User identification method and device, equipment, storage medium and product

Abstract

The invention discloses a user identification method and apparatus, a device, a storage medium and a product. The method comprises the steps of determining an extended number library according to user information and a preset identification rule; determining call range information of each user number in an extended number library; according to the call range information, risk levels of user numbers in an extended number library are determined, extended number information is obtained, and the extended number information comprises the risk levels of the user numbers in the extended number library; and when a service handling request is received, determining a target risk level of a target user corresponding to the service handling request according to the extended number information. The extended number library is determined according to the preset identification rule, the extended number information is determined according to the call range of the user numbers in the extended number library, and the risk level of the target user is determined according to the risk information of each number in the extended number information. Compared with an existing mode of identifying the risk level of the user according to the material submitted by the user, the method can improve the accuracy of user identification.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to user identification methods, devices, equipment, storage media and products. Background Art

[0002] In recent years, malicious complaint agents have been formed against banks, payment companies, consumer finance companies, insurance companies and other institutions (hereinafter referred to as financial institutions). Order taking, contract signing, "rights protection", profit sharing, gang operations, and clear division of labor. Financial institutions are overwhelmed by this. On the one hand, there are more and more malicious complaints, and on the other hand, there is indeed regulatory assessment pressure within the institutions. The ultimate goal of malicious complaints is to maliciously evade debts. These debt evasion behaviors in the financial field have caused the non-performing loan rate in the financial industry to continue to rise, causing the risks of some small and medium-sized financial institutions and financial institutions to continue to accumulate. Malicious debt evasion seriously damages the interests of lenders, disrupts the order of the financial market, and aggravates the spread of financial risks. The identification of malicious debt evasion has become more and more urgent. However, the existing user risk identification is based on the identification of materials submitted by users, and the identification efficiency is not high. Summary of the invention

[0003] The main purpose of this application is to provide a user identification method, device, equipment, storage medium and product, aiming to solve the technical problem of low efficiency of existing user risk identification.

[0004] To achieve the above objectives, the present application proposes a user identification method, which includes:

[0005] Obtaining user information, and determining an extended number library according to the user information and a preset identification rule;

[0006] Determine the call range information of each user number in the extended number library;

[0007] Determine the risk level of the user number in the extended number library according to the call range information, and obtain extended number information, wherein the extended number information includes the risk level of each user number in the extended number library;

[0008] When a service processing request is received, the target risk level of the target user corresponding to the service processing request is determined according to the extended number information.

[0009] Optionally, the step of determining an extended number library according to the user information and a preset identification rule includes:

[0010] Determine a first number database according to the user information and a preset identification rule;

[0011] Determine, based on the user information, an extended number for communicating with the number in the first number database;

[0012] An extended number library is constructed based on the extended number and the first number library.

[0013] Optionally, the step of determining the first number database according to the user information and a preset identification rule includes:

[0014] Determine the first call number between each user in the user information and the first call object;

[0015] determining a first user according to the first number of calls;

[0016] Determine the number of second calls made by the first user with the second call partner;

[0017] determining a second user according to the second number of calls;

[0018] Determine the target program usage flow information of the second user;

[0019] A third user is determined according to the target program usage traffic information and the second user, and a first number database is constructed based on the third user.

[0020] Optionally, the call range information includes a call quantity range and a call geographical range;

[0021] The step of determining the risk level of the user number in the extended number database according to the call range information to obtain the extended number information includes:

[0022] Determine first risk information of the user number in the extended number library according to the call quantity range;

[0023] Determining second risk information of the user number according to the call geographical range;

[0024] The risk level of the user number is determined according to the first risk information and the second risk information, and extended number information is obtained.

[0025] Optionally, when receiving a service processing request, the step of determining a target risk level of a target user corresponding to the service processing request according to the extended number information includes:

[0026] When receiving a service processing request, determining a target number of a target user according to the service processing request;

[0027] Determining whether the target number matches the extended number information;

[0028] If the target number matches the extended number information, determining the target risk level of the target user according to the extended number information and the target number;

[0029] If the target number does not match the extended number information, determining call information between the target number and the extended number in the extended number information;

[0030] A target risk level of the target user is determined according to the call information.

[0031] Optionally, after the step of determining the target risk level of the target user corresponding to the service processing request according to the extended number information when receiving the service processing request, the method further includes:

[0032] determining a response strategy based on the target risk level;

[0033] The service processing request is responded to based on the response strategy.

[0034] In addition, to achieve the above-mentioned purpose, the present application also proposes a user identification device, the user identification device comprising:

[0035] An acquisition module, used to acquire user information and determine an extended number library according to the user information and a preset identification rule;

[0036] A call range determination module, used to determine the call range information of each user number in the extended number library;

[0037] A risk level confirmation module, configured to determine the risk level of the user number in the extended number library according to the call range information, and obtain extended number information, wherein the extended number information includes the risk level of each user number in the extended number library;

[0038] The user identification module is used to determine the target risk level of the target user corresponding to the service processing request according to the extended number information when receiving the service processing request.

[0039] In addition, to achieve the above objectives, the present application also proposes a user identification device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the user identification method described above.

[0040] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the user identification method described above are implemented.

[0041] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the user identification method described above are implemented.

[0042] The present application obtains user information, determines an extended number library according to the user information and preset identification rules; determines the call range information of each user number in the extended number library; determines the risk level of the user number in the extended number library according to the call range information, and obtains extended number information, wherein the extended number information includes the risk level of each user number in the extended number library; upon receiving a service processing request, determines the target risk level of the target user corresponding to the service processing request according to the extended number information. Since the present application determines the extended number library according to preset identification rules, determines the extended number information according to the call range of the user number in the extended number library, and determines the risk level of the target user according to the risk information of each number in the extended number information, compared with the existing method of identifying the risk level of the user according to the materials submitted by the user, the above method of the present application can improve the accuracy of user identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0045] Figure 1 A flowchart of the first embodiment of the user identification method of the present application is provided;

[0046] Figure 2 A flowchart of the second embodiment of the user identification method of the present application is provided;

[0047] Figure 3 A call association diagram provided for the second embodiment of the user identification method of the present application;

[0048] Figure 4 This is a schematic diagram of the module structure of a user identification device according to an embodiment of the present application;

[0049] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the user identification method in the embodiment of the present application.

[0050] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0052] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0053] The main solution of the embodiment of the present application is: obtaining user information, determining an extended number library according to the user information and preset identification rules; determining the call range information of each user number in the extended number library; determining the risk level of the user number in the extended number library according to the call range information, and obtaining extended number information, wherein the extended number information includes the risk level of each user number in the extended number library; upon receiving a service processing request, determining the target risk level of the target user corresponding to the service processing request according to the extended number information.

[0054] Since the present application determines the extended number library according to preset identification rules, determines the extended number information according to the call range of the user number in the extended number library, and determines the risk level of the target user according to the risk information of each number in the extended number information, compared with the existing method of identifying the user's risk level based on the materials submitted by the user, the above method of the present application can improve the accuracy of user identification.

[0055] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a user identification device, etc. The following takes the user identification device as an example to illustrate this embodiment and the following embodiments.

[0056] Based on this, the present application embodiment provides a user identification method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the user identification method of the present application.

[0057] In this embodiment, the user identification method includes steps S10 to S40:

[0058] Step S10, obtaining user information, and determining an extended number library according to the user information and a preset identification rule;

[0059] It should be noted that the user information may be the call record information and traffic usage information of each user obtained from the operator database, and the traffic usage information may include the traffic usage information of each application installed on the user terminal. The preset identification rule may be a pre-set identification rule for identifying users with higher risks in user information. For example, the number of calls with a pre-set target call object is greater than a preset threshold. The extended number library contains the number information and call records of users who have been identified to have malicious behavior. The target call object may be a financial consumer protection agency, a financial regulatory agency, etc.

[0060] Step S20, determining the call range information of each user number in the extended number library;

[0061] It should be noted that the call range information may include call information between each user number in the extended number library and other users in the user information, and may include the call quantity range and the call geographical range. The call quantity range may be the number of users who have calls with the user numbers in the extended number library and the users in the user information. For example, there are 100 users in the user information, user number 1 in the extended number library has calls with 90 users in the user information, and user number 2 in the extended number library has calls with 80 users in the user information. Then the call quantity ranges of user number 1 and user number 2 are 90 and 80 respectively. The 90 users who have calls with user number 1 involve users in 30 urban areas, and the 80 users who have calls with user number 2 involve users in 10 urban areas, so the call geographical ranges of user number 1 and user number 2 are 30 and 10 respectively.

[0062] Step S30, determining the risk level of the user number in the extended number library according to the call range information, and obtaining extended number information, wherein the extended number information includes the risk level of each user number in the extended number library;

[0063] It should be noted that the determination of the risk level of the user number in the extended number library according to the call range information and the acquisition of the extended number information may be to determine whether the user number in the extended number library meets the first risk condition according to the call quantity range in the call range information, determine whether the user number in the extended number library meets the second risk condition according to the call geographic range in the call range information, determine the risk level of the user number according to whether the user number in the extended number library meets the first risk condition and / or the second risk condition, and generate the extended number information according to the user number and the risk level corresponding to the user number. The first risk condition and the second risk condition may be pre-set judgment conditions, for example, the first risk condition is that the number of call users is greater than 100, and the second risk condition is that the number of cities where the call users are located is greater than 10.

[0064] Step S40: upon receiving a service processing request, determining a target risk level of a target user corresponding to the service processing request according to the extended number information.

[0065] It should be noted that the business processing request may be a loan application request or an online complaint request from the target user, which includes the target user's phone number and identity information. The target risk level of the target user corresponding to the business processing request according to the extended number information may be determined by querying the extended number information according to the target user's phone number, and determining the risk level corresponding to the target user's phone number in the extended number information, which is the target risk level of the target user. Considering that the same mobile phone number may be applied for by multiple different users in succession, in order to improve the recognition accuracy, this embodiment obtains the target user's identity identification while obtaining the target user's mobile phone number, for example, the target user's ID number, the target user's face image, the target user's fingerprint image, the target user's iris image and other information that uniquely identifies the target user's identity, and matches the extended number information according to the phone number and identity identification to obtain the target risk level of the target user.

[0066] Further, in order to accurately determine the risk level of the target user, the step S40 may include: upon receiving a service processing request, determining a target number of the target user according to the service processing request;

[0067] Determining whether the target number matches the extended number information;

[0068] If the target number matches the extended number information, determining the target risk level of the target user according to the extended number information and the target number;

[0069] If the target number does not match the extended number information, determining call information between the target number and the extended number in the extended number information;

[0070] A target risk level of the target user is determined according to the call information.

[0071] It should be noted that determining the call information between the target number and the extended number in the extended number information may be determining the call information between the target number and the extended number in the extended number information within a preset time period, and the preset time period may be a preset time period such as one year or one month. The call information includes the number of calls between the target number and the extended numbers of each risk level in the extended number information. For example, the risk weight value of the extended number in the extended number information may include: 1.5, 1, 0.5, and the corresponding risk level may include three risk levels: "high risk", "medium risk", and "low risk". The call information includes the number of calls between the target number and the extended number of the high risk level in the extended number information, the number of calls with the extended number of the medium risk level, and the number of calls with the extended number of the low risk level. Determining the target risk level of the target user according to the call information may be calculating the risk value of the target user according to the number of calls with the extended users of each risk level in the call information and the corresponding weights, and determining the target risk level of the target user according to the calculated risk value. Specifically, first, determine a=the sum of the number of calls made between the target user's number and all the numbers with a "high" level in the extended number library in the past 12 months; secondly, determine β=the sum of the number of calls made between the target user's number and all the numbers with a "medium" level in the extended number library in the past 12 months; thirdly, determine γ=the sum of the number of calls made between the target user's number and all the numbers with a "low" level in the extended number library in the past 12 months; finally, calculate the risk value of the target user: T=a*1.5+β*1+γ*0.5. It can be set as follows: when 0≤T≤3, the risk level of the target user is determined to be no risk; when 3<T≤6, the risk level of the target user is determined to be low risk; when 6<T≤10, the risk level of the target user is determined to be medium risk; when T>10, the risk level of the target user is determined to be high risk.

[0072] Furthermore, in order to prevent users from evading debt, after step S40, the method may include: determining a response strategy according to the target risk level;

[0073] The service processing request is responded to based on the response strategy.

[0074] It should be noted that the response strategy can refer to the following Table 1-Response Strategy Table:

[0075] Table 1 - Response strategy table

[0076]

[0077] This embodiment can achieve that when identifying a user, regardless of whether the user exists in the extended number database, the user's risk level can be determined based on the call data between the user's number and the numbers of each risk level in the extended number database, without the need to collect excessive additional behavioral data of the user. The risk level of each user in the extended number database that is determined not only takes into account the malicious complaint behavior of the user himself, but also takes into account the malicious complaint behavior of suspected intermediary users. When identifying malicious debt evasion users, the risk level is determined based on the relationship between the user and the numbers of each risk level in the extended number database or the call data, thereby avoiding the problem that when some users entrust intermediaries to make malicious complaints, such users themselves cannot be identified as malicious debt evasion users.

[0078] This embodiment obtains user information, determines an extended number library according to the user information and preset identification rules; determines the call range information of each user number in the extended number library; determines the risk level of the user number in the extended number library according to the call range information, and obtains extended number information, wherein the extended number information includes the risk level of each user number in the extended number library; upon receiving a service processing request, determines the target risk level of the target user corresponding to the service processing request according to the extended number information. Since this embodiment determines the extended number library according to preset identification rules, determines the extended number information according to the call range of the user number in the extended number library, and determines the risk level of the target user according to the risk information of each number in the extended number information, compared with the existing method of identifying the risk level of the user according to the materials submitted by the user, the above method of this embodiment can improve the accuracy of user identification.

[0079] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , Figure 2 The flowchart of the second embodiment of the user identification method of the present application is provided, wherein the step S10 further includes the following steps:

[0080] Step S101: determining a first number database according to the user information and a preset identification rule;

[0081] It should be noted that the preset identification rule may be a pre-set identification rule for identifying users with higher risks in user information. It may be a rule such as making a call with a target call object, the number of call objects being greater than a preset threshold, etc. A first number database is constructed based on user information corresponding to user numbers that meet the preset identification rule.

[0082] Further, in order to accurately identify the risk level of the user, the step S101 may include: determining the first call number of calls between each user and the first call object in the user information;

[0083] determining a first user according to the first number of calls;

[0084] Determine the number of second calls made by the first user with the second call partner;

[0085] determining a second user according to the second number of calls;

[0086] Determine the target program usage flow information of the second user;

[0087] A third user is determined according to the target program usage traffic information and the second user, and a first number database is constructed based on the third user.

[0088] It should be noted that the first call object may be a financial consumer protection institution. The second call object may be a financial banking supervision institution, and the target program may be a financial consumer protection and banking supervision application. The third user is determined based on the traffic usage information of the target program and the second user, and the first number database is constructed based on the third user, which may be to determine that the user whose traffic size in the traffic usage information of the target program is greater than a preset traffic threshold is the third user. The first number database includes the telephone number and user identity information corresponding to the third user.

[0089] Specifically, the first number database can be obtained by screening according to the identification rules of three dimensions in sequence. Among them, the identification rules of the first dimension are used to screen the numbers whose first call times with the first type of call object in the historical call records in the past year reach the set first preset threshold, and the first type of call object may include financial consumer protection institutions. The identification rules of the second dimension are used to screen out the numbers whose second call times with the second type of call object in the historical call records in the past year reach the set second preset threshold from the screening results of the identification rules of the first dimension, and the second type of call object may include financial banking supervision institutions. The identification rules of the third dimension are used to screen out the numbers whose traffic consumption of the specified APP in the historical time period reaches the set third preset threshold from the screening results of the identification rules of the second dimension, and the specified APP includes financial consumer protection and banking supervision APPs.

[0090] In a specific implementation, the first type of call object specified in the identification rule of the first dimension is determined, and the number of first calls between the user and the first type of call object in the historical call records within the historical time period is counted, and the number of the first call counts reaching the set first preset threshold is screened out as the screening result of the identification rule of the first dimension. The first type of call object may be a financial consumer protection institution. In the screening result of the identification rule of the first dimension, the second type of call object specified in the identification rule of the second dimension is determined, and the number of second calls between the user and the second type of call object in the historical call records within the historical time period is counted, and the number of the second call counts reaching the set second preset threshold is screened out as the screening result of the identification rule of the second dimension. The second type of call object may be a financial banking supervision institution. In the screening result of the identification rule of the second dimension, the number of the traffic consumed by the designated APP of the user within the historical time period reaches the set third preset threshold is determined as the screening result of the identification rule of the third dimension, and the number in the screening result of the identification rule of the third dimension is added to the first number database. The designated APP may be a complaint platform.

[0091] Step S102: determining an extended number for communicating with a number in the first number database based on the user information;

[0092] It should be noted that the extended number determined based on the user information for communicating with the number in the first number database may be an extended number determined in the user information that has communicated with the number in the first number database within a preset time period. The preset time period may be a preset time period such as one year or one month.

[0093] Step S103: construct an extended number library based on the extended number and the first number library.

[0094] It should be noted that the construction of the extended number library based on the extended number and the first number library may be to construct the extended number library based on the first number library, the extended number and the user information corresponding to the extended number, that is, to expand the first number library based on the extended number.

[0095] In the specific implementation, the number of calls between all phone numbers in the entire network and the numbers in the first number database in the past 12 months can be calculated, and the mobile phone numbers with the number of calls ≥ 1 can be obtained to establish a new number database as an extended number database. Figure 3 , Figure 3 A call association diagram provided for the second embodiment of the user identification method of the present application, comprising Figure 3It can be seen that when a malicious debt-evading user entrusts an intermediary to make a malicious complaint, there will inevitably be a call connection between the intermediary and the intermediary user, and the call range of the intermediary user is wider than that of ordinary users. Based on these two points, this embodiment can expand the first number database based on the call records of user numbers that have interacted with the complaint platform, and build an extended number database including numbers that have call records with numbers in the first number database in the past year. Then, the risk level of each number in the extended number database is determined based on the call range of each number. Obviously, this embodiment can make the numbers in the extended database constructed as the basis for identifying malicious debt-evading users more comprehensive.

[0096] Further, in order to improve the risk identification efficiency of the user, the step S30 may include: determining the first risk information of the user number in the extended number library according to the call quantity range;

[0097] Determining second risk information of the user number according to the call geographical range;

[0098] The risk level of the user number is determined according to the first risk information and the second risk information, and extended number information is obtained.

[0099] It should be noted that the first risk information of the user number in the extended number library determined according to the call number range may be to determine whether the call number range of the user number in the extended number library is greater than the preset call range width according to the call number range. If it is greater, the first risk information is that there is a risk. The second risk information of the user number determined according to the call geographical range may be to determine whether the geographical range width of the user number is greater than the preset geographical range width according to the call geographical range. If it is greater, the second risk information is that there is a risk. If both the first risk information and the second risk information of the user number are that there is a risk, the risk level of the user number is high risk; if both the first risk information or the second risk information of the user number are that there is a risk, the risk level of the user number is medium risk; if both the first risk information and the second risk information of the user number are that there is no risk, the risk level of the user number is low risk, and the corresponding risk weight value can be set to 1.5, 1, 0.5. It can also be other values, which are not limited in this embodiment.

[0100] In a specific implementation, two conditions can be set, wherein the user quantity range condition is used to indicate the breadth of the call range between the user number in the extended number library and other user numbers in the extended number library, and the geographic range breadth condition is used to indicate the breadth of the geographic range of the call objects of the user number in the extended number library. The user quantity range condition and the geographic range breadth condition are used to determine whether each number in the extended number library has a call behavior whose call range reaches a set range. The set range includes the user range and the geographic range. If the range reaches the set range, it indicates that the user may be a malicious debt evasion intermediary. Combining the user quantity range condition and the geographic range breadth condition, it can be determined whether each number in the extended number library is an intermediary suspected of assisting in malicious complaints, and when determining whether a user is a malicious debt evasion user, the relationship or call situation between the user and the numbers of each risk level in the extended number library is used to determine whether the user is a malicious debt evasion user, and solve the problem that when a user makes a malicious complaint to a delegated intermediary, the target user himself cannot be identified as a malicious debt evasion user. As an example, the user quantity range condition is: if a number in the extended number library has a calling / called number with all other numbers (or 90%) in the extended number library, the number of phone numbers (after deduplication) that have a calling / called number is ≥1. The set user quantity range is 100% or 90%. The geographical scope breadth condition is: if a number in the extended number library has been the calling / called number in the past 12 months, the number of cities (after deduplication) of all numbers in the mobile network of the calling / called number is determined to be ≥31. The number of places of origin of the set numbers is 31. According to the above user quantity range condition and geographical scope breadth condition, it can be determined whether each number in the extended number library meets the above conditions, and the risk weight value and risk level corresponding to each number in the extended number library can be determined according to whether the conditions are met. At the same time, the mapping relationship between the user's number, identity, corresponding risk weight value and risk level can be stored to obtain the extended number information.

[0101] In the specific implementation, this embodiment obtains numbers whose risk assessment values ​​are greater than or equal to the preset risk threshold from the operator database, and adds these numbers to the first number database; wherein the risk assessment value of each number is used to characterize: the amount of interactive data between each number and the complaint platform for receiving financial consumption; then, based on the historical call records of the numbers in the first number database in the past year, and the preset operation time of the debt evasion event (for example, 1 year), an extended number database is constructed, and the extended number database includes numbers that have call records with the numbers in the first number database within the operation time of the debt evasion event (for example, the past year). Afterwards, based on the call data of each number in the extended number database in the past year, it is determined whether the call range of each number in the extended number database in the past year has reached the set range, and according to the relationship between the call range of each number in the past year and the set range, the risk weight value and corresponding risk level of each number are determined; wherein, the call range may include the number range of users who have called and the geographical range. The geographical range is a technical feature designed in this embodiment specifically for the situation where users may maliciously evade debt through "intermediaries". The geographical range can be determined by counting the number of places of origin of numbers that each number has called in the past year. If the range reaches the set range, it indicates that the user may be a malicious debt evasion intermediary. After determining the risk weight value and corresponding risk level of each number, if a complaint or other business request from the target user is received, it can be determined whether the target user's mobile phone number exists in the extended number database based on the target user's mobile phone number. If it does, the risk level corresponding to the target user's mobile phone number is determined according to the risk weight corresponding to the target user's mobile phone number in the extended number database, and the mapping relationship between the risk weight and the risk level. If it does not exist, the risk level corresponding to the target user's mobile phone number is determined based on the number of calls made by the target user's mobile phone number with numbers of each risk level in the extended number database in the past year, and the risk weight corresponding to numbers of each risk level.

[0102] This embodiment determines the first number database according to the user information and the preset identification rules; determines the extended number for calling the number in the first number database based on the user information; and constructs the extended number database based on the extended number and the first number database. This embodiment determines the first number database according to the user information and the preset identification rules, and then constructs the extended number database based on the first number database. Subsequently, the risk identification result of the user can be determined according to the risk level of the user number in the extended number database, thereby improving the risk identification efficiency of the user and preventing the user from evading debt.

[0103] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the user identification method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0104] This application also provides a user identification device, please refer to Figure 4 , the user identification device comprises:

[0105] An acquisition module 10 is used to acquire user information and determine an extended number library according to the user information and a preset identification rule;

[0106] A call range determination module 20, used to determine the call range information of each user number in the extended number library;

[0107] A risk level confirmation module 30, configured to determine the risk level of the user number in the extended number library according to the call range information, and obtain extended number information, wherein the extended number information includes the risk level of each user number in the extended number library;

[0108] The user identification module 40 is used to determine the target risk level of the target user corresponding to the service processing request according to the extended number information when receiving the service processing request.

[0109] This embodiment obtains user information, determines an extended number library according to the user information and preset identification rules; determines the call range information of each user number in the extended number library; determines the risk level of the user number in the extended number library according to the call range information, and obtains extended number information, wherein the extended number information includes the risk level of each user number in the extended number library; upon receiving a service processing request, determines the target risk level of the target user corresponding to the service processing request according to the extended number information. Since this embodiment determines the extended number library according to preset identification rules, determines the extended number information according to the call range of the user number in the extended number library, and determines the risk level of the target user according to the risk information of each number in the extended number information, compared with the existing method of identifying the risk level of the user according to the materials submitted by the user, the above method of this embodiment can improve the accuracy of user identification.

[0110] The user identification device provided by the present application adopts the user identification method in the above embodiment, which can solve the technical problem of low efficiency of existing user risk identification. Compared with the prior art, the beneficial effects of the user identification device provided by the present application are the same as the beneficial effects of the user identification method provided by the above embodiment, and other technical features in the user identification device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0111] The present application provides a user identification device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the user identification method in the above-mentioned embodiment 1.

[0112] Reference below Figure 5 , which shows a schematic diagram of the structure of a user identification device suitable for implementing the embodiment of the present application. The user identification device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The user identification device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0113] like Figure 5 As shown, the user identification device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the user identification device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the user identification device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a user identification device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0114] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0115] The user identification device provided by the present application adopts the user identification method in the above embodiment, which can solve the technical problem of low efficiency of existing user risk identification. Compared with the prior art, the beneficial effects of the user identification device provided by the present application are the same as the beneficial effects of the user identification method provided by the above embodiment, and the other technical features in the user identification device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0116] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0117] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0118] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the user identification method in the above-mentioned embodiment.

[0119] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0120] The computer-readable storage medium may be included in the user identification device; or may exist independently without being assembled into the user identification device.

[0121] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the user identification device, the user identification device executes the user identification method.

[0122] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0123] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0124] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0125] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned user identification method, and can solve the technical problem that the existing user risk identification efficiency is low. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the user identification method provided in the above-mentioned embodiment, and will not be repeated here.

[0126] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned user identification method when executed by a processor.

[0127] The computer program product provided by this application can solve the technical problem of low efficiency in existing user risk identification. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as those of the user identification method provided by the above embodiment, which will not be elaborated here.

[0128] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A user identification method, characterized in that: The user identification method comprises the following steps: Obtaining user information, and determining an extended number library according to the user information and a preset identification rule; Determine the call range information of each user number in the extended number library; Determine the risk level of the user number in the extended number library according to the call range information, and obtain extended number information, wherein the extended number information includes the risk level of each user number in the extended number library; When a service processing request is received, the target risk level of the target user corresponding to the service processing request is determined according to the extended number information.

2. The user identification method according to claim 1, characterized in that: The step of determining the extended number library according to the user information and the preset identification rule comprises: Determine a first number database according to the user information and a preset identification rule; Determine, based on the user information, an extended number for communicating with the number in the first number database; An extended number library is constructed based on the extended number and the first number library.

3. The user identification method according to claim 2, characterized in that: The step of determining the first number database according to the user information and the preset identification rule comprises: Determine the first call number between each user in the user information and the first call object; determining a first user according to the first number of calls; Determine the number of second calls made by the first user with the second call partner; determining a second user according to the second number of calls; Determine the target program usage flow information of the second user; A third user is determined according to the target program usage traffic information and the second user, and a first number database is constructed based on the third user.

4. The user identification method according to claim 1, characterized in that: The call range information includes the call quantity range and the call geographical range; The step of determining the risk level of the user number in the extended number database according to the call range information to obtain the extended number information includes: Determine first risk information of the user number in the extended number library according to the call quantity range; Determining second risk information of the user number according to the call geographical range; The risk level of the user number is determined according to the first risk information and the second risk information, and extended number information is obtained.

5. The user identification method according to any one of claims 1 to 4, characterized in that: The step of determining the target risk level of the target user corresponding to the service processing request according to the extended number information when the service processing request is received includes: When receiving a service processing request, determining a target number of a target user according to the service processing request; Determining whether the target number matches the extended number information; If the target number matches the extended number information, determining the target risk level of the target user according to the extended number information and the target number; If the target number does not match the extended number information, determining call information between the target number and the extended number in the extended number information; A target risk level of the target user is determined according to the call information.

6. The user identification method according to any one of claims 1 to 4, characterized in that: After the step of determining the target risk level of the target user corresponding to the service processing request according to the extended number information when receiving the service processing request, the method further includes: determining a response strategy based on the target risk level; The service processing request is responded to based on the response strategy.

7. A user identification device, characterized in that: The user identification device comprises: An acquisition module, used to acquire user information and determine an extended number library according to the user information and a preset identification rule; A call range determination module, used to determine the call range information of each user number in the extended number library; A risk level confirmation module, configured to determine the risk level of the user number in the extended number library according to the call range information, and obtain extended number information, wherein the extended number information includes the risk level of each user number in the extended number library; The user identification module is used to determine the target risk level of the target user corresponding to the service processing request according to the extended number information when receiving the service processing request.

8. A user identification device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the user identification method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the user identification method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the user identification method according to any one of claims 1 to 6 are implemented.

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