CN115187263A

CN115187263A - Risk control method and device for payment transaction

Info

Publication number: CN115187263A
Application number: CN202210867713.2A
Authority: CN
Inventors: 朱江波
Original assignee: Bank of China Ltd
Current assignee: Bank of China Ltd
Priority date: 2022-07-22
Filing date: 2022-07-22
Publication date: 2022-10-14

Abstract

The invention provides a risk control method and a risk control device for payment transaction, which relate to the technical field of financial data processing, and comprise the following steps: determining a correlation coefficient of a customer with a payment opponent when the customer is conducting a payment transaction; determining a safety index corresponding to the current payment transaction according to a corresponding relation between a pre-stored association coefficient and the safety index and the association coefficient between the customer and the payment opponent; and determining a payment threshold corresponding to the current payment transaction according to the safety index corresponding to the current payment transaction, wherein the payment threshold is used for carrying out risk control on the current payment transaction. According to the invention, the safety index corresponding to the current payment transaction is determined by analyzing the correlation coefficient between the customer and the payment opponent and the corresponding relation between the correlation coefficient and the safety index, the payment threshold of the current payment transaction is determined according to the safety index, the effective risk control is carried out on the payment transaction, the risk of the payment transaction is reduced, and the fund safety of the customer is protected.

Description

Risk control method and device for payment transaction

Technical Field

The invention relates to the technical field of financial data processing, in particular to a risk control method and device for payment transaction.

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 the payment transaction of the customer, the bank needs to control the risk encountered by the customer when paying to protect the fund security of the customer, for example, in the prior art, the bank sets a payment amount threshold value, the payment amount of the customer cannot exceed the value, and the risk of the payment transaction can be controlled to a certain extent.

However, in the prior art, the payment amount threshold is mostly set manually and is not related to a specific payment opponent, so that there is a problem: in some payment scenarios, the payment amount threshold is set too high, resulting in a higher risk of payment.

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 payment transactions.

Disclosure of Invention

In order to solve the problems in the prior art, the invention provides a risk control method and device for payment transaction.

In a first aspect of an embodiment of the present invention, a risk control method for a payment transaction is provided, including:

determining a correlation coefficient of a customer with a payment opponent when the customer is conducting a payment transaction;

determining a safety index corresponding to the current payment transaction according to a corresponding relation between a pre-stored association coefficient and the safety index and the association coefficient between the customer and the payment opponent;

and determining a payment threshold corresponding to the current payment transaction according to the safety index corresponding to the current payment transaction, wherein the payment threshold is used for carrying out risk control on the current payment transaction.

In a second aspect of an embodiment of the present invention, a risk control device for a payment transaction is provided, including:

the client association coefficient determining module is used for determining the association coefficient of the client and a payment opponent when the client carries out payment transaction;

the safety index determining module is used for determining the safety index corresponding to the current payment transaction according to the corresponding relation between the pre-stored association coefficient and the safety index and the association coefficient between the customer and the payment opponent;

and the payment transaction risk control module is used for determining a payment threshold corresponding to the current payment transaction according to the safety index corresponding to the current payment transaction, wherein the payment threshold is used for carrying out risk control on the current payment transaction.

In a third aspect of embodiments of the present invention, a computer device is presented, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a risk control method for a payment 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, which when executed by a processor, implements a risk control method for a payment transaction.

In a fifth aspect of embodiments of the present invention, a computer program product is presented, the computer program product comprising a computer program which, when executed by a processor, implements a risk control method for a payment transaction.

The risk control method and the risk control device for the payment transaction can determine the safety index corresponding to the current payment transaction by analyzing the correlation coefficient between the customer and the payment opponent and the corresponding relation between the correlation coefficient and the safety index, determine the payment threshold of the current payment transaction according to the safety index, effectively control the risk of the payment transaction, reduce the risk of the payment transaction and protect the fund safety of the customer.

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 schematic flow chart of a risk control method for payment transaction according to an embodiment of the invention.

Fig. 2 is a flow chart illustrating the process of determining the correlation coefficient between the customer and the payment opponent according to an embodiment of the invention.

Fig. 3 is a flowchart illustrating a process of determining a correspondence between a correlation coefficient and a safety index according to an embodiment of the present invention.

Fig. 4 is a flowchart illustrating a process of determining a correspondence between a payment threshold and a security index according to an embodiment of the present invention.

Fig. 5 is a schematic diagram of a risk control device for payment transaction according to an embodiment of the present invention.

Fig. 6 is a schematic diagram of a risk control device for payment transaction according to another embodiment of the present invention.

Fig. 7 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 only to enable those skilled in the art to better understand and to implement the present invention, and do not limit the scope of the present 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 risk control method and device for payment transaction are provided, and the technical field of financial 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 of a risk control method of a payment transaction according to an embodiment of the invention. As shown in fig. 1, the method includes:

s101, when a customer carries out payment transaction, determining the correlation coefficient of the customer and a payment opponent;

s102, determining a safety index corresponding to the current payment transaction according to a corresponding relation between a pre-stored association coefficient and the safety index and the association coefficient between the customer and the payment opponent;

s103, determining a payment threshold corresponding to the current payment transaction according to the safety index corresponding to the current payment transaction, wherein the payment threshold is used for carrying out risk control on the current payment transaction.

In order to explain the risk control method of the payment transaction more clearly, the following is a detailed description with reference to each step.

In S101, referring to fig. 2, when a customer is conducting a payment transaction, determining a correlation coefficient of the customer with a payment opponent includes:

s201, acquiring a customer association diagram constructed by a bank server, wherein each node of the customer association diagram is a personal customer or a commercial tenant, each edge of the customer association diagram corresponds to an association coefficient, and the association coefficient represents the association degree of two nodes corresponding to the edge, wherein the association coefficient is greater than or equal to 0 and less than or equal to 1;

s202, determining the correlation coefficient between the customer and the payment opponent according to the customer correlation diagram.

In one embodiment, (S202) the method for determining the association coefficient between the customer and the payment opponent according to the customer association map includes at least the following two methods.

The first method comprises the following steps:

determining an association distance value corresponding to each edge of the client association graph according to the following formula:

d = -lg (r), wherein d is an association distance value corresponding to the edge, and r is an association coefficient corresponding to the edge;

determining the minimum associated distance value between the customer and the payment opponent according to the customer association diagram and the associated distance valued _m ；

According to the minimum associated distance value d between the customer and the payment opponent _m Determining a correlation coefficient s of the customer with the payment opponent, wherein,

wherein, the second method is as follows:

initializing a potential association coefficient corresponding to each node which has direct connection with the client edge in a client association graph as an association coefficient corresponding to the client edge corresponding to the node, and initializing a potential association coefficient corresponding to each node which has no direct connection with the client edge in the client association graph as 0;

initializing a node set to be selected into all nodes except the client in the client association diagram;

and circularly executing the following 3 steps until the association coefficient of the client and the payment opponent is determined:

selecting the node B with the maximum corresponding potential correlation coefficient from the node set to be selected, and deleting the node B from the node set to be selected;

if the node B is the payment opponent, determining the association coefficient of the customer and the payment opponent as the potential association coefficient corresponding to the node B;

for each node C with an edge directly connected with the node B, if f (B) x r (B, C) is larger than f (C), the potential correlation coefficient corresponding to the updated node C is f (B) x r (B, C), wherein f (C) is the potential correlation coefficient corresponding to the node C before updating, f (B) is the potential correlation coefficient corresponding to the node B, and r (B, C) is the correlation coefficient corresponding to the node B and the edge corresponding to the node C.

In S102, the security index corresponding to the current payment transaction is determined according to the pre-stored correspondence between the association coefficient and the security index and the association coefficient between the customer and the payment opponent.

Specifically, referring to fig. 3, the correspondence between the correlation coefficient and the safety index is determined according to the following method:

s301, acquiring historical payment data of a bank;

s302, regarding each historical payment data, taking the correlation coefficient of the customer corresponding to the historical payment data and the corresponding payment opponent as the correlation coefficient corresponding to the historical payment data;

s303, setting a plurality of association coefficient intervals and determining representative association coefficients corresponding to the association coefficient intervals, wherein any two association coefficient intervals are not intersected with each other;

s304, regarding each correlation coefficient interval, taking the historical payment data of the correlation coefficient interval as the historical payment data corresponding to the correlation coefficient interval;

s305, determining a safety index corresponding to each correlation coefficient interval according to historical payment data corresponding to each correlation coefficient interval;

s306, constructing a correlation safety function, wherein the independent variable corresponding to the correlation safety function is a representative correlation coefficient corresponding to a plurality of set correlation coefficient intervals, and the function value of each representative correlation coefficient corresponding to the correlation safety function is a safety index corresponding to the correlation coefficient interval corresponding to the representative correlation coefficient;

s307, the correlation security function is serialized, and the obtained continuous function is used as the corresponding relation between the correlation coefficient and the security index.

In an embodiment, (S305) determining a security indicator corresponding to each correlation coefficient interval according to the historical payment data corresponding to the correlation coefficient interval, includes:

dividing historical payment data corresponding to each association coefficient interval into a plurality of payment data sets corresponding to the association coefficient interval, wherein the number of payment transactions contained in each payment data set is greater than a set transaction amount threshold value;

determining the proportion of payment transactions which do not involve risks in the payment transactions contained in each payment data set corresponding to the association coefficient interval as a safety proportion sample corresponding to the association coefficient interval;

taking the average value of the safety ratio samples corresponding to the correlation coefficient interval as a safety index corresponding to the correlation coefficient interval; and taking the ratio of the square of the variance of the safety ratio samples corresponding to the correlation coefficient interval to the number of the safety ratio samples corresponding to the correlation coefficient interval as the upper error bound of the safety index corresponding to the correlation coefficient interval.

In one embodiment, (S306) constructing an associative security function, including:

taking the correlation coefficient interval of which the upper error bound of the corresponding safety index is smaller than the error threshold value as a controllable correlation coefficient interval;

and constructing a correlation safety function, wherein the independent variable corresponding to the correlation safety function is a representative correlation coefficient corresponding to the controllable correlation coefficient interval, and the function value of the representative correlation coefficient corresponding to each controllable correlation coefficient interval corresponding to the correlation safety function is a safety index corresponding to the controllable correlation coefficient interval.

In S103, determining a payment threshold corresponding to the current payment transaction according to the security index corresponding to the current payment transaction includes:

and when the safety index corresponding to the current payment transaction is 0, determining the payment threshold corresponding to the current payment transaction as the payment threshold stored by the bank server and used for the customer to pay the counter-payment party.

And when the safety index corresponding to the current payment transaction is larger than 0, determining the payment threshold corresponding to the current payment transaction according to the safety index corresponding to the current payment transaction and the corresponding relation between the pre-stored payment threshold and the safety index.

Specifically, referring to fig. 4, the correspondence between the payment threshold and the security index is determined according to the following method:

s401, acquiring historical payment data of a bank;

s402, setting a plurality of payment discrete values;

s403, for each discrete payment value, determining the proportion of payment transactions which do not involve risks in the payment transactions contained in the historical payment data of the bank when the payment threshold value is set as the discrete payment value, and taking the proportion as a safety index corresponding to the discrete payment value;

s404, determining the corresponding relation between the payment threshold value and the safety index according to the set plurality of payment discrete values and the safety index corresponding to each payment discrete value.

In an embodiment, the risk control method for payment transaction further includes:

for each edge of the customer association graph, setting a payment threshold value corresponding to the edge as the maximum value of payment and transfer between two nodes corresponding to the edge;

initializing the pending payment amount of each edge to be 0;

looping through the following steps until a path from the customer to the payment opponent is not found, such that each edge of the path satisfies condition t: the pending payment amount corresponding to the edge is less than the payment threshold corresponding to the edge:

selecting a path from the customer to the payment opponent such that each edge of the path satisfies a condition t;

determining a plurality of differences between the payment threshold values corresponding to all edges of the path and the corresponding pending payment amounts, and determining the minimum value of the differences as an increased payment amount;

adding the added payment amount to the pending payment amount of each edge of the path;

when the path from the client to the payment opponent cannot be found, and each edge of the path meets the condition t, determining the sum of the pending payment amounts of all the edges corresponding to the client;

and determining a payment threshold value for the customer to pay the counter-payment according to the sum of the determined sum of the pending payment amounts of all sides corresponding to the customer.

In some cases, for example, the network signal is weak, and the mobile terminal of the client cannot interact with the bank server in time, the following method can be adopted for processing.

In an embodiment, the method further comprises:

when the client is determined to be a controllable client, issuing a client association diagram, a corresponding relation between the association coefficient and the safety index and a corresponding relation between the payment threshold and the safety index to a mobile terminal of the client;

and the mobile terminal of the client determines a payment threshold corresponding to the payment transaction of the client according to the client association diagram, the corresponding relation between the association coefficient and the safety index and the corresponding relation between the payment threshold and the safety index stored in the mobile terminal.

In one embodiment, the method further comprises the step that the bank server determines the controllable clients of the bank according to the following method:

classifying the clients to obtain a plurality of client categories;

determining the risk probability of each transaction scene corresponding to each customer category according to the transaction data of each customer category;

determining a partial order of customer categories, wherein the partial order is used for determining whether a first customer category is better than a second customer category in any two customer categories; if the risk probability of the first customer category corresponding to the trading scene is less than or equal to the risk probability of the second customer category corresponding to the trading scene for each trading scene, the partial order determines that the first customer category is better than the second customer category;

taking the partial order maximum elements of the client categories as extreme client categories;

and determining controllable customers of the bank according to the extreme value customer category. (e.g., a customer included in the extremum customer category as a controllable customer for a bank)

In one embodiment, taking the maximum element of the partial order of the client category as the extreme client category comprises:

initializing the to-be-selected customer category and the to-be-compared category into all customer categories;

selecting a transaction scene;

and circularly executing the following 3 steps until the category of the client to be selected is empty:

taking out the category S with the minimum risk probability corresponding to the selected transaction scene from the categories of the clients to be selected, and taking all other client categories except the category S in the categories to be compared as the categories to be compared corresponding to the category S;

according to the partial order of the customer categories, comparing the category S with each category B to be compared corresponding to the category S: if the category B to be compared is superior to the category S, deleting the category S from the category of the clients to be selected; if the category S is superior to the category B to be compared, deleting the category B to be compared from the category of the clients to be selected, and determining the category B to be compared as a secondary category of the category S;

if it is determined that any of the categories S to be compared are not better than category S, then category S is treated as the extremum customer category and category S is deleted from the candidate customer categories and all of the minor categories of category S are deleted from the categories to be compared.

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, the risk control device for payment transactions of an exemplary embodiment of the present invention is next described with reference to fig. 5.

The implementation of the risk control device for payment transaction can refer to the implementation of the above method, and the repeated description is 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 a risk control device for payment transaction, as shown in fig. 5, the device includes:

a customer association coefficient determination module 510 for determining an association coefficient of a customer with a payment opponent when the customer is conducting a payment transaction;

a security index determining module 520, configured to determine a security index corresponding to the current payment transaction according to a pre-stored correspondence between the correlation coefficient and the security index and the correlation coefficient between the customer and the payment opponent;

the payment transaction risk control module 530 is configured to determine a payment threshold corresponding to the current payment transaction according to the security indicator corresponding to the current payment transaction, where the payment threshold is used to perform risk control on the current payment transaction.

In an embodiment, the customer association coefficient determining module is specifically configured to:

acquiring a customer association diagram constructed by a bank server, wherein each node of the customer association diagram is a personal customer or a commercial tenant, each edge of the customer association diagram corresponds to an association coefficient, the association coefficient represents the association degree of two nodes corresponding to the edge, and the association coefficient is greater than or equal to 0 and less than or equal to 1;

and determining the association coefficient of the customer and the payment opponent according to the customer association graph.

determining the minimum associated distance value d between the customer and the payment opponent according to the customer association diagram and the associated distance value _m ；

in an embodiment, the customer relation coefficient determining module is specifically configured to:

initializing the potential association coefficient corresponding to each node which has direct connection with the client edge in the client association diagram as the association coefficient corresponding to the client edge corresponding to the node, and initializing the potential association coefficient corresponding to each node which has no direct connection with the client edge in the client association diagram as 0;

In an embodiment, referring to fig. 6, the apparatus further comprises: a module 540 for determining the corresponding relationship between the correlation coefficient and the safety index;

the corresponding relation determining module of the correlation coefficient and the safety index determines the corresponding relation of the correlation coefficient and the safety index according to the following method:

acquiring historical payment data of a bank;

for each historical payment data, taking the correlation coefficient of the customer corresponding to the historical payment data and the corresponding payment opponent as the correlation coefficient corresponding to the historical payment data;

setting a plurality of association coefficient intervals and determining representative association coefficients corresponding to the association coefficient intervals, wherein any two association coefficient intervals are not intersected with each other;

for each correlation coefficient interval, taking the historical payment data of the correlation coefficient in the correlation coefficient interval as the historical payment data corresponding to the correlation coefficient interval;

determining a safety index corresponding to each correlation coefficient interval according to the historical payment data corresponding to each correlation coefficient interval;

constructing a correlation safety function, wherein the independent variable corresponding to the correlation safety function is a representative correlation coefficient corresponding to a plurality of set correlation coefficient intervals, and the function value of each representative correlation coefficient corresponding to the correlation safety function is a safety index corresponding to the correlation coefficient interval corresponding to the representative correlation coefficient;

and (4) the correlation security function is serialized, and the obtained continuous function is used as the corresponding relation between the correlation coefficient and the security index.

In an embodiment, the payment transaction risk control module is specifically configured to:

and when the safety index corresponding to the current payment transaction is 0, determining the payment threshold corresponding to the current payment transaction as the payment threshold stored by the bank server for the customer to pay the payment opponent.

In an embodiment, referring again to fig. 6, the apparatus further comprises: a corresponding relationship determination module 550 for the payment threshold and the security index;

the corresponding relation determining module of the payment threshold and the safety index determines the corresponding relation of the payment threshold and the safety index according to the following method:

acquiring historical payment data of a bank;

setting a plurality of payment discrete values;

for each payment discrete value, determining the proportion of payment transactions which do not involve risks in the payment transactions contained in the historical payment data of the bank when the payment threshold value is set as the payment discrete value, and taking the proportion as a safety index corresponding to the payment discrete value;

and determining the corresponding relation between the payment threshold value and the safety index according to the set plurality of payment discrete values and the safety index corresponding to each payment discrete value.

It should be noted that although in the above detailed description several modules of the risk control means of a payment transaction are mentioned, this 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. 7, the present invention further provides a computer device 700, which includes a memory 710, a processor 720 and a computer program 730 stored on the memory 710 and operable on the processor 720, wherein the processor 720 executes the computer program 730 to implement the aforementioned risk control method for payment transaction.

Based on the aforementioned inventive concept, the present invention proposes a computer-readable storage medium storing a computer program which, when executed by a processor, implements the aforementioned risk control method for payment transactions.

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 risk control method for a payment transaction.

According to the technical scheme, the data acquisition, storage, use, processing and the like meet 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: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: 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 risk control method for a payment transaction, comprising:

determining a safety index corresponding to the current payment transaction according to a corresponding relation between a pre-stored association coefficient and a safety index and the association coefficient between the customer and the payment opponent;

2. The method of claim 1, wherein determining the correlation coefficient of the customer with the payment opponent comprises:

acquiring a customer association diagram constructed by a bank server, wherein each node of the customer association diagram is an individual customer or a commercial tenant, each edge of the customer association diagram corresponds to an association coefficient, and the association coefficient represents the association degree of two nodes corresponding to the edge, wherein the association coefficient is greater than or equal to 0 and less than or equal to 1;

3. The method of claim 2, wherein determining the correlation coefficient of the customer with the payment opponent based on the customer correlation map comprises:

4. the method of claim 2, wherein determining the correlation coefficient of the customer with the payment opponent based on the customer correlation map comprises:

for each node C having an edge directly connected to the node B, if f (B) × r (B, C) is greater than f (C), the potential correlation coefficient corresponding to the updated node C is f (B) × r (B, C), where f (C) is the potential correlation coefficient corresponding to the node C before updating, f (B) is the potential correlation coefficient corresponding to the node B, and r (B, C) is the correlation coefficient corresponding to the edge corresponding to the node B and the node C.

5. The method of claim 1, further comprising determining a correspondence of the correlation coefficient to the security index as follows:

acquiring historical payment data of a bank;

for each correlation coefficient interval, taking the historical payment data of the corresponding correlation coefficient in the correlation coefficient interval as the historical payment data corresponding to the correlation coefficient interval;

determining a safety index corresponding to each correlation coefficient interval according to historical payment data corresponding to each correlation coefficient interval;

6. The method of claim 1, wherein determining the payment threshold for the current payment transaction based on the security metric for the current payment transaction comprises:

7. The method of claim 1, wherein determining the payment threshold for the current payment transaction based on the security metric for the current payment transaction comprises:

8. The method of claim 7, further comprising determining a correspondence of the payment threshold to the security metric as follows:

acquiring historical payment data of a bank;

setting a plurality of payment discrete values;

9. A risk control device for payment transactions, comprising:

10. The apparatus of claim 9, wherein the client correlation coefficient determination module is specifically configured to:

and determining the association coefficient of the client and the payment opponent according to the client association diagram.

11. The apparatus of claim 10, wherein the client correlation coefficient determination module is specifically configured to:

According to the minimum associated distance value d between the customer and the payment opponent _m Determining a coefficient of association s of the customer with the payment opponent, wherein,

12. the apparatus of claim 10, wherein the client correlation coefficient determination module is specifically configured to:

13. The apparatus of claim 9, further comprising: a corresponding relation determining module of the correlation coefficient and the safety index;

acquiring historical payment data of a bank;

14. The apparatus of claim 9, wherein the payment transaction risk control module is specifically configured to:

15. The apparatus of claim 9, wherein the payment transaction risk control module is specifically configured to:

16. The apparatus as recited in claim 15, further comprising: a corresponding relation determination module of the payment threshold and the safety index;

acquiring historical payment data of a bank;

setting a plurality of payment discrete values;

and determining the corresponding relation between the payment threshold and the safety index according to the set plurality of payment discrete values and the safety index corresponding to each payment discrete value.

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 one 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.