Mobile phone user information verification method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses a mobile phone user information verification method and device, equipment and a storage medium, and the method comprises the steps: obtaining a current mobile phone number in mobile phone user information, and determining a number associated with the current mobile phone number according to a pre-stored operator registration record; determining multiple pieces of target order information corresponding to the current mobile phone number and the associated number according to the historical platform consumption record, and calculating an actual preferential proportion according to the original amount and the preferential amount; performing first risk verification on the target order information according to the actual preferential proportion and the order placing time, and determining risk order information and the total number of the risk order information; the risk type is judged according to the total quantity of the risk order information and the preset risk verification rule, and second risk verification is performed based on the payment mode in the risk order information when the risk type is high-risk order information to obtain the verification result, so that the comprehensiveness and accuracy of mobile phone user information verification are improved, and the user experience is improved. And the benefits of operators are prevented from being damaged.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of computer technology, and in particular to a method, device, equipment and storage medium for verifying mobile phone user information. Background Art

[0002] With the popularization of the Internet and people's increasing dependence on network services, network security issues are becoming more and more serious. User information verification technology is an important means to ensure network security. It can confirm the authenticity and legitimacy of user identities and prevent malicious operations and unauthorized access. For example, it can verify users' cash-out behavior and frequent wool-pulling behavior.

[0003] In the related art, when operators verify mobile phone users through a verification system, they usually only determine whether the user frequently takes advantage of the coupons by verifying the number of times the coupons are collected by the same account. However, the same user can take advantage of the coupons by changing to multiple different accounts, and in order to increase the sales of goods, operators usually support credit card payment or Huabei payment, but in this process, they do not perform security verification on the user's payment method and other information, which leads to user cashing out and other behaviors, resulting in losses to the operator's interests. Summary of the invention

[0004] The embodiments of the present application provide a method, device, equipment and storage medium for verifying mobile phone user information, which solves the problem that the existing mobile phone user information verification method cannot avoid frequent wool-pulling, and does not verify the user's payment information, resulting in cash-out behavior, causing damage to the interests of operators. By performing a first risk check on the target order information corresponding to the current mobile phone number and all associated numbers, it is possible to avoid the situation where users frequently pull wool by changing numbers, and by performing a second risk check on high-risk order information based on the first risk check, it is possible to avoid user cash-out behavior, improve the comprehensiveness and accuracy of mobile phone user information verification, and fully avoid damage to the interests of operators.

[0005] In a first aspect, an embodiment of the present application provides a method for verifying mobile phone user information, comprising:

[0006] Obtaining the current mobile phone number in the mobile phone user information, and determining the number associated with the current mobile phone number according to the pre-stored operator registration record;

[0007] Determine multiple target order information corresponding to the current mobile phone number and the associated number respectively according to the historical platform consumption records, the target order information includes the original amount, the discount amount and the order time, and calculate the actual discount ratio according to the original amount and the discount amount;

[0008] Performing a first risk check on the target order information according to the actual preferential ratio and the order placement time, and determining risky order information and the total number of risky order information;

[0009] The risk type is determined according to the total number of the risky order information and the preset risk verification rules. If the risk type is high-risk order information, a second risk verification is performed based on the payment method in the risky order information to obtain a verification result.

[0010] Optionally, performing a first risk check on the target order information according to the actual discount ratio and the order placement time to determine the risky order information and the total number of the risky order information includes:

[0011] Determine the large-amount preferential order information in each target order information based on the actual preferential ratio, and determine the time interval between adjacent order information according to the order placement time in each large-amount preferential order information;

[0012] Screening the adjacent target order information whose time interval is less than a preset time interval, and determining the delivery address in the adjacent target order information;

[0013] Whether the adjacent target order information is risky order information is determined according to the delivery address in the adjacent target order information, and the total quantity of the risky order information is determined.

[0014] Optionally, judging whether the adjacent target order information is risky order information according to the delivery address in the adjacent target order information includes:

[0015] When the delivery addresses in the adjacent target order information are the same, determining that the adjacent target order information are all risky order information;

[0016] When the delivery addresses in the adjacent target order information are different, it is determined that the adjacent target order information are all risk-free order information.

[0017] Optionally, the determining the risk type according to the total number of risky order information and a preset risk verification rule includes:

[0018] Compare the total number of risky order information with the preset number of discounts, and when the total number of risky order information is equal to the preset number of discounts, determine that the risk type is zero-risk order information;

[0019] When the total number of risky order information is greater than the preset number of discounts, determining the risk type as low-risk order information;

[0020] When the total number of risky order information is less than the preset number of preferential times, the risk type is determined to be high-risk order information.

[0021] Optionally, after determining the risk type according to the total number of risky order information and a preset risk verification rule, the method further includes:

[0022] In the case where the risky order information is low-risk order information, the ordering operations associated with the user name and delivery address in the risky order information are monitored in real time, and identity verification is performed on the ordering operations.

[0023] Optionally, performing a second risk check based on the payment method in the risky order information to obtain a check result includes:

[0024] Determining the payment type of the payment method in the risky order information, and if the payment type is a loan type, determining that the risky order information is target risky order information;

[0025] In a case where the payment type is a non-loan type, the risk order information is determined to be non-target risk order information.

[0026] Optionally, after determining that the risky order information is target risky order information, the method further includes:

[0027] The change frequency of the payment method is determined according to the order time and payment method in the target risk order information, corresponding alarm information is generated based on the change frequency, and the alarm information is sent to the target operator, so that the target operator blacklists the user identity information corresponding to the target risk order information.

[0028] In a second aspect, an embodiment of the present application provides a mobile phone user information verification device, including:

[0029] An information acquisition module, used to acquire the current mobile phone number in the mobile phone user information, and determine the associated number with the current mobile phone number according to the pre-stored operator registration record;

[0030] A target order information determination module, used to determine a plurality of target order information corresponding to the current mobile phone number and the associated number according to historical platform consumption records, wherein the target order information includes the original amount, the discount amount and the order time;

[0031] An actual preferential ratio calculation module, used to calculate the actual preferential ratio according to the original amount and the preferential amount;

[0032] A first risk verification module is used to perform a first risk verification on the target order information according to the actual preferential ratio and the order placement time, and determine the risky order information and the total number of the risky order information;

[0033] A risk type determination module, used to determine the risk type according to the total number of risk order information and preset risk verification rules;

[0034] The second risk verification module is used to perform a second risk verification based on the payment method in the risk order information when the risk type is high-risk order information, and obtain a verification result.

[0035] In a third aspect, an embodiment of the present application provides an electronic device, comprising: one or more processors; a storage device configured to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the mobile phone user information verification method described in the first aspect.

[0036] In a fourth aspect, an embodiment of the present application provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, are used to execute the mobile phone user information verification method as described in the first aspect.

[0037] The embodiment of the present application obtains the current mobile phone number in the mobile phone user information, determines the associated number with the current mobile phone number according to the pre-stored operator registration record, determines the multiple target order information corresponding to the current mobile phone number and the associated number according to the historical platform consumption record, calculates the actual discount ratio according to the original amount and the discount amount, performs a first risk check on the target order information according to the actual discount ratio and the order time, determines the risk order information and the total number of risk order information, judges the risk type according to the total number of risk order information and the preset risk check rules, and in the case where the risk type is high-risk order information, performs a second risk check based on the payment method in the risk order information to obtain the check result. By performing the first risk check on the target order information corresponding to the current mobile phone number and all associated numbers, the comprehensiveness of the mobile phone user information check is improved, and the situation that users frequently get wool by changing numbers is avoided. Moreover, by performing the second risk check on the high-risk order information on the basis of the first risk check, the user cash-out behavior is avoided, the accuracy of the mobile phone user information check is improved, and the interests of the operator are fully avoided from being damaged. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of a method for verifying mobile phone user information provided by an embodiment of the present application;

[0039] Figure 2is a flow chart of a first risk verification method provided in an embodiment of the present application;

[0040] Figure 3 This is a flow chart of a method for determining risk type provided in an embodiment of the present application;

[0041] Figure 4 is a flow chart of a second risk verification method provided in an embodiment of the present application;

[0042] Figure 5 It is a structural schematic diagram of a mobile phone user information verification device provided in an embodiment of the present application;

[0043] Figure 6 It is a structural schematic diagram of a mobile phone user information verification device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only the part related to the present application but not all the contents are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of each operation can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0045] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0046] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0047] The following, in conjunction with the accompanying drawings, describes in detail the mobile phone user information verification method, device, equipment and medium provided in the embodiments of the present application through specific embodiments and their application scenarios.

[0048] The mobile phone user information verification method provided in the embodiment of the present application can be used to verify the operation data generated by the mobile phone user's operation on the mobile phone, such as performing security verification on the operation data generated by the user on the shopping platform, and checking whether the user's operation behavior is a case of wool-pulling or cashing out, etc. Based on the above usage scenarios, it can be understood that the execution subject of the present application can be a server.

[0049] Figure 1 is a flow chart of a method for verifying mobile phone user information provided by an embodiment of the present application, such as Figure 1 As shown, including:

[0050] Step 101: Obtain a current mobile phone number from mobile phone user information, and determine a number associated with the current mobile phone number based on pre-stored operator registration records.

[0051] In one embodiment, the mobile phone user information may be the operation data generated by the mobile phone user performing any operation on the mobile phone, such as the game information in the mobile game platform and the shopping information in the mobile shopping platform. The current mobile phone number may be the mobile phone number contained in the information that needs to be verified, such as the mobile phone number used when logging into the game in the game information, the mobile phone number used when the user places an order for goods in the shopping information, etc. The operator registration record is used to record the business information handled by each user in the corresponding operator, which may record the specific business content corresponding to the user name or other user identity information, such as user A applying for the XXX package of the mobile operator. In one embodiment, the current mobile phone number in the mobile phone user information is obtained, and the associated number of the current operator associated with the current mobile phone number is queried in the pre-stored operator registration record, or the associated numbers of all operators associated with the current mobile phone number are queried. Exemplarily, the operator corresponding to the current mobile phone number is determined, the identity information corresponding to the current mobile phone number is queried in the registration record of the operator, and then the associated number of the current mobile phone number is queried in all operator registration record tables based on the identity information.

[0052] Step 102: Determine multiple target order information corresponding to the current mobile phone number and the associated number respectively according to the historical platform consumption records, wherein the target order information includes the original amount, the discount amount and the order time, and calculate the actual discount ratio according to the original amount and the discount amount.

[0053] Among them, the historical platform consumption record is used for the historical consumption record of the current mobile phone user in the shopping platform, and the historical consumption record includes multiple commodity order information. The target order information is the commodity order information corresponding to the current mobile phone number and the associated number in the multiple commodity order information, and the target order information may include the order number and the actual payment amount of the commodity. Optionally, the target order information includes the original amount, the preferential amount and the order time, wherein the original amount can be the price of the commodity in the platform, the preferential amount is the discount amount or the coupon amount deducted by the user during the order process, and the order time can be the time when the order information is generated, or it can be the time when the order amount is paid. The actual preferential ratio is used to represent the ratio of the preferential amount to the original amount. In one embodiment, the target order information associated with the current mobile phone number and the target order information associated with the associated number are queried in the historical platform consumption record, and the original amount, preferential amount and order time in each target order information are determined respectively, and the actual preferential ratio of each target order is calculated according to the original amount and preferential amount in each target order information. Exemplarily, if the original amount is 100 yuan and the preferential amount is 50 yuan, the actual preferential ratio can be calculated as 50%.

[0054] Step 103: Perform a first risk check on the target order information according to the actual discount ratio and the order time to determine the risky order information and the total number of the risky order information.

[0055] Among them, the first risk check can be used to check whether the user may frequently get free or discounted goods and services. Getting free or discounted goods and services means using various preferential activities, discounts, rebates, etc. This behavior is particularly common in the field of online shopping and is increasingly accepted and loved by consumers. However, if the same user frequently gets free, it will not only fail to increase the publicity of the goods, but also cause a certain degree of loss of interests to the operator. Therefore, in order to avoid damage to the interests of the operator, the first risk check is used to detect whether the user frequently gets free. In one embodiment, the target order information whose actual discount ratio is greater than the preset discount ratio and whose order time is within the preset time range is determined as risky order information, wherein the preset time range is the historical order time of the wool party obtained according to historical statistics. For example, within a certain time period, a large number of users place orders for the same product and all enjoy a large discount ratio, then the time period is considered to be a wool-getting time period for organized wool parties. Therefore, the first risk check can be performed by judging whether the order time of the target order information is within the wool-getting time period and whether a large discount is enjoyed, and the total number of risky order information is determined according to the first risk check result.

[0056] Step 104: determine the risk type according to the total number of the risky order information and a preset risk verification rule. If the risk type is high-risk order information, perform a second risk verification based on the payment method in the risky order information to obtain a verification result.

[0057] Among them, the second risk check refers to the check of cash-out behavior. Cash-out behavior refers to the use of credit cards, Huabei and other loan payment methods to make payments, and the credit limit or funds in the card are withdrawn in the form of cash through fictitious transactions, fictitious prices, non-loan type refunds, etc. In one embodiment, the type of each risk order information is judged according to the preset judgment rules and the total number of risk order information. If the number of risk order information exceeds the set threshold, the risk order information is considered to be high-risk order information. If the number of risk order information does not exceed the set threshold, the risk order information is considered to be low-risk order information. In the case of high-risk order information, the payment method in the risk order information is determined. If the payment method is credit card payment, it is considered that the risk order information may be the order information generated by the user's cash-out behavior, that is, the risk order information is high-risk order information with a second risk.

[0058] The embodiment of the present application obtains the current mobile phone number in the mobile phone user information, determines the associated number with the current mobile phone number according to the pre-stored operator registration record, determines the multiple target order information corresponding to the current mobile phone number and the associated number according to the historical platform consumption record, calculates the actual discount ratio according to the original amount and the discount amount, performs a first risk check on the target order information according to the actual discount ratio and the order time, determines the risk order information and the total number of risk order information, judges the risk type according to the total number of risk order information and the preset risk check rules, and in the case where the risk type is high-risk order information, performs a second risk check based on the payment method in the risk order information to obtain the check result. By performing the first risk check on the target order information corresponding to the current mobile phone number and all associated numbers, the comprehensiveness of the mobile phone user information check is improved, and the situation that users frequently get wool by changing numbers is avoided. Moreover, by performing the second risk check on the high-risk order information on the basis of the first risk check, the user cash-out behavior is avoided, the accuracy of the mobile phone user information check is improved, and the interests of the operator are fully avoided from being damaged.

[0059] Figure 2 is a flow chart of a first risk verification method provided by an embodiment of the present application, such as Figure 2 As shown, including:

[0060] Step S201: determine the large-amount preferential order information in each target order information based on the actual preferential ratio, and determine the time interval between adjacent order information according to the order time in each large-amount preferential order information.

[0061] Among them, large-amount preferential order information refers to target order information containing a large preferential amount. In one embodiment, the actual preferential ratio is compared with the preset preferential ratio, and the target order information that is greater than the preset preferential ratio is determined as large-amount preferential order information, and the number of large-amount preferential order information is determined. If the number of the large-amount order information is one, the large-amount preferential order information can be directly determined as order information without the first risk. If the number of large-amount preferential order information is multiple, the large-amount preferential order information is sorted according to the order time, and the time interval between each adjacent large-amount preferential order information is determined, that is, the time interval between adjacent order times. Exemplarily, if the order times corresponding to the large-amount preferential order information are 12:00 on November 1, 12:01 on November 1, and 20:01 on November 2, respectively, it can be determined that the time intervals between adjacent order information are 1 minute and 32 hours, respectively.

[0062] Step S202: Filter the adjacent target order information whose time interval is less than the preset time interval, and determine the delivery address in the adjacent target order information.

[0063] In one embodiment, if the preset time interval is 24 hours, the first order time corresponding to the first large-amount preferential order information is 12:00 on November 1, the second order time corresponding to the second large-amount preferential order information is 12:00 on November 1, 12:01 on November 1, and the third order time corresponding to the third large-amount preferential order information is 20:01 on November 2, then the time interval between the first order time and the second order time is determined to be 1 minute, which is less than the preset time interval, and the time interval between the second order time and the third order time is 32 hours, which is greater than the preset time interval. Therefore, it can be determined that the first large-amount preferential order information and the second large-amount preferential order information are adjacent target order information, and the delivery address in the first large-amount preferential order information and the delivery address in the second large-amount preferential order information are determined.

[0064] Step S203: judging whether the adjacent target order information is risky order information according to the delivery address in the adjacent target order information, and determining the total quantity of the risky order information.

[0065] In one embodiment, it is determined whether the delivery address in the adjacent target order information is the preset default delivery address. If the delivery address is the preset default delivery address, the target order information is determined to be risky order information. If the delivery address is not the preset default delivery address, the target order information is determined to be non-risky order information, and the total number of risky order information is determined.

[0066] In the above, by determining the large-amount preferential order information in each target order information based on the actual preferential ratio, the time interval of adjacent order information is determined according to the order time in each large-amount preferential order information; adjacent target order information with a time interval less than the preset time interval is screened, and the delivery address in the adjacent target order information is determined; according to the delivery address in the adjacent target order information, it is determined whether the adjacent target order information is risky order information, and the total number of risky order information is determined. The risky order information can be determined by judging the actual preferential ratio in the target order information and the time interval between orders, that is, the order frequency, which ensures the accuracy of the first risk verification and avoids the situation where the same user uses different mobile phone numbers to frequently get wool.

[0067] In one embodiment, judging whether the adjacent target order information is risky order information according to the delivery address in the adjacent target order information includes:

[0068] When the delivery addresses in the adjacent target order information are the same, determining that the adjacent target order information are all risky order information;

[0069] When the delivery addresses in the adjacent target order information are different, it is determined that the adjacent target order information are all risk-free order information.

[0070] Among them, if the delivery addresses in adjacent target order information are the same, it proves that the same user uses the same delivery address to place an order in a short period of time, which means there is a greater risk of being cheated. If the delivery addresses in adjacent target order information are different, it proves that although the same user frequently places orders in a short period of time, there may be cases of purchasing on behalf of others rather than cheating on others, which can play a corresponding publicity role to a certain extent. Therefore, the target order information can be considered as risk-free order information. The embodiment of the present application can accurately judge the situation of cheating on others and the situation of user purchasing on behalf of others by comparing the delivery addresses in the adjacent target order information, thereby improving the accuracy of identifying the situation of cheating on others.

[0071] Figure 3 is a flow chart of a method for determining risk type provided in an embodiment of the present application. Figure 3 As shown, including:

[0072] Step S301: compare the total number of risky order information with the preset number of discounts, and when the total number of risky order information is equal to the preset number of discounts, determine that the risk type is zero-risk order information.

[0073] Among them, the preset number of discounts is the number of coupons or product discounts set by the operator based on marketing needs. Zero-risk order information can be used to indicate order information that does not have the risk of frequent wool-pulling. In one embodiment, if the preset number of discounts is 1, the total number of risky order information is compared with the preset number of discounts. If the total number of risky order information is 1, it is determined that this transaction order can play a role in promoting the product and will not affect the overall revenue of the operator. Therefore, the risky order information is all zero-risk type order information.

[0074] Step S302: When the total number of risky order information is greater than the preset number of preferential times, determine that the risk type is low-risk order information.

[0075] Exemplarily, if the preset number of discounts is 1, the total number of risky order information is compared with the preset number of discounts. If the total number of risky order information is greater than 1, it is considered that each risky order information is order information generated by frequent wool-pulling, which will affect the overall revenue of the operator. Therefore, the risky order information is determined to be low-risk order information with frequent wool-pulling behavior.

[0076] Step S303: When the total number of risky order information is less than the preset number of preferential times, determine that the risk type is high-risk order information.

[0077] For example, if the preset number of discounts is 1, the total number of risky order information is compared with the preset number of discounts. If the total number of risky order information is less than 1, the operator can provide the user with a large discount opportunity, but the user does not use the large discount, then it is considered that the risky order information may be order information generated by the user for cashing out, which will also cause serious loss of interests to the operator. Therefore, the risky order information is determined to be high-risk order information with cashing out behavior.

[0078] In the above, by comparing the total number of risky order information with the preset number of discounts, when the total number of risky order information is equal to the preset number of discounts, the risk type is determined to be zero-risk order information; when the total number of risky order information is greater than the preset number of discounts, the risk type is determined to be low-risk order information; when the total number of risky order information is less than the preset number of discounts, the risk type is determined to be high-risk order information. The total number of risky order information can accurately determine whether each risky order information has risks, as well as the specific risk type, so that it is convenient for operators to take corresponding countermeasures based on different risk types, and accordingly, the satisfaction of operators is improved.

[0079] In one embodiment, after determining the risk type according to the total number of risky order information and a preset risk verification rule, the method further includes:

[0080] In the case where the risky order information is low-risk order information, the ordering operations associated with the user name and delivery address in the risky order information are monitored in real time, and identity verification is performed on the ordering operations.

[0081] Exemplarily, when the risky order information is low-risk order information, the order operation corresponding to the user identity information in the risky order information is controlled so that the user cannot complete the order operation within a short period of time, and the subsequent order operations associated with the user name and delivery address in the risky order information are monitored in real time, that is, all order operations with the same user name and delivery address are monitored, so that the order operation is authenticated through face recognition, which ensures the comprehensiveness of the detection of wool-pulling behavior and fully protects the interests of the operator from damage.

[0082] Figure 4 is a flow chart of a second risk verification method provided in an embodiment of the present application, such as Figure 4 As shown, including:

[0083] Step S401: determine the payment type of the payment method in the risk order information, and when the payment type is a loan type, determine that the risk order information is target risk order information.

[0084] Step S402: When the payment type is a non-loan type, determine that the risk order information is non-target risk order information.

[0085] Among them, the payment method refers to the payment method used by the user in the transaction, such as cash payment, third-party platform payment, and bank transfer. Payment types may include cash payment and non-cash payment. Optionally, the payment type may also include loan type and non-loan type. The target risk order information is the risk order information that may involve cash-out behavior. In one embodiment, the payment type of the payment method in the risk order information is judged. When the payment type is a loan type, it is considered that the user corresponding to the current risk order information does not enjoy the discount provided by the operator, and pays through a loan type payment method, thereby being able to cash out more amounts. Therefore, the risk order information is determined to be the target risk order information that may involve cash-out behavior.

[0086] In one embodiment, after determining that the risky order information is target risky order information, the method further includes:

[0087] The change frequency of the payment method is determined according to the order time and payment method in the target risk order information, corresponding alarm information is generated based on the change frequency, and the alarm information is sent to the target operator, so that the target operator blacklists the user identity information corresponding to the target risk order information.

[0088] Exemplarily, after determining that the risk order information is risk information that may involve cash-out behavior, one or more historical payment methods corresponding to the user can be queried in the historical platform consumption records, and the frequency of changing multiple historical payment methods can be determined based on the time of each order. If the frequency of changing historical payment methods is high, it is considered that the user may perform cash-out operations. Therefore, the risk order information obtained this time is determined to be the target risk order information, and an alarm message is generated and sent to the target operator, so that the target operator can blacklist the user identity information corresponding to the target risk order information to avoid damage to interests.

[0089] In the above, by judging the payment type of the payment method in the risk order information, when the payment type is a loan type, the risk order information is determined to be the target risk order information, and the payment method change frequency is determined according to the order time and payment method in the target risk order information, and the corresponding alarm information is generated based on the change frequency, and the alarm information is sent to the target operator, so that the target operator can blacklist the user identity information corresponding to the target risk order information, and when the payment type is a non-loan type, the risk order information is determined to be non-target risk order information. It can be verified based on multiple methods such as payment type and payment type change frequency, and generate corresponding alarm information, which ensures the accuracy and comprehensiveness of user information verification, and also facilitates users to take corresponding measures for different situations, thereby improving the experience of each target operator.

[0090] Figure 5 is a schematic diagram of the structure of a mobile phone user information verification device provided in an embodiment of the present application, such as Figure 5 As shown, including:

[0091] The information acquisition module 51 is used to acquire the current mobile phone number in the mobile phone user information, and determine the associated number with the current mobile phone number according to the pre-stored operator registration record;

[0092] A target order information determination module 52 is used to determine a plurality of target order information corresponding to the current mobile phone number and the associated number according to the historical platform consumption records, wherein the target order information includes the original amount, the discount amount and the order time;

[0093] An actual preferential ratio calculation module 53, used to calculate the actual preferential ratio according to the original amount and the preferential amount;

[0094] A first risk verification module 54 is used to perform a first risk verification on the target order information according to the actual preferential ratio and the order placement time, and determine the risky order information and the total number of the risky order information;

[0095] A risk type determination module 55 is used to determine the risk type according to the total number of risk order information and a preset risk verification rule;

[0096] The second risk verification module 56 is used to perform a second risk verification based on the payment method in the risky order information when the risk type is high-risk order information, and obtain a verification result.

[0097] The embodiment of the present application obtains the current mobile phone number in the mobile phone user information, determines the associated number with the current mobile phone number according to the pre-stored operator registration record, determines the multiple target order information corresponding to the current mobile phone number and the associated number according to the historical platform consumption record, calculates the actual discount ratio according to the original amount and the discount amount, performs a first risk check on the target order information according to the actual discount ratio and the order time, determines the risk order information and the total number of risk order information, judges the risk type according to the total number of risk order information and the preset risk check rules, and in the case where the risk type is high-risk order information, performs a second risk check based on the payment method in the risk order information to obtain the check result. By performing the first risk check on the target order information corresponding to the current mobile phone number and all associated numbers, the comprehensiveness of the mobile phone user information check is improved, and the situation that users frequently get wool by changing numbers is avoided. Moreover, by performing the second risk check on the high-risk order information on the basis of the first risk check, the user cash-out behavior is avoided, the accuracy of the mobile phone user information check is improved, and the interests of the operator are fully avoided from being damaged.

[0098] In a possible embodiment, the first risk verification module 54 is specifically used to:

[0099] Determine the large-amount preferential order information in each target order information based on the actual preferential ratio, and determine the time interval between adjacent order information according to the order placement time in each large-amount preferential order information;

[0100] Screening the adjacent target order information whose time interval is less than a preset time interval, and determining the delivery address in the adjacent target order information;

[0101] Whether the adjacent target order information is risky order information is determined according to the delivery address in the adjacent target order information, and the total quantity of the risky order information is determined.

[0102] In a possible embodiment, the first risk verification module 54 is further configured to:

[0103] When the delivery addresses in the adjacent target order information are the same, determining that the adjacent target order information are all risky order information;

[0104] When the delivery addresses in the adjacent target order information are different, it is determined that the adjacent target order information are all risk-free order information.

[0105] In a possible embodiment, the risk type determination module 55 is specifically used to:

[0106] Compare the total number of risky order information with the preset number of discounts, and when the total number of risky order information is equal to the preset number of discounts, determine that the risk type is zero-risk order information;

[0107] When the total number of risky order information is greater than the preset number of discounts, determining the risk type as low-risk order information;

[0108] When the total number of risky order information is less than the preset number of preferential times, the risk type is determined to be high-risk order information.

[0109] In one possible embodiment, the identity verification module is used to:

[0110] In the case where the risky order information is low-risk order information, the ordering operations associated with the user name and delivery address in the risky order information are monitored in real time, and identity verification is performed on the ordering operations.

[0111] In a possible embodiment, the second risk verification module 56 is specifically used to:

[0112] Determining the payment type of the payment method in the risky order information, and if the payment type is a loan type, determining that the risky order information is target risky order information;

[0113] In a case where the payment type is a non-loan type, the risk order information is determined to be non-target risk order information.

[0114] In a possible embodiment, the replacement frequency determination module is used to:

[0115] The change frequency of the payment method is determined according to the order time and payment method in the target risk order information, corresponding alarm information is generated based on the change frequency, and the alarm information is sent to the target operator, so that the target operator blacklists the user identity information corresponding to the target risk order information.

[0116] An embodiment of the present application also provides an electronic device, and the mobile phone user information verification device can be integrated with a mobile phone user information verification device provided in an embodiment of the present application. Figure 6 Schematic diagram of the structure of a mobile phone user information verification device provided by an embodiment of the present application. Figure 6The mobile phone user information verification device includes: an input device 63, an output device 64, a memory 62 and one or more processors 61; the memory 62 is used to store one or more programs; when one or more programs are executed by one or more processors 61, the one or more processors 61 implement the mobile phone user information verification method provided in the above embodiment. The input device 63, the output device 64, the memory 62 and the processor 61 can be connected by a bus or other means. Figure 6 The example of connecting through bus is taken in the following.

[0117] The memory 62, as a computing device readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the mobile phone user information verification method provided in any embodiment of the present application. The memory 62 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, at least one application required for a function; the data storage area may store data created according to the use of the device, etc. In addition, the memory 62 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 62 may further include a memory remotely arranged relative to the processor 61, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0118] The input device 63 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device 64 may include a display device such as a display screen.

[0119] The processor 61 executes the software programs, instructions and modules stored in the memory 62 to execute various functional applications and data processing of the device, that is, to implement the above-mentioned mobile phone user information verification method.

[0120] The mobile phone user information verification device, equipment and computer provided above can be used to execute the mobile phone user information verification method provided in any of the above embodiments, and have corresponding functions and beneficial effects.

[0121] The embodiment of the present application further provides a storage medium storing computer executable instructions. When the computer executable instructions are executed by a computer processor, they are used to execute the mobile phone user information verification method provided in the above embodiment. The mobile phone user information verification method includes:

[0122] Obtaining the current mobile phone number in the mobile phone user information, and determining the number associated with the current mobile phone number according to the pre-stored operator registration record;

[0123] Determine multiple target order information corresponding to the current mobile phone number and the associated number respectively according to the historical platform consumption records, the target order information includes the original amount, the discount amount and the order time, and calculate the actual discount ratio according to the original amount and the discount amount;

[0124] Performing a first risk check on the target order information according to the actual preferential ratio and the order placement time, and determining risky order information and the total number of risky order information;

[0125] The risk type is determined according to the total number of the risky order information and the preset risk verification rules. If the risk type is high-risk order information, a second risk verification is performed based on the payment method in the risky order information to obtain a verification result.

[0126] Storage medium - any of various types of memory devices or storage devices. The term "storage medium" is intended to include: installation media, such as CD-ROM, floppy disk or tape device; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (such as hard disk or optical storage); registers or other similar types of memory elements, etc. Storage media may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the first computer system in which the program is executed, or may be located in a different second computer system, which is connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations (for example, in different computer systems connected by a network). The storage medium may store program instructions (for example, embodied as a computer program) that can be executed by one or more processors.

[0127] Of course, the storage medium containing computer executable instructions provided in the embodiment of the present application is not limited to the mobile phone user information verification method described above, and can also execute related operations in the mobile phone user information verification method provided in any embodiment of the present application.

[0128] The mobile phone user information verification device, equipment and storage medium provided in the above embodiments can execute the mobile phone user information verification method provided in any embodiment of the present application. For technical details not described in detail in the above embodiments, please refer to the mobile phone user information verification method provided in any embodiment of the present application.

[0129] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A method for verifying mobile phone user information, characterized in that: include: Obtaining the current mobile phone number in the mobile phone user information, and determining the number associated with the current mobile phone number according to the pre-stored operator registration record; Determine multiple target order information corresponding to the current mobile phone number and the associated number respectively according to the historical platform consumption records, the target order information includes the original amount, the discount amount and the order time, and calculate the actual discount ratio according to the original amount and the discount amount; Performing a first risk check on the target order information according to the actual preferential ratio and the order placement time, and determining risky order information and the total number of risky order information; The risk type is determined according to the total number of the risky order information and the preset risk verification rules. If the risk type is high-risk order information, a second risk verification is performed based on the payment method in the risky order information to obtain a verification result.

2. The method for verifying mobile phone user information according to claim 1, characterized in that: The performing a first risk check on the target order information according to the actual preferential ratio and the order placement time to determine the risky order information and the total number of the risky order information includes: Determine the large-amount preferential order information in each target order information based on the actual preferential ratio, and determine the time interval between adjacent order information according to the order placement time in each large-amount preferential order information; Screening the adjacent target order information whose time interval is less than the preset time interval, and determining the delivery address in the adjacent target order information; Whether the adjacent target order information is risky order information is determined according to the delivery address in the adjacent target order information, and the total quantity of the risky order information is determined.

3. The method for verifying mobile phone user information according to claim 2, characterized in that: The determining whether the adjacent target order information is risky order information according to the delivery address in the adjacent target order information includes: When the delivery addresses in the adjacent target order information are the same, determining that the adjacent target order information are all risky order information; When the delivery addresses in the adjacent target order information are different, it is determined that the adjacent target order information are all risk-free order information.

4. The method for verifying mobile phone user information according to claim 1, characterized in that: The determining the risk type according to the total number of risky order information and a preset risk verification rule includes: Compare the total number of risky order information with the preset number of discounts, and when the total number of risky order information is equal to the preset number of discounts, determine that the risk type is zero-risk order information; When the total number of risky order information is greater than the preset number of discounts, determining the risk type as low-risk order information; When the total number of risky order information is less than the preset number of preferential times, the risk type is determined to be high-risk order information.

5. The method for verifying mobile phone user information according to claim 4, characterized in that: After determining the risk type according to the total number of risky order information and a preset risk verification rule, the method further includes: In the case where the risky order information is low-risk order information, the ordering operations associated with the user name and delivery address in the risky order information are monitored in real time, and identity verification is performed on the ordering operations.

6. The method for verifying mobile phone user information according to claim 1, characterized in that: The performing a second risk check based on the payment method in the risky order information to obtain a check result includes: Determining the payment type of the payment method in the risky order information, and if the payment type is a loan type, determining that the risky order information is target risky order information; In a case where the payment type is a non-loan type, the risk order information is determined to be non-target risk order information.

7. The method for verifying mobile phone user information according to claim 6, characterized in that: After determining that the risky order information is target risky order information, the method further includes: The change frequency of the payment method is determined according to the order time and payment method in the target risk order information, corresponding alarm information is generated based on the change frequency, and the alarm information is sent to the target operator, so that the target operator blacklists the user identity information corresponding to the target risk order information.

8. A mobile phone user information verification device, characterized in that: include: An information acquisition module, used to acquire the current mobile phone number in the mobile phone user information, and determine the associated number with the current mobile phone number according to the pre-stored operator registration record; A target order information determination module, used to determine multiple target order information corresponding to the current mobile phone number and the associated number according to the historical platform consumption records, wherein the target order information includes the original amount, the discount amount and the order time; An actual preferential ratio calculation module, used to calculate the actual preferential ratio according to the original amount and the preferential amount; A first risk verification module, configured to perform a first risk verification on the target order information according to the actual preferential ratio and the order placement time, and determine the risky order information and the total number of the risky order information; A risk type determination module, used to determine the risk type according to the total number of risk order information and preset risk verification rules; The second risk verification module is used to perform a second risk verification based on the payment method in the risk order information when the risk type is high-risk order information, and obtain a verification result.

9. An electronic device, comprising: one or more processors; A storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the mobile phone user information verification method as described in any one of claims 1-7.

10. A storage medium storing computer executable instructions, wherein the computer executable instructions are used to execute the mobile phone user information verification method according to any one of claims 1 to 7 when executed by a computer processor.

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