Method and apparatus for bank controlling transaction risk
By identifying customers' potential risk indicators and safe small amounts, the problem of transactions when the network signal is poor is solved, enabling small payments under weak signal conditions, ensuring smooth transactions and protecting customers' assets.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BANK OF CHINA
- Filing Date
- 2022-07-08
- Publication Date
- 2026-07-31
AI Technical Summary
Poor network signal can prevent customers from completing transactions at the bank, affecting their experience, especially for small payments.
By identifying potential risk indicators for customers, determining a safe minimum amount based on the bank's payment transaction data, and judging whether the payment amount is less than the safe minimum amount when the network signal strength is low, the transaction is supported if it is less than the safe minimum amount.
Allowing small payments when network signal is weak effectively controls transaction risks, ensures normal transaction processing, improves customer experience, and protects property security.
Smart Images
Figure CN115187257B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of computer data processing technology, and more particularly to a method and apparatus for banks to control transaction risks. Background Technology
[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.
[0003] Currently, customers need an internet connection for risk control and resource allocation when making transactions at banks. When the network signal is weak, transactions may be impossible, limiting customer access and resulting in a poor customer experience. Many customers frequently make small payments, such as grocery shopping in the evening, and are unable to complete these transactions when there is no network or a weak network signal.
[0004] In summary, there is an urgent need for a technical solution that can overcome the above-mentioned shortcomings and effectively control the transaction risks of customers. Summary of the Invention
[0005] To address the problems existing in the prior art, this invention proposes a method and apparatus for banks to control transaction risks.
[0006] In a first aspect of the present invention, a method for banks to control transaction risk is proposed, comprising:
[0007] Identify the potential risk indicators for each customer;
[0008] Based on the bank's payment transaction data and the customer's corresponding potential risk indicators, determine the corresponding safe small amount value for the customer;
[0009] When a customer makes a payment, if the network signal strength of the customer's mobile terminal is less than the signal strength threshold, it is determined whether the payment amount is less than the customer's corresponding safe small amount value; if it is less, the bank's mobile terminal app supports the customer's payment.
[0010] In a second aspect of the present invention, an apparatus for a bank to control transaction risk is provided, comprising:
[0011] The potential risk indicator identification module is used to identify the potential risk indicators corresponding to customers.
[0012] The secure small amount determination module is used to determine the secure small amount for a customer based on the bank's payment transaction data and the customer's corresponding potential risk indicators.
[0013] The risk control module is used to determine whether the payment amount is less than the customer's corresponding safe minimum amount if the network signal strength of the customer's mobile terminal is less than the signal strength threshold when the customer makes a payment; if it is less, the bank's mobile terminal app will support the customer's payment.
[0014] In a third aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a method for a bank to control transaction risk.
[0015] In a fourth aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements a method for a bank to control transaction risks.
[0016] In a fifth aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program, which, when executed by a processor, implements a method for banks to control transaction risks.
[0017] The method and apparatus for controlling transaction risks in banks proposed in this invention determine the potential risk indicators corresponding to customers; based on the bank's payment transaction data and the potential risk indicators corresponding to the customer, a safe small amount value is determined for the customer; when the customer makes a payment, if the network signal strength of the customer's mobile terminal is less than the signal strength threshold, it is determined whether the payment amount is less than the customer's safe small amount value; if it is less, the bank's APP on the mobile terminal supports the customer's payment. The overall solution can determine the customer's safe small amount value by analyzing payment transaction data and potential risk indicators, enabling customers to make small payments when the mobile terminal signal is weak. While effectively controlling customer transaction risks, it ensures the normal conduct of customer transactions, improves customer experience, and protects customer property security. Attached Figure Description
[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a schematic flowchart of a bank's method for controlling transaction risks according to an embodiment of the present invention.
[0020] Figure 2 This is a flowchart illustrating the process of determining potential risk indicators for a customer according to an embodiment of the present invention.
[0021] Figure 3 This is a schematic diagram illustrating the process by which a bank server determines the correspondence between payment thresholds and risk indicators according to an embodiment of the present invention.
[0022] Figure 4 This is a schematic diagram of the process for determining the security value corresponding to the customer according to an embodiment of the present invention.
[0023] Figure 5 This is a schematic diagram of the risk control process according to another embodiment of the present invention.
[0024] Figure 6 This is a schematic diagram of a bank's device architecture for controlling transaction risks according to an embodiment of the present invention.
[0025] Figure 7 This is a schematic diagram of a device architecture for controlling transaction risks in banks, according to another embodiment of the present invention.
[0026] Figure 8 This is a schematic diagram of a computer device structure according to an embodiment of the present invention. Detailed Implementation
[0027] The principles and spirit of the invention will now be described with reference to several exemplary embodiments. It should be understood that these embodiments are given merely to enable those skilled in the art to better understand and implement the invention, and are not intended to limit the scope of the invention in any way. Rather, these embodiments are provided to make this disclosure more thorough and complete, and to fully convey the scope of this disclosure to those skilled in the art.
[0028] Those skilled in the art will recognize that embodiments of the present invention can be implemented as a system, apparatus, device, method, or computer program product. Therefore, this disclosure can be specifically implemented in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.
[0029] According to an embodiment of the present invention, a method and apparatus for banks to control transaction risks are proposed, relating to the field of computer data processing technology.
[0030] The principles and spirit of the present invention will be explained in detail below with reference to several representative embodiments.
[0031] Figure 1 This is a schematic flowchart of a bank's method for controlling transaction risk according to an embodiment of the present invention. Figure 1 As shown, the method includes:
[0032] S1, Identify the potential risk indicators for the customer;
[0033] S2. Based on the bank's payment transaction data and the customer's corresponding potential risk indicators, determine the corresponding safe small value for the customer;
[0034] S3, when the customer makes a payment, if the network signal strength of the customer's mobile terminal is less than the signal strength threshold, determine whether the payment amount is less than the customer's corresponding safe small amount value; if it is less, the bank's mobile terminal app supports the customer's payment.
[0035] To provide a clearer explanation of the methods banks use to control transaction risks, each step will be explained in detail below.
[0036] In S1, refer to Figure 2 Identify the potential risk indicators for each customer, including:
[0037] S11, obtain the payment threshold stored by the customer in the bank's server;
[0038] S12. Based on the correspondence between payment thresholds and risk indicators pre-stored on the bank server, and the payment thresholds stored by the customer on the bank server, determine the potential risk indicators corresponding to the customer.
[0039] In one embodiment, reference Figure 3 The bank server determines the correspondence between payment thresholds and risk indicators using the following method:
[0040] S101, obtain transaction data for various customer categories of the bank;
[0041] S102, Based on the transaction data of each customer category, determine the probability of each customer category corresponding to each risk category;
[0042] S103, Based on the probability of each customer category corresponding to each risk category, determine the controllable customer categories;
[0043] S104, based on transactions of controllable customer categories, determine the correspondence between payment thresholds and risk indicators.
[0044] In one embodiment, (S102) based on the transaction data of each customer category, the probability of each customer category corresponding to each risk category is determined, including:
[0045] Set a transaction volume threshold;
[0046] The transaction data of each customer category is divided into multiple transaction data sets corresponding to that customer category according to a selected order (such as chronological order), wherein the number of transactions contained in each transaction data set is greater than the transaction volume threshold.
[0047] For each risk category, the proportion of transactions involving that risk category in each transaction dataset corresponding to each customer category is taken as the proportion sample for that customer category corresponding to that risk category;
[0048] Based on the proportion of the customer category corresponding to the corresponding risk category, determine the mean and variance of the proportion of the customer category to the corresponding risk category;
[0049] The probability of a customer category corresponding to a risk category is determined as the average proportion of that customer category to that risk category.
[0050] In one embodiment, the method further includes:
[0051] The upper bound of the probability error for each customer category corresponding to each risk category is defined as the ratio of the square of the proportion variance of that customer category to that risk category to the number of proportion samples of that customer category to that risk category.
[0052] Specifically, (S103) based on the probability of each customer category corresponding to each risk category, controllable customer categories are determined, including:
[0053] S103-1, Based on the probabilities of each customer category to each risk category, determine the partial order of customer categories. For any two customer categories, the partial order is used to determine whether the first customer category is superior to the second customer category. If for each risk category, the probability of the first customer category corresponding to the corresponding risk category is less than or equal to the probability of the second customer category corresponding to the corresponding risk category, then it is determined that the first customer category is superior to the second customer category in the partial order of customer categories.
[0054] S103-2, based on the partial order of customer categories, the maximal element of the partial order is taken as the controllable customer category.
[0055] In one embodiment, (S103-1) a partial order of customer categories is determined based on the probabilities of each customer category corresponding to each risk category, wherein, for any two customer categories, the partial order is used to determine whether the first customer category is superior to the second customer category, including:
[0056] For each customer category, if the upper bound of the error convergence of the probability of each risk category corresponding to that customer category is less than or equal to the set error convergence threshold, then that customer category is selected as a potential customer category.
[0057] For any two optional customer categories, if for each risk category, the probability of the first optional customer category corresponding to that risk category is less than or equal to the probability of the second optional customer category corresponding to that risk category, then the first optional customer category is determined to be superior to the second optional customer category in the partial order of customer categories.
[0058] Specifically, (S104) based on transactions of controllable customer categories, the correspondence between payment thresholds and risk indicators is determined, including:
[0059] S104-1, Determine multiple discrete payment thresholds based on transactions of controllable customer categories;
[0060] S104-2, For each discrete payment threshold, determine the proportion of risky transactions in the transactions of controllable customer categories when the payment threshold is set to that discrete payment threshold, and determine that proportion as the risk indicator corresponding to that discrete payment threshold;
[0061] S104-3, based on multiple discrete payment thresholds and the risk indicators corresponding to each discrete payment threshold, determine the correspondence between payment thresholds and risk indicators.
[0062] In S2, refer to Figure 4 Based on the bank's payment transaction data and the customer's corresponding potential risk indicators, the corresponding safe small amount value for the customer is determined, including:
[0063] S21, Select the payment transaction data of the customer category to which the customer belongs from the bank's payment transaction data, and use the selected payment transaction data as the payment transaction data corresponding to the customer;
[0064] S22, Based on the payment transaction amount contained in the payment transaction data corresponding to the customer, determine multiple payment amount ranges, wherein any two payment amount ranges do not intersect;
[0065] S23, For each payment amount range, select the corresponding payment transaction data whose payment transaction amount is within the payment amount range from the payment transaction data corresponding to the customer, and use the selected payment transaction data as the payment transaction data corresponding to the payment amount range;
[0066] S24. Based on the payment transaction data corresponding to the payment amount range, determine the risk indicators and transaction volume indicators corresponding to the payment amount range.
[0067] S25. Based on the risk indicators, transaction volume indicators, and potential risk indicators corresponding to the payment amount range, determine the safe small value corresponding to the customer.
[0068] In one embodiment, (S24) based on the payment transaction data corresponding to the payment amount range, the risk indicator and transaction volume indicator corresponding to the payment amount range are determined, including:
[0069] S241, divide the time range corresponding to the payment transaction data of the payment amount range into multiple time sub-ranges, wherein the time length of any two time sub-ranges is the same;
[0070] S242, take the number of transactions contained in the payment transaction data corresponding to each time sub-range as the transaction volume sample corresponding to the payment amount range, and take the proportion of risk-related transactions in the payment transaction data corresponding to each time sub-range as the risk sample corresponding to the payment amount range.
[0071] S243, the risk indicator corresponding to the payment amount range is determined as the mean of the risk sample corresponding to the payment amount range, and the transaction volume indicator corresponding to the payment amount range is determined as the mean of the transaction volume sample corresponding to the payment amount range.
[0072] In one embodiment, (S25) the safe minimum value for a customer is determined based on the risk indicators, transaction volume indicators, and potential risk indicators corresponding to the payment amount range, including:
[0073] S251, based on the risk indicators, transaction volume indicators, and potential risk indicators corresponding to the payment amount ranges, determine the partial order of the payment amount ranges. This partial order is used to determine whether the first payment amount range is superior to the second payment amount range among any two payment amount ranges. If the risk indicator corresponding to the first payment amount range is less than or equal to the risk indicator corresponding to the second payment amount range, and the transaction volume indicator corresponding to the first payment amount range is greater than or equal to the transaction volume indicator corresponding to the second payment amount range, and the risk indicator corresponding to the first payment amount range is less than or equal to the potential risk indicator corresponding to the customer, then it is determined that the first payment amount range is superior to the second payment amount range in the partial order of the payment amount ranges.
[0074] S252, Based on the partial order of the payment amount range, determine the extreme value amount range, where the extreme value amount range is the maximum element of the partial order;
[0075] S253, based on the extreme value range, determine the corresponding safe small amount value for this customer.
[0076] In one embodiment, (S252) determining the extreme value range based on the partial order of the payment amount range includes:
[0077] S252-1 initializes the set of payment intervals to be determined as the payment amount intervals where the corresponding risk indicators are less than or equal to the customer's corresponding potential risk indicators, initializes the set of payment intervals to be compared as all payment amount intervals, and initializes the set of extreme value payment intervals to empty;
[0078] S252-2, repeat the following steps until the set of pending payment intervals is empty:
[0079] S252-21, Select a payment amount interval A from the set of undetermined payment intervals, and perform a partial order comparison between the payment amount interval A and each payment amount interval B in the set of payment intervals to be compared, excluding the payment amount interval A.
[0080] S252-22, If payment amount interval B is better than payment amount interval A, then payment amount interval A is removed from the set of undetermined payment intervals; if payment amount interval A is better than payment amount interval B, then payment amount interval B is removed from the set of undetermined payment intervals, and payment amount interval B is determined as the next payment amount interval of payment amount interval A.
[0081] S252-23 If it is confirmed that every payment amount interval in the set of payment intervals to be compared, except for the payment amount interval A, is not better than the payment amount interval A, then the payment amount interval A is added to the extreme value payment interval set, and all the sub-payment amount intervals of the payment amount interval A are deleted from the set of payment intervals to be compared.
[0082] S252-3, the payment amount range in the extreme value payment range set is taken as the extreme value amount range.
[0083] Specifically, (S253) based on the extreme value range, the corresponding safe small amount value for the customer is determined, including:
[0084] S253-1, Select the rightmost extreme value range on the real number axis from the extreme value range;
[0085] S253-2, Based on the selected extreme value range, determine the corresponding safe small amount value for the customer.
[0086] In S3, when a customer makes a payment, if the network signal strength of the customer's mobile terminal is less than the signal strength threshold, it is determined whether the payment amount is less than the customer's corresponding safe small amount value; if it is less, the bank's mobile terminal app supports the customer's payment.
[0087] In one embodiment, reference Figure 5 The method also includes:
[0088] S01, For each customer, based on the partial order of customer categories, the customer category that is superior to the customer category to which the customer belongs is taken as the customer category corresponding to the customer;
[0089] S02, for each customer category corresponding to this customer, determine the risk length corresponding to this customer category based on the probability of each risk category corresponding to this customer category; where, the higher the probability, the smaller the risk length;
[0090] S03, The real-time risk control method for the customer category corresponding to the customer and the risk length corresponding to the customer category corresponding to the customer are sent to the customer's mobile terminal;
[0091] S04, when the network signal of the customer's mobile terminal is weak, the customer's mobile terminal performs real-time risk control on the customer's payment based on the received real-time risk control method and the risk length corresponding to the customer category.
[0092] In one embodiment, (S02) for each customer category corresponding to the customer, the risk length corresponding to the customer category is determined based on the probability of each risk category corresponding to the customer category, including:
[0093] For each customer category, the square root of the sum of squares of the probabilities of each risk category corresponding to that customer category is taken as the probability norm of that customer category; and the square root of the sum of squares of the upper bounds of the errors of the probabilities of each risk category corresponding to that customer category is taken as the error norm of that customer category.
[0094] Based on the probability norm and the error norm of the customer category, the risk length corresponding to the customer category is determined; where the smaller the probability norm and the smaller the error norm, the smaller the risk length.
[0095] In one embodiment, (S04) when the network signal of the customer's mobile terminal is weak, the customer's mobile terminal performs real-time risk control on the customer's payment based on the received real-time risk control method and the risk length corresponding to the customer category, including:
[0096] S041, The customer's mobile terminal sorts the various customer categories corresponding to the customer;
[0097] S042, the customer's mobile terminal determines the upper bound of the probability for each customer category based on the risk length corresponding to each customer category, wherein the upper bound of the probability for each customer category is determined according to the following formula:
[0098]
[0099] Among them, l i r is the upper bound of the probability corresponding to the i-th customer category.k and r j These are the risk lengths corresponding to the k-th and j-th customer categories, respectively. f is a real-valued function with a value greater than 0 and a derivative of f less than 0.
[0100] S043, the customer's mobile terminal selects a random number generator, wherein the generator satisfies the value range [0,1] and conforms to a uniform distribution;
[0101] S044, When a customer's mobile terminal has a weak network signal during payment, a random number is generated according to the selected random number generator, and this random number is used as the random number corresponding to the payment.
[0102] S045, Select the minimum probability upper bound that is greater than the random number corresponding to the payment from the probability upper bound corresponding to the customer category corresponding to the customer;
[0103] S046, Select the real-time risk control method for the customer category corresponding to the minimum probability upper bound from the received real-time risk control methods, and perform risk control on the payment based on the selected real-time risk control method.
[0104] It should be noted that although the operation of the method of the present invention has been described in a specific order in the above embodiments and figures, this does not require or imply that the operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.
[0105] After introducing the method of exemplary embodiments of the present invention, the following references are made. Figure 6 An apparatus for controlling transaction risk in banks according to an exemplary embodiment of the present invention will be described.
[0106] The implementation of the bank's device for controlling transaction risk can refer to the implementation of the above method, and repeated details will not be elaborated further. The term "module" or "unit" used below can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.
[0107] Based on the same inventive concept, this invention also proposes a device for banks to control transaction risks, such as... Figure 6 As shown, the device includes:
[0108] The potential risk indicator determination module 610 is used to determine the potential risk indicators corresponding to the customer.
[0109] The secure small amount determination module 620 is used to determine the secure small amount corresponding to the customer based on the bank's payment transaction data and the customer's corresponding potential risk indicators;
[0110] The risk control module 630 is used to determine whether the payment amount is less than the customer's corresponding safe small amount if the network signal strength of the customer's mobile terminal is less than the signal strength threshold when the customer makes a payment; if it is less, the bank's mobile terminal APP supports the customer's payment.
[0111] In one embodiment, the potential risk indicator determination module is specifically used for:
[0112] Retrieve the payment threshold stored for this customer on the bank's server;
[0113] Based on the correspondence between payment thresholds and risk indicators pre-stored on the bank's server, and the payment thresholds stored for this customer on the bank's server, the potential risk indicators corresponding to the customer are determined.
[0114] In one embodiment, reference Figure 7 The device also includes: a correspondence determination module 640;
[0115] The module for determining the correspondence between payment thresholds and risk indicators is located on the bank's server and determines the correspondence between payment thresholds and risk indicators using the following method:
[0116] Obtain transaction data for various customer categories within the bank;
[0117] Based on the transaction data of each customer category, determine the probability of each customer category corresponding to each risk category;
[0118] Based on the probability of each customer category corresponding to each risk category, controllable customer categories are determined;
[0119] Based on transactions of controllable customer categories, determine the correspondence between payment thresholds and risk indicators.
[0120] In one embodiment, the correspondence determination module is specifically used for:
[0121] Based on the probabilities of each customer category to each risk category, a partial order of customer categories is determined. For any two customer categories, this partial order is used to determine whether the first customer category is superior to the second customer category. If for each risk category, the probability of the first customer category corresponding to that risk category is less than or equal to the probability of the second customer category corresponding to that risk category, then the first customer category is determined to be superior to the second customer category in the partial order of customer categories.
[0122] Based on the partial order of customer categories, the maximal element of that partial order is taken as the controllable customer category.
[0123] In one embodiment, the correspondence determination module is specifically used for:
[0124] Based on transactions of controllable customer categories, determine multiple discrete payment thresholds;
[0125] For each discrete payment threshold, determine the proportion of risky transactions in the transactions of controllable customer categories when the payment threshold is set to that discrete payment threshold, and determine that proportion as the risk indicator corresponding to that discrete payment threshold;
[0126] Based on multiple discrete payment thresholds and the corresponding risk indicators for each discrete payment threshold, the correspondence between payment thresholds and risk indicators is determined.
[0127] In one embodiment, the security small amount determination module is specifically used for:
[0128] Select the customer category to which the customer belongs from the bank's payment transaction data, and use the selected payment transaction data as the corresponding payment transaction data for that customer;
[0129] Based on the payment transaction amount contained in the customer's corresponding payment transaction data, multiple payment amount ranges are determined, wherein any two payment amount ranges do not intersect.
[0130] For each payment amount range, select the corresponding payment transaction data whose payment amount falls within that payment amount range from the customer's corresponding payment transaction data, and use the selected payment transaction data as the payment transaction data corresponding to that payment amount range;
[0131] Based on the payment transaction data corresponding to the payment amount range, determine the risk indicators and transaction volume indicators corresponding to the payment amount range;
[0132] Based on the risk indicators, transaction volume indicators, and potential risk indicators corresponding to the payment amount range, the corresponding safe small amount value for the customer is determined.
[0133] In one embodiment, the security small amount determination module is specifically used for:
[0134] The time range corresponding to the payment transaction data of the payment amount range is divided into multiple time sub-ranges, wherein any two time sub-ranges have the same time length;
[0135] The number of transactions contained in the payment transaction data corresponding to each time sub-range is used as the transaction volume sample corresponding to that payment amount range, and the proportion of risk-related transactions in the payment transaction data corresponding to each time sub-range is used as the risk sample corresponding to that payment amount range.
[0136] The risk indicator corresponding to the payment amount range is determined as the mean of the risk sample corresponding to the payment amount range, and the transaction volume indicator corresponding to the payment amount range is determined as the mean of the transaction volume sample corresponding to the payment amount range.
[0137] In one embodiment, the security small amount determination module is specifically used for:
[0138] Based on the risk indicators, transaction volume indicators, and potential risk indicators corresponding to the payment amount ranges, a partial order of payment amount ranges is determined. This partial order is used to determine whether the first payment amount range is superior to the second payment amount range among any two payment amount ranges. If the risk indicator corresponding to the first payment amount range is less than or equal to the risk indicator corresponding to the second payment amount range, and the transaction volume indicator corresponding to the first payment amount range is greater than or equal to the transaction volume indicator corresponding to the second payment amount range, and the risk indicator corresponding to the first payment amount range is less than or equal to the potential risk indicator corresponding to the customer, then the first payment amount range is determined to be superior to the second payment amount range in the partial order of payment amount ranges.
[0139] Based on the partial order of the payment amount range, the extreme value amount range is determined, where the extreme value amount range is the maximal element of the partial order;
[0140] Based on the extreme value range, determine the corresponding safe small amount for this customer.
[0141] In one embodiment, the security small amount determination module is specifically used for:
[0142] Select the rightmost extreme value range on the real number axis from the extreme value ranges;
[0143] Based on the selected extreme value range, determine the corresponding safe small amount for this customer.
[0144] It should be noted that although several modules of a bank's risk control device are mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the invention, the features and functions of two or more modules described above can be embodied in a single module. Conversely, the features and functions of a single module described above can be further divided and embodied by multiple modules.
[0145] Based on the aforementioned inventive concept, such as Figure 8 As shown, the present invention also proposes a computer device 800, including a memory 810, a processor 820, and a computer program 830 stored in the memory 810 and executable on the processor 820. When the processor 820 executes the computer program 830, it implements the aforementioned method for controlling transaction risks in banks.
[0146] 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 method for banks to control transaction risks.
[0147] Based on the aforementioned inventive concept, the present invention proposes a computer program product, which includes a computer program that, when executed by a processor, implements a method for banks to control transaction risks.
[0148] The method and apparatus for controlling transaction risks in banks proposed in this invention determine the potential risk indicators corresponding to customers; based on the bank's payment transaction data and the potential risk indicators corresponding to the customer, a safe small amount value is determined for the customer; when the customer makes a payment, if the network signal strength of the customer's mobile terminal is less than the signal strength threshold, it is determined whether the payment amount is less than the customer's safe small amount value; if it is less, the bank's APP on the mobile terminal supports the customer's payment. The overall solution can determine the customer's safe small amount value by analyzing payment transaction data and potential risk indicators, enabling customers to make small payments when the mobile terminal signal is weak. While effectively controlling customer transaction risks, it ensures the normal conduct of customer transactions, improves customer experience, and protects customer property security.
[0149] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can 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, etc.) containing computer-usable program code.
[0150] This 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 block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, 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, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0151] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0152] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0153] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.
Claims
1. A method for a bank to control transaction risk, characterized in that, include: Identify the potential risk indicators for each customer; Based on the bank's payment transaction data and the customer's corresponding potential risk indicators, determine the corresponding safe small amount value for the customer; When a customer makes a payment, if the network signal strength of the customer's mobile terminal is less than the signal strength threshold, it is determined whether the payment amount is less than the customer's corresponding safe small amount value; if it is less, the bank's mobile terminal app supports the customer's payment. Specifically, based on the bank's payment transaction data and the customer's corresponding potential risk indicators, the customer's corresponding safe small amount value is determined, including: Select the customer category to which the customer belongs from the bank's payment transaction data, and use the selected payment transaction data as the corresponding payment transaction data for the customer; Based on the payment transaction amount contained in the customer's corresponding payment transaction data, multiple payment amount ranges are determined, wherein any two payment amount ranges do not intersect. For each payment amount range, select the corresponding payment transaction data whose payment amount falls within that payment amount range from the customer's corresponding payment transaction data, and use the selected payment transaction data as the payment transaction data corresponding to that payment amount range; Based on the payment transaction data corresponding to the payment amount range, determine the risk indicators and transaction volume indicators corresponding to the payment amount range; Based on the risk indicators, transaction volume indicators, and potential risk indicators corresponding to the payment amount range, the corresponding safe small amount value for the customer is determined.
2. The method of claim 1, wherein, Identify the potential risk indicators for each customer, including: Retrieve the payment threshold stored for this customer on the bank's server; Based on the correspondence between payment thresholds and risk indicators pre-stored on the bank's server, and the payment thresholds stored for this customer on the bank's server, the potential risk indicators corresponding to the customer are determined.
3. The method of claim 2, wherein, The bank server determines the correspondence between payment thresholds and risk indicators using the following method: Obtain transaction data for various customer categories within the bank; Based on the transaction data of each customer category, determine the probability of each customer category corresponding to each risk category; Based on the probability of each customer category corresponding to each risk category, controllable customer categories are determined; Based on transactions of controllable customer categories, determine the correspondence between payment thresholds and risk indicators.
4. The method of claim 3, wherein, Based on the probability of each customer category corresponding to each risk category, controllable customer categories are determined, including: Based on the probabilities of each customer category to each risk category, a partial order of customer categories is determined. For any two customer categories, this partial order is used to determine whether the first customer category is superior to the second customer category. If for each risk category, the probability of the first customer category corresponding to that risk category is less than or equal to the probability of the second customer category corresponding to that risk category, then the first customer category is determined to be superior to the second customer category in the partial order of customer categories. Based on the partial order of customer categories, the maximal element of that partial order is taken as the controllable customer category.
5. The method of claim 3, wherein, Based on transactions from controllable customer categories, determine the correspondence between payment thresholds and risk indicators, including: Based on transactions of controllable customer categories, determine multiple discrete payment thresholds; For each discrete payment threshold, determine the proportion of risky transactions in the transactions of controllable customer categories when the payment threshold is set to that discrete payment threshold, and determine that proportion as the risk indicator corresponding to that discrete payment threshold; Based on multiple discrete payment thresholds and the corresponding risk indicators for each discrete payment threshold, the correspondence between payment thresholds and risk indicators is determined.
6. The method of claim 1, wherein, Based on the payment transaction data corresponding to this payment amount range, determine the risk indicators and transaction volume indicators corresponding to this payment amount range, including: The time range corresponding to the payment transaction data of the payment amount range is divided into multiple time sub-ranges, wherein any two time sub-ranges have the same time length; The number of transactions contained in the payment transaction data corresponding to each time sub-range is used as the transaction volume sample corresponding to that payment amount range, and the proportion of risk-related transactions in the payment transaction data corresponding to each time sub-range is used as the risk sample corresponding to that payment amount range. The risk indicator corresponding to the payment amount range is determined as the mean of the risk sample corresponding to the payment amount range, and the transaction volume indicator corresponding to the payment amount range is determined as the mean of the transaction volume sample corresponding to the payment amount range.
7. The method of claim 1, wherein, Based on the risk indicators, transaction volume indicators, and potential risk indicators corresponding to the payment amount range, a safe minimum value is determined for each customer, including: Based on the risk indicators, transaction volume indicators, and potential risk indicators corresponding to the payment amount ranges, a partial order of payment amount ranges is determined. This partial order is used to determine whether the first payment amount range is superior to the second payment amount range among any two payment amount ranges. If the risk indicator corresponding to the first payment amount range is less than or equal to the risk indicator corresponding to the second payment amount range, and the transaction volume indicator corresponding to the first payment amount range is greater than or equal to the transaction volume indicator corresponding to the second payment amount range, and the risk indicator corresponding to the first payment amount range is less than or equal to the potential risk indicator corresponding to the customer, then the first payment amount range is determined to be superior to the second payment amount range in the partial order of payment amount ranges. Based on the partial order of the payment amount range, the extreme value amount range is determined, where the extreme value amount range is the maximal element of the partial order; Based on the extreme value range, determine the corresponding safe small amount for this customer.
8. The method of claim 7, wherein, Based on the extreme value range, determine the corresponding safe small amount value for this customer, including: Select the rightmost extreme value range on the real number axis from the extreme value ranges; Based on the selected extreme value range, determine the corresponding safe small amount for this customer.
9. An apparatus for a bank to control transaction risk, characterized by include: The potential risk indicator identification module is used to identify the potential risk indicators corresponding to customers. The secure small amount determination module is used to determine the secure small amount for a customer based on the bank's payment transaction data and the customer's corresponding potential risk indicators. The risk control module is used to determine whether the payment amount is less than the customer's corresponding safe minimum amount if the network signal strength of the customer's mobile terminal is less than the signal strength threshold when the customer makes a payment; if it is less, the bank's mobile terminal APP supports the customer's payment. The secure small-amount value determination module is specifically used for: Select the customer category to which the customer belongs from the bank's payment transaction data, and use the selected payment transaction data as the corresponding payment transaction data for that customer; Based on the payment transaction amount contained in the customer's corresponding payment transaction data, multiple payment amount ranges are determined, wherein any two payment amount ranges do not intersect. For each payment amount range, select the corresponding payment transaction data whose payment amount falls within that payment amount range from the customer's corresponding payment transaction data, and use the selected payment transaction data as the payment transaction data corresponding to that payment amount range; Based on the payment transaction data corresponding to the payment amount range, determine the risk indicators and transaction volume indicators corresponding to the payment amount range; Based on the risk indicators, transaction volume indicators, and potential risk indicators corresponding to the payment amount range, the corresponding safe small amount value for the customer is determined.
10. The apparatus of claim 9, wherein, The potential risk indicator identification module is specifically used for: Retrieve the payment threshold stored for this customer on the bank's server; Based on the correspondence between payment thresholds and risk indicators pre-stored on the bank's server, and the payment thresholds stored for this customer on the bank's server, the potential risk indicators corresponding to the customer are determined.
11. The apparatus of claim 10, wherein, Also includes: Correspondence determination module; The module for determining the correspondence between payment thresholds and risk indicators is located on the bank's server and determines the correspondence between payment thresholds and risk indicators using the following method: Obtain transaction data for various customer categories within the bank; Based on the transaction data of each customer category, determine the probability of each customer category corresponding to each risk category; Based on the probability of each customer category corresponding to each risk category, controllable customer categories are determined; Based on transactions of controllable customer categories, determine the correspondence between payment thresholds and risk indicators.
12. The apparatus of claim 11, wherein, The correspondence determination module is specifically used for: Based on the probabilities of each customer category to each risk category, a partial order of customer categories is determined. For any two customer categories, this partial order is used to determine whether the first customer category is superior to the second customer category. If for each risk category, the probability of the first customer category corresponding to that risk category is less than or equal to the probability of the second customer category corresponding to that risk category, then the first customer category is determined to be superior to the second customer category in the partial order of customer categories. Based on the partial order of customer categories, the maximal element of that partial order is taken as the controllable customer category.
13. The apparatus of claim 11, wherein, The correspondence determination module is specifically used for: Based on transactions of controllable customer categories, determine multiple discrete payment thresholds; For each discrete payment threshold, determine the proportion of risky transactions in the transactions of controllable customer categories when the payment threshold is set to that discrete payment threshold, and determine that proportion as the risk indicator corresponding to that discrete payment threshold; Based on multiple discrete payment thresholds and the corresponding risk indicators for each discrete payment threshold, the correspondence between payment thresholds and risk indicators is determined.
14. The apparatus of claim 9, wherein, The secure small-amount value determination module is specifically used for: The time range corresponding to the payment transaction data of the payment amount range is divided into multiple time sub-ranges, wherein any two time sub-ranges have the same time length; The number of transactions contained in the payment transaction data corresponding to each time sub-range is used as the transaction volume sample corresponding to that payment amount range, and the proportion of risk-related transactions in the payment transaction data corresponding to each time sub-range is used as the risk sample corresponding to that payment amount range. The risk indicator corresponding to the payment amount range is determined as the mean of the risk sample corresponding to the payment amount range, and the transaction volume indicator corresponding to the payment amount range is determined as the mean of the transaction volume sample corresponding to the payment amount range.
15. The apparatus of claim 9, wherein, The secure small-amount value determination module is specifically used for: Based on the risk indicators, transaction volume indicators, and potential risk indicators corresponding to the payment amount ranges, a partial order of payment amount ranges is determined. This partial order is used to determine whether the first payment amount range is superior to the second payment amount range among any two payment amount ranges. If the risk indicator corresponding to the first payment amount range is less than or equal to the risk indicator corresponding to the second payment amount range, and the transaction volume indicator corresponding to the first payment amount range is greater than or equal to the transaction volume indicator corresponding to the second payment amount range, and the risk indicator corresponding to the first payment amount range is less than or equal to the potential risk indicator corresponding to the customer, then the first payment amount range is determined to be superior to the second payment amount range in the partial order of payment amount ranges. Based on the partial order of the payment amount range, the extreme value amount range is determined, where the extreme value amount range is the maximal element of the partial order; Based on the extreme value range, determine the corresponding safe small amount for this customer.
16. The apparatus of claim 15, wherein, The secure small-amount value determination module is specifically used for: Select the rightmost extreme value range on the real number axis from the extreme value ranges; Based on the selected extreme value range, determine the corresponding safe small amount for this customer.
17. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the computer program comprises computer program code configured to cause the processor to perform the method of any one of claims 1 to 16. When the processor executes the computer program, it implements the method of any one of claims 1 to 8.
18. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 8.
19. A computer program product, characterised in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 8.