Payment authority management method

Abstract

The invention discloses a payment authority management method, and the method comprises the steps: receiving a payment request from a target user, and obtaining an operation behavior corresponding to the payment request in a preset time period; determining a first monitoring strict degree corresponding to the operation behavior according to the operation behavior; determining a target risk level corresponding to the target user based on the operation behavior, the first monitoring strict degree and an initial risk level corresponding to the target user; and granting payment authority corresponding to the target risk level to the target user.

Description

Technical Field

[0001] The present application belongs to the field of computer technology, and in particular, relates to a payment authority management method. Background Art

[0002] In related technologies, in order to ensure the security of cloud payments, the payment system is usually combined with a zero-trust security model to perform discrete verification operations on the user's payment process. And by controlling its operating permissions, its authenticity and effectiveness are dynamically verified to increase payment security. However, due to the principle of least privilege in the zero-trust security model, when facing some relatively low-risk operations, user operations may be subject to unnecessary restrictions, but the user's payment permissions cannot be adjusted in real time, which affects the user's operating experience. Summary of the invention

[0003] The embodiment of the present application provides a payment authority management method, which can adjust the payment authority of a user in real time and dynamically.

[0004] In a first aspect, an embodiment of the present application provides a payment authority management method, the method comprising: receiving a payment request from a target user, and obtaining an operation behavior corresponding to the payment request within a preset time period; determining a first monitoring strictness corresponding to the operation behavior based on the operation behavior; determining a target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness and the initial risk level corresponding to the target user; and granting the target user payment authority corresponding to the target risk level.

[0005] In the second aspect, an embodiment of the present application provides a payment authority management device, which includes: a receiving module, used to receive a payment request from a target user, and obtain an operation behavior corresponding to the payment request within a preset time period; a first determination module, used to determine a first monitoring strictness corresponding to the operation behavior based on the operation behavior; a second determination module, used to determine a target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness and the initial risk level corresponding to the target user; a granting module, used to grant the target user payment authority corresponding to the target risk level. In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect.

[0006] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0007] In a fifth aspect, an embodiment of the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect.

[0008] In a sixth aspect, a computer program product is provided, the computer program product comprising at least one computer program, and when the computer program is loaded and executed by a processor, the method as described in the first aspect is implemented.

[0009] In an embodiment of the present application, by receiving a payment request from a target user and obtaining an operation behavior corresponding to the payment request within a preset time period, then determining a first monitoring strictness corresponding to the operation behavior based on the operation behavior, and determining a target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness and the initial risk level corresponding to the target user, and finally granting the target user a payment authority corresponding to the target risk level, the problem that the user's payment authority cannot be adjusted in real time in the related technology is solved, and real-time, dynamic and accurate assessment of the user's risk level and refined management of corresponding authorities of different risk levels are realized. Furthermore, granting corresponding payment authority based on the determined target risk level can effectively constrain user behavior and improve the security of payment request processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 This is a flow chart of a payment authority management method provided by an embodiment of the present application; Figure 2 It is a structural diagram of another payment authority management device provided in an embodiment of the present application; Figure 3 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0011] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0012] In the following, in conjunction with the accompanying drawings, a payment authority management method provided by an embodiment of the present application is described in detail through specific embodiments and application scenarios.

[0013] Figure 1 A payment authority management method provided by an embodiment of the present application is shown, and the method can be executed by an electronic device, and the electronic device can include: a server and / or a terminal device. In other words, the method can be executed by software or hardware installed in the electronic device, and the method includes the following steps: S110: receiving a payment request from a target user, and obtaining an operation behavior corresponding to the payment request within a preset time period.

[0014] The target user may refer to the account number or accounts currently performing transaction operations, such as a bank account, credit card account, electronic wallet account or other types of accounts, or other application accounts or web accounts with payment functions. The operation behavior refers to various operation records and interaction records corresponding to the payment request generated by the target user during the use of the system, platform or service.

[0015] S120: Determine, according to the operation behavior, a first monitoring strictness corresponding to the operation behavior.

[0016] Among them, the degree of strictness refers to rigor and strictness, and the monitoring strictness is used to measure the strictness of monitoring the operation behavior. That is to say, through the first monitoring strictness, it can reflect the rigor and strictness of monitoring the operation behavior of the target user, and then reflect the current risk level of the target user. Exemplarily, assuming that the target user has mortgaged assets within the preset time period, that is, the operation behavior includes the mortgage behavior, the first monitoring strictness corresponding to the behavior will increase, and the user's subsequent operation behavior will be more strictly dynamically monitored. Assuming that the target user has signed a commitment agreement within the preset time period, that is, the operation behavior includes the agreement signing behavior, the first monitoring strictness corresponding to the agreement signing behavior will be reduced, and the degree of monitoring of the user's subsequent operation behavior will be reduced.

[0017] S130: Determine a target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness, and the initial risk level corresponding to the target user.

[0018] It can be understood that a security assessment is performed on the target user based on the operation behavior, the first monitoring strictness and the initial risk level corresponding to the target user, and a target risk level corresponding to the target user is determined based on the security assessment result.

[0019] S140: Granting the target user a payment authority corresponding to the target risk level.

[0020] Optionally, the types of payment permissions may include but are not limited to financial transaction permissions, account management permissions, customer support permissions, and data access permissions. Exemplarily, the risk level of the user can be divided into 5 levels: risk level I, risk level II, risk level III, risk level IV, and risk level V. As shown in Table 1, the payment permissions corresponding to different risk levels.

[0021] Table 1

[0022] In an embodiment of the present application, by receiving a payment request from a target user and obtaining the operation behavior corresponding to the payment request within a preset time period, and then determining a first monitoring strictness corresponding to the operation behavior based on the operation behavior, and determining a target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness and the initial risk level corresponding to the target user, and finally granting the target user a payment authority corresponding to the target risk level, the problem that the user's payment authority cannot be adjusted in real time in the related technology is solved, and real-time, dynamic and accurate assessment of the user's risk level and refined management of authorities corresponding to different risk levels are achieved. Furthermore, granting corresponding payment authority based on the determined target risk level can effectively constrain user behavior and improve the security of payment request processing.

[0023] In one implementation, the operation behavior includes at least one of an agreement signing behavior and a mortgage behavior; before determining a first monitoring strictness corresponding to the operation behavior based on the operation behavior, the method also includes: when the operation behavior includes the agreement signing behavior, obtaining a first behavior score corresponding to the agreement signing behavior; when the operation behavior includes the mortgage behavior, obtaining a second behavior score corresponding to the mortgage behavior.

[0024] It can be understood that within the preset time period, the target user performed relevant operations to trade the business corresponding to the payment request, and the operation behavior corresponding to the relevant operation may include at least one of the agreement signing behavior and the mortgage behavior, wherein the agreement signing behavior refers to the signing of the relevant commitment agreement or other written or electronic documents with legal effect, and the mortgage behavior refers to the act of mortgaging assets.

[0025] In one implementation, the score of the first behavior is calculated based on the first constant, the second constant and the initial score corresponding to the agreement signing behavior. , where Z represents the score of the first behavior, a represents the first constant, b represents the second constant, and z represents the initial score corresponding to the agreement signing behavior. Optionally, the initial score corresponding to the agreement signing behavior can be determined according to the number of signed agreements.

[0026] In another implementation, the second behavior score is calculated based on the third constant, the fourth constant, and the initial score corresponding to the mortgage behavior. For example, , where Y represents the score of the second behavior, c represents the third constant, d represents the fourth constant, and y represents the initial score corresponding to the mortgage behavior. Optionally, the initial score corresponding to the mortgage behavior can be determined according to the value of the mortgaged assets.

[0027] In this implementation, by determining the behavior scores corresponding to different operation behaviors, the accuracy of user risk level assessment can be improved.

[0028] In one implementation, determining a first monitoring strictness corresponding to the operation behavior based on the operation behavior includes: determining the first monitoring strictness based on at least one of the first behavior score and the second behavior score, a second monitoring strictness, and a target time amount; wherein the second monitoring strictness is an initial monitoring strictness corresponding to the target user, and the target time amount represents a measure of the preset time period after a logarithmic transformation.

[0029] It can be understood that, when the operation behavior only includes the agreement signing behavior, the first monitoring strictness is determined based on the first behavior score, the second monitoring strictness and the target time; when the operation behavior only includes the mortgage behavior, the first monitoring strictness is determined based on the second behavior score, the second monitoring strictness and the target time; when the operation behavior includes the agreement signing behavior and the mortgage behavior, the first monitoring strictness is determined based on the first behavior score, the second behavior score, the second monitoring strictness and the target time.

[0030] Among them, regarding the target time amount, it can be understood that the target time amount is determined by performing a logarithmic transformation on the length of the preset time period. Exemplarily, the target time amount can be calculated by the following formula: , where T represents the target time amount, t represents the length of the preset time period, and n represents a constant.

[0031] In addition, the first monitoring strictness can be expressed by the following formula: ; in, Indicates the first level of monitoring severity, represents the second monitoring strictness, and the function g(Y, Z) is a function for adjusting the monitoring strictness based on the actual business needs, the second behavior score Y corresponding to the user's mortgage behavior, and the first behavior score Z corresponding to the agreement signing behavior; wherein, g(Y, Z) = f(Y, Z) * ​​T(t), the function f(Y, Z) is a function for adjusting the monitoring strictness based on the second behavior score Y corresponding to the user's mortgage behavior and the first behavior score Z corresponding to the agreement signing behavior, ; Function T(t) is a function that adjusts the strictness of monitoring according to time t, .

[0032] In this implementation, the dynamic monitoring strictness of user operation behavior, namely the first monitoring strictness W, is defined, which solves the problem that risk assessment can only be performed statically in related technologies. At the same time, through logarithmic transformation, the impact of monitoring time, namely the preset time period, on risk level assessment becomes smoother, which can reduce the impact of extreme values ​​and make the assessment process more stable.

[0033] In one implementation, before determining the target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness and the initial risk level corresponding to the target user, the method also includes: acquiring basic information corresponding to the target user; determining a preset risk level corresponding to the target user based on the basic information; adjusting the preset risk level based on at least one of the first behavior score and the second behavior score; and determining the adjusted preset risk level as the initial risk level.

[0034] Among them, the basic information includes age, gender, purchase history, etc. By obtaining and analyzing this information, the user's preset risk level can be preliminarily determined, and then the user's operating behavior within the preset time period can be monitored. The preset risk level can be dynamically adjusted based on the operating behavior to determine the initial risk level.

[0035] In this implementation, since the basic information is predetermined and stable, but the operational behavior can reflect the current risk status, dynamic adjustment of the preset risk level based on the score corresponding to the operational behavior can improve the accuracy of risk assessment.

[0036] In one implementation, after determining the preset risk level corresponding to the target user based on the basic information, the method further includes: in the case where the target user has not performed any agreement signing behavior or mortgage behavior, determining the preset risk level as the initial risk level.

[0037] It is understandable that if the user does not perform any operational behavior that affects the risk level within the preset time period, there is no need to adjust the preset risk level.

[0038] The present application also provides two methods for determining the target risk level: (1) In one implementation, determining a target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness, and the initial risk level corresponding to the target user includes: if the payment request is a first request within the preset time period, dynamically adjusting the initial risk level based on at least one of the first behavior score and the second behavior score and the first monitoring strictness; and determining the dynamically adjusted initial risk level as the target risk level.

[0039] (2) In one implementation, the target risk level corresponding to the target user is determined based on the operation behavior, the first monitoring strictness and the initial risk level corresponding to the target user, including: if the payment request is not the first request within the preset time period, the initial risk level is dynamically adjusted according to at least one of the first behavior score and the second behavior score, the first monitoring strictness and the number of payment failures; wherein the number of payment failures is the number of payment failures in all payment requests corresponding to the target user within the preset time period.

[0040] It is understandable that, if the payment request is the first request within the preset time period, then there is no payment record within the preset time period, so it is only necessary to determine the target risk level based on at least one of the first behavior score and the second behavior score and the first monitoring strictness. In addition, if the payment request is not the first request within the preset time period, then there is a payment record within the preset time period, so it is also necessary to introduce the number of payment failures to determine the target risk level. In other words, if the user has a record of payment failures within the preset time period, there may be security risks. If there are multiple records of payment failures, there may be fraud. For example, an attacker may try to use stolen credit card information for payment, but the payment fails because other information such as the password is incorrect. Therefore, it is necessary to introduce the number of payment failures to increase the risk level of the target user to limit the user's operating authority, thereby improving the security of payment.

[0041] Optionally, the target risk level may be determined by the following formula: C = B + K (Y, Z, W) Among them, C represents the score corresponding to the target risk level, B represents the score corresponding to the initial risk level, and the function K (Y, Z, W) is a function that adjusts the risk level according to user behavior. Among them, the function K (Y, Z, W) can be expressed as:

[0042] Among them, Z represents the first behavior score, Y represents the second behavior score, Q represents the total asset score, that is, the score corresponding to the overall assets of the target user, r1 represents the fifth constant, which is used to adjust the base of the logarithmic function, r2 represents the sixth constant, which is used to adjust the size of p, W represents the first monitoring strictness, and P represents the number of payment failures.

[0043] It should be noted that, when the operation behavior only includes the agreement signing behavior, Z is set to 0; when the operation behavior only includes the mortgage behavior, Y is set to 0; when the payment request is the first request, P is set to 0.

[0044] In one implementation, determining a preset risk level corresponding to the target user based on the basic information includes: determining a score corresponding to the basic information according to the level corresponding to the basic information; and determining the preset risk level according to the score corresponding to the basic information.

[0045] Optionally, before determining the score corresponding to the basic information according to the level interval corresponding to the basic information, the method further includes: classifying the basic information according to the attributes corresponding to the basic information, and determining the score corresponding to each level.

[0046] Exemplarily, assuming that the basic information includes age, payment habits and place of residence, each basic information is divided according to the corresponding attributes, for example: the age is divided according to different age groups, such as 0-18 years old, 18-24 years old, 25-34 years old, 35-44 years old, 45-54 years old, 55 years old and above, etc. Based on big data analysis, it can be seen that people aged 45-54 have the highest payment ability and trustworthiness, and people aged 0-18 have the lowest payment ability and trustworthiness, as shown in Table 2, which shows the scores corresponding to each level interval.

[0047]

[0048] For payment habits, they can be divided according to consumption scores. For example, the ratio of the number of items in the shopping cart to the number of completed orders is used as the consumption score, where the larger the ratio is, the lower the consumption score is, and vice versa. In addition, the ratio of the total amount of items in the shopping cart to the total amount of completed orders can be used as the consumption score, where the larger the ratio is, the lower the consumption score is, and vice versa.

[0049] For the place of residence, it can be divided according to the attributes of city, town, village, etc., or according to different countries and regions. For example, economically developed areas have higher payment ability and their corresponding scores are lower.

[0050] In addition, for each basic information, its relevance can be considered. For example, the place of residence and age may affect the user's ability to pay and ability to keep their promises, and there may be mutual influence between these two factors. Therefore, a multiple linear regression model can be used for correction. For example, the multiple linear regression model can be expressed as: ; Among them, the value of g(X) can reflect the user's risk level, that is, the preset risk level, gn represents basic information, such as age, payment habits, and place of residence, and β1,...,βn are regression coefficients. Through multiple linear regression analysis, the degree and direction of the influence of each user factor on the user's risk level are obtained.

[0051] In this implementation, the basic information is graded to determine the preset risk level corresponding to the target user, thereby effectively improving the accuracy of risk assessment.

[0052] In one implementation, the preset risk level is adjusted based on at least one of the first behavior score and the second behavior score, including: obtaining the total asset score corresponding to the target user; dynamically adjusting the initial risk level according to the total asset score, at least one of the first behavior score and the second behavior score, and the weight corresponding to each of the behavior scores.

[0053] It is understandable that since the basic information is predetermined and stable, but the operational behavior can reflect the current risk situation, dynamic adjustment of the preset risk level based on the score corresponding to the operational behavior can improve the accuracy of risk assessment.

[0054] For example, the initial risk level can be expressed by the following formula: ; Among them, the function is a function for adjusting the risk level based on the mortgage behavior Y and the agreement signing behavior Z. α and β represent the effects of the mortgage behavior Y and the agreement signing behavior Z on the function For example, the weight of the mortgage behavior Y is set to 0.7, the weight of the agreement signing behavior Z is set to 0.3, and the overall asset correction of the user is introduced, then:

[0055] in, Represents the total asset score, that is, the score corresponding to the overall assets of the target user. Indicates that the second line is a fraction, Indicates the first behavior as a score. Optionally, the mortgaged assets, as actual carriers, have a greater trust basis than the commitment agreement, so a greater weight can be given to the mortgage behavior.

[0056] In one implementation, after determining the target risk level corresponding to the target user, the method further includes: acquiring a transaction status corresponding to the target user within a preset time period; and dynamically updating the target risk level based on the transaction status.

[0057] It is understandable that in addition to monitoring the target user's operation behavior, the target user's transaction status can also be monitored to improve the accuracy and reliability of risk level assessment. Optionally, the transaction status can include: number of login failures, abnormal transaction patterns, geographic location changes, etc.

[0058] Optionally, after determining the target risk level corresponding to the target user, the method further includes: receiving a user's appeal request, the appeal request being used to request a change in the user's risk level. That is, the user may be allowed to appeal the current risk level, and the user's risk level may be reduced or temporarily increased by providing additional information or supporting documents.

[0059] Figure 2 A schematic diagram showing the structure of a payment authority management device provided by an embodiment of the present application is shown as follows: Figure 2 As shown, the payment authority management device 200 may include: a receiving module 210 , a first determining module 220 , a second determining module 230 and a granting module 240 .

[0060] In this embodiment, a receiving module 210 is used to receive a payment request from a target user and obtain an operation behavior corresponding to the payment request within a preset time period; a first determination module 220 is used to determine a first monitoring strictness corresponding to the operation behavior based on the operation behavior; a second determination module 230 is used to determine a target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness and the initial risk level corresponding to the target user; and a granting module 240 is used to grant the target user payment authority corresponding to the target risk level.

[0061] In one implementation, the operation behavior includes at least one of an agreement signing behavior and a mortgage behavior; the payment authority management device also includes: a first acquisition module, used to obtain a first behavior score corresponding to the agreement signing behavior when the operation behavior includes the agreement signing behavior; a second acquisition module, used to obtain a second behavior score corresponding to the mortgage behavior when the operation behavior includes the mortgage behavior.

[0062] In one implementation, the first determination module 220 is specifically used to determine the first monitoring strictness based on at least one of the first behavior score and the second behavior score, a second monitoring strictness and a target time amount; wherein the second monitoring strictness is an initial monitoring strictness corresponding to the target user, and the target time amount represents a measure of the preset time period after logarithmic transformation.

[0063] In one implementation, the payment authority management device also includes: a third acquisition module, used to acquire basic information corresponding to the target user; a third determination module, used to determine the preset risk level corresponding to the target user based on the basic information; an adjustment module, used to adjust the preset risk level based on at least one of the first behavior score and the second behavior score; and a fourth determination module, used to determine the adjusted preset risk level as the initial risk level.

[0064] In one implementation, the payment authority management device further includes: a fifth determination module, configured to determine the preset risk level as the initial risk level when the target user has no agreement signing behavior and no mortgage behavior.

[0065] In one implementation, the second determination module 230 is specifically used to: when the payment request is the first request within the preset time period, dynamically adjust the initial risk level according to at least one of the first behavior score and the second behavior score and the first monitoring strictness; and determine the dynamically adjusted initial risk level as the target risk level.

[0066] In one implementation, the second determination module 230 is specifically used to: within the preset time period, if the payment request is not the first request, dynamically adjust the initial risk level based on at least one of the first behavior score and the second behavior score, the first monitoring strictness, and the number of payment failures; wherein the number of payment failures is the number of payment failures in all payment requests corresponding to the target user within the preset time period.

[0067] In one implementation, the third determination module is specifically used to: determine the score corresponding to the basic information according to the level corresponding to the basic information; and determine the preset risk level according to the score corresponding to the basic information.

[0068] In one implementation, the adjustment module is specifically used to: obtain the asset score corresponding to the target user; and dynamically adjust the initial risk level according to the asset score, at least one behavior score among the first behavior score and the second behavior score, and the weight corresponding to each of the behavior scores.

[0069] In one implementation, the payment authority management device further includes an updating module, which is used to: obtain a transaction status corresponding to the target user within a preset time period; and dynamically update the target risk level based on the transaction status.

[0070] A payment authority management device provided in an embodiment of the present application can implement each process implemented in the payment authority management method embodiment, and will not be described again here to avoid repetition.

[0071] The payment authority management device in the embodiment of the present application may be a device, or a component, an integrated circuit, or a chip in an electronic device. The embodiment of the present application is not specifically limited.

[0072] The payment authority management device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0073] Optional, such as Figure 3As shown, an embodiment of the present application also provides an electronic device 300, including a processor 310, a memory 320, and a program or instruction stored in the memory 320 and executable on the processor 310. When the program or instruction is executed by the processor 310, each process of the above-mentioned payment authority management method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0074] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned payment authority management method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0075] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0076] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned payment authority management method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0077] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0078] The embodiment of the present application also provides a computer program product, which includes at least one computer program. When the computer program is loaded and executed by a processor, it implements the various processes of the above-mentioned payment authority management method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0079] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0080] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0081] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A payment authority management method, characterized in that: The method comprises: Receive a payment request from a target user, and obtain an operation behavior corresponding to the payment request within a preset time period; Determining, according to the operation behavior, a first monitoring strictness corresponding to the operation behavior; Determining a target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness, and an initial risk level corresponding to the target user; The target user is granted payment authority corresponding to the target risk level.

2. The method according to claim 1, characterized in that The operation behavior includes at least one of the following: agreement signing behavior and mortgage behavior; Before determining, according to the operation behavior, a first monitoring strictness corresponding to the operation behavior, the method further includes: In a case where the operation behavior includes the agreement signing behavior, obtaining a first behavior score corresponding to the agreement signing behavior; In a case where the operation behavior includes the mortgage behavior, a second behavior score corresponding to the mortgage behavior is acquired.

3. The method according to claim 2, characterized in that The determining, according to the operation behavior, a first monitoring strictness corresponding to the operation behavior includes: determining the first monitoring severity based on at least one of the first behavior score and the second behavior score, a second monitoring severity, and a target amount of time; The second monitoring strictness is an initial monitoring strictness corresponding to the target user, and the target time quantity represents a measure of the preset time period after logarithmic transformation.

4. The method according to claim 2, characterized in that: Before determining the target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness and the initial risk level corresponding to the target user, the method further includes: Acquire basic information corresponding to the target user; Based on the basic information, determining a preset risk level corresponding to the target user; adjusting the preset risk level based on at least one of the first behavior score and the second behavior score; The adjusted preset risk level is determined as the initial risk level.

5. The method according to claim 4, characterized in that After determining the preset risk level corresponding to the target user based on the basic information, the method further includes: In the case that the target user does not have the agreement signing behavior and the mortgage behavior, the preset risk level is determined as the initial risk level.

6. The method according to claim 4 or 5, characterized in that: The determining, based on the operation behavior, the first monitoring strictness, and the initial risk level corresponding to the target user, a target risk level corresponding to the target user includes: Within the preset time period, if the payment request is a first request, dynamically adjusting the initial risk level according to at least one of the first behavior score and the second behavior score and the first monitoring strictness; The dynamically adjusted initial risk level is determined as the target risk level.

7. The method according to claim 4 or 5, characterized in that: The determining, based on the operation behavior, the first monitoring strictness, and the initial risk level corresponding to the target user, a target risk level corresponding to the target user includes: Within the preset time period, if the payment request is not the first request, the initial risk level is dynamically adjusted based on at least one of the first behavior score and the second behavior score, the first monitoring strictness and the number of payment failures; wherein the number of payment failures is the number of payment failures in all payment requests corresponding to the target user within the preset time period.

8. The method according to claim 4, characterized in that The determining, based on the basic information, a preset risk level corresponding to the target user includes: Determining a score corresponding to the basic information according to the level corresponding to the basic information; The preset risk level is determined according to the score corresponding to the basic information.

9. The method according to claim 4, characterized in that The adjusting the preset risk level based on at least one of the first behavior score and the second behavior score includes: Obtaining the total asset score corresponding to the target user; The initial risk level is dynamically adjusted according to the total asset score, at least one behavior score among the first behavior score and the second behavior score, and a weight corresponding to each of the behavior scores.

10. The method according to claim 1, characterized in that After determining the target risk level corresponding to the target user, the method further includes: Acquire the transaction status corresponding to the target user within the preset time period; The target risk level is dynamically updated based on the transaction status.

11. A payment authority management device, characterized in that: include: A receiving module, used to receive a payment request from a target user and obtain an operation behavior corresponding to the payment request within a preset time period; A first determination module, configured to determine, according to the operation behavior, a first monitoring strictness corresponding to the operation behavior; a second determination module, configured to determine a target risk level corresponding to the target user based on the operation behavior, the first monitoring strictness, and an initial risk level corresponding to the target user; The granting module is used to grant the target user a payment authority corresponding to the target risk level.

12. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein when the program or instruction is executed by the processor, the steps of the payment authority management method as described in any one of claims 1 to 10 are implemented.

13. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the payment authority management method according to any one of claims 1 to 10 are implemented.

14. A computer program product, characterized in that The computer program product includes program instructions, and when the program instructions are executed by a computer, the computer implements the steps of the payment authority management method according to any one of claims 1 to 10.

Images