CN115660815A

CN115660815A - Method and device for supporting bank customer withdrawal transaction

Info

Publication number: CN115660815A
Application number: CN202211401823.6A
Authority: CN
Inventors: 朱江波
Original assignee: Bank of China Ltd
Current assignee: Bank of China Ltd
Priority date: 2022-11-10
Filing date: 2022-11-10
Publication date: 2023-01-31

Abstract

The invention provides a method and a device for supporting a bank customer to withdraw money, which relate to the technical field of computer data processing, and the method comprises the following steps: the bank server determines the corresponding relation between the correlation coefficient and the characteristic value; determining the corresponding relation between the correlation coefficient and the characteristic modular length; a mobile terminal of a first client sends a withdrawal certificate acquisition request to a bank server; when the bank server determines that the first customer belongs to the controllable customer, generating a withdrawal certificate of the first customer; the second customer initiates a withdrawal transaction request based on the withdrawal certificate at a corresponding bank outlet; the bank outlet corresponding to the withdrawal obtains the identity information of the second customer; and the edge computing system of the bank outlets carries out risk control on the withdrawal transaction according to the identity information of the first customer and the second customer, prestored associated customers corresponding to each customer in the edge computing system, associated coefficients of each customer and the corresponding associated customers, corresponding relations between the associated coefficients and the characteristic modular length and the modular length threshold value.

Description

Method and device for supporting bank customer withdrawal transaction

Technical Field

The invention relates to the technical field of computer data processing, in particular to a method and a device for supporting a bank customer to withdraw money.

Background

This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.

In banking scenarios, withdrawal transactions are common transactions and also very important transactions. For the withdrawal transaction, risk analysis is usually performed based on fixed rules, and the risk control efficiency is not high, so that the withdrawal transaction mode is single, and the customer experience is poor.

In view of the above, there is a need for a technical solution that can overcome the above-mentioned drawbacks and effectively control the risk of withdrawal transactions.

Disclosure of Invention

In order to solve the problems in the prior art, the invention provides a method and a device for supporting a bank customer withdrawal transaction.

In a first aspect of an embodiment of the present invention, a method for supporting a cash withdrawal transaction of a bank customer is provided, including:

the bank server determines the corresponding relation between the association coefficient and the characteristic value and prestores the determined corresponding relation between the association coefficient and the characteristic value in the bank server;

the bank server determines the corresponding relation between the correlation coefficient and the characteristic modular length according to the corresponding relation between the correlation coefficient and the characteristic value, and issues the determined corresponding relation between the correlation coefficient and the characteristic modular length to an edge computing system of a bank outlet;

the method comprises the following steps that a mobile terminal of a first client sends a withdrawal certificate acquisition request to a bank server, wherein the request comprises: identity information of a first customer and a bank outlet corresponding to the withdrawal;

the bank server determining whether the first customer is a controllable customer;

when the bank server determines that the first client belongs to the controllable client, the bank server generates a withdrawal certificate of the first client according to the identity information of the first client and issues the generated withdrawal certificate to the mobile terminal of the first client;

the bank server issues the associated customer corresponding to the first customer, the association coefficient of the first customer and the corresponding associated customer and the modular length threshold value to an edge computing system of a bank outlet corresponding to the withdrawal;

the second customer initiates a withdrawal transaction request based on the withdrawal certificate at a corresponding bank outlet;

the bank outlet corresponding to the withdrawal obtains the identity information of the second customer and the identity information of the first customer included in the withdrawal certificate, and sends the identity information of the first customer and the identity information of the second customer to an edge computing system of the bank outlet;

the marginal computing system of the bank outlet carries out risk control on the money withdrawing transaction according to the identity information of the first customer, the identity information of the second customer, pre-stored associated customers corresponding to all the customers in the marginal computing system, the association coefficient of each customer and the corresponding associated customer, the corresponding relation between the association coefficient and the characteristic modular length and the modular length threshold value.

In a second aspect of an embodiment of the present invention, an apparatus for supporting a cash withdrawal transaction of a bank customer is provided, including:

the bank server is used for determining the corresponding relation between the association coefficient and the characteristic value, pre-storing the determined corresponding relation between the association coefficient and the characteristic value in the bank server, and issuing the bank server to an edge computing system of a bank outlet;

the mobile terminal of the first client is used for sending a withdrawal certificate acquisition request to the bank server, wherein the request comprises: identity information of a first customer and a bank outlet corresponding to the withdrawal;

the bank server is further used for determining whether the first client belongs to the controllable client;

when the bank server determines that the first client belongs to the controllable client, generating a withdrawal certificate of the first client according to the identity information of the first client, and issuing the generated withdrawal certificate to a mobile terminal of the first client;

the bank server is also used for issuing the associated customer corresponding to the first customer, the association coefficient of the first customer and the corresponding associated customer and the module length threshold value to an edge computing system of a bank outlet corresponding to the withdrawal;

the bank outlet corresponding to the withdrawal is used for acquiring a withdrawal transaction request initiated by a second customer based on the withdrawal certificate;

the bank outlet corresponding to the withdrawal is also used for acquiring the identity information of the second customer and the identity information of the first customer in the withdrawal certificate and sending the identity information of the first customer and the identity information of the second customer to the edge computing system of the bank outlet;

and the edge computing system of the bank outlets is used for carrying out risk control on the withdrawal transaction according to the identity information of the first customer, the identity information of the second customer, pre-stored associated customers corresponding to each customer in the edge computing system, and the association coefficients and the modular length threshold of each customer and the corresponding associated customers.

In a third aspect of an embodiment of the present invention, a computer device is presented, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing a method of supporting a bank customer withdrawal transaction when executing the computer program.

In a fourth aspect of embodiments of the present invention, a computer-readable storage medium is presented, which stores a computer program that, when executed by a processor, implements a method of supporting a bank customer withdrawal transaction.

In a fifth aspect of an embodiment of the invention, a computer program product is presented, the computer program product comprising a computer program which, when executed by a processor, implements a method of supporting a bank customer withdrawal transaction.

The method and the device for supporting the bank customer withdrawal transaction provided by the invention realize effective control on the withdrawal transaction risk by analyzing the identity information of the customer, the pre-stored associated customers corresponding to each customer in the edge computing system, and the association coefficients and the modular length threshold values of each customer and the corresponding associated customers, thereby ensuring the property safety of the customer and the bank.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a flow chart of a method for supporting a cash withdrawal transaction of a bank customer according to an embodiment of the present invention.

Fig. 2 is a flowchart illustrating a process of determining a correspondence between a correlation coefficient and a feature value according to an embodiment of the present invention.

Fig. 3 is a flow chart illustrating a process of determining controllable clients according to an embodiment of the present invention.

Fig. 4 is a schematic flow chart illustrating a risk control process performed on the withdrawal transaction according to an embodiment of the present invention.

Fig. 5 is a schematic flow chart illustrating a risk control process performed on the withdrawal transaction according to another embodiment of the present invention.

Fig. 6 is a schematic diagram of an apparatus for supporting a cash withdrawal transaction of a bank customer according to an embodiment of the present invention.

Fig. 7 is a schematic diagram of an apparatus for supporting a cash withdrawal transaction of a bank customer according to another embodiment of the present invention.

Fig. 8 is a schematic structural diagram of a computer device according to an embodiment of the present invention.

Detailed Description

The principles and spirit of the present invention will be described with reference to a number of exemplary embodiments. It is understood that these embodiments are given solely for the purpose of enabling those skilled in the art to better understand and to practice the invention, and are not intended to limit the scope of the invention in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

As will be appreciated by one skilled in the art, embodiments of the present invention may be embodied as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.

According to the embodiment of the invention, a method and a device for supporting a bank customer withdrawal transaction are provided, and the technical field of computer data processing is involved.

The principles and spirit of the present invention are explained in detail below with reference to several exemplary embodiments of the present invention.

FIG. 1 is a flow chart illustrating a method for supporting a withdrawal transaction of a bank customer according to an embodiment of the present invention. As shown in fig. 1, the method includes:

s1, a bank server determines a corresponding relation between a correlation coefficient and a characteristic value, prestores the determined corresponding relation between the correlation coefficient and the characteristic value in the bank server, and issues the corresponding relation to an edge computing system of a bank outlet;

s2, the bank server determines the corresponding relation between the correlation coefficient and the characteristic modular length according to the corresponding relation between the correlation coefficient and the characteristic value, and issues the determined corresponding relation between the correlation coefficient and the characteristic modular length to an edge computing system of a bank outlet;

s3, the mobile terminal of the first client sends a withdrawal certificate acquisition request to the bank server, wherein the request comprises: identity information of a first customer and a bank outlet corresponding to the withdrawal;

s4, the bank server determines whether the first client belongs to the controllable client;

s5, when the bank server determines that the first client belongs to the controllable client, the bank server generates a withdrawal certificate of the first client according to the identity information of the first client and issues the generated withdrawal certificate to the mobile terminal of the first client;

s6, the bank server issues the associated customer corresponding to the first customer, the association coefficient of the first customer and the corresponding associated customer and the module length threshold value to an edge computing system of a bank outlet corresponding to the withdrawal;

s7, the second customer initiates a withdrawal transaction request based on the withdrawal certificate at a corresponding bank outlet for withdrawing money;

s8, the corresponding bank outlet for withdrawing money acquires the identity information of a second customer and the identity information of a first customer in the withdrawal certificate, and sends the identity information of the first customer and the identity information of the second customer to an edge computing system of the bank outlet;

and S9, the marginal computing system of the bank outlet carries out risk control on the money withdrawing transaction according to the identity information of the first customer, the identity information of the second customer, pre-stored associated customers corresponding to the customers in the marginal computing system, and association coefficients and module length threshold values of the customers and the associated customers.

For a more clear explanation of the above method for supporting a withdrawal transaction of a bank customer, a detailed description is given below with reference to a specific embodiment.

In an embodiment, referring to fig. 2, the present invention further includes the bank server determining the corresponding relationship between the association coefficient and the characteristic value according to the following method:

s201, a bank server acquires transfer transaction data of a bank;

s202, for each transfer transaction data, the bank server determines the correlation coefficient between the transfer-out customer and the transfer-in customer of the transfer transaction data, and takes the correlation coefficient as the correlation coefficient corresponding to the transfer transaction data;

s203, for each correlation coefficient, determining the transfer transaction data of which the corresponding correlation coefficient is equal to the correlation coefficient as the transfer transaction data corresponding to the correlation coefficient;

s204, determining a risk matrix corresponding to the correlation coefficient according to the transfer transaction data corresponding to the correlation coefficient;

s205, the eigenvalue of the risk matrix corresponding to the correlation coefficient, which is not 0, is taken as the eigenvalue corresponding to the correlation coefficient.

Specifically, (S202) the bank server determines a correlation coefficient between the transferring-out customer and the transferring-in customer of the transfer transaction data, including:

s202-1, when the bank server determines that the correlation coefficient between the roll-out customer and the roll-in customer of the transfer transaction data is not prestored, the bank server sends a correlation customer acquisition request to each bank system, wherein the acquisition request comprises a selected hash function, identity information of the roll-out customer and identity information of the roll-in customer;

s202-2, for each bank system, the bank system takes the hash value of the identity information of each associated client corresponding to the roll-out client, which is prestored in the bank system, as the associated client fingerprint of the roll-out client corresponding to the bank system according to the selected hash function, and takes the hash value of the identity information of each associated client corresponding to the roll-in client, which is prestored in the bank system, as the associated client fingerprint of the roll-in client corresponding to the bank system; taking the correlation coefficient of the roll-out client and each corresponding correlation client as the correlation coefficient of the fingerprint of the correlation client corresponding to the roll-out client and the correlation client with respect to the banking system, and taking the correlation coefficient of the roll-in client and each corresponding correlation client as the correlation coefficient of the fingerprint of the correlation client corresponding to the roll-in client and the correlation client with respect to the banking system;

s202-3, each bank system feeds back the determined associated client fingerprint of the roll-out client corresponding to the bank system, the association coefficient of the roll-out client and the associated client fingerprint corresponding to the bank system with respect to the bank system, the associated client fingerprint of the roll-in client corresponding to the bank system, and the association coefficient of the roll-in client and the associated client fingerprint corresponding to the bank system with respect to the bank system to a bank server;

s202-4, the bank server determines a plurality of associated client fingerprints corresponding to the money withdrawing transaction according to the associated client fingerprints corresponding to each bank system of the transferring-out client and the associated client fingerprints corresponding to each bank system of the transferring-in client;

s202-5, for each associated client fingerprint corresponding to the money withdrawing transaction, the bank server determines the association coefficient of the fingerprint of the transferring-out client and the associated client according to the association coefficient of the fingerprint of the transferring-out client and the associated client relative to each bank system, and determines the association coefficient of the fingerprint of the transferring-in client and the associated client according to the association coefficient of the fingerprint of the transferring-in client and the associated client relative to each bank system;

s202-6, the bank server determines the correlation coefficient of the roll-out customer and the roll-in customer according to a plurality of correlation customer fingerprints corresponding to the withdrawal transaction, the correlation coefficient of the roll-out customer and each correlation customer fingerprint corresponding to the withdrawal transaction, and the correlation coefficient of the roll-in customer and each correlation customer fingerprint corresponding to the withdrawal transaction.

In one embodiment, (S202-6) the bank server determines the correlation coefficient between the outgoing customer and the incoming customer according to a plurality of correlation customer fingerprints corresponding to the current withdrawal transaction, the correlation coefficient between the outgoing customer and each correlation customer fingerprint corresponding to the current withdrawal transaction, and the correlation coefficient between the incoming customer and each correlation customer fingerprint corresponding to the current withdrawal transaction, including:

determining the correlation coefficient between the roll-out client and the roll-in client according to the following formula:

wherein r is the correlation coefficient between the roll-out client and the roll-in client, r _i ¹ Is the correlation coefficient of the fingerprint of the ith correlation client corresponding to the transfer-out client and the withdrawal transaction, r _i ² Is the correlation coefficient of the i-th correlated customer fingerprint corresponding to the transfer-in customer and the withdrawal transaction.

and when the bank server determines that the correlation coefficient between the roll-out client and the roll-in client of the transfer transaction data is prestored, taking the pre-stored correlation coefficient between the roll-out client and the roll-in client of the transfer transaction data as the correlation coefficient between the roll-out client and the roll-in client of the transfer transaction data.

In one embodiment, the bank server determines the association coefficient between each client according to the following method:

the bank server acquires the associated customers corresponding to the customers pre-stored in each bank system and the association coefficients of the customers and the corresponding associated customers;

determining the associated customers corresponding to the customers and the associated coefficients of the customers and the corresponding associated customers according to the associated customers corresponding to the customers and the associated coefficients of the customers and the corresponding associated customers pre-stored in the bank systems;

for any two clients in the client set, if an associated client corresponding to a third client of the two clients exists and the associated client is an associated client corresponding to a fourth client, taking the third client as a potential associated client corresponding to the fourth client;

initializing the association coefficient of the third customer and the fourth customer; initializing coefficient increments of a third customer and a fourth customer to a fixed number, wherein the fixed number is greater than an increment threshold;

the following steps are executed in a loop until the condition t is not satisfied by any two clients: the fifth client of the two clients is a potential associated client corresponding to the sixth client, and the coefficient increment of the fifth client and the sixth client is greater than the increment threshold:

finding two customers, wherein the two customers meet the condition t;

updating the association coefficient of the fifth client and the sixth client in the two clients;

and updating the coefficient increment according to the updated correlation coefficient and the correlation coefficient before updating of the fifth client and the sixth client.

In one embodiment, initializing the association coefficients of the third client and the fourth client comprises:

for each associated client corresponding to the third client, if the associated client is the associated client corresponding to the fourth client, taking the associated client as an associated common client;

for each associated common client, taking the product of the association coefficient of the third client and the associated common client and the association coefficient of the fourth client and the associated common client as the association product corresponding to the associated common client;

and initializing the association coefficient of the third client and the fourth client to the maximum value of the association product corresponding to each association common client.

In one embodiment, updating the association coefficient of the fifth client and the sixth client comprises:

for each associated client corresponding to the fifth client, if the associated client is the associated client corresponding to the sixth client, taking the associated client as an associated common client;

for each associated common client, taking the product of the association coefficient of the fifth client and the associated common client and the association coefficient of the sixth client and the associated common client as the association product corresponding to the associated common client;

and initializing the association coefficient of the fifth client and the sixth client to the maximum value of the association product corresponding to each association common client.

Specifically, (S204) determining a risk matrix corresponding to the correlation coefficient according to the transfer transaction data corresponding to the correlation coefficient, including:

s204-1, for each customer category and each transfer channel, selecting transfer transaction data corresponding to the customer category and the transfer channel from the transfer transaction data corresponding to the association coefficient;

s204-2, determining the risk probability of the customer category and the transfer channel corresponding to the correlation coefficient according to the transfer transaction data corresponding to the customer category and the transfer channel;

s204-3, determining a risk matrix corresponding to the association coefficient, wherein rows of the risk matrix correspond to customer categories, columns of the risk matrix correspond to transfer channels, and the element value of each element of the risk matrix is equal to the risk probability of the customer category corresponding to the element and the corresponding transfer channel corresponding to the association coefficient;

s204-4, when the row number and the column number of the risk matrix corresponding to the correlation coefficient are not equal, performing 0 complementing according to the row number and the column number of the risk matrix corresponding to the correlation coefficient to obtain a risk square matrix corresponding to the correlation coefficient.

In one embodiment, (S2) the bank server determines a corresponding relationship between the correlation coefficient and the characteristic length according to the corresponding relationship between the correlation coefficient and the characteristic value, and issues the determined corresponding relationship between the correlation coefficient and the characteristic length to the edge computing system of the bank branch, including:

and regarding each correlation coefficient, taking the maximum value of the modular length of each characteristic value corresponding to the correlation coefficient as the characteristic modular length corresponding to the correlation coefficient.

In one embodiment, referring to fig. 3, the present invention further comprises the bank server determining the controllable client according to the following method:

s301, a bank server acquires transaction data of each client category;

s302, for each customer category, determining a risk matrix corresponding to the customer category according to the transaction data of the customer category;

s303, supplementing 0 according to the row number and the column number of the risk matrix corresponding to the client category to obtain a risk square matrix corresponding to the client category;

s304, taking the characteristic value of the risk matrix corresponding to the client category, which is not 0, as the characteristic value corresponding to the client category;

s305, determining controllable customers according to the characteristic values corresponding to the customer categories.

Specifically, (S302) for each customer category, determining a risk matrix corresponding to the customer category according to the transaction data of the customer category, including:

s302-1, for each transaction channel and each transaction category, selecting the transaction data corresponding to the transaction channel and the transaction category from the transaction data of the customer category;

s302-2, determining the risk probability of the transaction channel and the transaction category corresponding to the customer category according to the transaction data corresponding to the transaction channel and the transaction category;

s302-3, determining a risk matrix corresponding to the customer category, wherein rows of the risk matrix correspond to transaction channels, columns of the risk matrix correspond to transaction categories, and the element value of each element of the risk matrix is equal to the risk probability of the transaction channel corresponding to the element and the corresponding transaction category corresponding to the customer category.

Specifically, (S305) determining controllable customers according to the feature values corresponding to the customer categories, including:

and for each customer category, if the modular length of the characteristic value corresponding to the customer category is smaller than the set risk threshold, the customer of the customer category is taken as a controllable customer.

In an embodiment, referring to fig. 4, in S9, the performing, by the edge computing system of the banking outlet, risk control on the withdrawal transaction according to the identity information of the first customer, the identity information of the second customer, pre-stored associated customers corresponding to each customer in the edge computing system, and association coefficients, correspondence between the association coefficients and the characteristic modular lengths, and a modular length threshold of each customer and the corresponding associated customers includes:

s91, when the edge computing system of the bank website determines that the edge computing system pre-stores the associated customer corresponding to the first customer, the association coefficient between the first customer and the corresponding associated customer, the associated customer corresponding to the second customer, and the association coefficient between the second customer and the corresponding associated customer according to the identity information of the first customer and the identity information of the second customer, determining the association coefficient between the first customer and the second customer according to the associated customer corresponding to the first customer, the association coefficient between the first customer and the corresponding associated customer, the associated customer corresponding to the second customer, and the association coefficient between the second customer and the corresponding associated customer;

and S92, carrying out risk control on the withdrawal transaction according to the correlation coefficient of the first customer and the second customer, the corresponding relation between the correlation coefficient and the characteristic modular length prestored in the edge computing system and the modular length threshold.

In one embodiment, (S92) performing risk control on the money withdrawal transaction according to the correlation coefficient between the first customer and the second customer, the corresponding relationship between the correlation coefficient and the characteristic modular length pre-stored in the edge computing system, and the modular length threshold, including:

determining a characteristic value corresponding to the withdrawal transaction according to the correlation coefficient of the first customer and the second customer and the corresponding relationship between the correlation coefficient and the characteristic value prestored in the edge computing system;

and when the modular length of the characteristic value corresponding to the withdrawal transaction is smaller than the modular length threshold value, not carrying out risk control on the withdrawal transaction.

In an embodiment, referring to fig. 5, the method further comprises:

s501, when the edge computing system of the banking outlet determines that the edge computing system does not pre-store the associated customer corresponding to the first customer, the association coefficient between the first customer and the corresponding associated customer, the associated customer corresponding to the second customer, and the association coefficient between the second customer and the corresponding associated customer according to the identity information of the first customer and the identity information of the second customer, the edge computing system sends a risk control request to a banking server, wherein the risk control request comprises the identity information of the first customer and the identity information of the second customer;

s502, the bank server determines the association coefficient of the first client and the second client according to the identity information of the first client and the identity information of the second client;

wherein, the calculation method of the correlation coefficient between the first client and the second client is determined (S502), and the calculation methods of S202-1 to S202-6 may be referred to.

S503, the bank server determines a characteristic value corresponding to the withdrawal transaction according to the correlation coefficient of the first customer and the second customer and the corresponding relationship between the correlation coefficient and the characteristic value pre-stored in the server;

and S504, the bank server carries out risk control on the money withdrawing transaction according to the characteristic value corresponding to the money withdrawing transaction.

In an embodiment, (S504) the bank server performs risk control on the withdrawal transaction according to the feature value corresponding to the withdrawal transaction, including:

s504-1, determining a risk control model corresponding to the withdrawal transaction according to the characteristic value corresponding to the withdrawal transaction;

and S504-2, performing risk control on the money withdrawing transaction according to the risk control model corresponding to the money withdrawing transaction.

In one embodiment, the bank server determines the threshold value of the fixed length as follows:

setting a plurality of discrete correlation coefficients;

for each discrete association coefficient, determining the risk probability corresponding to the discrete association coefficient according to the transfer transaction data corresponding to the discrete association coefficient;

performing function fitting according to a plurality of set discrete correlation coefficients and the risk probability corresponding to each discrete correlation coefficient to obtain the functional relation between the risk probability and the correlation coefficient, wherein the correlation coefficient is an independent variable, and the risk probability is a dependent variable;

determining a plurality of monotone intervals corresponding to the functional relation, wherein the product of the derivative functions of any two adjacent monotone intervals is less than 0;

taking the left endpoint of the monotone interval with the maximum value of the corresponding correlation coefficient as a correlation threshold value;

and taking the characteristic modular length corresponding to the correlation threshold as a modular length threshold according to the corresponding relation between the correlation coefficient and the characteristic modular length.

It should be noted that although the operations of the method of the present invention have been described in the above embodiments and the accompanying drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the operations shown must be performed, to achieve the desired results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.

Having described the method of an exemplary embodiment of the present invention, an apparatus for supporting a bank customer withdrawal transaction of an exemplary embodiment of the present invention is next described with reference to fig. 6.

The implementation of the device for supporting the cash withdrawal transaction of the bank customer can be referred to the implementation of the method, and repeated details are omitted. The term "module" or "unit" used hereinafter may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Based on the same inventive concept, the present invention also provides an apparatus for supporting a withdrawal transaction of a bank customer, as shown in fig. 6, the apparatus includes:

the bank server 110 is configured to determine a corresponding relationship between the correlation coefficient and the characteristic value, and prestore the determined corresponding relationship between the correlation coefficient and the characteristic value in the bank server;

the bank server 110 is further configured to determine a corresponding relationship between the correlation coefficient and the characteristic length according to the corresponding relationship between the correlation coefficient and the characteristic value, and issue the determined corresponding relationship between the correlation coefficient and the characteristic length to an edge computing system of a bank outlet;

the mobile terminal 120 of the first customer is configured to send a withdrawal certificate acquisition request to the bank server, where the request includes: identity information of a first customer and a bank outlet corresponding to the withdrawal;

a bank server 110, further configured to determine whether the first customer is a controllable customer;

the bank server 110 is further configured to issue the associated customer corresponding to the first customer, the association coefficient between the first customer and the corresponding associated customer, and the module length threshold to an edge computing system of a banking outlet corresponding to the withdrawal;

a corresponding bank outlet 130 for obtaining a withdrawal transaction request initiated by a second customer based on the withdrawal certificate;

the bank outlet 130 corresponding to the withdrawal is further configured to obtain the identity information of the second customer and the identity information of the first customer included in the withdrawal certificate, and send the identity information of the first customer and the identity information of the second customer to the edge computing system of the bank outlet;

the edge computing system 140 of the banking outlet is configured to perform risk control on the withdrawal transaction according to the identity information of the first customer, the identity information of the second customer, pre-stored associated customers corresponding to each customer in the edge computing system, association coefficients of each customer and the corresponding associated customers, a correspondence between the association coefficients and the characteristic modular lengths, and a modular length threshold.

In an embodiment, the bank server is further configured to determine a correspondence between the association coefficient and the feature value according to the following method:

acquiring transfer transaction data of a bank;

for each transfer transaction data, the bank server determines the correlation coefficient of the transfer-out customer and the transfer-in customer of the transfer transaction data, and takes the correlation coefficient as the correlation coefficient corresponding to the transfer transaction data;

for each correlation coefficient, determining the transfer transaction data of which the corresponding correlation coefficient is equal to the correlation coefficient as the transfer transaction data corresponding to the correlation coefficient;

determining a risk matrix corresponding to the correlation coefficient according to the transfer transaction data corresponding to the correlation coefficient;

and taking the characteristic value of the risk matrix corresponding to the correlation coefficient, which is not 0, as the characteristic value corresponding to the correlation coefficient.

In one embodiment, referring to fig. 7, the apparatus further includes a banking system 150.

The bank server is specifically configured to:

when the bank server determines that the correlation coefficient of the transfer-out customer and the transfer-in customer of the transfer transaction data is not prestored, sending a correlation customer acquisition request to each bank system, wherein the acquisition request comprises a selected hash function, identity information of the transfer-out customer and identity information of the transfer-in customer;

the banking system 150 is specifically configured to:

for each bank system, the bank system takes the hash value of the identity information of each associated client corresponding to the roll-out client and prestored in the bank system as the associated client fingerprint of the roll-out client corresponding to the bank system according to the selected hash function, and takes the hash value of the identity information of each associated client corresponding to the roll-in client and prestored in the bank system as the associated client fingerprint of the roll-in client corresponding to the bank system; taking the correlation coefficient of the roll-out client and each corresponding correlated client as the correlation coefficient of the correlated client fingerprint corresponding to the roll-out client and the correlated client relative to the banking system, and taking the correlation coefficient of the roll-in client and each corresponding correlated client as the correlation coefficient of the correlated client fingerprint corresponding to the roll-in client and the correlated client relative to the banking system;

each bank system feeds back the determined associated client fingerprint of the roll-out client corresponding to the bank system, the association coefficient of the roll-out client and the associated client fingerprint corresponding to the bank system with respect to the bank system, the associated client fingerprint of the roll-in client corresponding to the bank system, and the association coefficient of the roll-in client and the associated client fingerprint corresponding to the bank system with respect to the bank system to the bank server;

the bank server is further used for:

determining a plurality of associated client fingerprints corresponding to the withdrawal transaction according to the associated client fingerprints corresponding to each bank system of the roll-out client and the associated client fingerprints corresponding to each bank system of the roll-in client;

for each associated customer fingerprint corresponding to the withdrawal transaction, determining an association coefficient of the fingerprint of the transferring-out customer and the fingerprint of the associated customer according to the association coefficient of the fingerprint of the transferring-out customer and the fingerprint of the associated customer relative to each bank system, and determining an association coefficient of the fingerprint of the transferring-in customer and the fingerprint of the associated customer according to the association coefficient of the fingerprint of the transferring-in customer and the fingerprint of the associated customer relative to each bank system;

and determining the correlation coefficient of the transferring-out customer and the transferring-in customer according to a plurality of correlation customer fingerprints corresponding to the withdrawal transaction, the correlation coefficient of the transferring-out customer and each correlation customer fingerprint corresponding to the withdrawal transaction, and the correlation coefficient of the transferring-in customer and each correlation customer fingerprint corresponding to the withdrawal transaction.

In an embodiment, the bank server is specifically configured to:

for each customer category and each transfer channel, selecting transfer transaction data corresponding to the customer category and the transfer channel from transfer transaction data corresponding to the association coefficient;

determining the risk probability of the customer category and the transfer channel corresponding to the correlation coefficient according to the transfer transaction data corresponding to the customer category and the transfer channel;

determining a risk matrix corresponding to the correlation coefficient, wherein rows of the risk matrix correspond to customer categories, columns of the risk matrix correspond to transfer channels, and the element value of each element of the risk matrix is equal to the risk probability of the customer category corresponding to the element and the corresponding transfer channel corresponding to the correlation coefficient;

and when the row number and the column number of the risk matrix corresponding to the correlation coefficient are not equal, performing 0 complementing according to the row number and the column number of the risk matrix corresponding to the correlation coefficient to obtain a risk square matrix corresponding to the correlation coefficient.

In one embodiment, the bank server is further configured to determine the controllable client according to the following method:

acquiring transaction data of each customer category;

for each customer category, determining a risk matrix corresponding to the customer category according to the transaction data of the customer category;

supplementing 0 according to the row number and column number of the risk matrix corresponding to the client category to obtain a risk square matrix corresponding to the client category;

taking the characteristic value of the risk square matrix corresponding to the client category, which is not 0, as the characteristic value corresponding to the client category;

and determining controllable customers according to the characteristic values corresponding to the customer categories. In an embodiment, the bank server is specifically configured to:

for each transaction channel and each transaction category, selecting the transaction data corresponding to the transaction channel and the transaction category from the transaction data of the customer category;

determining the risk probability of the transaction channel and the transaction category corresponding to the customer category according to the transaction data corresponding to the transaction channel and the transaction category;

determining a risk matrix corresponding to the customer category, wherein rows of the risk matrix correspond to transaction channels, columns of the risk matrix correspond to transaction categories, and the element value of each element of the risk matrix is equal to the risk probability of the transaction channel corresponding to the element and the corresponding transaction category corresponding to the customer category.

In one embodiment, the edge computing system of a banking outlet is specifically configured to:

when the edge computing system of the banking site determines that the edge computing system prestores a related customer corresponding to the first customer, a related coefficient between the first customer and the corresponding related customer, a related customer corresponding to the second customer, and a related coefficient between the second customer and the corresponding related customer according to the identity information of the first customer and the identity information of the second customer, determining a related coefficient between the first customer and the second customer according to the related customer corresponding to the first customer, the related coefficient between the first customer and the corresponding related customer, the related customer corresponding to the second customer, and the related coefficient between the second customer and the corresponding related customer;

and performing risk control on the withdrawal transaction according to the correlation coefficient of the first customer and the second customer, the corresponding relation between the correlation coefficient and the characteristic modular length prestored in the edge computing system and the modular length threshold.

when the edge computing system of the banking outlet determines that the edge computing system does not pre-store the associated customer corresponding to the first customer, the association coefficient of the first customer and the corresponding associated customer, the associated customer corresponding to the second customer and the association coefficient of the second customer and the corresponding associated customer according to the identity information of the first customer and the identity information of the second customer, the edge computing system sends a risk control request to a banking server, wherein the risk control request comprises the identity information of the first customer and the identity information of the second customer;

the bank server is further used for:

determining a correlation coefficient between the first client and the second client according to the identity information of the first client and the identity information of the second client;

determining a characteristic value corresponding to the withdrawal transaction according to the correlation coefficient of the first customer and the second customer and the corresponding relationship between the correlation coefficient and the characteristic value pre-stored in the server;

and carrying out risk control on the withdrawal transaction according to the characteristic value corresponding to the withdrawal transaction.

It should be noted that although in the above detailed description several modules of the apparatus supporting a bank customer withdrawal transaction are mentioned, such division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more of the modules described above may be embodied in one module according to embodiments of the invention. Conversely, the features and functions of one module described above may be further divided into embodiments by a plurality of modules.

Based on the aforementioned inventive concept, as shown in fig. 8, the present invention further provides a computer device 800, which comprises a memory 810, a processor 820 and a computer program 830 stored in the memory 810 and operable on the processor 820, wherein the processor 820 executes the computer program 830 to implement the aforementioned method for supporting a bank customer withdrawal transaction.

Based on the aforementioned inventive concept, the present invention proposes a computer-readable storage medium, which stores a computer program that, when being executed by a processor, carries out the aforementioned method of supporting a banking customer withdrawal transaction.

Based on the aforementioned inventive concept, the present invention proposes a computer program product comprising a computer program which, when executed by a processor, implements a method of supporting a bank customer withdrawal transaction.

The method and the device for supporting the money withdrawing transaction of the bank customer realize effective control on the money withdrawing transaction risk by analyzing the identity information of the customer, prestored associated customers corresponding to each customer in the edge computing system, and the association coefficient and the modular length threshold value of each customer and the corresponding associated customers, thereby ensuring the property safety of the customer and the bank.

According to the technical scheme, the data acquisition, storage, use, processing and the like meet the relevant regulations of national laws and regulations.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. 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 product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

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

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that the following descriptions are only illustrative and not restrictive, and that the scope of the present invention is not limited to the above embodiments: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method of supporting a banking customer withdrawal transaction, comprising:

the method comprises the following steps that a mobile terminal of a first client sends a withdrawal certificate acquisition request to a bank server, wherein the request comprises:

identity information of a first customer and a bank outlet corresponding to the withdrawal;

the bank server issues the associated customer corresponding to the first customer, the association coefficient of the first customer and the corresponding associated customer and the module length threshold value to an edge computing system of a bank outlet corresponding to the withdrawal;

2. The method of claim 1, further comprising the bank server determining the correspondence of the correlation coefficient to the characteristic value as follows:

the bank server acquires transfer transaction data of a bank;

for each association coefficient, determining the transfer transaction data of which the corresponding association coefficient is equal to the association coefficient as the transfer transaction data corresponding to the association coefficient;

3. The method as recited in claim 2 wherein the bank server determining a correlation coefficient between the transferring-out customer and the transferring-in customer for the transfer transaction data comprises:

when the bank server determines that the correlation coefficient of the roll-out customer and the roll-in customer of the transfer transaction data is not prestored, the bank server sends a correlation customer acquisition request to each bank system, wherein the acquisition request comprises a selected hash function, identity information of the roll-out customer and identity information of the roll-in customer;

each bank system feeds back the determined associated client fingerprint of the roll-out client corresponding to the bank system, the association coefficient of the roll-out client and each associated client fingerprint corresponding to the bank system with respect to the bank system, the associated client fingerprint of the roll-in client corresponding to the bank system, and the association coefficient of each associated client fingerprint of the roll-in client and each associated client fingerprint corresponding to the bank system with respect to the bank system to a bank server;

the bank server determines a plurality of associated client fingerprints corresponding to the withdrawal transaction according to the associated client fingerprints corresponding to each bank system of the roll-out client and the associated client fingerprints corresponding to each bank system of the roll-in client;

for each associated customer fingerprint corresponding to the withdrawal transaction, the bank server determines the association coefficient of the fingerprint of the transferring-out customer and the associated customer according to the association coefficient of the fingerprint of the transferring-out customer and the associated customer about each bank system, and determines the association coefficient of the fingerprint of the transferring-in customer and the associated customer according to the association coefficient of the fingerprint of the transferring-in customer and the associated customer about each bank system;

and the bank server determines the correlation coefficient of the roll-out client and the roll-in client according to a plurality of correlation client fingerprints corresponding to the withdrawal transaction, the correlation coefficient of the roll-out client and each correlation client fingerprint corresponding to the withdrawal transaction and the correlation coefficient of each correlation client fingerprint corresponding to the transfer-in client and the withdrawal transaction.

4. The method of claim 2 wherein determining the risk matrix corresponding to the correlation coefficient based on the transfer transaction data corresponding to the correlation coefficient comprises:

for each customer category and each transfer channel, selecting transfer transaction data corresponding to the customer category and the transfer channel from the transfer transaction data corresponding to the association coefficient;

determining the risk probability of the customer category and the transfer channel corresponding to the association coefficient according to the transfer transaction data corresponding to the customer category and the transfer channel;

5. The method of claim 1, further comprising the bank server determining the controllable client as follows:

the bank server acquires transaction data of each client category;

supplementing 0 according to the row number and the column number of the risk matrix corresponding to the client category to obtain a risk square matrix corresponding to the client category;

and determining controllable customers according to the characteristic values corresponding to the customer categories.

6. The method of claim 5, wherein for each customer category, determining a risk matrix corresponding to the customer category based on the transaction data for the customer category comprises:

7. The method as claimed in claim 1, wherein the risk control of the money withdrawal transaction by the edge computing system of the banking outlet according to the identity information of the first customer, the identity information of the second customer, and the pre-stored associated customers corresponding to each customer in the edge computing system, and the association coefficient, the correspondence between the association coefficient and the characteristic modular length, and the modular length threshold of each customer and the corresponding associated customer comprises:

when the edge computing system of the banking outlet determines that the edge computing system prestores a relevant customer corresponding to the first customer, a relevant coefficient between the first customer and the relevant customer, a relevant customer corresponding to the second customer, and a relevant coefficient between the second customer and the relevant customer according to the identity information of the first customer and the identity information of the second customer, the relevant coefficient between the first customer and the second customer is determined according to the relevant customer corresponding to the first customer, the relevant coefficient between the first customer and the relevant customer, the relevant customer corresponding to the second customer, and the relevant coefficient between the second customer and the relevant customer;

8. The method of claim 1, further comprising:

the bank server determines the association coefficient of the first client and the second client according to the identity information of the first client and the identity information of the second client;

the bank server determines a characteristic value corresponding to the withdrawal transaction according to the correlation coefficient of the first customer and the second customer and the corresponding relationship between the correlation coefficient and the characteristic value pre-stored in the bank server;

and the bank server carries out risk control on the withdrawal transaction according to the characteristic value corresponding to the withdrawal transaction.

9. An apparatus for supporting a banking customer withdrawal transaction, comprising:

the bank server is used for determining the corresponding relation between the association coefficient and the characteristic value and prestoring the determined corresponding relation between the association coefficient and the characteristic value in the bank server;

the bank server is also used for determining the corresponding relation between the correlation coefficient and the characteristic modular length according to the corresponding relation between the correlation coefficient and the characteristic value, and issuing the determined corresponding relation between the correlation coefficient and the characteristic modular length to an edge computing system of a bank outlet;

the bank outlet corresponding to the withdrawal is used for acquiring that a second customer initiates a withdrawal transaction request based on the withdrawal certificate;

the bank outlet corresponding to the withdrawal is also used for acquiring the identity information of a second customer and the identity information of the first customer in the withdrawal certificate and sending the identity information of the first customer and the identity information of the second customer to the edge computing system of the bank outlet;

and the edge computing system of the bank outlets is used for carrying out risk control on the withdrawal transaction according to the identity information of the first customer, the identity information of the second customer, pre-stored associated customers corresponding to each customer in the edge computing system, the association coefficient of each customer and the corresponding associated customer, the corresponding relation between the association coefficient and the characteristic modular length and the modular length threshold value.

10. The apparatus of claim 9, wherein the bank server is further configured to determine the correspondence between the association coefficient and the feature value as follows:

acquiring transfer transaction data of a bank;

11. The apparatus of claim 10, wherein the bank server is specifically configured to:

the banking system is specifically configured to:

for each bank system, the bank system takes the hash value of the identity information of each associated client corresponding to the roll-out client and prestored in the bank system as the associated client fingerprint of the roll-out client corresponding to the bank system according to the selected hash function, and takes the hash value of the identity information of each associated client corresponding to the roll-in client and prestored in the bank system as the associated client fingerprint of the roll-in client corresponding to the bank system; taking the correlation coefficient of the roll-out client and each corresponding correlation client as the correlation coefficient of the fingerprint of the correlation client corresponding to the roll-out client and the correlation client with respect to the banking system, and taking the correlation coefficient of the roll-in client and each corresponding correlation client as the correlation coefficient of the fingerprint of the correlation client corresponding to the roll-in client and the correlation client with respect to the banking system;

the bank server is further used for:

and determining the correlation coefficient of the roll-out client and the roll-in client according to a plurality of correlation client fingerprints corresponding to the money withdrawing transaction, the correlation coefficient of the roll-out client and each correlation client fingerprint corresponding to the money withdrawing transaction, and the correlation coefficient of the roll-in client and each correlation client fingerprint corresponding to the money withdrawing transaction.

12. The apparatus of claim 10, wherein the bank server is specifically configured to:

13. The apparatus of claim 9, wherein the bank server is further configured to determine the controllable client as follows:

acquiring transaction data of each customer category;

14. The apparatus of claim 13, wherein the bank server is specifically configured to:

15. The apparatus as recited in claim 9, wherein the edge computing system of the banking outlet is specifically configured to:

16. The apparatus of claim 9, wherein the edge computing system of the banking outlet is further configured to:

when the edge computing system of the banking outlet determines that the edge computing system does not pre-store the associated customer corresponding to the first customer, the association coefficient of the first customer and the corresponding associated customer, the associated customer corresponding to the second customer, and the association coefficient of the second customer and the corresponding associated customer according to the identity information of the first customer and the identity information of the second customer, the edge computing system sends a risk control request to a banking server, wherein the risk control request comprises the identity information of the first customer and the identity information of the second customer;

the bank server is further used for:

determining an association coefficient between the first client and the second client according to the identity information of the first client and the identity information of the second client;

17. 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 8 when executing the computer program.

18. 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 of claims 1 to 8.

19. 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 8.