Transfer processing method and device, equipment, storage medium and program product

Abstract

The invention provides a transfer processing method and device, equipment, a storage medium and a program product, and relates to the field of artificial intelligence. The method comprises the following steps: in response to a target transfer processing request sent by a target client of a target account, determining whether the target transfer processing request has an abnormal risk according to target information and transfer setting information of the target account; the target information comprises target user information corresponding to a target account, login information of the target account, transfer information of the target account, and communication information of a user within a preset duration before the target transfer processing request is triggered; under the condition that the abnormal risk exists, first prompt information is output to the target client, and account transfer intention description information of the target client is acquired; based on the transfer intention description information, determining an abnormal risk level corresponding to the target transfer processing request; and processing the target transfer processing request based on a transfer processing mode corresponding to the abnormal risk level. According to the invention, the security of account transfer is improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence, and in particular to a transfer processing method, device, equipment, storage medium and program product. Background Art

[0002] With the rapid development of digital finance, users' transfer habits have changed from relying on traditional bank counters to using mobile phones, computers and other electronic devices to process transfer requests. This change has improved transfer efficiency and user experience.

[0003] However, while this method is convenient for users to transfer money, it is also accompanied by various potential risks. In order to protect the safety of users' funds, existing methods identify whether there are abnormal risks in users' transfer processing requests by comprehensively considering factors such as the user's age, transfer amount, and whether the operation is performed by the user himself during the transfer process, and perform risk control to reduce the risk of fund loss. However, existing risk identification methods have certain limitations and cannot identify and respond to these abnormal risks in a timely and effective manner. Therefore, how to improve the accuracy of risk assessment and increase corresponding response measures has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The present application provides a transfer processing method, device, equipment, storage medium and program product to solve the complex means of inducing users to actively transfer money by forging legal identities, improve the accuracy of risk assessment, and increase corresponding countermeasures.

[0005] In a first aspect, the present application provides a transfer processing method, the method comprising:

[0006] In response to a target transfer processing request sent by a target client of a target account, determining whether the target transfer processing request has an abnormal risk according to target information and transfer setting information of the target account; the target information includes: target user information corresponding to the target account, login information of the target account, transfer information of the target account, and communication information of users within a preset time period before triggering the target transfer processing request;

[0007] In the case of an abnormal risk, outputting first prompt information to the target client, and obtaining transfer intention description information fed back by the target client based on the first prompt information;

[0008] Determining, based on the transfer intention description information, an abnormal risk level corresponding to the target transfer processing request;

[0009] The target transfer processing request is processed based on the transfer processing method corresponding to the abnormal risk level.

[0010] In a second aspect, the present application provides a transfer processing device, comprising:

[0011] A first determination module is configured to respond to a target transfer processing request sent by a target client of a target account, and determine whether the target transfer processing request has an abnormal risk according to target information and transfer setting information of the target account; the target information includes: target user information corresponding to the target account, login information of the target account, transfer information of the target account, and communication information of users within a preset time period before triggering the target transfer processing request;

[0012] An interaction module, configured to output first prompt information to the target client when there is an abnormal risk, and obtain transfer intention description information fed back by the target client based on the first prompt information;

[0013] A second determination module, configured to determine an abnormal risk level corresponding to the target transfer processing request based on the transfer intention description information;

[0014] A processing module is used to process the target transfer processing request based on the transfer processing method corresponding to the abnormal risk level.

[0015] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0016] The memory stores computer-executable instructions;

[0017] The processor executes the computer-executable instructions stored in the memory to implement the method as described in any one of the first aspects.

[0018] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method as described in any one of the first aspects.

[0019] In a fifth aspect, the present application provides a computer program product, including a computer program, which implements the method described in any one of the first aspects when executed by a processor.

[0020] The transfer processing method, device, equipment, storage medium and program product provided by the present application can achieve more comprehensive identification and assessment of abnormal risks by comprehensively analyzing user information, login records, transfer history, communication data and transfer settings. The risk level is further determined by obtaining the user's transfer intention description information, and the target transfer processing request is processed according to the abnormal risk level. The security of the transfer is significantly improved and the risk of user property loss is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] 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.

[0022] Figure 1 A flowchart of a method for processing a transfer provided in an embodiment of the present application;

[0023] Figure 2 A flowchart of a method for determining that a target transfer processing request has an abnormal risk provided by an embodiment of the present application;

[0024] Figure 3 A flowchart of a method for processing a target transfer request provided in an embodiment of the present application;

[0025] Figure 4 A schematic diagram of a flow chart of reflecting a transfer process through a change in a user interface provided in an embodiment of the present application;

[0026] Figure 5 A flowchart of a method for processing a transfer provided in an embodiment of the present application;

[0027] Figure 6 A schematic diagram of the structure of a transfer processing device provided in an embodiment of the present application;

[0028] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0029] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0030] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0031] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0032] In addition, this application involves conducting big data analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.), and using artificial intelligence technology to make automated decisions, and making technical solutions that have a significant impact on personal rights and interests based on the results of automated decisions. The application provides users with corresponding operation entrances for them to choose to agree or reject the results of automated decisions; if the user chooses to reject, the expert decision-making process will be entered.

[0033] It should be noted that the transfer processing method, device, equipment, storage medium and program product provided in this application can be used in the field of artificial intelligence, and can also be used in any field other than artificial intelligence. The application field of the transfer processing method, device, equipment, storage medium and program product in this application is not limited.

[0034] With the rapid development of digital finance, users' transfer habits have also changed significantly. Users have gradually shifted from relying on traditional bank counters to process transfers to using mobile phones, computers and other electronic devices to process transfer requests. This change not only makes transfer operations more efficient and convenient, but also greatly improves the user experience.

[0035] The user end of the banking system is the interface for users to interact with the server end of the banking system, which is usually presented to users in the form of mobile applications or web pages. Users can initiate transfer processing requests through the user end. When the user end receives the user's transfer processing request, it will securely send the content of the transfer processing request to the server end. The server end executes the corresponding transfer process according to the content of the transfer processing request.

[0036] The following is a detailed description of the steps for users to implement transfer processing through interaction between the user end and the server end:

[0037] (1) The user opens the client and authenticates using a username, password, or biometrics.

[0038] (2) The user selects the transfer option in the user interface.

[0039] (3) The user enters the transfer recipient information, including the recipient account, recipient account bank name, transfer amount, and any remarks that may be required.

[0040] (4) After verifying that the information is correct, the user confirms and submits the transfer request.

[0041] (5) The user package the user's transfer processing request into a data packet and send it to the server in an encrypted manner.

[0042] (6) After receiving the transfer processing request from the user, the server performs preliminary authentication of the transfer processing.

[0043] For example: check whether the receiving account exists and whether the receiving bank name is accurate.

[0044] (7) After the initial authentication of the transfer process is passed, the server will perform transfer processing and risk assessment.

[0045] For example: judging whether there is a transfer risk based on the user's age, the amount of the transfer and whether the operation is made by the user himself.

[0046] (8) If a risk is detected in the transfer request, the server will mark the current transfer as suspicious, triggering manual review or sending a prompt message to the user to prompt the user through the user. For example, feedback that the current transfer request has a risk is sent through SMS, email or user prompt message.

[0047] (9) The user confirms the transfer through additional verification steps.

[0048] (10) If the user passes the verification step and chooses to continue the transfer, the transfer operation will continue.

[0049] (11) If the user chooses to abandon the transfer during the verification step, the transfer operation will be terminated.

[0050] The above transfer processing method improves the convenience of user operation and makes fund transfer more efficient and convenient. However, while this method facilitates user transfer, it is also accompanied by various potential risks, including but not limited to fraud, illegal fund transactions and other security issues.

[0051] In order to protect the user's funds, the above method identifies whether the user's transfer request has abnormal risks by comprehensively considering factors such as the user's age, transfer amount, and whether the operation is performed by the user himself during the transfer process, and identifies and controls the risks of the user's transfer behavior. The transfer risk is reduced as much as possible. This method enhances the security of the transfer to a certain extent and reduces the risk of user fund loss.

[0052] However, the existing risk identification methods have certain limitations and cannot effectively identify and respond to these abnormal risks in a timely manner. Therefore, how to improve the accuracy of risk assessment and increase corresponding response measures has become a technical problem that needs to be solved urgently.

[0053] In view of this, the present application provides a transfer processing method, which identifies whether a target transfer processing request has an abnormal risk by analyzing the target user information, login information, transfer information, communication information of the user within a preset time period before the target transfer processing request, and transfer setting information of the target account corresponding to the target account. In the case of an abnormal risk, the transfer intention description information of the target user is obtained through the target user terminal. The abnormal risk level corresponding to the target transfer processing request can also be determined based on the transfer intention description information. And the target transfer processing request is processed according to the abnormal risk level.

[0054] The method provided by this application can achieve a more comprehensive identification and assessment of abnormal risks by comprehensively analyzing user information, login records, transfer history, communication data and transfer settings. The risk level is further determined by obtaining the user's transfer intention description information, and the target transfer processing request is processed according to the abnormal risk level. This method significantly improves the security of transfers and reduces the risk of user property loss.

[0055] It should be understood that the method of the embodiment of the present application can be applied to a banking system, or to other third-party systems with a transfer function, etc., without limitation. The following is an example of a service end of a banking system.

[0056] The following is a detailed description of the method provided in the embodiments of the present application. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0057] Figure 1 A flow chart of a transfer processing method provided in an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0058] S101. In response to a target transfer processing request sent by a target user terminal of a target account, determine whether the target transfer processing request has an abnormal risk according to target information and transfer setting information of the target account.

[0059] The target account may be a bank account of any user in the banking system. The target user terminal may be a client terminal of the user currently using the target account to log in to the target account.

[0060] The target information includes: target user information corresponding to the target account, login information of the target account, transfer information of the target account, and communication information of the user within a preset time period before triggering the target transfer processing request.

[0061] Exemplarily, the target user information corresponding to the target account may be, for example, the user's account opening information, that is, the user's age, and / or the user's personal phone number and other information.

[0062] The login information of the target account may be, for example, the login time, the login device type, and / or the login region, etc. The transfer information of the target account may be, for example, the transaction information of the user, that is, the transfer-out account, and / or the transfer-in account, etc.

[0063] The communication information of the user within the preset time before the target transfer processing request is triggered can be, for example, the phone number answered within the preset time before the target transfer processing request is triggered, the number of the sender of the short message received within the preset time before the target transfer processing request is triggered, and the type of social software used within the preset time before the target transfer processing request is triggered.

[0064] The transfer setting information of the target account may be, for example, information set when the user first uses the target user terminal, and the information may be, for example, a maximum transfer limit, a transfer region limit, and / or a transfer time limit, and the transfer setting of the target account may also include, for example, a family account. A family account is an account that allows family members and / or friends to be associated with one's own account.

[0065] For example, in response to the target transfer processing request sent by the target user of the target account, the server can determine whether the target transfer processing request hits the risk identification rule in the abnormal risk identification rule set according to the target information, the transfer setting information of the target account, the account blacklist library, and the abnormal risk identification rule set. If at least one abnormal risk identification rule is hit, it is determined that the target transfer processing request has an abnormal risk.

[0066] The account blacklist database may be, for example, a comprehensive database including suspicious accounts obtained from external institutions and suspicious accounts obtained by the bank system based on historical transactions, etc. The account mentioned here may be a bank card number or information that can determine the bank card number, such as the user's phone number, ID card number, etc.

[0067] The abnormal risk identification rule set may be, for example, a series of detection standards and logical judgment conditions formulated by the server based on historical transfer transaction data, experience, and / or risk management requirements.

[0068] It should be noted that the embodiments of the present application do not limit the presentation form of the account blacklist library and the abnormal risk identification rule set.

[0069] Exemplarily, in response to the target transfer processing request sent by the target client of the target account, the server can determine whether the target transfer processing request hits the risk identification rule in the abnormal risk identification rule set according to the target information, the transfer setting information of the target account, the account blacklist library, and the degree of matching with the abnormal risk identification rule set. If at least one abnormal risk identification rule is hit, it is determined that the target transfer processing request has an abnormal risk.

[0070] For another example, in response to a target transfer processing request sent by a target client of a target account, the server may input the target information and the transfer setting information of the target account into a pre-trained abnormal risk judgment model, and determine that the target transfer processing request has abnormal risk through the model. The pre-trained abnormal risk judgment model may be obtained by training based on historical risk transfer transaction data, for example.

[0071] For another example, in response to a target transfer processing request sent by a target client of a target account, the server may use machine learning and data analysis techniques to determine, through target information and transfer setting information of the target account, that there is an abnormal risk in the target transfer processing request.

[0072] S102: In the case of abnormal risk, output first prompt information to the target client, and obtain transfer intention description information fed back by the target client based on the first prompt information.

[0073] For example, in the case of abnormal risk, after receiving the first prompt information sent by the server, the target client can output the first prompt information to trigger the user to provide feedback transfer intention description information. The first prompt information can be as follows: Your current transfer may be risky, please provide your transfer intention.

[0074] Exemplarily, the target client may output the first prompt information by, for example, popping up a prompt box to prompt the user to provide feedback on the transfer intention description information. Alternatively, the target client may prompt the user to provide feedback on the transfer intention description information by issuing a voice prompt.

[0075] The transfer intention description information is a detailed description of the transfer reason provided by the user. This embodiment does not limit the way in which the user feeds back the transfer intention description information, for example, the transfer intention description information can be provided by text input, and / or voice input, and / or video input.

[0076] For example, the server obtains the input data of the user through the target client based on the first prompt information. If the input data is text data, the transfer intention description information is obtained based on the text data. Exemplarily, the server can use the text data as the transfer intention description information, or perform semantic analysis on the text data to obtain the semantics of the text data, and use the semantics as the transfer intention description information. For how to understand the semantics of text data, please refer to the existing implementation method.

[0077] If the input data is voice data, the voice data is understood to obtain the transfer intention description information. Exemplarily, the server sends the voice data to a pre-trained intention recognition model, and the model converts the voice data into the transfer intention description information. The intention recognition model can be pre-trained by the server based on historical voice data.

[0078] If the input data is video data, the server can extract text data based on the video data, and obtain the transfer intention description information based on the text data. For example, the server can extract voice data from the video data, and thus obtain the transfer intention description information based on the voice data.

[0079] Optionally, when the above input data is voice data or video data, the server can also verify the reliability of the input data based on the input data and the user's physiological characteristics data to improve the reliability of the input data. Taking voice data as an example, for example, the voiceprint data pre-set by the user can be used to identify whether the voice data is the user's voice data. Taking video data as an example, for example, video analysis can be used to identify whether the video data is synthetic data, and the user's facial expressions or body movements in the video data can also be used to identify whether the user voluntarily inputs the data.

[0080] Optionally, in some embodiments, the server may also output a second prompt information before obtaining the transfer intention description information, and the second prompt information is used to instruct the target user to authenticate the identity. After obtaining the collected target user identity information fed back by the target client based on the second prompt information, the server may authenticate the target user based on the identity information. If the identity authentication is successful, the input data fed back by the target client based on the first prompt information is obtained.

[0081] For example, based on the target user information, the server sends a text message containing a one-time verification code to the user's personal phone to instruct the target user to authenticate the identity, and the user enters the verification code on the target client operation interface to authenticate the identity. For another example, the server notifies the user to scan the fingerprint through the target client, and the user enters the fingerprint on the target client to authenticate the identity. For another example, the server notifies the user to perform a face recognition operation through the target client, and the user authenticates the identity according to the face recognition operation. For another example, the server outputs preset security questions through the target client, and the user authenticates the identity by answering the security questions.

[0082] Through the above multi-level identity authentication steps, when the user enters the transfer intention description information, it can more accurately determine whether the intention really reflects the user's true intention, thereby effectively preventing unauthorized illegal transfers. The accuracy of risk identification is significantly improved, and the security of user funds is guaranteed. At the same time, the risk loss caused by erroneous transfer operations is reduced, providing users with a safer and more reliable transfer environment.

[0083] S103: Determine the abnormal risk level corresponding to the target transfer processing request based on the transfer intention description information.

[0084] Exemplarily, the server inputs the transfer intention into a pre-trained abnormal risk level classification model, and the abnormal risk level classification model determines the abnormal risk level corresponding to the target transfer processing request. The abnormal risk level classification model can be pre-trained by the server based on the transfer intention description information.

[0085] Exemplarily, the server may also extract transfer intention keywords from the transfer intention description information, and obtain the abnormal risk level based on the transfer intention keywords using an abnormal risk level identification model.

[0086] For example, the server can segment the transfer intention description information and extract keywords based on a probability statistics method, and obtain the abnormal risk level based on the transfer intention keywords using an abnormal risk level recognition model.

[0087] For another example, the server can input the transfer intention description information into a pre-trained classifier, and obtain the transfer intention keywords based on the output of the classifier. Based on the transfer intention keywords, the abnormal risk level is obtained using the abnormal risk level recognition model. The classifier can be pre-trained by the server based on historical transfer intention description information.

[0088] For another example, the server can extract keywords through a predefined transfer risk template, and obtain the abnormal risk level based on the transfer intention keywords using an abnormal risk level recognition model. The predefined transfer risk template can be obtained by the server using multiple groups of historical transfer intention keywords and label data corresponding to the keywords for training.

[0089] S104: Process the target transfer processing request based on the transfer processing method corresponding to the abnormal risk level.

[0090] For example, the higher the abnormal risk level, the greater the risk of the target transfer processing request. Therefore, the target transfer processing request can be processed differently according to the abnormal risk level. The granularity of the abnormal risk level can be set according to actual needs and is not limited to this.

[0091] For example, for a target transfer processing request with an abnormal risk level greater than or equal to a preset level, the transfer processing may not be performed and an alarm operation may be triggered. For a target transfer processing request with an abnormal risk level less than a preset level, the transfer processing may be performed according to the transfer processing flow.

[0092] The method provided by this application can more comprehensively identify and assess abnormal risks by comprehensively analyzing user information, login records, transfer history, communication data, transfer settings and other information. The risk level is further determined by obtaining the user's transfer intention description information, ensuring the accuracy of the risk level classification. The target transfer processing request is processed according to the abnormal risk level. The security of the transfer is significantly improved and the risk of user property loss is reduced.

[0093] Figure 2 A flowchart of a method for determining whether a target transfer processing request has an abnormal risk is provided in an embodiment of the present application, such as Figure 2 As shown, the above step S101 may include the following steps:

[0094] S201. Determine whether the target transfer processing request matches a risk identification rule in the abnormal risk identification rule set according to target information, transfer setting information of the target account, an account blacklist library, and an abnormal risk identification rule set.

[0095] Exemplarily, the server may determine whether the target transfer processing request hits the abnormal risk identification rule related to the user information based on the target user information. For example, when the user age in the target user information exceeds the transfer age threshold set by the server, the server determines that the target transfer processing request hits the abnormal risk identification rule related to the user information.

[0096] Exemplarily, the server may determine whether the target transfer processing request matches an abnormal risk identification rule related to the transfer based on the transfer information of the target account and the transfer setting information of the target account.

[0097] For example, when the transfer amount in the target transfer processing request exceeds the maximum transfer limit in the transfer setting information of the target account, and the transferee account in the transfer information of the target account is the first transfer, the server determines that the target transfer processing request hits the abnormal risk identification rule related to the user information.

[0098] For another example, when the region of the transferee account in the target transfer processing request is not within the transfer region restriction in the transfer setting information of the target account, and the transferee account in the transfer information of the target account is a first-time transfer, the server determines that the target transfer processing request hits the abnormal risk identification rule related to the user information.

[0099] For another example, when the transfer time in the target transfer processing request is not within the transfer time limit in the transfer setting information of the target account, and the transferee account in the transfer information of the target account is the first transfer, the server determines that the target transfer processing request hits the abnormal risk identification rule related to the user information.

[0100] Exemplarily, the server may calculate an abnormal risk score based on the login information of the target account and the transfer information of the target account, and determine whether the target transfer processing request hits an abnormal risk identification rule related to the abnormal risk score based on the abnormal risk score.

[0101] For example, the server inputs the login information of the target account and the transfer information of the target account into the abnormal risk scoring algorithm. The algorithm calculates the abnormal risk score. When the abnormal risk score is greater than the preset score threshold, the server determines that the target transfer processing request hits the abnormal risk identification rule related to the user information.

[0102] For another example, the server inputs the target account login information and the target account transfer information into the abnormal risk score calculation model, and the abnormal risk score calculation model outputs the abnormal risk score result. When the abnormal risk score is greater than the preset score threshold, the server determines that the target transfer processing request hits the abnormal risk identification rule related to the user information.

[0103] Exemplarily, the server may determine whether the target transfer processing request matches the risk identification rules related to the account based on the transfer account information in the transfer information of the target account, the account information in the communication information, and the account blacklist library.

[0104] For example, the server can determine whether the transfer account information in the transfer information of the target account, the transfer account, and the account information in the communication information are located in the account blacklist library. If they are located in the account blacklist library, the server determines that the target transfer processing request hits the abnormal risk identification rules related to the user information.

[0105] Among them, the account information in the communication information is the phone number answered within the preset time before triggering the target transfer processing request, and the SMS sender number received within the preset time before triggering the target transfer processing request.

[0106] Exemplarily, the server may determine whether the target transfer processing request matches a risk identification rule related to the communication behavior based on the communication information.

[0107] For example, the phone number answered within a preset time before the target transfer processing request is triggered is an unknown number and is not in the user's contact list. The server determines that the target transfer processing request hits the abnormal risk identification rule related to user information.

[0108] For another example, the sender number of the SMS received within a preset period of time before the target transfer processing request is triggered is an unknown number and is not in the user's contact list. The server determines that the target transfer processing request hits the abnormal risk identification rule related to user information.

[0109] For another example, the social software used within a preset time period before triggering the target transfer processing request includes calling microphone or camera permissions. The server determines that the target transfer processing request hits the abnormal risk identification rule related to user information.

[0110] It should be understood that the above embodiments are merely exemplary of the risk identification rules provided by the abnormal risk identification rule set, and the present application is not limited thereto, and the specific examples may be related to the risk dimensions that need to be identified in practice.

[0111] S202: When at least one abnormal risk identification rule is matched, it is determined that the target transfer processing request has an abnormal risk.

[0112] Exemplarily, when the target transfer processing request matches at least one abnormal risk identification rule, the server determines that the target transfer processing request has an abnormal risk.

[0113] The method provided in the present application comprehensively analyzes whether the target transfer processing request hits the abnormal risk identification rules, thereby determining whether the target transfer request has abnormal risks. This method can more comprehensively identify and evaluate abnormal risks and improve the accuracy of abnormal risk identification.

[0114] The following takes the abnormal risk level as three levels as an example to explain how to process the target transfer processing request based on the transfer processing method corresponding to the abnormal risk level. The three levels may include, for example: a first risk level, a second risk level, and a third risk level, wherein the first risk level is less than the second risk level, and the second risk level is less than the third risk level.

[0115] Figure 3 A flowchart of a method for processing a target transfer request provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, the above step S104 may include the following steps:

[0116] S301. Based on the transfer intention keywords, an abnormal risk level recognition model is used to obtain an abnormal risk level.

[0117] Exemplarily, the abnormal risk level identification model can be, for example, a machine learning model pre-trained by the target server using historical transfer intention keywords. The embodiment of the present application does not limit the category of the abnormal risk level identification model, and it only needs to be able to obtain the abnormal risk level based on the transfer intention keyword.

[0118] If the abnormal risk level is the first risk level, it means that the transfer risk of the target transfer processing request is low, and the transfer operation can be performed directly, that is, S306 is performed. If the abnormal risk level is the second risk level, it means that the target transfer processing request may have a transfer risk, so it can be determined whether to continue the transfer operation by a second confirmation with the user, and S302 is performed. If the abnormal risk level is the third risk level, it means that the transfer risk of the target transfer processing request is high. In this implementation, other channels other than the user can be used to assist in confirming whether the transfer operation is performed, and S303 is performed.

[0119] S302, outputting a third prompt message indicating that there is a transfer risk to the target client, and if receiving information fed back by the target client based on the third prompt message, determining whether to continue the transfer operation based on the information. If yes, that is, the target client feeds back confirmation information of continuing the transfer based on the third prompt message, then executing S306, if no, that is, the target client feeds back confirmation information of stopping the transfer based on the third prompt message, then the transfer request is not processed.

[0120] Exemplarily, the third prompt information may be, for example, a prompt box popped up by the server through the target client, and the user may provide feedback through the prompt box to confirm whether to continue the transfer.

[0121] The third prompt information may also be, for example, the user server asking the user whether to continue the transfer through a voice call, and the user providing confirmation information of whether to continue the transfer through voice description.

[0122] The third prompt information may also be, for example, a risk warning SMS message sent by the server to the user, and the user may provide confirmation information on whether to continue the transfer based on the SMS prompt.

[0123] S303: Determine the target processing method of the target transfer processing request based on whether the target account has a family account, and process it based on the target processing method. If yes, execute S305. If no, execute S304.

[0124] S304, outputting the third prompt information of the existence of the transfer risk to the target client, and triggering the target platform to issue a transfer warning prompt to the target user, and judging whether to continue the transfer operation based on the information received from the target client based on the third prompt information and the transfer warning prompt feedback. If yes, that is, the target client continues the transfer based on the third prompt information and the confirmation information of the transfer warning prompt feedback, then S306 is executed; if no, that is, the target client stops the transfer based on the third prompt information and the confirmation information of the transfer warning prompt feedback, then the transfer request is not processed.

[0125] The target platform may be a preset platform for risk warning and control of transfer operations. The target platform may, for example, remind the user by phone through manual or intelligent outbound calls that the current transfer request has a high risk.

[0126] S305. Output a fourth prompt message indicating that there is a transfer risk in the target account to the user terminal corresponding to the family account, and determine whether to continue the transfer operation based on the transfer request fed back by the user terminal corresponding to the family account based on the fourth prompt message. If so, that is, the target client receives confirmation information of continuing the transfer based on the fourth prompt message, then execute S306; if not, that is, the target client receives confirmation information of stopping the transfer based on the fourth prompt message, then do not process the transfer request.

[0127] Exemplarily, the fourth prompt information may be, for example, a prompt message sent by the service end to the user end of the family account, and a prompt box pops up on the client end of the family account, and the user corresponding to the family account can feedback through the prompt box whether to continue the transfer request. Alternatively, the service end may ask the user corresponding to the family account whether to continue the transfer through a voice call, and the user may feedback through voice description whether to continue the transfer request. For example, the service end may send a risk warning SMS to the family account, and the family account may feedback whether to continue the transfer request based on the SMS prompt.

[0128] S306: Continue to execute the transfer processing operation.

[0129] The method provided in this application processes the target transfer processing request accordingly according to the abnormal risk level. The processing method of the target transfer processing request can be adjusted according to different abnormal risk levels, and is applicable to various types of transfer scenarios, with strong adaptability and flexibility. That is, it can more effectively protect the property safety of users and improve the user experience.

[0130] The following is a specific example to illustrate how to implement the transfer process. Figure 4 A flow chart of reflecting transfer processing through changes in a user interface provided in an embodiment of the present application. Figure 5 A flow chart of a transfer processing method provided in an embodiment of the present application is shown as follows: Figure 5 As shown, the method may include the following steps:

[0131] S501. The server responds to a target transfer processing request sent by a target client of a target account, and determines whether the target transfer processing request has an abnormal risk according to target information and transfer setting information of the target account.

[0132] For example, Figure 4 As shown in a, b, and c, the target client inputs the target transfer processing request.

[0133] S502: In the case of abnormal risk, the server outputs a second prompt message to instruct to authenticate the target user.

[0134] For example, Figure 4 As shown in d, the target client outputs the second prompt information.

[0135] S503: When the identity authentication is passed, the server outputs first prompt information to the target client, and obtains transfer intention description information fed back by the target client based on the first prompt information.

[0136] For example, Figure 4 As shown in e, the target client outputs the first prompt information.

[0137] S504: The server determines the abnormal risk level corresponding to the target transfer processing request based on the transfer intention description information.

[0138] If the abnormal risk level is the first risk level, execute S509. If the abnormal risk level is the second risk level, execute S505. If the abnormal risk level is the third risk level, execute S506.

[0139] S505, the server outputs a third prompt message indicating that there is a transfer risk to the target client, and if the target client receives feedback based on the third prompt message, determines whether to continue the transfer operation based on the information. If yes, execute S509, if no, execute S510.

[0140] S506. The server determines the target processing method of the target transfer processing request based on whether the target account has a family account set up, and processes it based on the target processing method. If yes, execute S508. If not, execute S507.

[0141] S507, the server outputs the third prompt information of the transfer risk to the target client, and triggers the target platform to issue a transfer warning prompt to the target user, if the target client receives the information based on the third prompt information and the transfer warning prompt feedback, and determines whether to continue the transfer operation based on the information, if yes, execute S509, if no, execute S510.

[0142] S508. The server outputs a fourth prompt message to the user end corresponding to the family account indicating that there is a transfer risk in the target account. If the server receives information fed back by the user end corresponding to the family account based on the fourth prompt message, and determines whether to continue the transfer operation based on the information, if so, execute S509; if not, execute S510.

[0143] S509: The server continues to execute the transfer processing operation.

[0144] S510: The server ends the transfer processing operation.

[0145] For example, Figure 4 As shown in f, the target client indicates that the transfer is completed.

[0146] The method provided in this application realizes a more comprehensive identification and assessment of abnormal risks by comprehensively analyzing user information, login records, transfer history, communication data and transfer settings. The risk level is further determined by obtaining the user's transfer intention description information, and the target transfer processing request is processed accordingly according to the abnormal risk level. The processing method of the target transfer processing request can be adjusted according to different abnormal risk levels, which is suitable for various types of transfer scenarios and has strong adaptability and flexibility. This can not only more effectively protect the user's property safety, but also improve the user experience.

[0147] The above is the method of the embodiment of the present application. The device provided by the embodiment of the present application is described below.

[0148] Figure 6 A schematic diagram of a transfer processing device provided in an embodiment of the present application is shown in FIG. Figure 6 As shown, the transfer processing device includes: a first processing module 601, an interaction module 602, a second determination module 603 and a processing module 604.

[0149] The first determination module 601 is used to respond to the target transfer processing request sent by the target client of the target account, and determine whether the target transfer processing request has an abnormal risk according to the target information and the transfer setting information of the target account. The target information includes: the target user information corresponding to the target account, the login information of the target account, the transfer information of the target account, and the communication information of the user within a preset time before triggering the target transfer processing request.

[0150] The interaction module 602 is used to output first prompt information to the target client when there is an abnormal risk, and obtain transfer intention description information fed back by the target client based on the first prompt information.

[0151] The second determination module 603 is used to determine the abnormal risk level corresponding to the target transfer processing request based on the transfer intention description information.

[0152] The processing module 604 is used to process the target transfer processing request based on the transfer processing method corresponding to the abnormal risk level.

[0153] Optionally, the first determination module 601 is specifically configured to determine whether the target transfer processing request hits a risk identification rule in an abnormal risk identification rule set according to the target information, the transfer setting information of the target account, the account blacklist library, and the abnormal risk identification rule set. If at least one abnormal risk identification rule is hit, it is determined that the target transfer processing request has an abnormal risk.

[0154] For example, the first determination module 601 is specifically used to: determine whether the target transfer processing request hits the abnormal risk identification rule related to the user information based on the target user information. Determine whether the target transfer processing request hits the abnormal risk identification rule related to the transfer based on the transfer information of the target account and the transfer setting information of the target account. Calculate the abnormal risk score based on the login information of the target account and the transfer information of the target account, and determine whether the target transfer processing request hits the abnormal risk identification rule related to the abnormal risk score based on the abnormal risk score. Determine whether the target transfer processing request hits the risk identification rule related to the account based on the transfer account information in the transfer information of the target account, the account information in the communication information, and the account blacklist library. Determine whether the target transfer processing request hits the risk identification rule related to the communication behavior based on the communication information.

[0155] Optionally, the interaction module 602 is specifically configured to obtain input data of the target client based on the first prompt information. If the input data is text data, the transfer intention description information is obtained based on the text data. If the input data is voice data, the voice data is interpreted to obtain the transfer intention description information.

[0156] Optionally, the interaction module 602 is specifically configured to output a second prompt message, wherein the second prompt message is used to indicate that the target user is to be authenticated. The target user's identity information collected based on the second prompt message is obtained. The target user is authenticated based on the identity information. If the identity authentication is successful, the input data of the target client based on the first prompt message is obtained.

[0157] Optionally, the second determination module 603 is specifically configured to extract transfer intention keywords from the transfer intention description information, and obtain the abnormal risk level based on the transfer intention keywords using the abnormal risk level recognition model.

[0158] Optionally, the processing module 604 is specifically used to perform transfer processing on the target transfer processing request if the abnormal risk level is the first risk level. If the abnormal risk level is the second risk level, a third prompt message indicating the existence of a transfer risk is output to the target client, and if confirmation information of continuing the transfer based on the third prompt message is received from the target client, the target transfer processing request is transferred. If the abnormal risk level is the third risk level, a target processing method of the target transfer processing request is determined based on whether the target account is set with a family account, and the processing is performed based on the target processing method. Among them, the first risk level is less than the second risk level, and the second risk level is less than the third risk level.

[0159] For example, processing module 604 is specifically used to output third prompt information indicating that there is a transfer risk to the target client if the target account is not set with a family account, and trigger the target platform to issue a transfer warning prompt to the target user, and if confirmation information of continuing the transfer is received based on the third prompt information and the transfer warning prompt feedback to the target client, then transfer processing is performed on the target transfer processing request. If the target account is set with a family account, fourth prompt information indicating that there is a transfer risk in the target account is output to the user terminal corresponding to the family account, and if confirmation information of continuing the transfer is received based on the fourth prompt information feedback from the user terminal corresponding to the family account, then transfer processing is performed on the target transfer processing request.

[0160] The transfer processing device provided in the embodiment of the present application can be used to execute the aforementioned transfer processing method. Its implementation principle, process and beneficial effects can be found in the aforementioned embodiment and will not be repeated here.

[0161] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 7 As shown, the electronic device 700 may include: a memory 701 and a processor 702. Optionally, the electronic device may further include a transceiver 703, wherein the memory 701 and the processor 702 communicate; illustratively, the memory 701, the processor 702 and the transceiver 703 may communicate via a communication bus 704, the memory 701 is used to store a computer program, and the processor 702 executes the computer program to implement the method of the above embodiment.

[0162] Optionally, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The steps in the method embodiments disclosed in the present application may be directly implemented as being executed by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.

[0163] An embodiment of the present application further provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, a method in any of the above method embodiments is implemented.

[0164] An embodiment of the present application also provides a computer program product, including a computer program, which implements the method in any of the above method embodiments when the computer program is executed by a processor.

[0165] All or part of the steps of the above-mentioned method embodiments can be completed by hardware related to program instructions. The above-mentioned program can be stored in a readable memory. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the above-mentioned memory (storage medium) includes: read-only memory (ROM), RAM, flash memory, hard disk, solid state drive, magnetic tape, floppy disk, optical disc and any combination thereof.

[0166] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processing unit of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0167] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0168] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0169] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0170] It should be further noted that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flow chart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0171] It should be understood that the above-mentioned device embodiments are only illustrative, and the device of the present application can also be implemented in other ways. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0172] In addition, unless otherwise specified, each functional unit / module in each embodiment of the present application may be integrated into one unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of a software program module.

[0173] If the integrated unit / module is implemented in the form of hardware, the hardware may be a digital circuit, an analog circuit, etc. The physical implementation of the hardware structure includes but is not limited to transistors, memristors, etc. Unless otherwise specified, the processor may be any appropriate hardware processor, such as CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0174] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0175] In the above embodiments, the description of each embodiment has its own emphasis. For the part not described in detail in a certain embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0176] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0177] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for processing transfer, characterized in that: The method comprises: In response to a target transfer processing request sent by a target client of a target account, determining whether the target transfer processing request has an abnormal risk according to target information and transfer setting information of the target account; the target information includes: target user information corresponding to the target account, login information of the target account, transfer information of the target account, and communication information of users within a preset time period before triggering the target transfer processing request; In the case of an abnormal risk, outputting first prompt information to the target client, and obtaining transfer intention description information fed back by the target client based on the first prompt information; Determining, based on the transfer intention description information, an abnormal risk level corresponding to the target transfer processing request; The target transfer processing request is processed based on the transfer processing method corresponding to the abnormal risk level.

2. The method according to claim 1, characterized in that The determining, based on the target information and the transfer setting information of the target account, whether the target transfer processing request has an abnormal risk includes: Determine whether the target transfer processing request matches a risk identification rule in the abnormal risk identification rule set according to the target information, the transfer setting information of the target account, the account blacklist library, and the abnormal risk identification rule set; When at least one abnormal risk identification rule is matched, it is determined that the target transfer processing request has an abnormal risk.

3. The method according to claim 2, characterized in that The determining, based on the target information, the transfer setting information of the target account, the account blacklist library, and the abnormal risk identification rule set, whether the target transfer processing request hits at least one risk identification rule in the abnormal risk identification rule set includes: Based on the target user information, determining whether the target transfer processing request matches an abnormal risk identification rule related to the user information; Based on the transfer information of the target account and the transfer setting information of the target account, determining whether the target transfer processing request matches an abnormal risk identification rule related to the transfer; Calculating an abnormal risk score based on the login information of the target account and the transfer information of the target account, and determining whether the target transfer processing request hits an abnormal risk identification rule related to the abnormal risk score based on the abnormal risk score; Based on the transfer account information in the transfer information of the target account, the account information in the communication information, and the account blacklist library, determining whether the target transfer processing request hits a risk identification rule related to the account; Based on the communication information, it is determined whether the target transfer processing request matches a risk identification rule related to the communication behavior.

4. The method according to any one of claims 1 to 3, characterized in that: The obtaining the transfer intention description information fed back by the target client based on the first prompt information includes: Acquire input data of the target client based on the first prompt information; If the input data is text data, obtaining the transfer intention description information based on the text data; If the input data is voice data, the intention of the voice data is understood to obtain the transfer intention description information.

5. The method according to claim 4, characterized in that Before obtaining the input data of the target client based on the first prompt information, the method further includes: Outputting second prompt information, where the second prompt information is used to instruct to authenticate the target user; Acquire the target user identity information collected by the target client based on the second prompt information feedback; authenticating the target user based on the identity information; The obtaining input data of the target client based on the first prompt information includes: When the identity authentication is passed, input data of the target client based on the first prompt information is obtained.

6. The method according to any one of claims 1 to 3, characterized in that: The determining, based on the transfer intention description information, the abnormal risk level corresponding to the target transfer processing request includes: Extracting transfer intention keywords from the transfer intention description information; Based on the transfer intention keywords, the abnormal risk level is obtained using an abnormal risk level identification model.

7. The method according to any one of claims 1 to 3, characterized in that: The processing of the target transfer processing request based on the transfer processing method corresponding to the abnormal risk level includes: If the abnormal risk level is the first risk level, performing transfer processing on the target transfer processing request; If the abnormal risk level is the second risk level, outputting third prompt information indicating that there is a transfer risk to the target client, and if confirmation information of continuing the transfer fed back by the target client based on the third prompt information is received, performing transfer processing on the target transfer processing request; If the abnormal risk level is the third risk level, the target processing method of the target transfer processing request is determined based on whether the target account is set up with a family account, and processing is performed based on the target processing method; wherein, the first risk level is lower than the second risk level, and the second risk level is lower than the third risk level.

8. The method according to claim 7, characterized in that The determining of the target processing method of the target transfer processing request based on whether the target account is set with a family account includes: If the target account is not set with a family account, outputting a third prompt message indicating that there is a transfer risk to the target client, and triggering the target platform to issue a transfer warning prompt to the target user, and if receiving confirmation information of continuing the transfer based on the third prompt message and the transfer warning prompt feedback to the target client, performing transfer processing on the target transfer processing request; If the target account is set with a family account, a fourth prompt message indicating that there is a transfer risk to the target account is output to the user terminal corresponding to the family account. If confirmation information of continuing the transfer is received from the user terminal corresponding to the family account based on the fourth prompt message, the target transfer processing request is transferred.

9. A transfer processing device, characterized in that: The device comprises: A first determination module is configured to respond to a target transfer processing request sent by a target client of a target account, and determine whether the target transfer processing request has an abnormal risk according to target information and transfer setting information of the target account; the target information includes: target user information corresponding to the target account, login information of the target account, transfer information of the target account, and communication information of users within a preset time period before triggering the target transfer processing request; An interaction module, configured to output first prompt information to the target client when there is an abnormal risk, and obtain transfer intention description information fed back by the target client based on the first prompt information; A second determination module, configured to determine an abnormal risk level corresponding to the target transfer processing request based on the transfer intention description information; A processing module is used to process the target transfer processing request based on the transfer processing method corresponding to the abnormal risk level.

10. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor.

12. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 8 when being executed by a processor.

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