CN114862551A - Mobile phone number risk control method and device for bank outlets - Google Patents

Abstract

The invention provides a mobile phone number risk control method and device for a bank outlet, which is suitable for the field of financial technology. The method includes: constructing a customer phone number relationship diagram of a bank outlet; for each phone number, determining a potential associated phone number of the phone number. When a customer modifies a mobile phone number at a bank outlet, if the new mobile phone number is in the set of potentially associated mobile phone numbers of the old mobile phone number, the customer will be identified based on the set of potential associated mobile phone numbers and the customer’s face recognition threshold. Determine whether to support mobile phone number modification according to the face recognition result; if the new mobile phone number is not in the set of potential associated mobile phone numbers of the old mobile phone number, determine the correlation distance between the old mobile phone number and the new mobile phone number, and correct the customer's face according to the correlation distance Recognition threshold, according to the revised face recognition threshold, perform face recognition on customers, and judge whether to support mobile phone number modification according to the face recognition result. The invention can realize the risk control of the mobile phone number of the bank outlet.

Description

Mobile phone number risk control method and device for bank outlets

technical field

The invention relates to the field of financial technology, and in particular, to a method and device for risk control of mobile phone numbers in bank outlets.

Background technique

Mobile phone numbers are important information for customers. To some extent, mobile phone numbers are closely related to the identity of customers. Especially when customers make payments or modify information on the banking system, they need to verify their identity information through mobile phone verification codes. At the same time, it also brings risks to customers' funds, especially the potential risks to customers within the bank. At present, there is a lack of a risk control method for mobile phone numbers in bank branches.

SUMMARY OF THE INVENTION

The embodiment of the present invention proposes a mobile phone number risk control method in a bank outlet, so as to realize the risk control of the mobile phone number in a bank outlet, and the method includes:

Build a relationship map of customer mobile phone numbers of bank outlets;

According to the customer mobile phone number relationship diagram and historical modification data, for each mobile phone number, determine the set of potential associated mobile phone numbers of the mobile phone number;

When a customer modifies a mobile phone number at a bank outlet, if the new mobile phone number is in the set of potential associated mobile phone numbers of the old mobile phone number, the face recognition of the customer will be performed according to the set of potential associated mobile phone numbers and the customer's face recognition threshold. The face recognition result judges whether the mobile phone number modification is supported;

If the new mobile phone number is not in the set of potential related mobile phone numbers of the old mobile phone number, determine the correlation distance between the old mobile phone number and the new mobile phone number, correct the customer's face recognition threshold according to the correlation distance, and determine the customer's face recognition threshold according to the modified face recognition threshold. Perform face recognition, and determine whether to support mobile phone number modification according to the face recognition result.

The embodiment of the present invention provides a mobile phone number risk control device in a bank outlet, which is used to realize the risk control of the mobile phone number in a bank outlet. The device includes:

The building module of the customer mobile phone number relationship diagram, which is used to construct the customer mobile phone number relationship diagram in the bank;

The potential associated person determination module is used to determine the set of potential associated mobile phone numbers for each mobile phone number according to the relationship diagram of the customer's mobile phone number and historical modification data;

The mobile phone number modification judgment module is used for when a customer modifies a mobile phone number at a bank outlet, if the new mobile phone number is in the set of potential related mobile phone numbers of the old mobile phone number, based on the set of potential related mobile phone numbers and the customer's face recognition threshold, the mobile phone number is determined. The customer performs face recognition, and judges whether to support the modification of the mobile phone number according to the face recognition result;

The face recognition threshold correction module is used to determine the correlation distance between the old mobile phone number and the new mobile phone number if the new mobile phone number is not in the set of potential related mobile phone numbers of the old mobile phone number, and correct the customer's face recognition threshold according to the correlation distance, Correct the customer's face recognition threshold according to the association distance, perform face recognition on the customer according to the revised face recognition threshold, and determine whether to support the modification of the mobile phone number according to the face recognition result.

An embodiment of the present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and running on the processor, where the processor implements the above-mentioned risk control of the mobile phone number of a bank outlet when the processor executes the computer program method.

Embodiments of the present invention further provide a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the above-mentioned risk control method for a mobile phone number of a bank outlet is implemented.

An embodiment of the present invention further provides a computer program product, where the computer program product includes a computer program, and when the computer program is executed by a processor, the above-mentioned risk control method for a mobile phone number of a bank outlet is implemented.

In the embodiment of the present invention, a customer mobile phone number relationship diagram of the bank outlet is constructed; according to the customer mobile phone number relationship diagram and historical modification data, for each mobile phone number, the set of potential associated mobile phone numbers of the mobile phone number is determined; when the customer is at the bank outlet When modifying the mobile phone number, if the new mobile phone number is in the set of potential associated mobile phone numbers of the old mobile phone number, the customer will be identified based on the set of potential associated mobile phone numbers and the customer's face recognition threshold, and the customer will be identified according to the face recognition result. Support mobile phone number modification; if the new mobile phone number is not in the set of potential related mobile phone numbers of the old mobile phone number, determine the correlation distance between the old mobile phone number and the new mobile phone number, and correct the customer's face recognition threshold according to the correlation distance. The face recognition threshold performs face recognition on customers, and judges whether to support mobile phone number modification according to the face recognition results. In the above process, it is judged whether to support the modification of the mobile phone number according to the relationship map of the customer's mobile phone number, the historical modification data and the face recognition threshold of the bank outlet, and the above face recognition threshold can be determined according to the correlation distance between the old mobile phone number and the new mobile phone number. Make corrections, so that the risk control of mobile phone number modification can be carried out accurately in real time.

Description of drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative efforts. In the attached image:

1 is a flow chart of a method for risk control of mobile phone number in a bank outlet in an embodiment of the present invention;

Fig. 2 is the flow chart of constructing the customer mobile phone number relation diagram of the bank outlet in the embodiment of the present invention;

3 is a flowchart of calculating the degree of association between each mobile phone number and the associated mobile phone number of the mobile phone number in an embodiment of the present invention;

Fig. 4 is the flow chart of constructing the customer mobile phone number relationship diagram according to the described association distance in the embodiment of the present invention;

5 is a flowchart of determining a set of potential associated mobile phone numbers of each mobile phone number in an embodiment of the present invention;

6 is a flow chart of determining a plurality of boundary separation distances corresponding to a client mobile phone number relationship diagram and a boundary association distance corresponding to each boundary separation distance in an embodiment of the present invention;

7 is a flowchart 1 of determining a potential associated mobile phone number of a mobile phone number in an embodiment of the present invention;

8 is a flowchart 2 of determining a potential associated mobile phone number of a mobile phone number in an embodiment of the present invention;

9 is a flowchart 3 of determining a potential associated mobile phone number of a mobile phone number in an embodiment of the present invention;

10 is a flow chart of judging whether to support mobile phone number modification through face recognition in an embodiment of the present invention;

11 is a flow chart of correcting a customer's face recognition threshold in an embodiment of the present invention;

12 is a schematic diagram of a mobile phone number risk control device in a bank outlet in an embodiment of the present invention;

FIG. 13 is a schematic diagram of a computer device in an embodiment of the present invention.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present invention more clearly understood, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but not to limit the present invention.

In the description of this specification, the use of "comprising", "including", "having", "containing" and the like are all open-ended terms, that is, meaning including but not limited to. Description with reference to the terms "one embodiment", "one particular embodiment", "some embodiments", "for example" etc. means that a particular feature, structure or characteristic described in connection with the embodiment or example is included in at least one of the present application examples or examples. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The sequence of steps involved in each embodiment is used to schematically illustrate the implementation of the present application, and the sequence of steps is not limited and can be appropriately adjusted as required.

Fig. 1 is the flow chart of the risk control method of the mobile phone number of the bank outlet in the embodiment of the present invention, including:

Step 101, building a customer mobile phone number relationship diagram of a bank outlet;

Step 102, for each mobile phone number, determine a set of potential associated mobile phone numbers of the mobile phone number according to the customer mobile phone number relationship diagram and historical modification data;

Step 103, when the customer modifies the mobile phone number at the bank outlet, if the new mobile phone number is in the set of potential associated mobile phone numbers of the old mobile phone number, perform face recognition on the customer according to the set of potential associated mobile phone numbers and the customer's face recognition threshold , according to the face recognition results to determine whether to support mobile phone number modification;

Step 104, if the new mobile phone number is not in the set of potential associated mobile phone numbers of the old mobile phone number, determine the correlation distance between the old mobile phone number and the new mobile phone number, correct the customer's face recognition threshold according to the correlation distance, The threshold is used to recognize the customer's face, and determine whether to support the modification of the mobile phone number according to the face recognition result.

2 is a flowchart of constructing a relationship diagram of customer mobile phone numbers of a bank outlet in an embodiment of the present invention. In one embodiment, building a relationship diagram of customer mobile phone numbers of a bank outlet includes:

Step 201, determine the associated mobile phone number of each mobile phone number;

Step 202, calculating the degree of association between each mobile phone number and the associated mobile phone number of the mobile phone number;

Step 203, based on the degree of association between each mobile phone number and the associated mobile phone number of the mobile phone number, calculate the association distance between each mobile phone number and the associated mobile phone number of the mobile phone number;

Step 204 , constructing a customer mobile phone number relationship graph according to the association distance.

In one embodiment, determining the associated mobile phone number of each mobile phone number includes:

Acquire two accounts involved in each transfer data, and determine the two mobile phone numbers corresponding to the two accounts as the associated mobile phone numbers of the other party.

3 is a flowchart of calculating the degree of association between each mobile phone number and the mobile phone number associated with the mobile phone number in an embodiment of the present invention. In one embodiment, calculating the relationship between each mobile phone number and the mobile phone number associated with the mobile phone number correlations, including:

Step 301, for each mobile phone number, determine the amount of transfer data involved between the mobile phone number and each associated mobile phone number of the mobile phone number as the amount of associated data corresponding to each associated mobile phone number of the mobile phone number;

Step 302, determining the maximum value in all the associated data volumes as the associated data maximum value;

Step 303: For each mobile phone number, the degree of association between the mobile phone number and each associated mobile phone number of the mobile phone number is determined as the amount of associated data corresponding to each associated mobile phone number of the mobile phone number and the maximum value of the associated data. ratio.

It should be noted that the above-mentioned transfer data includes transfer transactions and payment transactions.

In one embodiment, calculating the degree of association between each mobile phone number and the mobile phone number associated with the mobile phone number includes:

Obtain the customers and tellers involved in each piece of business processing data, and determine the customer's mobile phone number as the mobile phone number associated with the teller's mobile phone number;

For each customer's mobile phone number, determine the amount of business transaction data involved with the customer and the teller as the amount of associated data corresponding to the customer's mobile phone number and the teller's mobile phone number;

Determine the maximum value of all the associated data volumes as the associated data maximum value;

For each customer's mobile phone number, the correlation degree corresponding to the customer's mobile phone number and the teller's mobile phone number is set as the ratio of the associated data volume corresponding to the customer's mobile phone number and the teller's mobile phone number to the maximum value of the associated data.

In one embodiment, based on the degree of association between each mobile phone number and the associated mobile phone number of the mobile phone number, calculating the association distance between each mobile phone number and the associated mobile phone number of the mobile phone number, including:

For each mobile phone number, determine the association distance between the mobile phone number and each associated mobile phone number of the mobile phone number as -lg(r), where r is the distance between the mobile phone number and each associated mobile phone number of the mobile phone number The correlation degree of , lg is the logarithmic function of base 10.

FIG. 4 is a flowchart of constructing a customer mobile phone number relationship diagram according to the association distance in an embodiment of the present invention. In one embodiment, building a customer mobile phone number relationship diagram according to the association distance includes:

Step 401, taking each mobile phone number as a node, if and only if the two mobile phone numbers are each other's associated mobile phone numbers, the nodes corresponding to the two mobile phone numbers have edges;

Step 402 , determining the association distance of an edge to be the association distance between two mobile phone numbers corresponding to the edge, and determining that the separation distance of the edges is 1.

Among them, if there is no edge between two nodes, the shortest distance algorithm needs to be used to calculate.

5 is a flow chart of determining a set of potential associated mobile phone numbers for each mobile phone number in an embodiment of the present invention. In one embodiment, for each mobile phone number, the mobile phone number is determined according to a relationship diagram of customer mobile phone numbers and historical modification data. A collection of potentially associated mobile phone numbers, including:

Step 501, according to the historical modification data, determine a plurality of boundary separation distances corresponding to the customer mobile phone number relationship diagram and a boundary association distance corresponding to each boundary separation distance;

Step 502 , for each mobile phone number, determine a set of potential associated mobile phone numbers for the mobile phone number according to a plurality of boundary separation distances and a boundary association distance corresponding to each boundary separation distance.

The historical modification data is the historical modification data of the mobile phone number.

6 is a flow chart of determining a plurality of boundary separation distances corresponding to a relationship diagram of customer mobile phone numbers and a boundary associated distance corresponding to each boundary separation distance in an embodiment of the present invention. In one embodiment, according to historical modification data, the customer mobile phone is determined The multiple boundary separation distances corresponding to the relationship diagram and the boundary association distances corresponding to each boundary separation distance, including:

Step 601, for each piece of historical modification data, determine the mobile phone number involved in the historical modification data;

Step 602, according to the customer mobile phone number relationship diagram, determine the association distance and the separation distance between the mobile phone numbers involved in the historical modification data;

Step 603, according to the association distance and the interval distance, determine the partial order of the historical modification data, wherein, for any two historical modification data, the partial order is used to determine whether the first historical modification data in the two historical modification data is greater than the The second historical modification data in the two historical modification data; wherein, among the two historical modification data, one is the first historical modification data, and the other is the second historical modification data;

Step 604, according to the partial order of the historical modification data, determine a plurality of maximum historical modification data in all the historical modification data, wherein the maximum historical modification data is the maximum element of the partial order;

Step 605, for each maximum historical modification data, determine the separation distance between the mobile phone numbers involved in the maximum historical modification data as the boundary separation distance, and determine the distance between the mobile phone numbers involved in the maximum historical modification data. The association distance is determined as the boundary association distance corresponding to the boundary separation distance.

It should be noted that, in this application, determining the correlation distance between the mobile phone numbers involved in the historical modification data refers to the relationship graph of the customer mobile phone numbers, the correlation distance and the shortest path algorithm corresponding to each edge on the graph, Determine the shortest distance between the involved mobile phone numbers, and use the shortest distance as the correlation distance between the involved mobile phone numbers; similarly, to determine the interval distance between the mobile phone numbers involved in the historical modification data, refer to the method based on the customer's mobile phone number Number relationship graph, and the interval distance and shortest path algorithm corresponding to each edge on the graph, determine the shortest distance between the involved mobile phone numbers, and use the shortest distance as the interval distance between the involved mobile phone numbers.

It should be noted that the maximal element of the partial order is in the set corresponding to the partial order, and there is no other element superior to the maximal element. In this application, the maximum historical modification data in all the historical modification data refers to: there is no other historical modification data in all other historical modification data except the maximum historical modification data in all the historical modification data, so that The other historical modification data is larger than the maximum historical modification data.

In one embodiment, in step 604, according to the partial order of the historical modification data, a method for determining a plurality of maximum historical modification data in all the historical modification data is as follows:

1. Initialize the maximum identifier corresponding to each historical modification data in all the historical modification data as possible, and initialize the corresponding comparison identifier as yes;

2. For each historical modification data in all historical modification data in turn, if the corresponding maximal identification of the historical modification data is possible, all other historical modification data except the historical modification data will be selected from all historical modification data. From the data, select a plurality of other historical modification data whose corresponding comparison marks are yes, and then set the historical modification data to be compared corresponding to the historical modification data as the selected other historical modification data; if the historical modification data corresponds to is not possible, then continue to perform step 2 for the next historical modification data;

3. Select each historical modification data to be compared corresponding to the historical modification data in turn. If the historical modification data to be compared is better than the historical modification data, then the maximum identifier corresponding to the historical modification data is set to No, and then continue to The next historical modification data performs the above-mentioned step 2; if the historical modification data is better than the historical modification data to be compared, then the maximum identifier corresponding to the historical modification data to be compared is set to No, and the historical modification data to be compared is determined. It is the secondary historical modification data of the historical modification data; otherwise, the maximum identifier corresponding to the historical modification data and the maximum identifier corresponding to the historical modification data to be compared remain unchanged;

4. If it is confirmed that all the historical modification data to be compared in the historical modification data are not superior to the historical modification data (that is, after comparing the historical modification data and each corresponding historical modification data to be compared in turn, the historical modification data corresponds to The maximum identification is still possible), then determine the historical modification data as the maximum historical modification data among all the historical modification data, and update the comparison identification of each sub-historical modification data of the maximum historical modification data as no;

5. Then continue to perform step 2 for the next historical modification data until the above steps are completed for all historical modification data.

In one embodiment, the partial order of the historical modification data is determined according to the association distance and the separation distance, including:

Determine the partial order of the historical modification data, wherein, for any two historical modification data, if the correlation distance between the mobile phone numbers involved in the first historical modification data of the two historical modification data is greater than or equal to the distance between the two historical modification data The association distance between the mobile phone numbers involved in the second historical modification data, and the distance between the mobile phone numbers involved in the first historical modification data is greater than or equal to the interval between the mobile phone numbers involved in the second historical modification data distance, it is determined that the first historical modification data is greater than the second historical modification data.

7 is a flow chart 1 of determining a potential associated mobile phone number of a mobile phone number according to an embodiment of the present invention. In one embodiment, for each mobile phone number, a plurality of boundary separation distances and a boundary association corresponding to each boundary separation distance are performed. Distance, to identify potential associated phone numbers for this phone number, including:

Step 701, in the customer mobile phone number relationship diagram, for each mobile phone number, calculate the associated distance between the mobile phone number and all other mobile phone numbers and the distance between the mobile phone number and all mobile phone numbers;

Step 702, for each other mobile phone number, if there is a border separation distance and a border associated distance corresponding to the border separation distance, so that the separation distance between the mobile phone number and the other mobile phone numbers is less than or equal to the border separation distance, and the mobile phone number is equal to or equal to the border separation distance. The association distance of the other mobile phone numbers is less than or equal to the boundary association distance corresponding to the boundary separation distance, and the other mobile phone numbers are determined as potential associated mobile phone numbers of the mobile phone number.

It should be noted that, the method corresponding to FIG. 7 is applicable to the situation when the structural complexity of the client phone number relationship graph is less than the first threshold. Otherwise, the complexity of the corresponding method will be very high, that is, there will be redundancy in the calculation of this method. When the structural complexity of the customer mobile phone number relationship diagram is not less than the first threshold, the following methods corresponding to the second and third flowcharts of determining a potential associated mobile phone number of a mobile phone number may be used.

FIG. 8 is a second flowchart of determining a potentially associated mobile phone number of a mobile phone number in an embodiment of the present invention, and another method for determining a potential associated mobile phone number of a mobile phone number is presented here. In one embodiment, for each mobile phone number, the potential associated mobile phone number of the mobile phone number is determined according to a plurality of boundary separation distances and a boundary association distance corresponding to each boundary separation distance, including:

Step 801, when the structural complexity of the customer mobile phone number relationship graph is not less than the first threshold, delete the edges with the corresponding association distance greater than the specified threshold from the customer mobile phone number relationship graph, and use the following in the customer mobile phone number relationship graph: The steps to determine potential associated phone numbers for that phone number:

Step 802, for each mobile phone number, add the mobile phone number associated with the mobile phone number to the queue in ascending order according to the associated distance with the mobile phone number, and determine the relationship between the mobile phone number and each associated mobile phone number of the mobile phone number. The first distance is the distance between the corresponding sides of the mobile phone number and the associated mobile phone number in the customer mobile phone number relationship diagram, and the second distance between the mobile phone number and each associated mobile phone number of the mobile phone number is the mobile phone number and the mobile phone number. For the association distance of the corresponding edge of the associated mobile phone number in the customer mobile phone number relationship graph, repeat the following steps until the queue corresponding to the mobile phone number is empty, and obtain the set of potential associated mobile phone numbers for the mobile phone number:

Step 8021, pop up the mobile phone number of the team leader from the queue, and add the mobile phone number of the team leader to the set of potential associated mobile phone numbers of the mobile phone number;

Step 8022: Obtain the associated mobile phone number of the team's first mobile phone number, and for each associated mobile phone number of the team's first mobile phone number, determine whether the associated mobile phone number is added to the set of potential associated mobile phone numbers of the mobile phone number; if not, determine The first distance and the second distance between the mobile phone number and the associated mobile phone number; if there is a border separation distance and a border associated distance corresponding to the border separation distance, the first distance between the mobile phone number and the associated mobile phone number is less than or equal to the border separation distance, and the second distance between the mobile phone number and the associated mobile phone number is less than or equal to the boundary associated distance corresponding to the boundary separation distance, then the associated mobile phone number is used as the team’s first mobile phone number to be added; The second distance of the number is added to the queue in order from small to large.

The calculation method for determining the first distance between the mobile phone number and the associated mobile phone number (the second distance is similar and will not be repeated here): M _i IN(d1(i)+d2(i)), where d1(i ) is the ith potential associated mobile phone among all potential associated mobile phone numbers that have been added to the mobile phone number and that are directly connected to the associated mobile phone number in the client mobile phone number relationship graph The first distance of the mobile phone number, d2(i) is all potential associations between the associated mobile phone number and the set of potential associated mobile phone numbers that have been added to the mobile phone number and are directly connected to the associated mobile phone number in the customer mobile phone number relationship graph The distance between the edges corresponding to the i-th potential associated mobile phone number in the mobile phone number relationship graph of the customer.

FIG. 9 is a third flowchart of determining a potentially associated mobile phone number of a mobile phone number according to an embodiment of the present invention, and another method for determining a potential associated mobile phone number of a mobile phone number is presented here. In one embodiment, for each mobile phone number, the potential associated mobile phone number of the mobile phone number is determined according to a plurality of boundary separation distances and a boundary association distance corresponding to each boundary separation distance, including:

Step 901, for each mobile phone number A, add all associated mobile phone numbers of the mobile phone number A to the candidate set corresponding to the mobile phone number A; and add the third distance corresponding to each associated mobile phone number of the mobile phone number A Initialized as the separation distance between the mobile phone number A and the associated mobile phone number in the client mobile phone number relationship diagram, and the corresponding fourth distance is initialized as the mobile phone number A and the associated mobile phone number in the client mobile phone number relationship diagram. The associated distance of the edge of ; for other mobile phone numbers except the mobile phone number A and the associated mobile phone number of the mobile phone number A, the corresponding third distance is initialized to a value greater than the distance between all boundaries, and the corresponding third distance is initialized. The four distances are initialized to a value greater than the distance associated with all boundaries;

Step 902, select the mobile phone number B with the minimum corresponding association distance from the candidate set corresponding to the mobile phone number A; The third distance of the mobile phone number B is less than or equal to the border interval distance, and the fourth distance between the mobile phone number A and the selected mobile phone number B is less than or equal to the border associated distance corresponding to the border interval distance, then the selected The mobile phone number B is added to the set of potential associated mobile phone numbers of the mobile phone number A, and the selected mobile phone number B is deleted from the candidate set corresponding to the mobile phone number A; otherwise, stop determining the potential association of the mobile phone number A Phone number;

Step 903, for each associated phone number C of the selected phone number B in turn, determine whether the associated phone number C has been added to the set of potential associated phone numbers of the phone number A, if not, the associated phone number C is added to the candidate set corresponding to the mobile phone number A;

Step 904, for each associated mobile phone number C of the selected mobile phone number B in turn, update the third distance of the associated mobile phone number C to min(d1 _Co , d1 _B +d1(B, C)), where d1 _Co is the third distance of the associated mobile phone number C before the update, d1 _B is the third distance of the selected mobile phone number B, and d1(B, C) is the relationship between the mobile phone number B and the mobile phone number C in the customer mobile phone number diagram The distance between the corresponding sides in , and the fourth distance for updating the associated mobile phone number C is min(d2 _Co , d2 _B +d2(B, C)), where d2 _Co is the associated mobile phone number C before the update The fourth distance, d2 _B is the fourth distance of the selected mobile phone number B, and d2 (B, C) is the associated distance between the corresponding edges of the mobile phone number B and the mobile phone number C in the customer mobile phone number relationship diagram;

Step 905 , after steps 903 and 904 are performed on all associated mobile phone numbers of the selected mobile phone number B, step 902 is performed.

10 is a flowchart of determining whether to support mobile phone number modification through face recognition in an embodiment of the present invention. In one embodiment, if the new mobile phone number is in the set of potential associated mobile phone numbers of the old mobile phone number, according to the potential associated mobile phone number Set the face recognition thresholds of customers, perform face recognition on customers, and judge whether to support mobile phone number modification according to the face recognition results, including:

Step 1001, compare the collected customer face with the old mobile phone number and the customer face in the potential associated mobile phone number set of the old mobile phone number one by one to obtain a matching value;

Step 1002: Determine the face corresponding to the mobile phone number with the largest matching value as the face of the customer who handles the modification of the mobile phone number this time;

Step 1003, if the customer corresponding to the determined face and the customer corresponding to the old mobile phone number are the same customer, it is determined that the mobile phone number modification is supported; otherwise, the mobile phone number modification is not supported.

11 is a flow chart of correcting a customer's face recognition threshold in an embodiment of the present invention. In one embodiment, the correlation distance between the old mobile phone number and the new mobile phone number is determined, and the customer's face recognition threshold is corrected according to the correlation distance, include:

Step 1101, according to the shortest path algorithm, determine the association distance between the two nodes corresponding to the old mobile phone number and the new mobile phone number in the customer mobile phone number relationship graph;

Step 1102: Determine the degree of association between the old mobile phone number and the new mobile phone number according to the correlation distance between the two nodes corresponding to the old mobile phone number and the new mobile phone number in the client mobile phone number relationship graph;

Step 1103, according to the correlation degree, from the historical modification data, select the historical modification data whose correlation degree of the corresponding two mobile phone numbers is equal to the correlation degree;

Step 1104, according to the selected historical modification data, determine the face recognition threshold value corresponding to the correlation degree, so that when the face recognition threshold value of the selected historical modification data is set to the face recognition threshold value corresponding to the correlation degree, the corresponding The risk factor is less than or equal to the set value;

Step 1105, amend the face recognition threshold corresponding to the current mobile phone number to be the maximum value of the face recognition threshold corresponding to the correlation between the two mobile phone numbers and the customer's previous face recognition threshold.

其中s₁是旧手机号与新手机号在客户手机号关系图中对应的两个节点之间的关联距离。Among them, according to the correlation distance between the two nodes corresponding to the old mobile phone number and the new mobile phone number in the customer mobile phone number relationship graph, determine the degree of correlation between the old mobile phone number and the new mobile phone number, which can be: The correlation degree of the number is determined as:

where s ₁ is the association distance between the two nodes corresponding to the old mobile phone number and the new mobile phone number in the customer mobile phone number relationship graph.

Among them, for each historical modification data, the correlation degree of the two mobile phone numbers corresponding to the historical modification data is determined according to the following method: according to the relationship graph of customer mobile phone numbers, and the correlation distance and shortest path algorithm corresponding to each edge on the graph, The shortest distance between the two mobile phone numbers is determined, and the shortest distance is taken as the correlation distance s between the two mobile phone numbers; the correlation degree of the two mobile phone numbers is determined to be 10 ^-s .

The above-mentioned corresponding risk coefficient is determined as the proportion of risk data in the selected historical modification data when the face recognition threshold of the selected historical modification data is set to the face recognition threshold corresponding to the association distance. Risk data is risky data. For example, when the face recognition threshold is set relatively low, others can tamper with the customer's mobile phone number, causing risks to the customer. If the set value is set relatively high, this risk data (after modifying before) is no longer risk data (after modification). The higher the face recognition threshold, the smaller the risk factor. ). The set value can be the risk coefficient corresponding to all mobile phone number modification business data (that is, the proportion of risk data in all mobile phone number modification business data), and the risk coefficient is stored in the bank server.

To sum up, in the method proposed in the embodiment of the present invention, a relationship diagram of customer mobile phone numbers of bank outlets is constructed; according to the relationship diagram of customer mobile phone numbers and historical modification data, for each mobile phone number, the potential associated mobile phone of the mobile phone number is determined. When a customer modifies a mobile phone number at a bank outlet, if the new mobile phone number is in the potentially associated mobile phone number set of the old mobile phone number, the customer will be recognized based on the potential associated mobile phone number set and the customer's face recognition threshold. , according to the face recognition result to determine whether to support the modification of the mobile phone number; if the new mobile phone number is not in the set of potential associated mobile phone numbers of the old mobile phone number, determine the correlation distance between the old mobile phone number and the new mobile phone number, and correct the customer's person according to the correlation distance Face recognition threshold, perform face recognition on customers according to the revised face recognition threshold, and judge whether to support mobile phone number modification according to the face recognition result. In the above process, it is judged whether to support the modification of the mobile phone number according to the relationship map of the customer's mobile phone number, the historical modification data and the face recognition threshold of the bank branch, and the above-mentioned face recognition threshold can be determined according to the correlation distance between the old mobile phone number and the new mobile phone number. Make corrections, so that the risk control of mobile phone number modification can be carried out accurately in real time.

The embodiment of the present invention also proposes a mobile phone number risk control device in a bank outlet, the principle of which is similar to that of the mobile phone number risk control method in a bank outlet, and will not be repeated here.

12 is a schematic diagram of a mobile phone number risk control device in a bank outlet according to an embodiment of the present invention, including:

The customer mobile phone number relationship diagram building module 1201 is used to construct the customer mobile phone number relationship diagram in the bank;

A potential associated person determination module 1202, configured to determine, for each phone number, a set of potential associated phone numbers of the phone number according to the customer phone number relationship diagram and historical modification data;

The mobile phone number modification judgment module 1203 is used for when the customer modifies the mobile phone number at the bank outlet, if the new mobile phone number is in the set of potential associated mobile phone numbers of the old mobile phone number, according to the set of potential associated mobile phone numbers and the customer's face recognition threshold, Perform face recognition on customers, and judge whether to support mobile phone number modification according to the results of face recognition;

The face recognition threshold correction module 1204 is used to determine the correlation distance between the old mobile phone number and the new mobile phone number if the new mobile phone number is not in the set of potential associated mobile phone numbers of the old mobile phone number, and correct the customer's face recognition threshold according to the correlation distance , modify the customer's face recognition threshold according to the association distance, perform face recognition on the customer according to the revised face recognition threshold, and judge whether to support the modification of the mobile phone number according to the face recognition result.

In one embodiment, the customer mobile phone number relationship graph building module is specifically used for:

Determine the associated mobile number for each mobile number;

Calculate the degree of association between each mobile phone number and the mobile phone number associated with the mobile phone number;

Calculate the association distance between each mobile phone number and the associated mobile phone number of the mobile phone number based on the degree of association between each mobile phone number and the mobile phone number associated with the mobile phone number;

According to the association distance, a relationship graph of customer mobile phone numbers is constructed.

In one embodiment, the customer mobile phone number relationship graph building module is specifically used for:

Acquire two accounts involved in each transfer data, and determine the two mobile phone numbers corresponding to the two accounts as the associated mobile phone numbers of the other party.

In one embodiment, the customer mobile phone number relationship graph building module is specifically used for:

For each mobile phone number, the amount of transfer data involved between the mobile phone number and each associated mobile phone number of the mobile phone number is determined as the amount of associated data corresponding to each associated mobile phone number of the mobile phone number;

Determine the maximum value of all the associated data volumes as the associated data maximum value;

For each mobile phone number, the degree of association between the mobile phone number and each associated mobile phone number of the mobile phone number is determined as the ratio of the amount of associated data corresponding to each associated mobile phone number of the mobile phone number to the maximum value of the associated data.

In one embodiment, the customer mobile phone number relationship graph building module is specifically used for:

For each mobile phone number, determine the association distance between the mobile phone number and each associated mobile phone number of the mobile phone number as -lg(r), where r is the distance between the mobile phone number and each associated mobile phone number of the mobile phone number The correlation degree of , lg is the logarithmic function of base 10.

In one embodiment, the customer mobile phone number relationship graph building module is specifically used for:

Take each mobile phone number as a node;

If and only if the two mobile phone numbers are each other's associated mobile phone numbers, the nodes corresponding to the two mobile phone numbers have edges;

The association distance of the determined edge is the association distance between the two mobile phone numbers corresponding to the edge, and the interval distance of the determined edge is 1.

In one embodiment, the potential associated person determination module is specifically used for:

According to the historical modification data, determine a plurality of boundary separation distances corresponding to the customer mobile phone number relationship diagram and the boundary association distance corresponding to each boundary separation distance;

For each mobile phone number, a set of potential associated mobile phone numbers of the mobile phone number is determined according to a plurality of boundary separation distances and a boundary association distance corresponding to each boundary separation distance.

In one embodiment, the potential associated person determination module is specifically used for:

For each piece of historical modification data, determine the mobile phone number involved in the historical modification data;

Determine the correlation distance and separation distance between the mobile phone numbers involved in the historical modification data according to the customer mobile phone number relationship diagram;

Determine the partial order of the historical modification data according to the association distance and the interval distance, wherein, for any two historical modification data, the partial order is used to determine whether the first historical modification data in the two historical modification data is greater than the two historical modification data Modify the second historical modification data in the modification data;

According to the partial order of the historical modification data, determine a plurality of maximum historical modification data in all the historical modification data, wherein the maximum historical modification data is the maximum element of the partial order;

For each maximum historical modification data, the separation distance between the mobile phone numbers involved in the maximum historical modification data is determined as the boundary separation distance, and the correlation distance between the mobile phone numbers involved in the maximum historical modification data is determined. It is the boundary association distance corresponding to the boundary separation distance.

In one embodiment, the potential associated person determination module is specifically used for:

Determine the partial order of the historical modification data, wherein, for any two historical modification data, if the correlation distance between the mobile phone numbers involved in the first historical modification data of the two historical modification data is greater than or equal to the distance between the two historical modification data The association distance between the mobile phone numbers involved in the second historical modification data, and the distance between the mobile phone numbers involved in the first historical modification data is greater than or equal to the interval between the mobile phone numbers involved in the second historical modification data distance, it is determined that the first historical modification data is greater than the second historical modification data.

In one embodiment, the potential associated person determination module is specifically used for:

When the structural complexity of the customer mobile phone number relationship diagram is less than the first threshold, in the customer mobile phone number relationship diagram, for each mobile phone number, the correlation distance between the mobile phone number and all other mobile phone numbers and the mobile phone number and all mobile phone numbers are calculated. the separation distance;

For each other mobile phone number, if there is a border separation distance and a border associated distance corresponding to the border separation distance, such that the separation distance between the mobile phone number and the other mobile phone number is less than or equal to the border separation distance, and the mobile phone number and the other mobile phone number If the associated distance of the mobile phone number is less than or equal to the border associated distance corresponding to the border interval distance, the other mobile phone number is determined as the potential associated mobile phone number of the mobile phone number.

In one embodiment, the mobile phone number modification judgment module is specifically used for:

Compare the collected customer faces with the old mobile phone numbers and the customer faces in the set of potential associated mobile phone numbers of the old mobile phone numbers to obtain a matching value;

Determine the face corresponding to the mobile phone number with the largest matching value as the face of the customer who handles the modification of the mobile phone number this time;

If the customer corresponding to the determined face and the customer corresponding to the old mobile phone number are the same customer, confirm that the mobile phone number modification is supported; otherwise, the mobile phone number modification is not supported.

In one embodiment, the face recognition threshold correction module is specifically used for:

According to the shortest path algorithm, determine the association distance between the two nodes corresponding to the old mobile phone number and the new mobile phone number in the customer mobile phone number relationship graph;

According to the association distance, from the historical modification data, select the historical modification data in which the association distance of the corresponding two mobile phone numbers is equal to the association distance;

According to the selected historical modification data, determine the face recognition threshold corresponding to the association distance, so that when the face recognition threshold of the selected historical modification data is set to the face recognition threshold corresponding to the association distance, the corresponding risk factor is less than equal to the set value;

Modify the face recognition threshold corresponding to the mobile phone number this time to the maximum value of the face recognition threshold corresponding to the correlation distance between the two mobile phone numbers and the customer's previous face recognition threshold.

To sum up, in the device proposed in the embodiment of the present invention, the customer mobile phone number relationship diagram building module is used to construct the customer mobile phone number relationship diagram in the bank; the potential associated person determination module is used to build a customer mobile phone number relationship diagram according to the customer phone number relationship diagram and history. Modification data, for each mobile phone number, determine the set of potential associated mobile phone numbers of the mobile phone number; the mobile phone number modification judgment module is used when the customer modifies the mobile phone number at the bank outlet, if the new mobile phone number is in the potential associated mobile phone of the old mobile phone number In the set of mobile phone numbers, according to the set of potentially associated mobile phone numbers and the customer's face recognition threshold, face recognition is performed on the customer, and according to the face recognition result, it is judged whether to support the modification of the mobile phone number; the face recognition threshold correction module is used for new mobile phones. If the number is not in the set of potential associated mobile phone numbers of the old mobile phone number, determine the correlation distance between the old mobile phone number and the new mobile phone number, correct the customer's face recognition threshold according to the correlation distance, and correct the customer's face recognition threshold according to the correlation distance. , perform face recognition on the customer according to the revised face recognition threshold, and judge whether to support the modification of the mobile phone number according to the face recognition result. In the above process, it is judged whether to support the modification of the mobile phone number according to the relationship map of the customer's mobile phone number, the historical modification data and the face recognition threshold of the bank outlet, and the above face recognition threshold can be determined according to the correlation distance between the old mobile phone number and the new mobile phone number. Make corrections, so that the risk control of mobile phone number modification can be carried out accurately in real time.

An embodiment of the present invention further provides a computer device. FIG. 13 is a schematic diagram of a computer device in an embodiment of the present invention. The computer device 1300 includes a memory 1310, a processor 1320, and is stored in the memory 1310 and can run on the processor 1320. The computer program 1330 described above, when the processor 1320 executes the computer program 1330, implements the above risk control method for the mobile phone number of a bank outlet.

Embodiments of the present invention further provide a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the above-mentioned risk control method for a mobile phone number of a bank outlet is implemented.

An embodiment of the present invention further provides a computer program product, where the computer program product includes a computer program, and when the computer program is executed by a processor, the above-mentioned risk control method for a mobile phone number of a bank outlet is implemented.

Those skilled in the art will appreciate that embodiments of the present invention may be provided as a method, a system, or a computer program business system. Accordingly, 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 business system implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present invention is described with reference to flowcharts and/or block diagrams of methods, apparatus (systems), and computer program business systems according to embodiments of the present invention. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above-mentioned specific embodiments are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (16)

1. A bank branch mobile phone number risk control method is characterized by comprising the following steps:

constructing a customer mobile phone number relation diagram of a bank outlet;

determining a potential associated mobile phone number set of each mobile phone number according to the relation graph of the mobile phone numbers of the clients and historical modification data;

when a customer modifies the mobile phone number at a bank outlet, if the new mobile phone number is in a potential associated mobile phone number set of the old mobile phone number, carrying out face recognition on the customer according to the potential associated mobile phone number set and a face recognition threshold value of the customer, and judging whether the modification of the mobile phone number is supported or not according to a face recognition result;

if the new mobile phone number is not in the set of potential associated mobile phone numbers of the old mobile phone number, determining the associated distance between the old mobile phone number and the new mobile phone number, correcting the face recognition threshold value of the customer according to the associated distance, carrying out face recognition on the customer according to the corrected face recognition threshold value, and judging whether the mobile phone number modification is supported or not according to the face recognition result.

2. The method as claimed in claim 1, wherein constructing a phone number relationship diagram for a customer at a banking site comprises:

determining an associated mobile phone number of each mobile phone number;

calculating the association degree between each mobile phone number and the associated mobile phone number of the mobile phone number;

calculating the association distance between each mobile phone number and the associated mobile phone number of the mobile phone number based on the association degree between each mobile phone number and the associated mobile phone number of the mobile phone number;

and constructing a customer mobile phone number relation graph according to the association distance.

3. The method of claim 2, wherein determining the associated phone number for each phone number comprises:

and acquiring two accounts related to each piece of transfer data, and determining two mobile phone numbers corresponding to the two accounts as the related mobile phone numbers of the opposite party.

4. The method of claim 3, wherein calculating the association between each phone number and the associated phone number for that phone number comprises:

for each mobile phone number, determining the quantity of transfer data related between the mobile phone number and each associated mobile phone number of the mobile phone number as the associated data quantity corresponding to each associated mobile phone number of the mobile phone number;

determining the maximum value in all the related data quantities as the maximum value of the related data;

for each mobile phone number, determining the association degree between the mobile phone number and each associated mobile phone number of the mobile phone number as the ratio of the associated data amount corresponding to each associated mobile phone number of the mobile phone number to the maximum value of the associated data.

5. The method of claim 2, wherein calculating the association distance between each mobile phone number and the associated mobile phone number of the mobile phone number based on the association degree between each mobile phone number and the associated mobile phone number of the mobile phone number comprises:

for each mobile phone number, determining the association distance between the mobile phone number and each associated mobile phone number of the mobile phone number as-lg (r), wherein r is the association degree between the mobile phone number and each associated mobile phone number of the mobile phone number, and lg is a logarithmic function with the base 10 as the base.

6. The method of claim 2, wherein constructing a customer mobile phone number relationship graph based on the association distances comprises:

each mobile phone number is used as a node;

if and only if the two mobile phone numbers are the related mobile phone numbers of the opposite party, the nodes corresponding to the two mobile phone numbers have edges;

and determining the association distance of the edge as the association distance between the two mobile phone numbers corresponding to the edge, and determining the interval distance of the edge as 1.

7. The method of claim 1, wherein determining, for each phone number, a set of potential associated phone numbers for the phone number based on the customer phone number relationship graph and the historical modification data comprises:

determining a plurality of boundary interval distances corresponding to the customer mobile phone number relation graph and a boundary association distance corresponding to each boundary interval distance according to historical modification data;

and for each mobile phone number, determining a potential associated mobile phone number set of the mobile phone number according to the plurality of boundary spacing distances and the boundary associated distance corresponding to each boundary spacing distance.

8. The method of claim 7, wherein determining a plurality of boundary separation distances and a boundary association distance corresponding to each boundary separation distance for the customer mobile phone number relationship graph based on historical modification data comprises:

for each piece of historical modification data, determining the mobile phone number related in the historical modification data;

determining the association distance and the interval distance between the mobile phone numbers related in the historical modification data according to the mobile phone number relation graph of the client;

determining a partial order of the historical modified data according to the association distance and the interval distance, wherein for any two pieces of historical modified data, the partial order is used for determining whether a first historical modified data of the two pieces of historical modified data is larger than a second historical modified data of the two pieces of historical modified data;

determining a plurality of maximum historical modification data in all the historical modification data according to the partial order of the historical modification data, wherein the maximum historical modification data are maximum elements of the partial order;

for each maximum historical modification data, determining the interval distance between the mobile phone numbers involved in the maximum historical modification data as a boundary interval distance, and determining the association distance between the mobile phone numbers involved in the maximum historical modification data as a boundary association distance corresponding to the boundary interval distance.

9. The method of claim 8, wherein determining a partial order of historical modification data as a function of the correlation distance and the separation distance comprises:

determining the partial order of historical modification data, wherein for any two pieces of historical modification data, if the association distance between the mobile phone numbers involved in the first historical modification data of the two pieces of historical modification data is greater than or equal to the association distance between the mobile phone numbers involved in the second historical modification data of the two pieces of historical modification data, and the separation distance between the mobile phone numbers involved in the first historical modification data is greater than or equal to the separation distance between the mobile phone numbers involved in the second historical modification data, determining that the first historical modification data is greater than the second historical modification data.

10. The method of claim 9, wherein for each mobile phone number, determining the potential associated mobile phone number for the mobile phone number according to the plurality of boundary separation distances and the boundary associated distance corresponding to each boundary separation distance comprises:

in the customer mobile phone number relation graph, for each mobile phone number, calculating the association distance between the mobile phone number and all other mobile phone numbers and the spacing distance between the mobile phone number and all mobile phone numbers;

and for each other mobile phone number, if the boundary interval distance and the boundary association distance corresponding to the boundary interval distance exist, enabling the interval distance between the mobile phone number and the other mobile phone number to be smaller than or equal to the boundary interval distance, and enabling the association distance between the mobile phone number and the other mobile phone number to be smaller than or equal to the boundary association distance corresponding to the boundary interval distance, and determining the other mobile phone number as the potential association mobile phone number of the mobile phone number.

11. The method of claim 1, wherein if the new mobile phone number is in the set of potential associated mobile phone numbers of the old mobile phone number, performing face recognition on the customer according to the set of potential associated mobile phone numbers and a face recognition threshold of the customer, and determining whether the mobile phone number modification is supported according to the face recognition result comprises:

comparing the collected customer faces with the old mobile phone numbers and the customer faces in the potential associated mobile phone number set of the old mobile phone numbers one by one to obtain matching values;

determining the face corresponding to the mobile phone number with the maximum matching value as the face of the client handling the modification of the mobile phone number;

and if the determined customer corresponding to the face and the customer corresponding to the old mobile phone number are the same customer, determining that the mobile phone number modification is supported, otherwise, not supporting the mobile phone number modification.

12. The method of claim 2, wherein determining an associated distance between an old phone number and a new phone number, and modifying the face recognition threshold of the customer based on the associated distance comprises:

determining the association distance between two corresponding nodes of the old mobile phone number and the new mobile phone number in the customer mobile phone number relation graph according to the shortest path algorithm;

determining the association degree of the old mobile phone number and the new mobile phone number according to the association distance between two corresponding nodes of the old mobile phone number and the new mobile phone number in the mobile phone number relation graph of the customer;

according to the association degree, selecting historical modification data of which the association degree of the corresponding two mobile phone numbers is equal to the association degree from the historical modification data;

determining a face recognition threshold corresponding to the association degree according to the selected historical modification data, so that when the face recognition threshold of the selected historical modification data is set as the face recognition threshold corresponding to the association degree, the corresponding risk coefficient is less than or equal to a set value;

and correcting the face recognition threshold corresponding to the modified mobile phone number to be the face recognition threshold corresponding to the association degree of the two mobile phone numbers and the maximum value of the face recognition threshold before the client.

13. A bank branch mobile phone number risk control device is characterized by comprising:

the customer mobile phone number relation graph building module is used for building a customer mobile phone number relation graph in a bank;

the potential associated person determining module is used for determining a potential associated mobile phone number set of each mobile phone number according to the customer mobile phone number relation graph and the historical modification data;

the mobile phone number modification judging module is used for carrying out face recognition on the customer according to the potential associated mobile phone number set and the face recognition threshold value of the customer when the customer modifies the mobile phone number at a bank branch point and if a new mobile phone number is in the potential associated mobile phone number set of an old mobile phone number, and judging whether the modification of the mobile phone number is supported or not according to the face recognition result;

and the face recognition threshold correction module is used for determining the association distance between the old mobile phone number and the new mobile phone number if the new mobile phone number is not in the potential association mobile phone number set of the old mobile phone number, correcting the face recognition threshold of the customer according to the association distance, carrying out face recognition on the customer according to the corrected face recognition threshold, and judging whether the mobile phone number is supported to be modified according to the face recognition result.

14. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 12 when executing the computer program.

15. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of any one of claims 1 to 12.

16. A computer program product, characterized in that the computer program product comprises a computer program which, when being executed by a processor, carries out the method of any one of claims 1 to 12.

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