Bank data processing method and device and electronic equipment

Abstract

The invention provides a bank data processing method and device and electronic equipment, and relates to the technical field of data processing, and the method comprises the steps: in response to a transaction request, obtaining behavior data, related to a business activity of a bank, of a user in a target application program, so as to judge whether to start a risk detection function or not; if the target application program is determined to be enabled, determining an associated application program which corresponds to the target application program in the current service scene and is used for risk detection according to scene information corresponding to the current service scene; and obtaining the to-be-detected data from the interface of the application program module corresponding to the associated application program based on the preset interface, performing risk detection on the to-be-detected data and the behavior data by using the determined target detection mode, and executing the transaction operation corresponding to the transaction request after the detection is passed. And the efficiency, accuracy and flexibility of risk detection in banking business are improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a banking data processing method, device and electronic equipment. Background Art

[0002] In the financial field and banking applications, risk detection of user behavior in applications is an important measure to ensure transaction security.

[0003] In the prior art, a static rule model is usually used to perform risk detection on a large amount of operation data collected from users in an application. For example, a static rule model is used to perform risk detection on a large amount of operation data from users in a bank transfer application. The static rule model performs risk detection based on predefined rules and thresholds.

[0004] However, due to the large amount of data to be detected, the efficiency of using static rule models for detection is low, and static rule models are also difficult to adapt to rapidly changing user behaviors and lack a certain degree of flexibility. Summary of the invention

[0005] The present application provides a banking data processing method, device and electronic device for solving the problems of low efficiency of risk detection using static rule models, difficulty in adapting to rapidly changing user behaviors, and lack of flexibility.

[0006] In a first aspect, the present application provides a banking data processing method, which is applied to a target application program, and the method comprises:

[0007] In response to a transaction request initiated by a user through a target application, obtaining behavior data of the user in the target application, and determining whether to enable a risk detection function according to the behavior data; the behavior data includes at least one type of data related to the business activities of the bank;

[0008] If it is determined to enable the risk detection function, a configuration list for risk detection corresponding to the target application is determined according to the scenario information corresponding to the current business scenario, wherein the configuration list is used to indicate: an associated application corresponding to the current business scenario determined from multiple applications;

[0009] Wherein, different associated applications correspond to interfaces of respective application modules; the application modules include communication module, call module, media management module and browser module;

[0010] Acquire the data to be detected from the interface of the application module corresponding to the associated application based on a preset interface, wherein the data to be detected includes at least one of the text data of the communication module, the call record data of the call module, the image data of the media management module, and the browsing record data of the browser module;

[0011] A target detection method is determined from at least one detection method to perform risk detection on the data to be detected and the behavior data, and a transaction operation corresponding to the transaction request is executed after the risk detection passes.

[0012] Optionally, the multiple applications are determined by a pre-stored configuration file; the scenario information includes: business information and user information; and the configuration file is used to indicate: associated applications corresponding to different scenario information.

[0013] Optionally, the method further includes:

[0014] Visually displaying a configuration page; the configuration page includes a plurality of configuration options, and the configuration options are used to configure: risk preference information and application authorization information;

[0015] In response to a user's touch operation on the plurality of configuration options on the configuration page, an associated application corresponding to at least a portion of the scene information in the configuration file is adjusted to obtain an adjusted configuration file.

[0016] Optionally, the configuration file further includes: a pre-configured active duration threshold corresponding to each application; and determining a configuration list for risk detection corresponding to the target application according to scenario information corresponding to the current business scenario, including:

[0017] Determining at least one candidate associated application according to the scenario information and the configuration file;

[0018] The active duration of the at least one candidate associated application is obtained, and a final associated application is determined from the at least one candidate associated application according to the active duration and an active duration threshold.

[0019] Optionally, according to the scenario information corresponding to the current business scenario, a configuration list for risk detection corresponding to the target application is determined, including:

[0020] Determine the current risk level based on the scenario information corresponding to the current business scenario;

[0021] A configuration list for risk detection corresponding to the target application is determined based on the current risk level; different risk levels correspond to different numbers of associated applications.

[0022] Optionally, the application module further includes a clipping service module, which obtains user behavior data in the target application and determines whether to enable the risk detection function according to the behavior data, including:

[0023] Acquiring behavior data from the clipping service module based on the preset interface;

[0024] Parsing the behavior data to identify the account information and transaction amount to be traded;

[0025] An initial risk detection is performed on the account information and transaction amount to be traded, and based on the result of the initial risk detection, it is determined whether to enable the risk detection function.

[0026] Optionally, the method further includes:

[0027] After the risk detection passes, determining the location information of the first device of the user and the location information of the second device having a binding relationship with the first device;

[0028] Determining a target verification strategy based on the location information of the first device and the location information of the second device;

[0029] The transaction request is securely verified using the target verification strategy.

[0030] Optionally, the method further includes:

[0031] Obtaining user identity information of the user in the target application;

[0032] Obtaining device information of self-service terminals within a preset time and / or preset area from the cloud using a preset protocol, and determining whether the user identity information exists in the device information;

[0033] When it is determined that the user identity information exists in the device information and the business status of the user in the current business scenario is unfinished, prompt information is generated based on the transaction request of the user in the target application.

[0034] In a second aspect, the present application provides a banking data processing device, applied to a target application, the device comprising:

[0035] a judgment module, configured to respond to a transaction request initiated by a user through a target application, obtain behavior data of the user in the target application, and judge whether to enable the risk detection function according to the behavior data; the behavior data includes at least one type of data related to the business activities of the bank;

[0036] A determination module, for determining, upon determining to enable the risk detection function, a configuration list for risk detection corresponding to a target application according to scenario information corresponding to a current business scenario, wherein the configuration list is used to indicate: associated applications corresponding to the current business scenario determined from a plurality of applications; wherein different associated applications correspond to interfaces of respective application modules; and the application modules include a communication module, a call module, a media management module, and a browser module;

[0037] an acquisition module, configured to acquire the data to be detected from the interface of the application module corresponding to the associated application based on a preset interface, wherein the data to be detected includes at least one of the text data of the communication module, the call record data of the call module, the image data of the media management module, and the browsing record data of the browser module;

[0038] The detection module is used to determine a target detection method from at least one detection method to perform risk detection on the data to be detected and the behavior data, and execute the transaction operation corresponding to the transaction request after the risk detection passes.

[0039] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0040] The memory stores computer-executable instructions;

[0041] The processor executes the computer-executable instructions stored in the memory to implement the method as described in any one of the first aspects.

[0042] In summary, the present application provides a banking data processing method, device and electronic device, which are applied to a target application, and in response to a transaction request initiated by a user through the target application, obtain the user's behavior data in the target application, and then determine whether to enable the risk detection function based on the user's behavior data in the target application, that is, through at least one type of data related to the bank's business activities. This dynamic activation mechanism dynamically determines according to specific circumstances, which can reduce unnecessary detections and thus improve overall efficiency. Furthermore, if it is determined that the risk detection function needs to be enabled, a configuration list is generated based on the specific information of the current business scenario, and the configuration list indicates which associated applications need to participate in risk detection. This configuration is dynamically generated based on current business needs and user behavior patterns, and then based on preset interfaces. The data to be detected is obtained from the interface of the application module corresponding to the associated application determined in the configuration list, such as the data to be detected includes at least one of the text data of the communication module, the call record data of the call module, the image data of the media management module, and the browsing record data of the browser module. Further, the user behavior data from the target application and the data to be detected obtained from the associated application are combined to perform comprehensive risk detection, and the transaction operation corresponding to the transaction request is executed after the risk detection passes. This combination of multi-source data enables risk detection to understand user behavior and potential risks more comprehensively, overcomes the dependence and limitations of the static rule model on a single data source, and this combination of multi-source data enables risk detection to be not limited to the data of a single application, thereby improving the accuracy of detection and the security of transactions. Therefore, the present application uses these dynamic and flexible mechanisms to select the data of the associated application to be read according to the actual situation, which can effectively respond to the rapid changes in user behavior and improve the efficiency and flexibility of risk detection, especially the efficiency and flexibility of risk detection in banking business. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0044] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application;

[0045] Figure 2 A flowchart of a banking data processing method provided in an embodiment of the present application;

[0046] Figure 3 A schematic diagram of the structure of a banking data processing device provided in an embodiment of the present application;

[0047] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0048] 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

[0049] In order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first", "second" and the like are used to distinguish the same items or similar items with substantially the same functions and effects. For example, the first device and the second device are only used to distinguish different devices, and their order is not limited. Those skilled in the art can understand that the words "first", "second" and the like do not limit the quantity and execution order, and the words "first", "second" and the like do not necessarily limit them to be different.

[0050] It should be noted that, in this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in this application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0051] In this application, "at least one" means one or more, and "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0052] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of financial data or user data and other information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals. It should be noted that in the embodiments of this application, some existing solutions in the industry such as certain software, components, models, etc. may be mentioned, and they should be considered as exemplary. Their purpose is only to illustrate the feasibility of the implementation of the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0053] In one possible implementation, a static rule model can be used to perform risk detection on a large amount of operation data collected from users in an application. For example, a static rule model can be used to perform risk detection on a large amount of operation data from users in a bank transfer application. The static rule model performs risk detection based on predefined rules and thresholds.

[0054] However, due to the large amount of data to be detected, the efficiency of using static rule models for detection is low, and static rule models are also difficult to adapt to rapidly changing user behaviors and lack a certain degree of flexibility.

[0055] In response to the above problems, the present application provides a banking data processing method, which is applied to a target application, such as an online banking application. Specifically, in response to a transaction request initiated by a user through the target application, the user's behavior data in the target application is obtained, and then the user's behavior data in the target application, that is, at least one type of data related to the bank's business activities, is used to determine whether to enable the risk detection function. This dynamic activation mechanism dynamically determines according to specific circumstances, which can reduce unnecessary detections and thus improve overall efficiency. Furthermore, if it is determined that the risk detection function needs to be enabled, a configuration list is generated based on the specific information of the current business scenario, and the configuration list indicates which associated applications need to participate in risk detection. This configuration is dynamically generated based on current business needs and user behavior patterns, and then Based on the preset interface, the data to be detected is obtained from the interface of the application module corresponding to the associated application determined in the configuration list, such as the data to be detected includes at least one of the text data of the communication module, the call record data of the call module, the image data of the media management module, and the browsing record data of the browser module. Further, the user behavior data from the target application and the data to be detected obtained from the associated application are combined to perform comprehensive risk detection, and the transaction operation corresponding to the transaction request is executed after the risk detection passes. This combination of multi-source data enables risk detection to understand user behavior and potential risks more comprehensively, overcomes the dependence and limitations of the static rule model on a single data source, and this combination of multi-source data enables risk detection to be not limited to the data of a single application, thereby improving the accuracy of detection and improving the security of transactions. Therefore, the present application uses these dynamic and flexible mechanisms to select the data of the associated application to be read according to the actual situation, which can effectively respond to the rapid changes in user behavior and improve the efficiency and flexibility of risk detection, especially the efficiency and flexibility of risk detection in banking business.

[0056] For example, Figure 1 A schematic diagram of an application scenario provided in an embodiment of the present application, such as Figure 1As shown, the application scenario can be applied to the process of transferring money using a bank transfer application. The application scenario includes: a user's first terminal device 101, a bank transfer system 102 and a payee's second terminal device 103; the first terminal device 101 and the second terminal device 103 are installed with a bank transfer application (Application, APP), and the display interface of the APP has multiple applications.

[0057] Specifically, when a user transfers a certain amount of money to a payee, the user can perform the corresponding transfer operation on the first terminal device 101. However, when the payee is a stranger or the transfer behavior is a financial fraud, there is a certain security risk. Therefore, a method is needed to help users identify fraudulent means against mobile banking transfers.

[0058] When the user transfers money to the second terminal device 103 by performing the corresponding transfer operation on the first terminal device 101, the user needs to open the bank transfer APP on the first terminal device 101 and then input transaction data, such as bank card number, transfer amount, etc. After the bank transfer APP detects a transaction request initiated by the user in the bank transfer APP, such as a transfer request, it determines whether to enable the risk detection function based on the behavioral data of the above operation. For example, if the transfer amount is greater than a threshold, or if the user is determined to be an elderly person based on the behavioral data, the risk detection function can be enabled.

[0059] Furthermore, a configuration list for risk detection is determined based on the current transfer scenario, and the configuration list includes associated applications corresponding to the current transfer scenario determined from multiple applications in the first terminal device 101, such as associated applications such as text messages and call records, and then the data to be detected is obtained from the associated applications, such as the content of text messages in the past day, the frequency of calls with a certain person, and other data, and then risk detection is performed on these data to be detected and the user's behavior data in the target application to identify whether there is any fraud in mobile banking transfers, thereby increasing the security of transfer transactions.

[0060] Among them, the target detection method can be determined from at least one preset detection method, and risk detection can be performed on the data to be detected and the user's behavior data in the target application. The present application does not specifically limit the method for selecting the target detection method. For example, the target detection method can be selected by using preset rule matching, machine learning models, etc. The at least one detection method can be a bank-customized detection method or a risk detection method formulated according to business needs.

[0061] Optionally, if the result of the risk detection is safe, then in response to the transfer request of the first terminal device 101, the bank transfer system 102 automatically completes the transfer operation for the customer, that is, transfers the corresponding amount to the payee's account. Correspondingly, the payee can view it based on the APP of the second terminal device 103.

[0062] The terminal device may also be referred to as a user terminal, user equipment (UE), mobile station (MS), mobile terminal, terminal, etc. In practical applications, user terminals are, for example, desktop computers, notebooks, personal digital assistants (PDA), personal computers (PC), smart phones, tablet computers, vehicle-mounted devices, wearable devices (such as smart watches and smart bracelets), smart home devices (such as smart display devices), etc., and the embodiments of the present application do not specifically limit this.

[0063] It should be noted that the embodiments of the present application do not specifically limit the scenarios for applying bank data processing methods for risk detection. The above is only an example. Optionally, the target application can be an application related to the bank's business activities, such as a bank financial management APP, a bank digital wallet APP, a credit card management APP, etc. The embodiments of the present application do not specifically limit this.

[0064] It should be noted that the main application scenarios in this application and the contents described in the following embodiments are business scenarios related to the banking or financial industry and will not be repeated later.

[0065] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0066] Figure 2 A flow chart of a banking data processing method provided in an embodiment of the present application is provided. The banking data processing method can be applied to the target application of the above-mentioned terminal device, such as Figure 2 As shown, the bank data processing method includes the following steps:

[0067] S201. In response to a transaction request initiated by a user through a target application, obtain the user's behavior data in the target application, and determine whether to enable a risk detection function based on the behavior data; the behavior data includes at least one type of data related to the bank's business activities.

[0068] In the embodiment of the present application, the transaction request may be a transfer request, a credit card consumption request, a request to purchase a financial product, etc. The embodiment of the present application does not specifically limit the type of transaction request. The transaction requests generated in different types of target applications are different, or the transaction requests corresponding to different transaction operations performed in the target application are different.

[0069] Therefore, the behavioral data in the target application covers many aspects of bank operations, including customer information, transaction records, financial data, operation data, etc. For example, it may include the user's login information, access path, click behavior, operation frequency, timestamp, etc. The embodiment of this application does not specifically limit the content of the behavioral data.

[0070] Exemplarily, after a user initiates a transaction request through a target application, the target application can analyze the collected behavior data to identify the user's operation mode and behavior characteristics. The analysis method can include statistical analysis, pattern recognition, machine learning models, etc., so as to extract useful information from a large amount of data. Further, based on the analysis of the operation mode and behavior characteristics, it is determined whether there are abnormalities or potential risks. For example, when abnormalities such as abnormal access frequency, abnormal geographical location login, abnormal transaction operation behavior, etc. are detected, the risk detection function can be enabled.

[0071] It should be noted that the embodiment of the present application does not specifically limit the process of analyzing behavioral data to determine whether to enable the risk detection function and the method used. The above is only an example.

[0072] It is understandable that by obtaining and analyzing user behavior data to promptly determine whether to enable the risk detection function, potential security threats such as account hijacking, fraud, etc. can be more effectively prevented, thereby improving overall security.

[0073] S202. If it is determined to enable the risk detection function, a configuration list for risk detection corresponding to the target application is determined based on the scenario information corresponding to the current business scenario, and the configuration list is used to indicate: associated applications corresponding to the current business scenario determined from multiple applications, wherein different associated applications correspond to interfaces of their respective application modules; the application modules include a communication module, a call module, a media management module and a browser module.

[0074] In the embodiment of the present application, the scenario information may include the type of operation being performed by the user, business information, user information, user permissions, etc. The embodiment of the present application does not limit the specific content corresponding to the scenario information.

[0075] In the present application, the communication module is used to obtain text data, such as message content and sending records of text messages, emails, etc.; the call module is used to obtain call record data, including call time, duration, frequency and participants; the media management module is used to obtain image data, such as pictures uploaded or received by users; the browser module is used to obtain browsing record data, such as visited websites and timestamps.

[0076] Since the configuration list is used to indicate the associated applications that need to be involved in the risk detection process, it means that the data sources that need to be monitored and analyzed can be dynamically adjusted according to different business scenarios. These associated applications may be other applications that have data interaction, access rights or functional associations with the target application. By identifying these associated applications, more comprehensive data to be detected can be obtained from the interfaces of the application modules corresponding to these associated applications.

[0077] For example, by dynamically generating a configuration list according to specific business scenarios, risk detection can be performed in a more targeted manner. This targeting ensures that the detection process can accurately identify potential risks associated with current operations.

[0078] S203. Obtain the data to be detected from the interface of the application module corresponding to the associated application, wherein the data to be detected includes at least one of the text data of the communication module, the call record data of the call module, the image data of the media management module, and the browsing record data of the browser module.

[0079] In the present application, the data to be detected is obtained from the interfaces of specific application modules of different associated applications through a preset unified interface, such as obtaining text message content and call records from the communication module and the call module. Correspondingly, the user's behavior data is obtained from the target application, such as obtaining behavior data from a bank transfer APP, which may include: transaction data, i.e., transaction records conducted by users in the bank transfer APP, such as purchase history, amount and transaction time, etc.; historical browsing data, i.e., the user's browsing history in the bank transfer APP, such as the pages visited and the duration of stay, etc.

[0080] It should be noted that obtaining data from different application modules makes it possible to handle a variety of risk scenarios, especially scenarios such as communication fraud, abnormal transactions, and the dissemination of inappropriate content.

[0081] S204: Determine a target detection method from at least one detection method to perform risk detection on the data to be detected and the behavior data, and execute a transaction operation corresponding to the transaction request after the risk detection passes.

[0082] In the present application, the data to be detected obtained from the associated application can be integrated with the user behavior data in the target application, and then the integrated data can be used for risk detection.

[0083] Optionally, the above integration process may involve steps such as data cleaning, format conversion, and data matching to ensure that data from different sources can be effectively combined; the risk detection process may involve a variety of analysis techniques, such as pattern recognition, anomaly detection, machine learning algorithms, etc., to identify potential security threats or abnormal behaviors. The embodiments of the present application do not specifically limit the integration process and the risk detection process.

[0084] Therefore, by obtaining multiple types of data from multiple application modules, a more comprehensive risk analysis can be performed. This comprehensiveness helps to identify complex risks across modules. Moreover, by obtaining the data to be detected in the application modules corresponding to the associated applications and the behavioral data in the target applications for comprehensive analysis, anomalies and potential threats can be more accurately identified, improving the accuracy of detection and providing a safer user experience. Therefore, by using interfaces and modular design, different data sources and detection methods can be flexibly integrated and expanded. This flexibility makes it possible to quickly adapt to new risks and business needs. By selecting a suitable target detection method, the use of computing resources can be optimized, unnecessary analysis and processing can be avoided, efficiency can be improved, and the reliability of detection results and user trust can be improved.

[0085] In this way, after the user initiates a transaction request through the target application, by analyzing the user behavior in the early stage, a more in-depth risk detection function can be enabled only when potential risks are detected. This on-demand activation strategy reduces unnecessary computing burden and improves overall efficiency. By analyzing user behavior data in real time, it can quickly respond to potential security threats. This rapid response capability is crucial to protecting user data and security. Furthermore, a configuration list can be dynamically generated so that applications related to the current scenario can be selected according to changes in business needs. This flexibility makes it possible to adapt to different business scenarios and user behavior patterns, improving adaptability. By identifying and utilizing data from associated applications, cross-application collaborative risk detection can be achieved. This collaborative capability improves the comprehensiveness and depth of detection. By integrating data from multiple applications, user behavior can be analyzed more comprehensively, which helps to identify complex risks and anomalies that cannot be revealed by a single data source, thereby improving the accuracy of detection. Through more comprehensive and accurate risk detection, potential risks can be more effectively prevented, and overall security and user experience can be improved.

[0086] Optionally, the multiple applications are determined by a pre-stored configuration file; the scenario information includes: business information and user information; and the configuration file is used to indicate: associated applications corresponding to different scenario information.

[0087] In an embodiment of the present application, a pre-stored configuration file is used to determine the association relationship between multiple applications. The configuration file contains a mapping relationship between different scenario information and associated applications. This pre-stored configuration file can provide a quick search and matching mechanism for determining the associated applications required for risk detection based on the scenario information. This mechanism makes it possible to quickly adapt to different business scenarios and user needs.

[0088] Among them, the scenario information is composed of business information and user information. The business information includes the current transaction type, operation process, business goals set by the user, etc. For example, the transaction type can indicate that the current business scenario is password-free payment, and the business goal set by the user can indicate whether to perform weak detection or strong detection, etc.; user information includes the user's role, authority, historical behavior data, etc. For example, the user's role can indicate an elderly or a young person. The embodiment of the present application does not limit the specific content corresponding to the business information and user information, and it can be set based on the actual application scenario requirements.

[0089] Optionally, configuration files can be updated and adjusted based on changes in business requirements and user behavior to quickly adapt to new business scenarios and changing user behavior patterns. The use of configuration files makes updates and maintenance easier. When business requirements change or new applications are added, only the configuration files need to be updated, thereby reducing development and maintenance costs.

[0090] In this way, by using pre-stored configuration files, associated applications can be quickly determined, and by pre-configuring the relationship between scenario information and associated applications, the complexity of real-time judgment is simplified and the burden of real-time calculation and judgment is reduced. This efficiency improvement helps to maintain good performance under high load conditions and improves accuracy in different scenarios. The use of configuration files ensures that the selection of associated applications is based on proven logic and rules, which can provide a fast search mechanism and respond to different business scenarios and user requests more quickly.

[0091] Optionally, the method further includes:

[0092] Visually displaying a configuration page; the configuration page includes a plurality of configuration options, and the configuration options are used to configure: risk preference information and application authorization information;

[0093] In response to a user's touch operation on the plurality of configuration options on the configuration page, an associated application corresponding to at least a portion of the scene information in the configuration file is adjusted to obtain an adjusted configuration file.

[0094] In the embodiment of the present application, risk preference information refers to the user's ability to set preferences for different risk levels, and the risk preference information is used to adjust the associated applications corresponding to each scenario information; application authorization information refers to the user's ability to manage which applications are authorized to access data or participate in risk detection, which involves the configuration and adjustment of application permissions.

[0095] Optionally, the multiple configuration options may include: strategy configuration options, recommended label options and risk preference rule options; the strategy configuration options include risk detection strategies, account unblocking strategies and risk reminder strategies; the recommended label options include at least one type of risk factors required for risk detection.

[0096] Risk detection strategy refers to how users can configure risk detection, including the selection of algorithms to be used, detection frequency, and the depth and breadth of detection.

[0097] Account unblocking policy refers to the conditions and processes that users can set when their account is blocked, such as the verification steps required, the supporting documents to be submitted, or the waiting time.

[0098] Risk reminder policy means that users can define how to remind users or administrators when risks are detected, including the method and content of reminders, such as reminders via text messages, emails, etc.

[0099] Therefore, the setting of strategy configuration options allows users to fine-tune the management of risk detection, account management and risk reminders.

[0100] Exemplarily, the user can select at least one type of risk factor as a recommended label, which is used to identify specific risk factors that require risk detection, such as "high-value transactions", "abnormal login locations", etc. The recommended label option is used to focus on specific risk factors to improve the pertinence and effectiveness of detection, so that users can select the most relevant risk factors for detection according to actual needs.

[0101] Users can also set risk preference rules for individuals or organizations, which define tolerance and response strategies for different risk levels. For example, users can choose to strictly monitor high-risk operations and adopt a loose strategy for low-risk operations; users can also adjust response strategies through risk preference rule options to optimize user experience. For example, to reduce unnecessary alerts or verification steps, you can choose to use multiple strategies or collect more information from associated applications for the elderly, while using fewer strategies or verifying information from associated applications for young people.

[0102] In this step, a visual configuration page is provided through the terminal device, through which the user can view and manage multiple configuration options. Furthermore, the user selects or adjusts the configuration options on the configuration page through touch operations. In response to these operations, the terminal device adjusts the associated applications corresponding to at least part of the scenario information in the configuration file, such as adding new associated applications, removing no longer needed applications, or modifying the permissions of existing applications, and then generates an adjusted configuration file based on the user's touch operations. The configuration file can reflect the user's latest risk preferences and application authorization settings, and is used to guide subsequent risk detection and management processes.

[0103] In the present application, a visual interface is provided to make complex configurations intuitive and easy to understand, and users can operate more conveniently. Through the visual interface, complex configuration management becomes more intuitive and simple, and users can effectively configure without in-depth understanding of the internal structure, which lowers the usage threshold. Since a variety of configuration options are provided on the configuration page, users are allowed to adjust the associated applications corresponding to at least part of the scene information according to their own needs and personal preferences. This flexibility makes it possible to adapt to different business environments and user needs, improve user satisfaction, and optimize risk management strategies through users' precise configuration of configuration files. This optimization helps to improve the reliability and accuracy of detection results, and can also better control data access rights, enhance security, and make risk management more efficient and personalized.

[0104] Optionally, the configuration file further includes: a pre-configured active duration threshold corresponding to each application; and determining a configuration list for risk detection corresponding to the target application according to scenario information corresponding to the current business scenario, including:

[0105] Determining at least one candidate associated application according to the scenario information and the configuration file;

[0106] The active duration of the at least one candidate associated application is obtained, and a final associated application is determined from the at least one candidate associated application according to the active duration and an active duration threshold.

[0107] In the present application, the configuration file may pre-define an active duration threshold for each application, which indicates the minimum usage time for an application to be considered "active" within a specific time period. If the active duration of an application exceeds the active duration threshold, it indicates that the application should be subject to focused detection.

[0108] Exemplarily, at least one candidate associated application can be identified based on the scenario information of the current business scenario and the configuration file. These candidate applications can be applications that are preliminarily considered to be possibly related to the current business scenario. Furthermore, the actual active duration of each candidate associated application is obtained, and the actual active duration of each candidate associated application is compared with its corresponding active duration threshold. When the active duration reaches or exceeds the threshold, the associated application is deemed to be the final associated application. These associated applications will be used in subsequent risk detection processes because they are considered to have sufficient activity and relevance in the current business scenario.

[0109] Among them, obtaining the actual active duration of each candidate associated application can be achieved by monitoring the application's usage log, access frequency and other data. The embodiment of the present application does not specifically limit the method of obtaining the active duration of the associated application.

[0110] Therefore, by screening the active duration, we can ensure that truly active and relevant applications in the current business scenario participate in risk detection. This correlation improves the accuracy and effectiveness of detection, and only selects applications with active duration greater than the threshold for detection, avoiding the waste of resources on inactive or irrelevant applications. This optimization helps to improve detection efficiency and response speed, and reduce unnecessary computing burden. By ensuring that the applications participating in the detection are sufficiently active, it can also reduce false detections caused by irrelevant data and improve the reliability of detection results.

[0111] Optionally, according to the scenario information corresponding to the current business scenario, a configuration list for risk detection corresponding to the target application is determined, including:

[0112] Determine the current risk level based on the scenario information corresponding to the current business scenario;

[0113] A configuration list for risk detection corresponding to the target application is determined based on the current risk level; different risk levels correspond to different numbers of associated applications.

[0114] Exemplarily, the target application can evaluate and determine the current risk level based on current business scenario information, such as transaction type, user information, transaction operations, etc. For example, the risk level can be divided into multiple levels such as low, medium, and high. The embodiments of the present application do not specifically limit the division of risk levels.

[0115] Furthermore, after determining the risk level, you can select applications related to the risk level according to predefined policies or rules to generate a configuration list based on the selected associated applications; different risk levels will correspond to different numbers and types of associated applications. For example, a high risk level corresponds to multiple associated applications, such as text messages, browsers, file management, calls, and other associated applications that need to be detected; a low risk level corresponds to one associated application, such as an application that has been opened in the recent period of time, which needs to be detected. The embodiment of the present application does not limit the number and type of associated applications that need to be detected for risk corresponding to different risk levels, and it can be set based on the actual application scenario requirements.

[0116] In this way, the present application can dynamically select associated applications for risk detection based on real-time business scenarios and risk conditions. This flexibility enables it to adapt to changing environments and threats and enhance overall security. Moreover, by determining the different numbers of associated applications for detection in the current business scenario through risk levels, computing resources can be used more effectively and unnecessary overhead can be avoided. This can improve the accuracy and effectiveness of risk detection while improving overall efficiency and performance.

[0117] Optionally, the application module further includes a clipping service module, which obtains user behavior data in the target application and determines whether to enable the risk detection function according to the behavior data, including:

[0118] Acquiring behavior data from the clipping service module based on the preset interface;

[0119] Parsing the behavior data to identify the account information and transaction amount to be traded;

[0120] An initial risk detection is performed on the account information and transaction amount to be traded, and based on the result of the initial risk detection, it is determined whether to enable the risk detection function.

[0121] In the present application, the user's behavior data can also be obtained from the clipping service module through a preset interface. The clipping service module is used to obtain the content copied, cut and pasted by the user, which may contain sensitive information, such as account information and transaction amount.

[0122] Exemplarily, after obtaining the content copied by the user from the clipping service module based on a preset interface, the content can be parsed to identify the account information to be traded and the transaction amount. Furthermore, an initial risk detection is performed on the identified account information to be traded and the transaction amount, such as checking the legality of the account information, the rationality of the transaction amount, and the degree of matching with the user's historical behavior, etc. The embodiment of the present application does not specifically limit the content of the initial detection.

[0123] Furthermore, based on the result of the initial risk detection, it is determined whether a more in-depth risk detection function needs to be enabled. If the initial detection result shows that there is a potential risk or anomaly, a comprehensive risk detection process is enabled, that is, S202-S204 is executed.

[0124] Among them, identifying the account information and transaction amount to be traded may include methods such as text parsing and pattern recognition to accurately extract relevant financial information. The embodiment of the present application does not specifically limit the identification method.

[0125] In this way, by obtaining data through the clipboard service module, the copy and paste operations performed by the user in the application can be captured. These operations may involve sensitive transaction information. Furthermore, by parsing the clipboard data, transaction-related information can be accurately identified and extracted, so as to perform more targeted initial risk detection. This initial risk detection, as a quick screening step, can effectively filter out low-risk operations and enable comprehensive detection only for high-risk operations. This hierarchical detection strategy optimizes resource utilization and improves detection efficiency. Through rapid initial detection, the detection and response time can be shortened, unnecessary comprehensive risk detection can be reduced, and the user experience can be improved. Users will not frequently trigger security alerts due to normal copy and paste operations, and can also enjoy a safer trading environment, that is, they can identify and prevent potential security threats earlier, such as fraudulent transactions and account information leakage, thereby improving overall security.

[0126] Optionally, the method further includes:

[0127] After the risk detection passes, determining the location information of the first device of the user and the location information of the second device having a binding relationship with the first device;

[0128] Determining a target verification strategy based on the location information of the first device and the location information of the second device;

[0129] The transaction request is securely verified using the target verification strategy.

[0130] In the embodiment of the present application, after the risk detection is passed, the user's transaction request such as a transfer request can be prepared to be processed. However, when transferring money, the transaction data still needs to be securely verified, such as SMS verification, password verification, face verification, gesture verification and other methods. After the verification is passed, the transaction transfer can be carried out. However, different user groups correspond to different verification strategies, and the existing verification strategies, such as SMS verification, face verification, etc., lack a certain degree of security. For example, when transferring money to the elderly, since the elderly have a weak sense of security, only security verification is performed through existing strategies, and the security is relatively low.

[0131] Therefore, after the risk detection is passed, the location information of the user's first device can be obtained, and at the same time, the location information of the second device that has a binding relationship with the first device, such as the terminal device of the user's children or other associated persons, can be obtained, and then based on the location information of the two devices obtained, the target verification strategy suitable for the current scenario is determined to perform security verification on the transfer request. For example, if the location information of the two devices shows that they are geographically close, a more relaxed verification strategy may be selected. At this time, the user's children or other associated persons can help view the transfer information of the first device; if the location information shows that they are far apart, a stricter verification strategy or more types of verification strategies may be selected to enhance the security of the verification.

[0132] Among them, the method of obtaining location information can be achieved through technologies such as Global Positioning System (GPS) and Wireless Fidelity (Wi-Fi) positioning, which is not limited in the embodiments of the present application.

[0133] In this way, by combining the device's location information, the user's real environment and behavior can be judged more accurately, and then the verification strategy can be dynamically adjusted according to the device's location information to avoid unnecessary strict verification processes, thereby improving the security of transfer requests. Since the present application can dynamically select verification strategies based on real-time location information, this flexibility makes it possible to adapt to different usage scenarios and risk levels, and then quickly respond to potential risks and conduct timely security verification and processing. This real-time risk management capability is crucial to protecting user assets and information security, thereby greatly improving the user experience.

[0134] Optionally, the method further includes:

[0135] Obtaining user identity information of the user in the target application;

[0136] Obtaining device information of self-service terminals within a preset time and / or preset area from the cloud using a preset protocol, and determining whether the user identity information exists in the device information;

[0137] When it is determined that the user identity information exists in the device information and the business status of the user in the current business scenario is unfinished, prompt information is generated based on the transaction request of the user in the target application.

[0138] In an embodiment of the present application, the user's identity information can be extracted from the target application. The identity information may include the user's account identification (ID), user name, ID number, etc., which is used to uniquely identify the user.

[0139] Exemplarily, a preset protocol may be used to obtain device information of self-service terminals within a specific time and / or specific area from the cloud. The device information may include the geographic location of the self-service terminal, usage records, and identity information of users interacting with the self-service terminal, etc., and then the device information obtained from the self-service terminal is checked to see whether the user identity information is included. This step is used to determine whether the user has used the self-service terminal within the preset time and / or area.

[0140] Furthermore, it is necessary to check whether the user's business status in the current business scenario is incomplete, that is, to determine whether the user has completed the corresponding business at the corresponding branch or counter service. If it is determined that the user identity information exists in the self-service terminal device information, and the user's business status in the current business scenario is incomplete, that is, the user has not completed the corresponding business at the corresponding branch or counter service, but the user has initiated a transfer request in the target application, then a prompt message can be generated to remind the user to complete the unfinished business, or to warn of possible risks.

[0141] The prompt information may be sent to a user's terminal device or to a staff member's terminal device, and this embodiment of the present application does not specifically limit this.

[0142] Optionally, the possible risk may be that after the staff reminds the user that the current business is risky, the user does not successfully complete the transaction at the counter, but continues to transfer money on the terminal device. The embodiments of the present application do not specifically limit the scenarios in which the possible risks may occur, and the above is merely an example.

[0143] Therefore, by checking the user's identity information and business status, potential security risks can be identified, such as suspicious transactions initiated by users at different locations at the same time. This multi-level verification improves overall security, and by identifying the user's unfinished business status and prompting the user when initiating a new transaction request, it can also prevent business conflicts or erroneous operations, thereby helping to maintain the integrity and consistency of business processes. In particular, the prompt information can help users identify unfinished tasks or potential problems, thereby avoiding unnecessary troubles and delays. This proactive reminder can improve user experience and satisfaction.

[0144] Optionally, the method further includes:

[0145] After the risk detection is passed, the target verification strategy can also be determined based on the user's environmental information and / or the user's behavioral data, so as to use the target verification strategy to perform security verification on the transfer request; wherein, the environmental information may include light intensity information, noise volume information, etc. For example, when the light intensity is too dim, the SMS verification strategy can be determined, and the face verification strategy is not suitable at this time; when the noise volume is noisy, the gesture verification strategy can be determined, and the audio and video verification strategy is not suitable at this time.

[0146] Exemplarily, the behavioral data may be data generated by multiple behavioral operations of a user in a target application. For example, if a user purchases financial products multiple times in an APP, each purchase requires security verification using a verification strategy. At this time, if the time interval between purchases of financial products is less than a threshold or the types are similar, the target verification strategy can be determined by referring to the previous (last) verification strategy.

[0147] In this way, by reusing previous verification strategies, the time and resources required to re-evaluate and formulate strategies can be reduced, the verification process can be simplified and accelerated, and the customer experience can be improved.

[0148] Therefore, this application can also formulate more personalized verification strategies based on the user's specific environment and behavior data to ensure that the verification process is both safe and does not affect the user experience, and dynamically adjust the verification strategy according to real-time environment and behavior changes to make it more adaptable.

[0149] Optionally, data in other application scenarios can also be processed for risk detection using steps similar to the banking data processing method, except that the type of behavioral data is different from the type of behavioral data in the banking data processing method, and other processing processes are similar. For example, it can be applied to the following application scenarios: when a user logs in or performs sensitive operations, the risk of account theft is detected based on the behavioral data corresponding to the user logging in to the APP or performing sensitive operations and the data of the associated applications; when a user conducts a transaction, the behavioral data corresponding to the user's transaction on the APP and the data of the associated applications are analyzed in real time to detect potential fraud; during the game, the player's behavioral data on the APP and the data of the associated applications are analyzed to identify and prevent cheating; when an employee accesses sensitive data, the potential risk of data leakage is detected based on the user's behavioral data on the APP and the data of the associated applications (such as document management systems, email services), etc.

[0150] Correspondingly, if applied to different application scenarios, the types of corresponding target applications may be different, and the number of target applications is at least one.

[0151] Exemplarily, behavioral data of users in at least one type of target application is obtained, and whether to enable the risk detection function is determined based on the behavioral data; the at least one type of target application may include: trading applications, game applications, financial management applications, enterprise management applications, etc.; if it is determined to enable the risk detection function, then based on the scenario information corresponding to the current business scenario, a configuration list for risk detection corresponding to at least one type of target application is determined, and the configuration list is used to indicate: associated applications corresponding to the current business scenario determined from multiple applications; wherein different associated applications correspond to interfaces of their respective application modules; based on a preset interface, data to be detected is obtained from the interface of the application module corresponding to the associated application, a target detection method is determined from at least one detection method to perform risk detection on the data to be detected and the behavior data, and corresponding transaction operations are performed after the risk detection passes.

[0152] It is understandable that the specific implementation principle and effect of the above-mentioned data processing method can refer to the relevant description and effect of the bank data processing method in the above-mentioned embodiment, and no further details will be given here. In the above-mentioned embodiment, the bank data processing method provided in the embodiment of the present application is introduced, and in order to realize the various functions in the method provided in the above-mentioned embodiment of the present application, the electronic device as the execution subject may include a hardware structure and / or a software module, and the above-mentioned functions are realized in the form of a hardware structure, a software module, or a hardware structure plus a software module. Whether one of the above-mentioned functions is executed in the form of a hardware structure, a software module, or a hardware structure plus a software module depends on the specific application and design constraints of the technical solution.

[0153] For example, Figure 3 A schematic diagram of the structure of a bank data processing device provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, the bank data processing device 300 is applied to a target application program, and the bank data processing device 300 includes:

[0154] The judgment module 310 is used to respond to a transaction request initiated by a user through a target application, obtain the user's behavior data in the target application, and judge whether to enable the risk detection function according to the behavior data; the behavior data includes at least one type of data related to the bank's business activities;

[0155] The determination module 320 is used to determine, when determining to enable the risk detection function, a configuration list for risk detection corresponding to the target application according to the scenario information corresponding to the current business scenario, wherein the configuration list is used to indicate: associated applications corresponding to the current business scenario determined from multiple applications; wherein different associated applications correspond to interfaces of respective application modules; and the application modules include a communication module, a call module, a media management module, and a browser module;

[0156] an acquisition module 330, configured to acquire the data to be detected from the interface of the application module corresponding to the associated application based on a preset interface, wherein the data to be detected includes at least one of the text data of the communication module, the call record data of the call module, the image data of the media management module, and the browsing record data of the browser module;

[0157] The detection module 340 is used to determine a target detection method from at least one detection method to perform risk detection on the data to be detected and the behavior data, and execute the transaction operation corresponding to the transaction request after the risk detection passes.

[0158] Optionally, the multiple applications are determined by a pre-stored configuration file; the scenario information includes: business information and user information; and the configuration file is used to indicate: associated applications corresponding to different scenario information.

[0159] Optionally, the bank data processing device 300 further includes a configuration module, wherein the configuration module is used to:

[0160] Visually displaying a configuration page; the configuration page includes a plurality of configuration options, and the configuration options are used to configure: risk preference information and application authorization information;

[0161] In response to a user's touch operation on the plurality of configuration options on the configuration page, an associated application corresponding to at least a portion of the scene information in the configuration file is adjusted to obtain an adjusted configuration file.

[0162] Optionally, the configuration file further includes: a pre-configured active duration threshold corresponding to each application; the determination module 320 is specifically configured to:

[0163] Determining at least one candidate associated application according to the scenario information and the configuration file;

[0164] The active duration of the at least one candidate associated application is obtained, and a final associated application is determined from the at least one candidate associated application according to the active duration and an active duration threshold.

[0165] Optionally, the determining module 320 is specifically configured to:

[0166] Determine the current risk level based on the scenario information corresponding to the current business scenario;

[0167] A configuration list for risk detection corresponding to the target application is determined based on the current risk level; different risk levels correspond to different numbers of associated applications.

[0168] Optionally, the application module further includes a clipping service module, and the determination module 310 is specifically configured to:

[0169] Acquiring behavior data from the clipping service module based on the preset interface;

[0170] Parsing the behavior data to identify the account information and transaction amount to be traded;

[0171] An initial risk detection is performed on the account information and transaction amount to be traded, and based on the result of the initial risk detection, it is determined whether to enable the risk detection function.

[0172] Optionally, the bank data processing device 300 further includes a verification module, wherein the verification module is used to:

[0173] After the risk detection passes, determining the location information of the first device of the user and the location information of the second device having a binding relationship with the first device;

[0174] Determining a target verification strategy based on the location information of the first device and the location information of the second device;

[0175] The transaction request is securely verified using the target verification strategy.

[0176] Optionally, the bank data processing device 300 further includes a prompt module, wherein the prompt module is used to:

[0177] Obtaining user identity information of the user in the target application;

[0178] Obtaining device information of self-service terminals within a preset time and / or preset area from the cloud using a preset protocol, and determining whether the user identity information exists in the device information;

[0179] When it is determined that the user identity information exists in the device information and the business status of the user in the current business scenario is unfinished, prompt information is generated based on the transaction request of the user in the target application.

[0180] It should be noted that the specific implementation principles and effects of the above-mentioned bank data processing device can be found in the relevant descriptions and effects corresponding to the above-mentioned embodiments, and will not be elaborated here.

[0181] The present application also provides a schematic diagram of the structure of an electronic device. Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 401 and a memory 402 communicatively connected to the processor; the memory 402 stores a computer program; the processor 401 executes the computer program stored in the memory 402, so that the processor 401 executes the method described in any of the above embodiments.

[0182] The memory 402 and the processor 401 may be connected via a bus 403 .

[0183] An embodiment of the present application further provides a computer-readable storage medium, which stores computer program execution instructions. When the computer program execution instructions are executed by a processor, they are used to implement the method described in any of the aforementioned embodiments of the present application.

[0184] An embodiment of the present application further provides a chip for executing instructions, wherein the chip is used to execute the method described in any of the aforementioned embodiments as executed by an electronic device in any of the aforementioned embodiments of the present application.

[0185] An embodiment of the present application further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method described in any of the aforementioned embodiments of the present application executed by an electronic device can be implemented.

[0186] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0187] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of this embodiment.

[0188] In addition, each functional module in each embodiment of the present application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The above-mentioned module-composed unit can be implemented in the form of hardware or in the form of hardware plus software functional units.

[0189] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the method described in each embodiment of the present application.

[0190] It should be understood that the above processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. The general-purpose processor can be a microprocessor or the processor can be any conventional processor, etc. The steps of the method disclosed in the application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0191] The memory may include high-speed random access memory (RAM), and may also include non-volatile memory (NVM), such as at least one disk storage, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a disk or an optical disk, etc.

[0192] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0193] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general or special computer.

[0194] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic device or a main control device.

[0195] 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.

[0196] It should be further noted that, although the various steps in the flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless there is a clear description 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 flowchart 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.

[0197] 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.

[0198] 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 claims.

[0199] The above is only a specific implementation of the embodiment of the present application, but the protection scope of the embodiment of the present application is not limited thereto, and any changes or replacements within the technical scope disclosed in the embodiment of the present application should be included in the protection scope of the embodiment of the present application. Therefore, the protection scope of the embodiment of the present application should be based on the protection scope of the claims.

Claims

1. A banking data processing method, characterized in that: Applied to a target application, the method comprises: In response to a transaction request initiated by a user through a target application, obtaining behavior data of the user in the target application, and determining whether to enable a risk detection function according to the behavior data; the behavior data includes at least one type of data related to the business activities of the bank; If it is determined to enable the risk detection function, a configuration list for risk detection corresponding to the target application is determined according to the scenario information corresponding to the current business scenario, and the configuration list is used to indicate: associated applications corresponding to the current business scenario determined from multiple applications; wherein different associated applications correspond to interfaces of respective application modules; the application modules include a communication module, a call module, a media management module and a browser module; Based on a preset interface, the data to be detected is obtained from the interface of the application module corresponding to the associated application, and the data to be detected includes at least one of the text data of the communication module, the call record data of the call module, the image data of the media management module, and the browsing record data of the browser module; a target detection method is determined from at least one detection method to perform risk detection on the data to be detected and the behavior data, and a transaction operation corresponding to the transaction request is executed after the risk detection passes.

2. The method according to claim 1, characterized in that The multiple applications are determined by a pre-stored configuration file; the scenario information includes: business information and user information; the configuration file is used to indicate: associated applications corresponding to different scenario information.

3. The method according to claim 2, characterized in that The method further comprises: Visually displaying a configuration page; the configuration page includes a plurality of configuration options, and the configuration options are used to configure: risk preference information and application authorization information; In response to a user's touch operation on the plurality of configuration options on the configuration page, an associated application corresponding to at least a portion of the scene information in the configuration file is adjusted to obtain an adjusted configuration file.

4. The method according to claim 2, characterized in that: The configuration file also includes: a pre-configured active duration threshold corresponding to each application; and a configuration list for risk detection corresponding to the target application is determined according to the scenario information corresponding to the current business scenario, including: Determining at least one candidate associated application according to the scenario information and the configuration file; The active duration of the at least one candidate associated application is obtained, and a final associated application is determined from the at least one candidate associated application according to the active duration and an active duration threshold.

5. The method according to claim 1, characterized in that According to the scenario information corresponding to the current business scenario, determine the configuration list for risk detection corresponding to the target application, including: Determine the current risk level based on the scenario information corresponding to the current business scenario; A configuration list for risk detection corresponding to the target application is determined based on the current risk level; different risk levels correspond to different numbers of associated applications.

6. The method according to claim 1, characterized in that The application module also includes a clipping service module, which obtains the user's behavior data in the target application and determines whether to enable the risk detection function according to the behavior data, including: Acquiring behavior data from the clipping service module based on the preset interface; Parsing the behavior data to identify the account information and transaction amount to be traded; An initial risk detection is performed on the account information and transaction amount to be traded, and based on the result of the initial risk detection, it is determined whether to enable the risk detection function.

7. The method according to claim 1, characterized in that The method further comprises: After the risk detection passes, determining the location information of the first device of the user and the location information of the second device having a binding relationship with the first device; Determining a target verification strategy based on the location information of the first device and the location information of the second device; The transaction request is securely verified using the target verification strategy.

8. The method according to any one of claims 1 to 7, characterized in that: The method further comprises: Obtaining user identity information of the user in the target application; Obtaining device information of self-service terminals within a preset time and / or preset area from the cloud using a preset protocol, and determining whether the user identity information exists in the device information; When it is determined that the user identity information exists in the device information and the business status of the user in the current business scenario is unfinished, prompt information is generated based on the transaction request of the user in the target application.

9. A banking data processing device, characterized in that: Applied to a target application, the device comprises: a judgment module, configured to respond to a transaction request initiated by a user through a target application, obtain behavior data of the user in the target application, and judge whether to enable the risk detection function according to the behavior data; the behavior data includes at least one type of data related to the business activities of the bank; A determination module, for determining, upon determining to enable the risk detection function, a configuration list for risk detection corresponding to a target application according to scenario information corresponding to a current business scenario, wherein the configuration list is used to indicate: associated applications corresponding to the current business scenario determined from a plurality of applications; wherein different associated applications correspond to interfaces of respective application modules; and the application modules include a communication module, a call module, a media management module, and a browser module; an acquisition module, configured to acquire the data to be detected from the interface of the application module corresponding to the associated application based on a preset interface, wherein the data to be detected includes at least one of the text data of the communication module, the call record data of the call module, the image data of the media management module, and the browsing record data of the browser module; The detection module is used to determine a target detection method from at least one detection method to perform risk detection on the data to be detected and the behavior data, and execute the transaction operation corresponding to the transaction request after the risk detection passes.

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.

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