the bank server;

[0015] A vector processing module is used to determine, for each customer's mobile phone number change data, a first vector and a second vector corresponding to the customer's mobile phone number change data based on the mobile phone number before the change and the mobile phone number after the change;

[0016] A clustering module, configured to cluster the customer mobile phone number change data based on the first vector and the second vector to obtain multiple change data subsets;

[0017] A risk indicator determination module is used to determine, for each change data subset, the risk indicator of each identity confirmation method in the change data subset;

[0018] A changed data subset determination module is configured to, upon receiving a request from a first customer to modify a mobile phone number, determine a changed data subset corresponding to the request based on the request data;

[0019] The identity confirmation method processing module is used to determine the identity confirmation method corresponding to this request based on the risk indicators of each identity confirmation method in the change data subset corresponding to this request.

[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 processing changes in mobile phone numbers of bank customers when executing the computer program.

[0021] In a fourth aspect of an embodiment of the present invention, a computer-readable storage medium is proposed, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, a method for processing a change in a mobile phone number of a bank customer 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 processing a change in a mobile phone number of a bank customer is implemented.

[0023] The present invention proposes a method and device for processing mobile phone number changes for bank customers, which obtains customer mobile phone number change data stored on a bank server; for each customer mobile phone number change data, determines a first vector and a second vector corresponding to the customer mobile phone number change data based on the mobile phone number before and after the change, respectively; clusters the customer mobile phone number change data based on the first and second vectors to obtain multiple change data subsets; for each change data subset, determines a risk indicator for each identity confirmation method in the change data subset; when a request to modify a mobile phone number initiated by a first customer is obtained, determines a change data subset corresponding to the request based on the request data; and determines an identity confirmation method corresponding to the request based on the risk indicators of each identity confirmation method in the change data subset corresponding to the request. Compared with the prior art in which customers need to go to a bank branch in person to handle the matter, the overall solution of the present invention determines the identity confirmation method for the customer's mobile phone number change by analyzing the customer mobile phone number change data, allowing customers to change their mobile phone numbers safely and conveniently online, improving the efficiency of mobile phone number changes, and enhancing the customer experience. It also effectively controls the risks of mobile phone number changes and protects customer information security. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. 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 any creative work.

[0025] Figure 1 The present invention is a flowchart of a method for changing a bank customer's mobile phone number according to an embodiment of the present invention.

[0026] Figure 2 It is a schematic diagram of a specific process of determining the first vector and the second vector corresponding to the customer's mobile phone number change data according to an embodiment of the present invention.

[0027] Figure 3 The figure is a flow chart of clustering customer mobile phone number change data according to an embodiment of the present invention.

[0028] Figure 4 This is a schematic diagram of a specific process for determining risk indicators for each identity confirmation method in a change data subset according to an embodiment of the present invention.

[0029] Figure 5 This is a schematic diagram of a specific process of determining a change data subset corresponding to a current request according to an embodiment of the present invention.

[0030] Figure 6 This is a schematic diagram of a specific flow of determining the identity confirmation method corresponding to this request according to an embodiment of the present invention.

[0031] Figure 7 The figure is a schematic diagram of the architecture of a device for processing mobile phone number changes for bank customers according to an embodiment of the present invention.

[0032] Figure 8 It is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] 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 solely 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. Rather, these embodiments are provided to make this disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0034] Those skilled in the art will appreciate that the embodiments of the present invention may be implemented as a system, apparatus, device, method, or computer program product. Therefore, the present disclosure may be implemented in the following forms: entirely in hardware, entirely in software (including firmware, resident software, microcode, etc.), or in a combination of hardware and software.

[0035] According to an embodiment of the present invention, a method and device for processing a change in a bank customer's mobile phone number are proposed, relating to the field of data processing technology.

[0036] The principles and spirit of the present invention are explained in detail below with reference to several representative embodiments of the present invention.

[0037] Figure 1 This is a flow chart of a method for processing a bank customer's mobile phone number change according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0038] S1, obtain the customer's mobile phone number change data stored in the bank server;

[0039] S2, for each customer's mobile phone number change data, determine the first vector and the second vector corresponding to the customer's mobile phone number change data based on the mobile phone number before the change and the mobile phone number after the change respectively;

[0040] S3, clustering the customer's mobile phone number change data based on the first vector and the second vector to obtain multiple change data subsets;

[0041] S4, for each changed data subset, determining a risk indicator for each identity confirmation method in the changed data subset;

[0042] S5, when a request to modify the mobile phone number initiated by the first customer is obtained, the change data subset corresponding to this request is determined based on the request data;

[0043] S6. Determine the identity confirmation method corresponding to the current request based on the risk indicators of each identity confirmation method in the change data subset corresponding to the current request.

[0044] In order to explain more clearly how to change the mobile phone number of the above-mentioned bank customers, each step is explained in detail below.

[0045] In S1, the customer's mobile phone number change data stored in the bank server is obtained.

[0046] In actual application scenarios, customer mobile phone number change data includes data on successful and failed mobile phone number changes.

[0047] In S2, reference Figure 2 For each customer's mobile phone number change data, the specific method for determining the first vector and the second vector corresponding to the customer's mobile phone number change data according to the mobile phone number before the change and the mobile phone number after the change is as follows:

[0048] S201, selecting multiple address items;

[0049] In actual application scenarios, the address item includes at least: the ID card number address, the address of the bank branch where the account was opened, and the address of the bank branch where the business was recently handled;

[0050] S202, obtaining the address value of each address item corresponding to the customer's mobile phone number change data from the bank server;

[0051] Specifically, the address value refers to the address name, for example, No. 21, Haidian South Road, Haidian District, Beijing, Beijing;

[0052] The address value corresponding to the mobile phone number is generally the address to which the mobile phone number belongs, such as Beijing and Chengdu, Sichuan Province;

[0053] The address values ​​corresponding to each address item of the customer can refer to S201: for example, if the customer's ID number starts with 110106, then the ID number address is Fengtai District, Beijing; the address corresponding to the bank branch where the account was opened is No. 96, Zhichun Road, Haidian District, Beijing; the address corresponding to the bank branch where the business was recently handled is No. 400, Jiefang South Road, Hexi District, Tianjin;

[0054] S203: Determine, based on a distance function corresponding to the addresses, the distance between the address value corresponding to the mobile phone number before the change and the address values ​​of each address item corresponding to the customer; determine a first vector corresponding to the mobile phone number change data of the customer, wherein the components of the first vector correspond one-to-one to the selected address items, and the value of each component is equal to the distance between the address value corresponding to the mobile phone number before the change and the address value of the address item corresponding to the component of the customer;

[0055] S204, based on the distance function corresponding to the address, determine the distance between the address value corresponding to the changed mobile phone number and the address values ​​of each address item corresponding to the customer; determine the second vector corresponding to the customer's mobile phone number change data, wherein the components of the second vector correspond one-to-one to the selected address items, and the component value of each component is equal to the distance between the address value corresponding to the changed mobile phone number and the address value of the address item corresponding to the component of the customer.

[0056] Among them, the mobile phone number before the change and the mobile phone number after the change mentioned in S203 and S204 are obtained through the customer's mobile phone number change data.

[0057] In actual application scenarios, the distance function corresponding to the address can be a pre-set distance function. If the two address values ​​are the same or one of them belongs to the other, the distance between the two addresses is 0, otherwise, it can be 1; or, a certain measurement of the actual addresses corresponding to the two addresses is used. For example, the actual distance from Beijing to Zhangjiakou is 190 kilometers, so the Beijing-Zhangjiakou distance can be set to 0.19.

[0058] For example, the address value corresponding to the mobile phone number before the change is a, and the address value corresponding to the mobile phone number after the change is b. The distance between the address values ​​of the customer corresponding to each address item is: ID card number address c, address of the bank branch where the account is opened d.

[0059] Then the first vector corresponds to two components, namely the distance between a and c, and the distance between a and d;

[0060] The second vector corresponds to two components, namely the distance between b and c, and the distance between b and d.

[0061] If the address value of the address item corresponding to the customer also includes the address corresponding to the nearest bank branch where the business was handled, the first vector and the second vector correspond to 3 components.

[0062] In S3, reference Figure 3 , based on the first vector and the second vector, the customer mobile phone number change data is clustered to obtain multiple change data subsets. The specific method is:

[0063] S301, determining a distance function corresponding to the customer's mobile phone number change data based on the first vector and the second vector, wherein the distance function is used to determine the distance between any two customer's mobile phone number change data;

[0064] Specifically, a distance may be determined based on each vector, and the weighted sum of the two distances may be used as the distance between the two customers' mobile phone number change data.

[0065] S302 , clustering the customer mobile phone number change data according to a distance function corresponding to the customer mobile phone number change data to obtain a plurality of change data subsets.

[0066] For example, K-means and support vector quantization algorithms are selected to cluster customer mobile phone number change data. Other methods can also be selected in actual application scenarios. The purpose of this step is to divide customer mobile phone number change data to facilitate the subsequent steps to determine the risk indicators of the identity confirmation method.

[0067] In one embodiment, (S302) clustering the customer mobile phone number change data based on the distance function corresponding to the customer mobile phone number change data to obtain multiple change data subsets is as follows:

[0068] S3021, selecting multiple customer mobile phone number change data from the customer mobile phone number change data as change data subset centers, each change data subset center corresponding to a change data subset, and the initial element of the change data subset only contains the corresponding change data subset center;

[0069] S3022: For each customer's mobile phone number change data, perform the following steps:

[0070] Based on the distance function corresponding to the customer's mobile phone number change data, calculate the distance between the center of each change data subset and the customer's mobile phone number change data, and use this distance as the distance corresponding to the center of the change data subset;

[0071] Select multiple change data subset centers from all the change data subset centers that are consistent with the customer category of the customer corresponding to the customer's mobile phone number change data;

[0072] The minimum value of the distances corresponding to the centers of the selected change data subsets is used as the first distance corresponding to the customer's mobile phone number change data, and the center of the change data subset corresponding to the minimum value is used as the center of the change data subset corresponding to the customer's mobile phone number change data; the minimum value of the distances corresponding to the centers of the unselected change data subsets is used as the second distance corresponding to the customer's mobile phone number change data;

[0073] If the difference between the corresponding second distance and the corresponding first distance is greater than a specified threshold, a new change data subset center is created based on the customer's mobile phone number change data. The newly created change data subset center corresponds to a new change data subset, and the initial elements of the new change data subset only contain the customer's mobile phone number change data. Otherwise, the customer's mobile phone number change data is divided into the change data subset corresponding to the change data subset center corresponding to the customer's mobile phone number change data.

[0074] S3023. After executing the above step (S3022) for all customer mobile phone number change data, for each change data subset, update the first vector corresponding to the change data subset center corresponding to the change data subset to the mean of the first vectors corresponding to all customer mobile phone number change data in the change data subset, and update the second vector corresponding to the change data subset center corresponding to the change data subset to the mean of the second vectors corresponding to all customer mobile phone number change data in the change data subset; update the customer category corresponding to the change data subset center corresponding to the change data subset to the data value with the largest number among the data values ​​of the customer category of all customer mobile phone number change data in the change data subset;

[0075] S3024, repeat the above step S3022 for each customer's mobile phone number change data and the above step S3023 for each change data subset, until the change in the first vector and the corresponding second vector corresponding to the center of all change data subsets is less than the set threshold, thereby obtaining multiple change data subsets.

[0076] In S4, ref. Figure 4 For each change data subset, the specific method for determining the risk index of each identity confirmation method in the change data subset is as follows:

[0077] S401, for each changed data subset, using the identity confirmation method included in the changed data subset as multiple identity confirmation methods corresponding to the changed data subset;

[0078] S402 : For each identity confirmation method corresponding to the changed data subset, determine a risk indicator of the identity confirmation method according to the identity confirmation data corresponding to the identity confirmation method in the changed data subset.

[0079] In one embodiment, the specific method of determining the risk indicator of the identity confirmation method (S402) is:

[0080] A, dividing the identity confirmation data corresponding to the identity confirmation method in the first time range into multiple identity confirmation data subsets, wherein the number of confirmations in each identity confirmation data subset is greater than a specified value;

[0081] B. For each identity confirmation data subset, the proportion of risk data in the identity confirmation data subset is used as the risk indicator sample of the identity confirmation method;

[0082] C, based on all risk indicator samples of this identity confirmation method, determine the sample variance μ and sample size n of the risk indicator;

[0083] Sure Is it greater than the first threshold? If If the value is greater than the first threshold, then continue with steps A, B and C until less than a first threshold;

[0084] The risk indicator of the identity confirmation method is determined as the mean of all risk indicator samples of the identity confirmation method.

[0085] According to the law of large numbers, the first threshold is determined as ε 2 ×P, ε is the risk indicator error threshold, and P is the acceptable probability that the risk indicator error is greater than ε.

[0086] In S5, reference Figure 5 When the request to modify the mobile phone number initiated by the first customer is obtained, the specific method for determining the change data subset corresponding to this request is as follows based on the request data:

[0087] S501, obtaining the mobile phone number before and after the change corresponding to this request;

[0088] S502: Determine a third vector and a fourth vector corresponding to the current request based on the mobile phone number before and after the change in the current request;

[0089] S503: Determine a partial order of the customer mobile phone number change data based on the first vector, the second vector, the third vector, and the fourth vector, wherein the partial order is used to determine whether, among any two customer mobile phone number change data, the first mobile phone number change data is closer than the second mobile phone number change data;

[0090] S504, determining a maximum mobile phone number change data in the customer mobile phone number change data based on the partial order of the customer mobile phone number change data, wherein the maximum mobile phone number change data is a maximum element of the partial order;

[0091] S505: Determine the change data subset corresponding to this request based on the maximum mobile phone number change data.

[0092] Specifically, in S505 , the changed data subset containing the largest amount of mobile phone number change data is used as the changed data subset corresponding to this request.

[0093] In one embodiment, (S502), the method of determining the third vector and the fourth vector corresponding to the current request according to the mobile phone number before and after the change of the current request can refer to the above-mentioned S2.

[0094] The specific method of S502 is as follows:

[0095] S5021: Determine, based on a distance function corresponding to the address, the distance between the address value corresponding to the mobile phone number before the change and the address values ​​of each address item corresponding to the customer; determine a third vector corresponding to the customer's mobile phone number change data, wherein the components of the third vector correspond one-to-one to the selected address items, and the value of each component is equal to the distance between the address value corresponding to the mobile phone number before the change and the address value of the address item corresponding to the component for the customer;

[0096] S5022. Determine the distance between the address value corresponding to the changed mobile phone number and the address values ​​of each address item corresponding to the customer based on the distance function corresponding to the address; determine the fourth vector corresponding to the customer's mobile phone number change data, wherein the components of the fourth vector correspond one-to-one to the selected address items, and the component value of each component is equal to the distance between the address value corresponding to the changed mobile phone number and the address value of the address item corresponding to the component of the customer.

[0097] Among them, the mobile phone number before the change and the mobile phone number after the change mentioned in S5021 and S5022 are obtained through this request.

[0098] In one embodiment, (S503) a specific method for determining the partial order of the customer mobile phone number change data based on the first vector, the second vector, the third vector, and the fourth vector is:

[0099] For each customer's mobile phone number change data, the distance between the first vector of the customer's mobile phone number change data and the third vector corresponding to the current request is used as the first distance corresponding to the customer's mobile phone number change data, and the distance between the second vector of the customer's mobile phone number change data and the fourth vector corresponding to the current request is used as the second distance corresponding to the customer's mobile phone number change data;

[0100] For any two customer mobile phone number change data, if the first distance corresponding to the first customer mobile phone number change data in the two customer mobile phone number change data is less than or equal to the first distance corresponding to the second customer mobile phone number change data in the two customer mobile phone number change data, and the second distance corresponding to the first customer mobile phone number change data is less than or equal to the second distance corresponding to the second customer mobile phone number change data, then it is determined that the first customer mobile phone number change data is closer to the second customer mobile phone number change data.

[0101] In one embodiment, (S504) determining the maximum mobile phone number change data in the customer mobile phone number change data based on the partial order of the customer mobile phone number change data includes:

[0102] S5041, initialize the maximum flag corresponding to each customer's mobile phone number change data to "possible" and initialize the comparison flag corresponding to each customer's mobile phone number change data to "yes";

[0103] S5042: For each customer's mobile phone number change data, perform the following steps:

[0104] S50421: If the maximum flag corresponding to the customer's mobile phone number change data is not "possible", continue to execute step S5042 for the next customer's mobile phone number change data;

[0105] S50422, if the maximum flag corresponding to the customer's mobile phone number change data is "possible", then sequentially compare the customer's mobile phone number change data (except the customer's mobile phone number change data) with the corresponding comparison flag of "yes" with the customer's mobile phone number change data;

[0106] If the customer's mobile phone number change data corresponding to the comparison flag "yes" is close to the customer's mobile phone number change data, then the maximum flag corresponding to the customer's mobile phone number change data is set to "no", and then the above step S5042 is continued for the next customer's mobile phone number change data;

[0107] If the customer's mobile phone number change data is close to the corresponding customer's mobile phone number change data with a comparison flag of "yes", the maximum flag corresponding to the corresponding customer's mobile phone number change data with a comparison flag of "yes" is set to "no", and the customer's mobile phone number change data with a comparison flag of "yes" is used as the secondary customer's mobile phone number change data of the customer's mobile phone number change data;

[0108] S50423, if it is confirmed that all customer mobile phone number change data with the corresponding comparison identifier of "yes" are not close to the customer mobile phone number change data, then the customer mobile phone number change data is determined as the maximum mobile phone number change data in the bank's customer mobile phone number change data, and the comparison identifier of each secondary customer mobile phone number change data of the maximum mobile phone number change data is updated to "no".

[0109] In S6, reference Figure 6 Based on the risk indicators of each identity confirmation method in the change data subset corresponding to this request, the specific method for determining the identity confirmation method corresponding to this request is as follows:

[0110] S601, determining the selection probability of each identity confirmation method in the change data subset corresponding to the current request based on the risk index of each identity confirmation method in the change data subset corresponding to the current request;

[0111] S602, sorting the identity confirmation methods in the change data subset corresponding to the current request;

[0112] S603: Select a probability density function g, and perform the following steps on each identity confirmation method in the change data subset corresponding to the current request in order of sorting:

[0113] Determine the sum of the probabilities of selection corresponding to all identity confirmation methods that precede the identity confirmation method in the ranking; determine the left endpoint corresponding to the identity confirmation method based on the sum of the probabilities of selection, where the integral of the function g from the minimum value of the independent variable of g to the left endpoint corresponding to the identity confirmation method is equal to the sum of the probabilities of selection;

[0114] S604: For each identity confirmation method in the change data subset corresponding to the current request, determine a probability interval corresponding to the identity confirmation method based on the left endpoint corresponding to the identity confirmation method and the left endpoint corresponding to the next identity confirmation method in the sorted order.

[0115] S605, generating a random number based on the function g, and determining a probability interval to which the random number belongs;

[0116] S606: Determine the identity confirmation method corresponding to the probability interval to which the random number belongs as the identity confirmation method corresponding to this request.

[0117] In one embodiment, (S601) determining the selection probability of each identity confirmation method in the change data subset corresponding to the current request based on the risk index of each identity confirmation method in the change data subset corresponding to the current request includes:

[0118] The probability of being selected corresponding to the i-th identity confirmation method is determined as

[0119] Among them, r j is the risk indicator of the jth identity confirmation method.

[0120] 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 drawings, this does not require or imply that these operations must be performed in this specific order, or that all illustrated operations must be performed to achieve the desired results. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0121] After introducing the method of the exemplary embodiment of the present invention, next, reference is made to Figure 7 A device for processing a change in a mobile phone number of a bank customer according to an exemplary embodiment of the present invention is introduced.

[0122] The implementation of the bank customer mobile phone number change processing device can refer to the implementation of the above method, and the repeated parts will not be repeated here. The terms "module" or "unit" used below can be a combination of software and / or hardware that implements the predetermined function. Although the device described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

[0123] Based on the same inventive concept, the present invention also proposes a bank customer's mobile phone number change processing device, such as Figure 7 As shown, the device includes:

[0124] The data acquisition module 710 is used to obtain the customer's mobile phone number change data stored in the bank server;

[0125] A vector processing module 720 is configured to determine, for each customer's mobile phone number change data, a first vector and a second vector corresponding to the customer's mobile phone number change data based on the mobile phone number before the change and the mobile phone number after the change, respectively;

[0126] A clustering module 730 is configured to cluster the customer mobile phone number change data based on the first vector and the second vector to obtain multiple change data subsets;

[0127] A risk indicator determination module 740 is configured to determine, for each change data subset, a risk indicator of each identity confirmation method in the change data subset;

[0128] The changed data subset determination module 750 is configured to, upon receiving a request from the first customer to modify a mobile phone number, determine the changed data subset corresponding to the request based on the request data;

[0129] The identity confirmation method processing module 760 is used to determine the identity confirmation method corresponding to the current request based on the risk indicators of each identity confirmation method in the change data subset corresponding to the current request.

[0130] In one embodiment, the vector processing module is specifically configured to:

[0131] Select multiple address items;

[0132] Obtain the address values ​​of each address item corresponding to the customer's mobile phone number change data from the bank server;

[0133] Determine, based on a distance function corresponding to the address, the distance between the address value corresponding to the mobile phone number before the change and the address values ​​of each address item corresponding to the customer; determine a first vector corresponding to the customer's mobile phone number change data, wherein components of the first vector correspond one-to-one to the selected address items, and the value of each component is equal to the distance between the address value corresponding to the mobile phone number before the change and the address value of the address item corresponding to the component for the customer;

[0134] Based on the distance function corresponding to the address, determine the distance between the address value corresponding to the changed mobile phone number and the address values ​​of each address item corresponding to the customer; determine the second vector corresponding to the customer's mobile phone number change data, wherein the components of the second vector correspond one-to-one to the selected address items, and the component value of each component is equal to the distance between the address value corresponding to the changed mobile phone number and the address value of the address item corresponding to the component of the customer.

[0135] In one embodiment, the clustering module is specifically configured to:

[0136] Determine a distance function corresponding to the customer mobile phone number change data based on the first vector and the second vector, wherein the distance function is used to determine the distance between any two customer mobile phone number change data;

[0137] According to the distance function corresponding to the customer mobile phone number change data, the customer mobile phone number change data is clustered to obtain multiple change data subsets.

[0138] In one embodiment, the risk indicator determination module is specifically configured to:

[0139] For each changed data subset, the identity confirmation methods included in the changed data subset are used as the multiple identity confirmation methods corresponding to the changed data subset;

[0140] For each identity confirmation method corresponding to the change data subset, a risk indicator of the identity confirmation method is determined based on the identity confirmation data corresponding to the identity confirmation method in the change data subset.

[0141] In one embodiment, the changed data subset determination module is specifically configured to:

[0142] Get the mobile phone number before and after the change corresponding to this request;

[0143] Determine the third vector and the fourth vector corresponding to the request based on the mobile phone number before and after the change, respectively.

[0144] Determine a partial order of the customer mobile phone number change data based on the first vector, the second vector, the third vector, and the fourth vector, wherein the partial order is used to determine whether, among any two customer mobile phone number change data, the first mobile phone number change data is closer than the second mobile phone number change data;

[0145] Determine, based on the partial order of the customer mobile phone number change data, a maximum mobile phone number change data in the customer mobile phone number change data, wherein the maximum mobile phone number change data is a maximum element of the partial order;

[0146] Determine the change data subset corresponding to this request based on the maximum mobile phone number change data.

[0147] In one embodiment, the changed data subset determination module is specifically configured to:

[0148] For each customer's mobile phone number change data, the distance between the first vector of the customer's mobile phone number change data and the third vector corresponding to the current request is used as the first distance corresponding to the customer's mobile phone number change data, and the distance between the second vector of the customer's mobile phone number change data and the fourth vector corresponding to the current request is used as the second distance corresponding to the customer's mobile phone number change data;

[0149] For any two customer mobile phone number change data, if the first distance corresponding to the first customer mobile phone number change data in the two customer mobile phone number change data is less than or equal to the first distance corresponding to the second customer mobile phone number change data in the two customer mobile phone number change data, and the second distance corresponding to the first customer mobile phone number change data is less than or equal to the second distance corresponding to the second customer mobile phone number change data, then it is determined that the first customer mobile phone number change data is closer to the second customer mobile phone number change data.

[0150] In one embodiment, the identity confirmation mode processing module is specifically configured to:

[0151] Determine the probability of selection for each identity confirmation method in the change data subset corresponding to this request based on the risk indicator of each identity confirmation method in the change data subset corresponding to this request;

[0152] Sort the identity confirmation methods in the change data subset corresponding to this request;

[0153] Select a probability density function g and perform the following steps for each identity confirmation method in the change data subset corresponding to this request in the sorted order:

[0154] Determine the sum of the probabilities of selection corresponding to all identity confirmation methods that precede the identity confirmation method in the ranking; determine the left endpoint corresponding to the identity confirmation method based on the sum of the probabilities of selection, where the integral of the function g from the minimum value of the independent variable of g to the left endpoint corresponding to the identity confirmation method is equal to the sum of the probabilities of selection;

[0155] For each identity confirmation method in the change data subset corresponding to this request, determine the probability interval corresponding to the identity confirmation method based on the left endpoint corresponding to the identity confirmation method and the left endpoint corresponding to the next identity confirmation method in the sorted order;

[0156] Generate a random number based on the function g, and determine the probability interval to which the random number belongs;

[0157] The identity confirmation method corresponding to the probability interval to which the random number belongs is determined as the identity confirmation method corresponding to this request.

[0158] It should be noted that while the detailed description above mentions several modules of the apparatus for processing bank customer mobile phone number changes, this division is merely exemplary and not mandatory. In practice, depending on the embodiments of the present invention, the features and functions of two or more modules described above may be embodied in a single module. Conversely, the features and functions of a single module described above may be further divided and embodied by multiple modules.

[0159] Based on the above invention concept, Figure 8 As shown, the present invention also proposes a computer device 800, including a memory 810, a processor 820 and a computer program 830 stored in the memory 810 and executable on the processor 820, wherein the processor 820 implements the aforementioned method for processing the change of mobile phone numbers of bank customers when executing the computer program 830.

[0160] Based on the aforementioned inventive concept, the present invention proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the aforementioned method for processing mobile phone number changes for bank customers.

[0161] Based on the aforementioned inventive concept, the present invention proposes a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements a method for processing a bank customer's mobile phone number change.

[0162] The present invention proposes a method and device for processing mobile phone number changes for bank customers, which obtains customer mobile phone number change data stored on a bank server; for each customer mobile phone number change data, determines a first vector and a second vector corresponding to the customer mobile phone number change data based on the mobile phone number before and after the change, respectively; clusters the customer mobile phone number change data based on the first and second vectors to obtain multiple change data subsets; for each change data subset, determines a risk indicator for each identity confirmation method in the change data subset; when a request to modify a mobile phone number initiated by a first customer is obtained, determines a change data subset corresponding to the request based on the request data; and determines an identity confirmation method corresponding to the request based on the risk indicators of each identity confirmation method in the change data subset corresponding to the request. Compared with the prior art in which customers need to go to a bank branch in person to handle the matter, the overall solution of the present invention determines the identity confirmation method for the customer's mobile phone number change by analyzing the customer mobile phone number change data, allowing customers to change their mobile phone numbers safely and conveniently online, improving the efficiency of mobile phone number changes, and enhancing the customer experience. It also effectively controls the risks of mobile phone number changes and protects customer information security.

[0163] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, apparatus, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, 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 magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0164] 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 flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. 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.

[0165] These computer program instructions may 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 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 The function specified in one or more boxes.

[0166] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0167] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A method for processing a bank customer's mobile phone number change, characterized in that: include: Obtain customer mobile phone number change data stored on the bank server; For each customer's mobile phone number change data, determine the first vector and the second vector corresponding to the customer's mobile phone number change data based on the mobile phone number before the change and the mobile phone number after the change respectively; Clustering the customer's mobile phone number change data based on the first vector and the second vector to obtain multiple change data subsets; For each subset of changed data, determine the risk indicators of each identity confirmation method in the subset of changed data; When a request to modify a mobile phone number is received from the first customer, the change data subset corresponding to the request is determined based on the request data; Determine the identity confirmation method corresponding to this request based on the risk indicators of each identity confirmation method in the change data subset corresponding to this request; For each customer's mobile phone number change data, the first vector and the second vector corresponding to the customer's mobile phone number change data are determined based on the mobile phone number before the change and the mobile phone number after the change, respectively, including: Select multiple address items; Obtain the address values ​​of each address item corresponding to the customer's mobile phone number change data from the bank server; Determine, based on a distance function corresponding to the address, the distance between the address value corresponding to the mobile phone number before the change and the address values ​​of each address item corresponding to the customer; determine a first vector corresponding to the customer's mobile phone number change data, wherein components of the first vector correspond one-to-one to the selected address items, and the value of each component is equal to the distance between the address value corresponding to the mobile phone number before the change and the address value of the address item corresponding to the component for the customer; Determine, based on a distance function corresponding to the address, the distance between the address value corresponding to the changed mobile phone number and the address values ​​of each address item corresponding to the customer; determine a second vector corresponding to the customer's mobile phone number change data, wherein components of the second vector correspond one-to-one to the selected address items, and the value of each component is equal to the distance between the address value corresponding to the changed mobile phone number and the address value of the address item corresponding to the component; When a request to modify a mobile phone number is received from the first customer, the change data subset corresponding to the request is determined based on the request data, including: Get the mobile phone number before and after the change corresponding to this request; Determine the third vector and the fourth vector corresponding to the request based on the mobile phone number before and after the change, respectively. Determine a partial order of the customer mobile phone number change data based on the first vector, the second vector, the third vector, and the fourth vector, wherein the partial order is used to determine whether, among any two customer mobile phone number change data, the first mobile phone number change data is closer than the second mobile phone number change data; Determine, based on the partial order of the customer mobile phone number change data, a maximum mobile phone number change data in the customer mobile phone number change data, wherein the maximum mobile phone number change data is a maximum element of the partial order; Determine the change data subset corresponding to this request based on the maximum number of mobile phone number change data; Determining the partial order of customer mobile phone number change data based on the first vector, the second vector, the third vector, and the fourth vector includes: For each customer's mobile phone number change data, the distance between the first vector of the customer's mobile phone number change data and the third vector corresponding to the current request is used as the first distance corresponding to the customer's mobile phone number change data, and the distance between the second vector of the customer's mobile phone number change data and the fourth vector corresponding to the current request is used as the second distance corresponding to the customer's mobile phone number change data; For any two customer mobile phone number change data, if the first distance corresponding to the first customer mobile phone number change data of the two customer mobile phone number change data is less than or equal to the first distance corresponding to the second customer mobile phone number change data of the two customer mobile phone number change data, and the second distance corresponding to the first customer mobile phone number change data is less than or equal to the second distance corresponding to the second customer mobile phone number change data, then the first customer mobile phone number change data is determined to be closer to the second customer mobile phone number change data; The identity confirmation method corresponding to this request is determined based on the risk indicators of each identity confirmation method in the change data subset corresponding to this request, including: Determine the probability of selection for each identity confirmation method in the change data subset corresponding to this request based on the risk indicator of each identity confirmation method in the change data subset corresponding to this request; Sort the identity confirmation methods in the change data subset corresponding to this request; Choose a probability density function , and perform the following steps for each identity confirmation method in the change data subset corresponding to this request in the sorted order: Determine the sum of the selected probabilities of all identity confirmation methods before the identity confirmation method in the ranking; based on the sum of the selected probabilities, determine the left endpoint corresponding to the identity confirmation method, where the probability density function from The integral value from the minimum value of the independent variable to the left endpoint corresponding to the identity confirmation method is equal to the sum of the selected probabilities; For each identity confirmation method in the change data subset corresponding to this request, determine the probability interval corresponding to the identity confirmation method based on the left endpoint corresponding to the identity confirmation method and the left endpoint corresponding to the next identity confirmation method in the sorted order; Based on the probability density function Generate a random number and determine the probability interval to which the random number belongs; The identity confirmation method corresponding to the probability interval to which the random number belongs is used as the identity confirmation method corresponding to this request.

2. The method according to claim 1, characterized in that Based on the first vector and the second vector, the customer mobile phone number change data is clustered to obtain multiple change data subsets, including: Determine a distance function corresponding to the customer mobile phone number change data based on the first vector and the second vector, wherein the distance function is used to determine the distance between any two customer mobile phone number change data; According to the distance function corresponding to the customer mobile phone number change data, the customer mobile phone number change data is clustered to obtain multiple change data subsets.

3. The method according to claim 1, characterized in that For each subset of changed data, determine the risk indicators for each identity confirmation method in the subset of changed data, including: For each changed data subset, the identity confirmation methods included in the changed data subset are used as the multiple identity confirmation methods corresponding to the changed data subset; For each identity confirmation method corresponding to the change data subset, a risk indicator of the identity confirmation method is determined based on the identity confirmation data corresponding to the identity confirmation method in the change data subset.

4. A device for processing changes in mobile phone numbers of bank customers, characterized in that: include: A data acquisition module is used to obtain customer mobile phone number change data stored in the bank server; A vector processing module is used to determine, for each customer's mobile phone number change data, a first vector and a second vector corresponding to the customer's mobile phone number change data based on the mobile phone number before the change and the mobile phone number after the change; A clustering module, configured to cluster the customer mobile phone number change data based on the first vector and the second vector to obtain multiple change data subsets; A risk indicator determination module is used to determine, for each change data subset, the risk indicator of each identity confirmation method in the change data subset; A changed data subset determination module is configured to, upon receiving a request from a first customer to modify a mobile phone number, determine a changed data subset corresponding to the request based on the request data; An identity confirmation method processing module is used to determine the identity confirmation method corresponding to this request based on the risk indicators of each identity confirmation method in the change data subset corresponding to this request; The vector processing module is specifically used for: Select multiple address items; Obtain the address values ​​of each address item corresponding to the customer's mobile phone number change data from the bank server; Determine, based on a distance function corresponding to the address, the distance between the address value corresponding to the mobile phone number before the change and the address values ​​of each address item corresponding to the customer; determine a first vector corresponding to the customer's mobile phone number change data, wherein components of the first vector correspond one-to-one to the selected address items, and the value of each component is equal to the distance between the address value corresponding to the mobile phone number before the change and the address value of the address item corresponding to the component for the customer; Determine, based on a distance function corresponding to the address, the distance between the address value corresponding to the changed mobile phone number and the address values ​​of each address item corresponding to the customer; determine a second vector corresponding to the customer's mobile phone number change data, wherein components of the second vector correspond one-to-one to the selected address items, and the value of each component is equal to the distance between the address value corresponding to the changed mobile phone number and the address value of the address item corresponding to the component; The changed data subset determination module is specifically used to: Get the mobile phone number before and after the change corresponding to this request; Determine the third vector and the fourth vector corresponding to the request based on the mobile phone number before and after the change, respectively. Determine a partial order of the customer mobile phone number change data based on the first vector, the second vector, the third vector, and the fourth vector, wherein the partial order is used to determine whether, among any two customer mobile phone number change data, the first mobile phone number change data is closer than the second mobile phone number change data; Determine, based on the partial order of the customer mobile phone number change data, a maximum mobile phone number change data in the customer mobile phone number change data, wherein the maximum mobile phone number change data is a maximum element of the partial order; Determine the change data subset corresponding to this request based on the maximum number of mobile phone number change data; The changed data subset determination module is specifically used to: For each customer's mobile phone number change data, the distance between the first vector of the customer's mobile phone number change data and the third vector corresponding to the current request is used as the first distance corresponding to the customer's mobile phone number change data, and the distance between the second vector of the customer's mobile phone number change data and the fourth vector corresponding to the current request is used as the second distance corresponding to the customer's mobile phone number change data; For any two customer mobile phone number change data, if the first distance corresponding to the first customer mobile phone number change data of the two customer mobile phone number change data is less than or equal to the first distance corresponding to the second customer mobile phone number change data of the two customer mobile phone number change data, and the second distance corresponding to the first customer mobile phone number change data is less than or equal to the second distance corresponding to the second customer mobile phone number change data, then the first customer mobile phone number change data is determined to be closer to the second customer mobile phone number change data; The identity confirmation processing module is specifically used to: Determine the probability of selection for each identity confirmation method in the change data subset corresponding to this request based on the risk indicator of each identity confirmation method in the change data subset corresponding to this request; Sort the identity confirmation methods in the change data subset corresponding to this request; Choose a probability density function , and perform the following steps for each identity confirmation method in the change data subset corresponding to this request in the sorted order: Determine the sum of the selected probabilities of all identity confirmation methods before the identity confirmation method in the ranking; based on the sum of the selected probabilities, determine the left endpoint corresponding to the identity confirmation method, where the probability density function from The integral value from the minimum value of the independent variable to the left endpoint corresponding to the identity confirmation method is equal to the sum of the selected probabilities; For each identity confirmation method in the change data subset corresponding to this request, determine the probability interval corresponding to the identity confirmation method based on the left endpoint corresponding to the identity confirmation method and the left endpoint corresponding to the next identity confirmation method in the sorted order; Based on the probability density function Generate a random number and determine the probability interval to which the random number belongs; The identity confirmation method corresponding to the probability interval to which the random number belongs is used as the identity confirmation method corresponding to this request.

5. The device according to claim 4, characterized in that The clustering module is specifically used for: Determine a distance function corresponding to the customer mobile phone number change data based on the first vector and the second vector, wherein the distance function is used to determine the distance between any two customer mobile phone number change data; According to the distance function corresponding to the customer mobile phone number change data, the customer mobile phone number change data is clustered to obtain multiple change data subsets.

6. The device according to claim 4, characterized in that The risk indicator determination module is specifically used to: For each changed data subset, the identity confirmation methods included in the changed data subset are used as the multiple identity confirmation methods corresponding to the changed data subset; For each identity confirmation method corresponding to the change data subset, a risk indicator of the identity confirmation method is determined based on the identity confirmation data corresponding to the identity confirmation method in the change data subset.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 3 is implemented.

8. 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 3 is implemented.

9. 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 3 is implemented.

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