CN117058821A

CN117058821A - Bank self-service terminal control method, device, equipment and storage medium

Info

Publication number: CN117058821A
Application number: CN202310966825.8A
Authority: CN
Inventors: 朱江波; 胡佳锋; 丁彤; 郭龙航; 张凯宁
Original assignee: Bank of China Ltd
Current assignee: Bank of China Ltd
Priority date: 2023-08-02
Filing date: 2023-08-02
Publication date: 2023-11-14

Abstract

The application provides a bank self-service terminal control method, a device, equipment and a storage medium, which can be used in the financial field or other fields. The method comprises the following steps: acquiring first historical environment payment data of a first self-service terminal, and determining a mapping relation between cash transaction risk entropy and cash transaction threshold of the first self-service terminal according to the first historical environment payment data. When a target user initiates cash transaction on a first self-service terminal, acquiring cash transaction risk entropy of the target user, determining a cash transaction threshold of the target user on the first self-service terminal according to the cash transaction risk entropy of the target user and the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold, and controlling the cash transaction threshold when the target user uses the first self-service terminal according to the cash transaction threshold. The method of the application is the security of cash transaction of the self-service terminal.

Description

Bank self-service terminal control method, device, equipment and storage medium

Technical Field

The present application relates to the financial field or other fields, and in particular, to a method, an apparatus, a device, and a storage medium for controlling a self-service terminal of a bank.

Background

With the rapid development of banking industry, self-service terminals of banks have been widely installed in various public places. The bank self-service terminal is an automatic financial equipment which utilizes a computer network to realize high-speed transmission of transaction data and applies an automatic control technology to online process various transactions of a bank in real time, thereby replacing the traditional manual operation of a bank teller and providing convenience for life of people. However, it is currently difficult for banks to risk control the transaction behavior of other banks 'self-service terminals, or of such banks' self-service terminals having less historical cash transaction data.

Therefore, how to improve the control force of the bank on the cash transaction behavior of the self-service terminals of other banks or the self-service terminals of the banks with less historical cash transaction data and the security of the cash transaction of the self-service terminals are the problems to be solved.

Disclosure of Invention

The application provides a bank self-service terminal control method, device, equipment and storage medium, which are used for solving the problems of improving the control force of cash transaction behaviors of a bank to self-service terminals of other banks or the self-service terminals of the bank with less historical cash transaction data and the security of cash transaction of the self-service terminals in the prior art.

In a first aspect, the present application provides a method for controlling a self-service terminal of a bank, including:

acquiring first historical environment payment data of a first self-service terminal, wherein the distance between a payment place of the first historical environment payment data and the first self-service terminal is smaller than a preset distance threshold value, and the historical cash transaction quantity of the first self-service terminal is smaller than or equal to a cash transaction quantity threshold value;

determining a mapping relation between cash transaction risk entropy of the first self-service terminal and a cash transaction threshold according to the first historical environment payment data, wherein the cash transaction risk entropy represents information quantity of related risks when cash transaction is carried out on the self-service terminal;

when a target user initiates cash transaction on a first self-service terminal, acquiring cash transaction risk entropy of the target user;

determining a cash transaction threshold of the target user at the first self-service terminal according to the cash transaction risk entropy of the target user and the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold;

and controlling the cash transaction threshold value when the target user uses the first self-service terminal according to the cash transaction threshold value.

Optionally, the determining, according to the first historical environmental payment data, a mapping relationship between a cash transaction risk entropy of the first self-service terminal and a cash transaction threshold value includes:

determining an environmental risk entropy of the first self-service terminal according to the first historical environmental payment data, wherein the environmental risk entropy represents information quantity of related risks when payment is carried out within a specified distance range of the first self-service terminal;

acquiring an environment risk entropy of the second self-service terminal;

determining similar self-service terminals of the first self-service terminal according to the environmental risk entropy of the second self-service terminal;

and determining the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold according to the similar self-service terminals.

Optionally, the determining, according to the first historical environmental payment data, an environmental risk entropy of the first self-service terminal includes:

selecting historical environment payment data of at least one payment scene from the first historical environment payment data;

taking historical environment payment data related to risks in the first historical environment payment data of each payment scene as risk environment payment data of the payment scene;

And determining the environmental risk entropy of the first self-service terminal according to the risk environment payment data and the first historical environment payment data.

Optionally, the determining, according to the similar self-service terminals, a mapping relationship between a cash transaction risk entropy of the first self-service terminal and a cash transaction threshold includes:

taking the historical cash transaction data of the similar self-service terminals as potential historical cash transaction data of the first self-service terminal;

acquiring a cash transaction threshold set, wherein the cash transaction threshold set comprises at least one cash transaction threshold;

for each cash transaction threshold, taking potential historical cash transaction data with cash transaction amount smaller than or equal to the cash transaction threshold in the potential historical cash transaction data of the first self-service terminal as potential historical cash transaction data corresponding to the cash transaction threshold;

determining cash transaction risk entropy corresponding to the cash transaction threshold according to potential historical cash transaction data corresponding to the cash transaction threshold;

and determining the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold according to the cash transaction threshold set and the cash transaction risk entropy corresponding to each cash transaction threshold in the cash transaction threshold set.

Optionally, the determining, according to the potential historical cash transaction data corresponding to the cash transaction threshold, cash transaction risk entropy corresponding to the cash transaction threshold includes:

taking potential historical cash transaction data with transaction abnormality in the potential historical cash transaction data as potential risk cash transaction data;

acquiring a risk category of the potential risk cash transaction data;

and determining cash transaction risk entropy corresponding to the cash transaction threshold according to the potential risk cash transaction data of each risk category and the potential history cash transaction data.

Optionally, when the target user initiates the cash transaction on the first self-service terminal, acquiring the cash transaction risk entropy of the target user includes:

acquiring a prestored cash transaction threshold value of the target user;

determining cash transaction risk entropy of the target user according to the cash transaction threshold;

the determining the cash transaction threshold of the target user at the first self-service terminal according to the cash transaction risk entropy of the target user and the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold comprises the following steps:

Acquiring historical cash transaction data of the target user, and determining the maximum cash transaction amount of the target user;

taking a cash transaction threshold value which is larger than or equal to the maximum cash transaction amount in the cash transaction threshold values contained in the mapping relation as a potential cash transaction threshold value;

determining potential cash transaction risk entropy according to the mapping relation and the potential cash transaction threshold value;

if a first potential cash transaction risk entropy smaller than or equal to the cash transaction risk entropy of the target user exists, taking the minimum value of the first potential cash transaction risk entropy as a cash transaction risk entropy to be selected;

and taking the cash transaction threshold corresponding to the cash transaction risk entropy to be selected in the mapping relation as the cash transaction threshold of the target user at the first self-service terminal.

Optionally, the determining the cash transaction risk entropy of the target user according to the cash transaction threshold includes:

acquiring first historical cash transaction data of a banking system, wherein the first historical cash transaction data comprises cash transaction amount;

taking first historical cash transaction data with cash transaction amount smaller than or equal to the cash transaction threshold value as second historical cash transaction data corresponding to the cash transaction threshold value;

Taking third historical cash transaction data related to risks in the second historical cash transaction data as risk cash transaction data;

acquiring a risk category of the risk cash transaction data;

and determining the cash transaction risk entropy of the target user according to the risk cash transaction data of each risk category and the second historical cash transaction data.

In a second aspect, the present application provides a bank self-service terminal control device, comprising:

the first acquisition module is used for acquiring first historical environment payment data of a first self-service terminal, wherein the distance between a payment place of the first historical environment payment data and the first self-service terminal is smaller than a preset distance threshold value, and the historical cash transaction quantity of the first self-service terminal is smaller than or equal to a cash transaction quantity threshold value;

the first processing module is used for determining the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold according to the first historical environment payment data, wherein the cash transaction risk entropy represents the information quantity of related risks when cash transaction is carried out on the self-service terminal;

the second acquisition module is used for acquiring cash transaction risk entropy of the target user when the target user initiates cash transaction on the first self-service terminal;

The second processing module is used for determining the cash transaction threshold value of the target user at the first self-service terminal according to the cash transaction risk entropy of the target user and the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold value; and controlling the cash transaction threshold value when the target user uses the first self-service terminal according to the cash transaction threshold value.

In a third aspect, the present application provides an electronic device comprising: a processor, a communication interface, and a memory; the processor is respectively in communication connection with the communication interface and the memory;

the memory stores computer-executable instructions;

the communication interface performs communication interaction with external equipment;

the processor executes computer-executable instructions stored by the memory to implement the method of any one of the first aspects.

In a fourth aspect, the present application provides a computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of bank self-service terminal control as in any of the first aspects.

In a fifth aspect, the present application provides a computer program product for implementing a bank self-service terminal control method as claimed in any one of the first aspects when executed by a processor.

According to the bank self-service terminal control method, the bank self-service terminal control device, the bank self-service terminal control equipment and the storage medium, the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold value is determined according to the first historical environment payment data by acquiring the first historical environment payment data of the first self-service terminal. When a target user initiates cash transaction on a first self-service terminal, acquiring cash transaction risk entropy of the target user, determining the cash transaction threshold of the target user on the first self-service terminal according to the cash transaction risk entropy of the target user and the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold, and controlling the cash transaction threshold of the target user when using the first self-service terminal according to the cash transaction threshold, so that the cash transaction safety of the self-service terminal is improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.

FIG. 1 is a schematic view of a bank self-service terminal control scenario provided by the application;

FIG. 2 is a schematic flow chart of a method for controlling a self-service terminal of a bank according to an embodiment of the present application;

FIG. 3 is a schematic flow chart of another method for controlling a self-service terminal of a bank according to an embodiment of the present application;

FIG. 4 is a schematic flow chart of a method for controlling a self-service terminal of a bank according to an embodiment of the present application;

FIG. 5 is a schematic flow chart of a method for controlling a self-service terminal of a bank according to an embodiment of the present application;

FIG. 6 is a schematic flow chart of a method for controlling a self-service terminal of a bank according to an embodiment of the present application;

FIG. 7 is a schematic diagram of a control device of a self-service terminal of a bank according to an embodiment of the present application;

fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Specific embodiments of the present application have been shown by way of the above drawings and will be described in more detail below. The drawings and the written description are not intended to limit the scope of the inventive concepts in any way, but rather to illustrate the inventive concepts to those skilled in the art by reference to the specific embodiments.

Detailed Description

Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.

It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or fully authorized by each party, and the collection, use and processing of the related data need to comply with related laws and regulations and standards, and provide corresponding operation entries for the user to select authorization or rejection.

It should be noted that the self-service terminal control method and apparatus of the present application may be used in financial field or other fields, and may be used in any field other than financial field or other fields.

For easy understanding, the application scenario of the present application will be described in detail first.

Fig. 1 is a schematic diagram of a scenario of self-service terminal control of a bank according to the present application. As shown in fig. 1, the scene includes: a server of a banking system and N self-service terminals.

The N self-service terminals comprise M self-service terminals of banks to which the banking system belongs and P self-service terminals of other banks. Among the M self-service terminals, the self-service terminal 1 having less historic cash transaction data may be included. The self-service terminal may be a terminal device such as an automatic teller machine (Automated Teller Machine, ATM) or a self-service counter, and the cash transaction is a transaction involving cash such as deposit and withdrawal at the ATM or the self-service counter.

At present, along with the perfection of bank risk control, any bank must implement a risk control principle to ensure the asset security of the bank to the maximum extent. When a user uses a self-service terminal, abnormal cash transaction behavior may occur due to the inability to manually review the cash transaction behavior of the user. Thus, banks typically limit cash transactions performed by users using self-service terminals by setting deposit thresholds (i.e., limits), withdrawal thresholds, etc., to effectively control losses that may be incurred. For example, a user may be at risk of fraudulent use of a user account by performing high-volume withdrawal transactions multiple times through a self-service terminal in a short period of time, or the user may be at risk of fraud, etc., which may be effectively reduced by limiting the threshold value of the cash transaction.

However, the server of the current banking system can only set a threshold value on the self-service terminal belonging to the bank to reduce the loss caused by the abnormal cash transaction, and cannot control the action of using the bank card of the bank to conduct the cash transaction on the self-service terminals of other banks.

In addition, the setting of cash transaction threshold values of the self-service terminal by banks is usually carried out for different areas and different users at present, for example, in areas with less abnormal cash transaction amounts, a higher cash transaction threshold value can be set, in areas with more abnormal cash transaction amounts, a lower cash transaction threshold value can be set, on the other hand, cash transaction threshold values of the self-service terminal can be set for users with different user figures, so that the cash transaction threshold values of the self-service terminal are more reasonable. However, if the self-service terminal is the self-service terminal 1 with less historical cash transaction data, the cash transaction threshold of the self-service terminal cannot be accurately determined according to the historical cash transaction data of the self-service terminal.

In summary, the current banks have low cash transaction control capability on other banks' self-service terminals or the self-service terminals of the banks with less historical cash transaction data, and the self-service terminals have poor security of cash transaction.

In view of the above, the application provides a bank self-service terminal control method, which determines cash transaction risk entropy of a self-service terminal of other banks by acquiring the self-service terminal of the other banks or historical environment payment data near an area where the self-service terminal of the bank has less historical cash transaction data. And determining the cash transaction threshold of the self-service terminal through the cash transaction risk entropy and the cash transaction risk entropy of the target user, and controlling the cash transaction behavior of the target user on the self-service terminal through the cash transaction threshold of the self-service terminal, so that the security of the cash transaction behavior of the self-service terminal is improved.

The following describes the technical scheme of the present application and how the technical scheme of the present application solves the above technical problems in detail with specific embodiments. The execution main body of the bank self-service terminal control method is the server of the bank system shown in the figure 1. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

Fig. 2 is a schematic flow chart of a method for controlling a self-service terminal of a bank according to an embodiment of the present application. As shown in fig. 2, the method may include:

s201, acquiring first historical environment payment data of a first self-service terminal.

The distance between the payment place of the first historical environment payment data and the first self-service terminal is smaller than a preset distance threshold, and the historical cash transaction quantity of the first self-service terminal is smaller than or equal to a cash transaction quantity threshold. The preset distance threshold may be determined according to an actual requirement, that is, the payment location of the first historical environment payment data is the payment data in the area around the location where the first self-service terminal is located. Specifically, the first historical environmental payment data is historical payment data of other users using other terminals capable of being used for payment, for example, the terminals can be point-of-sale information management systems (Point of sales terminal, POS), or cashier terminals which can interact with the banking system by merchants around the first self-service terminal. The period of time of the first historical environmental payment data may be determined according to actual requirements, for example, may be historical environmental payment data in a week, or may be one month, one year, etc., which is not limited by the present application.

In one possible implementation, the first historical environmental payment data may be actively uploaded to the server of the banking system by other users in the area using other terminals that can be used for payment.

In another possible implementation manner, the server of the banking system may actively collect the first historical environmental payment data from other users in the area using other terminals capable of being used for payment according to actual requirements.

S202, according to the first historical environment payment data, determining a mapping relation between cash transaction risk entropy of the first self-service terminal and a cash transaction threshold.

Wherein the cash transaction risk entropy characterizes the information quantity about the risk when the cash transaction is carried out on the self-service terminal, the risk can be, for example, the risk related to the abnormal cash transaction, and the risk entropy can measure the size and uncertainty of the risk of the cash transaction. The environmental risk entropy of the first self-service terminal can be obtained through calculation of data with transaction risk and data without transaction risk in the first historical environmental payment data.

One possible implementation manner may determine, through the data feature of the first historical environment payment data, a mapping relationship between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold, for example, may determine, according to a pre-stored correspondence between the data feature and the mapping relationship, and the data feature, a mapping relationship between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold.

In another possible implementation manner, the environmental risk entropy of the first self-service terminal is determined through the first historical environmental payment data, a self-service terminal with the environmental risk entropy similar to that of the first self-service terminal is selected from the self-service terminals with more historical cash transaction data according to the environmental risk entropy of the first self-service terminal, and the mapping relationship between the cash transaction risk entropy of the self-service terminal and the cash transaction threshold is used as the mapping relationship between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold.

S203, when a target user initiates cash transaction on the first self-service terminal, acquiring cash transaction risk entropy of the target user.

The cash transaction risk entropy of the target user refers to cash transaction risk entropy corresponding to the identity of the target user, and represents information quantity of related risks when the target user conducts cash transaction.

One possible implementation determines a cash transaction risk entropy for the target user based on the identity information of the target user. In this implementation, the identity information of the target user and the cash transaction risk entropy of the target user are stored in a server of the banking system. And determining the target user according to the identity information of the target user, and further obtaining the cash transaction risk entropy of the target user.

In another possible implementation, the cash transaction risk entropy of the target user is determined according to a pre-stored cash transaction threshold of the target user. The cash transaction threshold is used to limit the cash transaction amount of the target user, and may be, for example, limiting the cash transaction amount of the target user in one day, or the cash transaction amount in one year, etc.

S204, determining the cash transaction threshold value of the target user at the first self-service terminal according to the cash transaction risk entropy of the target user and the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold value.

One possible implementation manner is to determine a maximum cash transaction amount of a target user according to cash transaction risk entropy of the target user, determine a selection range of the cash transaction risk entropy of a first self-service terminal according to the cash transaction amount and the cash transaction threshold, and take a cash transaction threshold corresponding to the cash transaction risk entropy of the first self-service terminal, which is smaller than or equal to the cash transaction risk entropy of the target user, as a cash transaction threshold of the target user at the first self-service terminal.

In another possible implementation manner, according to the cash transaction risk entropy of the target user and the cash transaction risk entropy of the first self-service terminal, a selection range of the cash transaction risk entropy of the first self-service terminal is determined, and a cash transaction threshold corresponding to the cash transaction risk entropy of the first self-service terminal, which is smaller than or equal to the cash transaction risk entropy of the target user, is used as the cash transaction threshold of the target user at the first self-service terminal. For example, the selection range of the cash transaction risk entropy of the first self-service terminal may be determined according to the difference between the cash transaction risk entropy of the target user and the cash transaction risk entropy of the first self-service terminal, and the determination method may be determined by a mapping relationship, or after a pre-trained model is input, the selection range is output, and the like.

S205, controlling the cash transaction threshold value when the target user uses the first self-service terminal according to the cash transaction threshold value.

And the server of the banking system sets a cash transaction threshold value when the target user uses the first self-service terminal in the first self-service terminal according to the cash transaction threshold value so as to control cash transaction limit when the target user uses the first self-service terminal to conduct cash transaction.

According to the method provided by the embodiment of the application, the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold is determined according to the first historical environment payment data by acquiring the first historical environment payment data of the first self-service terminal. When a target user initiates cash transaction on a first self-service terminal, acquiring cash transaction risk entropy of the target user, determining the cash transaction threshold of the target user on the first self-service terminal according to the cash transaction risk entropy of the target user and the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold, and controlling the cash transaction threshold of the target user when using the first self-service terminal according to the cash transaction threshold, so that the cash transaction safety of the self-service terminal is improved.

Next, a detailed description will be given of how to determine the mapping relationship between the cash transaction risk entropy and the cash transaction threshold of the first self-service terminal according to the historical environmental payment data in the aforementioned step S202.

Fig. 3 is a flowchart of another method for controlling a self-service terminal of a bank according to an embodiment of the present application. As shown in fig. 3, the foregoing step S202 may include:

s301, determining the environmental risk entropy of the first self-service terminal according to the first historical environmental payment data.

The environment risk entropy represents information quantity of related risks when payment is carried out within a specified distance range of the first self-service terminal. The data of the abnormal transaction in the historical environment payment data is obtained, for example, whether the data of the abnormal transaction exists or not can be determined by obtaining the abnormal transaction identifier in the first historical environment payment data, and if the data of the abnormal transaction exists, the data of the abnormal transaction is obtained.

One possible implementation manner may extract a data feature of the first historical environmental payment data, and determine an environmental risk entropy of the first self-service terminal according to a mapping relationship between the data feature and the environmental risk entropy, and the data feature of the first historical environmental payment data. The mapping relationship may be preset, and the data feature extraction may be implemented by using any existing data feature extraction algorithm, which is not described in detail in the present application.

In another possible implementation manner, the environmental risk entropy of the first self-service terminal is determined according to the historical environment payment data corresponding to different payment scenes of the first historical environment payment data. The method of implementing this implementation may be as follows steps S3011 to S3013:

s3011, selecting historical environment payment data of at least one payment scene from the first historical environment payment data.

The first historical environment payment data are classified according to different payment scenes of the first historical environment payment data, and historical environment payment data corresponding to each payment scene are obtained. The payment scenario may be determined according to actual requirements, for example, payment scenarios such as consumer payment, transfer payment, etc., which the present application is not limited to.

S3012, taking historical environment payment data related to risks in the first historical environment payment data of each payment scene as risk environment payment data of the payment scene.

The historical environmental payment data related to risk may be historical environmental payment data with abnormal transaction as described above, and the abnormal transaction identification may be used to determine which of the first historical environmental payment data of the payment scenario is the historical environmental payment data related to risk. When there are multiple payment scenarios, then there are corresponding multiple risk environment payment data.

S3013, determining the environmental risk entropy of the first self-service terminal according to the risk environment payment data and the first historical environment payment data.

And determining cash transaction amount contained in the first historical environment payment data from the historical environment payment data corresponding to the first self-service terminal, and determining the environment risk entropy of the first self-service terminal according to the cash transaction amount and the risk environment payment data of each scene. Illustratively, the calculation formula for determining the environmental risk entropy of the first self-service terminal according to the cash transaction amount and the risk environment payment data of each scene may be as follows (1):

wherein F is the environmental risk entropy corresponding to the first self-service terminal, v is the cash transaction amount contained in the first historical environmental payment data, and u _i The risk environment payment data, which is the ith payment scenario, contains the cash transaction amount, u _j Is the amount of cash transactions contained in the risk environment payment data for the j-th payment scenario.

Through the formula (1), the environmental risk entropy of the first self-service terminal can be determined according to the risk environment payment data and the first historical environment payment data.

S302, acquiring the environment risk entropy of the second self-service terminal.

The second self-service terminal is at least one self-service terminal other than the first self-service terminal. The manner of obtaining the environmental risk entropy of the second self-service terminal is similar to how to determine the environmental risk entropy of the first self-service terminal according to the first historical environmental payment data in the above step S301, and will not be described herein.

S303, determining similar self-service terminals of the first self-service terminal according to the environmental risk entropy of the second self-service terminal.

One possible implementation manner is to select a second self-service terminal with the environmental risk entropy similar to that of the first self-service terminal as a similar self-service terminal of the first self-service terminal. For example, a second self-service terminal with the smallest difference between the environmental risk entropy and the environmental risk entropy of the first self-service terminal can be selected as a similar self-service terminal of the first self-service terminal; or selecting any self-service terminal from the second self-service terminals similar to the first self-service terminal environmental risk entropy as the similar self-service terminal of the first self-service terminal.

In another possible implementation manner, the similar self-service terminals of the first self-service terminal are determined according to the similar entropy of the environments of the second self-service terminal and the first self-service terminal. And taking the second self-service terminal with the absolute value of the difference value of the environmental risk entropy and the environmental risk entropy of the first self-service terminal smaller than a preset difference value threshold as a candidate self-service terminal, and determining the environmental similarity entropy of each candidate self-service terminal and the first self-service terminal according to the historical environmental payment data of each candidate self-service terminal and the first self-service terminal, wherein the environmental similarity entropy is used for representing the information quantity of the similarity of payment transactions in a specified distance range of the two self-service terminals. And selecting the similar self-service terminals corresponding to the first self-service terminal from the candidate self-service terminals according to the environmental similar entropy of each candidate self-service terminal and the first self-service terminal.

In this implementation manner, determining the environmental similarity entropy of each candidate self-service terminal and the first self-service terminal according to the historical environmental payment data of each candidate self-service terminal and the first self-service terminal may be implemented in the following manner:

and for each candidate self-service terminal, taking the payment amount contained in the historical environment payment data of each payment scene in the historical environment payment data of the candidate self-service terminal as the first payment amount of each payment scene, and taking the payment amount contained in the first historical environment payment data of each payment scene in the first historical environment payment data of the first self-service terminal as the second payment amount of each payment scene. For each payment scenario, a minimum and maximum value of a data set of first and second payment amounts of the payment scenario is determined.

If the maximum value is greater than 2 times of the minimum value, determining that the environmental similarity entropy of the candidate self-service terminal and the first self-service terminal corresponding to the payment scene is:

wherein P is the similar entropy of the environments of the candidate self-service terminal and the first self-service terminal corresponding to the payment scene, m is the maximum value of a data set formed by the first payment amount and the second payment amount of the payment scene, and n is the minimum value of the data set formed by the first payment amount and the second payment amount of the payment scene.

If the maximum value is less than or equal to 2 times of the minimum value, determining that the environmental similarity entropy of the candidate self-service terminal and the first self-service terminal corresponding to the payment scene is:

and determining the environmental similarity entropy of the candidate self-service terminal and the first self-service terminal according to the environmental similarity entropy of the candidate self-service terminal and the first self-service terminal corresponding to each payment scene.

S304, according to the similar self-service terminals, determining the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold.

Implementation a: and taking the mapping relation between the cash transaction risk entropy of the similar self-service terminal and the cash transaction threshold value as the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold value.

Implementation mode B: and determining the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold according to the similar self-service terminals and the terminal risk model.

And acquiring a plurality of terminal risk models, wherein the terminal risk models can determine the risk magnitude relation of two self-service terminals. The terminal risk model corresponds to the value range of the two variables and is a self-service terminal, and the terminal risk model comprises the size relation of the attribute values of the two variables corresponding to the attributes of the self-service terminal and the risk size relation of the two variables.

For each similar self-service terminal corresponding to the first self-service terminal, determining whether other similar self-service terminals corresponding to the first self-service terminal exist, wherein the risk of the other similar self-service terminals is greater than that of the similar self-service terminals. If it is determined that other similar self-service terminals corresponding to the first self-service terminal do not exist, deleting the similar self-service terminal from the similar self-service terminals corresponding to the first self-service terminal. And determining the corresponding relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold according to the similar self-service terminals corresponding to the deleted first self-service terminal.

Implementation C: and determining the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold according to the similar self-service terminals and the cash transaction threshold set.

The cash transaction threshold set is preset, at least one preset cash transaction threshold is included in the cash transaction threshold set, and the cash transaction threshold set can be set according to actual requirements, so that the application is not limited to the above.

In implementation C, fig. 4 is a schematic flow chart of another method for controlling a self-service terminal of a bank according to an embodiment of the present application. As shown in fig. 4, the foregoing implementation C may include:

S401, historical cash transaction data of similar self-service terminals are used as potential historical cash transaction data of the first self-service terminal.

The historical cash transaction data of the similar self-service terminal may be cash transaction data of the similar self-service terminal within a certain period of time of the history, and the historical cash transaction data may be stored in the similar terminal or a server of a banking system.

Because the environmental risk entropy of the similar self-service terminal is close to that of the first self-service terminal, the historical cash transaction data of the similar self-service terminal can be approximately regarded as the historical cash transaction data of the first self-service terminal, namely the historical cash transaction data of the similar self-service terminal is potential historical cash transaction data of the first self-service terminal.

S402, acquiring a cash transaction threshold set.

The cash transaction threshold set may be pre-stored in a server of the banking system, for example, different cash transaction threshold sets may be preset according to self-service terminals in different areas, or the same cash transaction threshold set may be preset for all self-service terminals. When cash transaction threshold sets of self-service terminals in different areas are different, a server of a banking system can determine the area where the self-service terminal is located according to the position where the self-service terminal is located, and further obtain the cash transaction threshold set corresponding to the self-service terminal. When the cash transaction threshold sets of the self-service terminals in different areas are the same, the server of the banking system directly reads the cash transaction threshold sets from the locations where the cash transaction threshold sets are stored.

S403, regarding each cash transaction threshold, taking the potential historical cash transaction data with the cash transaction amount smaller than or equal to the cash transaction threshold in the potential historical cash transaction data of the first self-service terminal as the potential historical cash transaction data corresponding to the cash transaction threshold.

Since the cash transaction amount cannot exceed the cash transaction threshold value during the cash transaction, the cash transaction data corresponding to each cash transaction threshold value is cash transaction data with the cash transaction amount smaller than or equal to the cash transaction threshold value. In addition, because the historical cash transaction data of the first self-service terminal is too little, the potential historical cash transaction data of the first self-service terminal is used as the historical cash transaction data of the first self-service terminal, and the cash transaction threshold is matched with the potential historical cash transaction data smaller than or equal to the cash transaction threshold as the potential historical cash transaction data corresponding to the cash transaction threshold.

S404, determining cash transaction risk entropy corresponding to the cash transaction threshold according to the potential historical cash transaction data corresponding to the cash transaction threshold.

One possible implementation may extract data characteristics of potential historical cash transaction data, and determine cash transaction risk entropy corresponding to the cash transaction threshold according to a mapping relationship between the data characteristics of the historical cash transaction data and cash transaction risk entropy, and the data characteristics of the historical cash transaction data. The mapping relationship may be preset, and the data feature extraction may be implemented by using any existing data feature extraction algorithm, which is not described in detail in the present application.

In another possible implementation, the cash transaction risk entropy corresponding to the cash transaction threshold is determined according to a risk category of the potential historical cash transaction data with transaction anomalies. The method of implementing this implementation may be as follows steps S4041 to S4043:

s4041, using the potential historical cash transaction data with transaction abnormality as the potential risk cash transaction data.

The potentially historic cash transaction data of the transaction anomaly may be, for example, historic transaction data with risk of account theft, historic transaction data with risk of money back-washing, historic transaction data with risk of fraud, and the like. And determining the potential historical cash transaction data with transaction abnormality by identifying transaction abnormality tags carried in the potential historical cash transaction data, and taking the potential historical cash transaction data with transaction abnormality as potential risk cash transaction data.

S4042, acquiring risk categories of the potential risk cash transaction data.

And acquiring the risk category of the acquired potential risk cash transaction data according to the transaction anomaly label of each potential risk cash transaction data. For example, the transaction anomaly tag carries a risk category, and the risk category can be directly extracted from the tag; or determining the risk category of the potential risk cash transaction data according to the mapping relation between the transaction abnormal label and the risk category and the transaction abnormal label.

S4043, determining cash transaction risk entropy corresponding to the cash transaction threshold according to the potential risk cash transaction data of each risk category and the potential history cash transaction data.

And determining the total cash transaction amount contained in the potential historical cash transaction data from the potential historical cash transaction data, and determining the cash transaction risk entropy corresponding to the cash transaction threshold according to the total cash transaction amount and the potential risk cash transaction data of each risk category. Illustratively, the calculation formula for determining the cash transaction risk entropy corresponding to the cash transaction threshold according to the total cash transaction amount and the potential risk cash transaction data of each risk category may be as follows (4):

wherein G is the cash transaction risk entropy corresponding to the cash transaction threshold, q is the total cash transaction amount, p _i The cash transaction amount, p, contained in the potentially risky cash transaction data which is the ith risk category _j Is the cash transaction amount contained in the risk category j's potential risk cash transaction data.

Through the formula (4), cash transaction risk entropy corresponding to the cash transaction threshold can be determined according to the potential risk cash transaction data of each risk category and the potential history cash transaction data.

S405, determining a mapping relation between cash transaction risk entropy of the first self-service terminal and cash transaction thresholds according to the cash transaction threshold set and cash transaction risk entropy corresponding to each cash transaction threshold in the cash transaction threshold set.

And forming a set of mapping relations between the cash transaction threshold values and the corresponding cash transaction risk entropies according to the mapping relations between all cash transaction threshold values and the corresponding cash transaction risk entropies included in the cash transaction threshold value set, and taking the set as the mapping relation set between the cash transaction risk entropies and the cash transaction threshold values of the first self-service terminal.

According to the method provided by the embodiment of the application, the environmental risk entropy of the first self-service terminal is determined through the first historical environmental payment data, the environmental risk entropy of the second self-service terminal is obtained, the similar self-service terminal of the first self-service terminal is determined according to the environmental risk entropy of the second self-service terminal, the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold is determined according to the similar self-service terminal, the function of obtaining the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold according to the existing mapping relation between the cash transaction risk entropy of the similar self-service terminal and the cash transaction threshold, which is similar to the environmental risk entropy of the first self-service terminal, is realized, and therefore the problem that the mapping relation between the cash transaction risk entropy and the cash transaction threshold cannot be determined according to the historical cash transaction data of the first self-service terminal due to the fact that the historical cash transaction data of the first self-service terminal is less is avoided, and the control degree of the cash transaction behavior of the bank on the first self-service terminal and the security of the cash transaction function of the first self-service terminal are improved.

In the following, a detailed description will be given of how to obtain the cash transaction risk entropy of the target user when the target user initiates a cash transaction on the first self-service terminal.

Fig. 5 is a schematic flow chart of another method for controlling a self-service terminal of a bank according to an embodiment of the present application. As shown in fig. 5, the foregoing step S203 may include:

s501, acquiring a prestored cash transaction threshold value of a target user;

the cash transaction threshold refers to a cash transaction threshold corresponding to the identity of the target user, characterizing a cash transaction limit at which the target user performs a cash transaction. And determining a cash transaction threshold of the target user according to the identity information of the target user. In this implementation, the identity information of the target user is stored in a server of the banking system, as well as the cash transaction threshold of the target user. The target user can be determined according to the identity information of the target user, and the cash transaction threshold value of the target user is further obtained.

S502, determining cash transaction risk entropy of the target user according to the cash transaction threshold.

In a possible implementation manner, a mapping relation between a preset cash transaction threshold value of a target user and cash transaction risk entropy of the target user exists in a server of the banking system, and the cash transaction risk entropy of the target user is determined according to the cash transaction threshold value of the target user and the mapping relation.

In another possible implementation, the cash transaction risk entropy of the target user is determined based on cash transaction thresholds and historical cash transaction data of the banking system. First historical cash transaction data of a banking system is obtained. Wherein the first historical cash transaction data includes a cash transaction amount. The first historical cash transaction data may be all the historical cash transaction data in the banking system, may be the historical cash transaction data of all the target users of the type corresponding to the type of the target users, may also be a specific amount of historical cash transaction data, and the like, and may be obtained from a database of the banking system.

And taking the first historical cash transaction data with the cash transaction amount smaller than or equal to the cash transaction threshold value as the second historical cash transaction data corresponding to the cash transaction threshold value. And taking third historical cash transaction data related to risks in the second historical cash transaction data as risk cash transaction data. The risk category of the risk cash transaction data is obtained, which is similar to the risk category of the potential risk cash transaction data described above and will not be described in detail herein.

And determining the cash transaction risk entropy of the target user according to the risk cash transaction data of each risk category and the second historical cash transaction data. Determining a total cash transaction amount contained in the second historical cash transaction data from the second historical cash transaction data, and determining cash transaction risk entropy of the target user according to the total cash transaction amount and risk cash transaction data of each risk category. Illustratively, the calculation formula for determining the risk entropy of the cash transaction of the target user according to the total cash transaction amount and the risk cash transaction data of each risk category may be as follows (5):

where R is the risk entropy of the cash transaction of the target user, q is the total cash transaction amount, p _i The cash transaction amount, p, included in the risk cash transaction data of the i-th risk category _j Is the cash transaction amount contained in the risk cash transaction data of the j-th risk category.

Through the above formula (5), the cash transaction risk entropy of the target user can be determined according to the risk cash transaction data of each risk category and the second historical cash transaction data.

Next, in the implementation manner shown in fig. 5, a detailed description is given of how to determine the cash transaction threshold of the target user at the first self-service terminal according to the cash transaction risk entropy of the target user and the mapping relationship between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold in the foregoing step S204.

Fig. 6 is a flowchart of another method for controlling a self-service terminal of a bank according to an embodiment of the present application. As shown in fig. 6, the foregoing step S204 may include:

s601, acquiring historical cash transaction data of a target user, and determining the maximum cash transaction amount of the target user.

The historical cash transaction data of the target user may be all the historical cash transaction data of the target user, or may be historical cash transaction data of a period of time in the near future, such as historical cash transaction data of a year. The maximum cash transaction amount of the target user may characterize the demand for the cash transaction amount of the target user, obtain historical cash transaction data having a maximum cash transaction amount from the historical cash transaction data, and determine the maximum cash transaction amount of the target user.

S602, taking a cash transaction threshold value which is larger than or equal to the maximum cash transaction amount in cash transaction thresholds contained in the mapping relation as a potential cash transaction threshold value.

Considering that the cash transaction amount needs to be met when no abnormal transaction exists for the target user, the cash transaction threshold value of the target user needs to be larger than the maximum cash transaction amount to meet the cash transaction amount needs when no abnormal transaction exists for the target user, and therefore the cash transaction threshold value which is larger than or equal to the maximum cash transaction amount in the cash transaction threshold value contained in the mapping relation is taken as the potential cash transaction threshold value so as to meet the requirements of the user.

S603, determining potential cash transaction risk entropy according to the mapping relation and the potential cash transaction threshold value.

And determining the cash transaction risk entropy of the first self-service terminal corresponding to the potential cash transaction threshold of the target user in the mapping relation according to the potential cash transaction threshold and the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold, and taking the cash transaction risk entropy of the first self-service terminal as the potential cash transaction risk entropy.

S604, if a first potential cash transaction risk entropy smaller than or equal to the cash transaction risk entropy of the target user exists, taking the minimum value of the first potential cash transaction risk entropy as the cash transaction risk entropy to be selected.

If there is a first potential cash transaction risk entropy that is less than or equal to the cash transaction risk entropy of the target user, the risk of characterizing the first potential cash transaction risk entropy of the target user using the first self-service terminal is lower, and cash transactions can be further provided for the target user. Further to control the risk of the cash transaction, the minimum value of the first potential cash transaction risk entropy can be used as the cash transaction risk entropy to be selected, namely, the cash transaction risk entropy with the lowest risk is selected, so that a cash transaction threshold value with smaller risk can be acquired conveniently, and the security of the cash transaction is improved.

If there is no first potential cash transaction risk entropy less than or equal to the cash transaction risk entropy of the target user, the risk of characterizing the first potential cash transaction risk entropy of the target user using the first self-service terminal is higher, and the cash transaction for the target user needs to be refused.

S605, taking a cash transaction threshold corresponding to the risk entropy of the cash transaction to be selected in the mapping relation as the cash transaction threshold of the target user at the first self-service terminal.

According to the method provided by the embodiment of the application, the cash transaction risk entropy of the target user is determined according to the cash transaction threshold by acquiring the prestored cash transaction threshold of the target user, and the cash transaction threshold of the target user at the first self-service terminal is determined according to the cash transaction risk entropy of the target user and the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold, so that the cash transaction safety is improved.

Fig. 7 is a schematic structural diagram of a self-service terminal control device for a bank according to an embodiment of the present application. As shown in fig. 7, the self-service terminal control device of the bank may include: the first acquisition module 11, the first processing module 12, the second acquisition module 13 and the second processing module 14.

The first obtaining module 11 is configured to obtain first historical environmental payment data of a first self-service terminal, where a distance between a payment location of the first historical environmental payment data and the first self-service terminal is less than a preset distance threshold, and a historical cash transaction amount of the first self-service terminal is less than or equal to a cash transaction amount threshold.

The first processing module 12 is configured to determine, according to the first historical environmental payment data, a mapping relationship between a cash transaction risk entropy of the first self-service terminal and a cash transaction threshold, where the cash transaction risk entropy characterizes an information amount related to a risk when performing a cash transaction on the self-service terminal.

A second obtaining module 13, configured to obtain a cash transaction risk entropy of the target user when the target user initiates a cash transaction on the first self-service terminal.

The second processing module 14 is configured to determine a cash transaction threshold of the target user at the first self-service terminal according to the cash transaction risk entropy of the target user and a mapping relationship between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold. And controlling the cash transaction threshold when the target user uses the first self-service terminal according to the cash transaction threshold.

In one possible implementation, the first processing module 12 is specifically configured to determine an environmental risk entropy of the first self-service terminal according to the first historical environmental payment data. And acquiring the environmental risk entropy of the second self-service terminal. And determining similar self-service terminals of the first self-service terminal according to the environmental risk entropy of the second self-service terminal. And determining the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold according to the similar self-service terminals. The environment risk entropy represents information quantity of related risks when payment is carried out within a specified distance range of the first self-service terminal.

In this implementation manner, a possible implementation manner, the first processing module 12 is specifically configured to select historical environmental payment data of at least one payment scenario from the first historical environmental payment data. And taking the historical environment payment data related to risks in the first historical environment payment data of each payment scene as risk environment payment data of the payment scene. And determining the environmental risk entropy of the first self-service terminal according to the risk environment payment data and the first historical environment payment data.

In another possible implementation manner, the first processing module 12 is specifically configured to use the historical cash transaction data of the similar self-service terminal as the potential historical cash transaction data of the first self-service terminal. A cash transaction threshold set is obtained, the cash transaction threshold set including at least one cash transaction threshold. And for each cash transaction threshold, taking potential historical cash transaction data with cash transaction amount smaller than or equal to the cash transaction threshold in the potential historical cash transaction data of the first self-service terminal as potential historical cash transaction data corresponding to the cash transaction threshold. And determining cash transaction risk entropy corresponding to the cash transaction threshold according to the potential historical cash transaction data corresponding to the cash transaction threshold. And determining the mapping relation between the cash transaction risk entropy of the first self-service terminal and the cash transaction threshold according to the cash transaction threshold set and the cash transaction risk entropy corresponding to each cash transaction threshold in the cash transaction threshold set.

Wherein, optionally, the first processing module 12 is specifically configured to take the potential historical cash transaction data with transaction abnormality in the potential historical cash transaction data as the potential risk cash transaction data. A risk category of the potentially risk cash transaction data is obtained. And determining cash transaction risk entropy corresponding to the cash transaction threshold according to the potential risk cash transaction data of each risk category and the potential history cash transaction data.

Optionally, when the target user initiates a cash transaction on the first self-service terminal, the second obtaining module 13 is specifically configured to obtain a prestored cash transaction threshold value of the target user. The second processing module 14 is specifically configured to determine a cash transaction risk entropy of the target user according to the cash transaction threshold.

In this implementation, the second obtaining module 13 is specifically configured to obtain historical cash transaction data of the target user, and determine a maximum cash transaction amount of the target user. The second processing module 14 is specifically configured to take, as the potential cash transaction threshold, a cash transaction threshold that is greater than or equal to the maximum cash transaction amount of the cash transaction thresholds included in the mapping relationship. And determining potential cash transaction risk entropy according to the mapping relation and the potential cash transaction threshold value. And if the first potential cash transaction risk entropy is smaller than or equal to the cash transaction risk entropy of the target user, taking the minimum value of the first potential cash transaction risk entropy as the cash transaction risk entropy to be selected. And taking the cash transaction threshold corresponding to the risk entropy of the cash transaction to be selected in the mapping relation as the cash transaction threshold of the target user at the first self-service terminal.

Wherein, optionally, the second obtaining module 13 is specifically configured to obtain first historical cash transaction data of the banking system, where the first historical cash transaction data includes a cash transaction amount. The second processing module 14 is specifically configured to take the first historical cash transaction data with the cash transaction amount less than or equal to the cash transaction threshold value as the second historical cash transaction data corresponding to the cash transaction threshold value. And taking third historical cash transaction data related to risks in the second historical cash transaction data as risk cash transaction data. The second acquiring module 13 is specifically configured to acquire a risk category of the risk cash transaction data. The second processing module 14 is specifically configured to determine a cash transaction risk entropy of the target user according to the risk cash transaction data of each risk category and the second historical cash transaction data.

The self-service terminal control device for the bank provided by the embodiment of the application can execute the self-service terminal control method for the bank in the embodiment of the method, and the implementation principle and the technical effect are similar and are not repeated here.

Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device is configured to execute the method for controlling the self-service terminal of the bank, for example, the method may be a server of the banking system. As shown in fig. 8, the electronic device 800 may include: at least one processor 801, a memory 802, a communication interface 803.

A memory 802 for storing programs. In particular, the program may include program code including computer-operating instructions.

Memory 802 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

The processor 801 is configured to execute computer-executable instructions stored in the memory 802 to implement the methods described in the foregoing method embodiments. The processor 801 may be a CPU or an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC) or one or more integrated circuits configured to implement embodiments of the present application.

The processor 801 may interact with external devices, such as the self-service terminals described above, via the communication interface 803. In a specific implementation, if the communication interface 803, the memory 802, and the processor 801 are implemented independently, the communication interface 803, the memory 802, and the processor 801 may be connected to each other and perform communication with each other through a bus. The bus may be an industry standard architecture (Industry Standard Architecture, abbreviated ISA) bus, an external device interconnect (Peripheral Component, abbreviated PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated EISA) bus, among others. Buses may be divided into address buses, data buses, control buses, etc., but do not represent only one bus or one type of bus.

Alternatively, in a specific implementation, if the communication interface 803, the memory 802, and the processor 801 are implemented on a single chip, the communication interface 803, the memory 802, and the processor 801 may complete communication through internal interfaces.

The present application also provides a computer-readable storage medium, which may include: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, etc., in which program codes may be stored, and in particular, the computer-readable storage medium stores program instructions for the methods in the above embodiments.

The present application also provides a program product comprising execution instructions stored in a readable storage medium. The at least one processor of the computing device may read the execution instructions from the readable storage medium, the execution instructions being executed by the at least one processor to cause the computing device to implement the bank self-service terminal control method described above.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application.

Claims

1. The bank self-service terminal control method is characterized by comprising the following steps:

2. The method of claim 1, wherein the determining a mapping relationship between cash transaction risk entropy and cash transaction threshold of the first self-service terminal based on the first historical environmental payment data comprises:

acquiring an environment risk entropy of the second self-service terminal;

3. The method of claim 2, wherein the determining the environmental risk entropy of the first self-service terminal based on the first historical environmental payment data comprises:

taking historical environment payment data related to risks in the first historical environment payment data of each payment scene as risk environment payment data of each payment scene;

4. The method of claim 2, wherein the determining, from the similar self-service terminals, a mapping relationship between cash transaction risk entropy and cash transaction threshold of the first self-service terminal comprises:

5. The method of claim 4, wherein the determining the cash transaction risk entropy corresponding to the cash transaction threshold from the potential historical cash transaction data corresponding to the cash transaction threshold comprises:

acquiring a risk category of the potential risk cash transaction data;

6. The method of claim 1, wherein the obtaining cash transaction risk entropy for the target user when the target user initiates a cash transaction on the first self-service terminal comprises:

acquiring a prestored cash transaction threshold value of the target user;

7. The method of claim 6, wherein the determining the cash transaction risk entropy of the target user based on the cash transaction threshold comprises:

acquiring a risk category of the risk cash transaction data;

8. A bank self-service terminal control device, comprising:

9. An electronic device, comprising: the processor is respectively in communication connection with the communication interface and the memory;

the memory stores computer-executable instructions;

the processor executes computer-executable instructions stored in the memory to implement the method of any one of claims 1-7.

10. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are for implementing a method of controlling a self-service banking terminal as claimed in any one of claims 1 to 7.