Business processing method, apparatus, device, storage medium, and program product

Abstract

The application provides a service processing method and device, equipment, storage medium and program product, which are applied to the field of artificial intelligence technology. The method comprises the following steps: after receiving a starting instruction, environment data is acquired in real time, and a target adjustment operation is performed according to the environment data; identity transaction information corresponding to a user is determined according to human feature information of the user, and a target recommendation service is performed according to the identity transaction information; a transaction request of the user is received, the transaction request is preprocessed, and target transaction data is obtained; target risk information and a risk processing mode are determined according to the target transaction data, the environment data and the human feature information; the target risk information and the risk processing mode are used to adjust a service processing flow to obtain a target service processing flow, and the transaction request is processed according to the target service processing flow; and a target processing result corresponding to the transaction request is output. In this way, the service processing flow can be simplified, and the service processing efficiency and response speed can be improved.

Description

TECHNICAL FIELD

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

[0002] With the continuous development of Internet, artificial intelligence and other technologies, the functions of financial transaction devices have been greatly enriched and enhanced.

[0003] In related technologies, traditional financial transaction devices, such as automated teller machines (ATMs) and self-service terminals, etc., in actual application process, usually need users (or customers) to perform a series of preset, relatively complex operation processes, such as inserting a card, entering a password, selecting a business type, and confirming transaction information, etc., each step needs to be accurately and correctly performed by the user, and the response speed of the traditional financial transaction device is slow.

[0004] Therefore, the traditional financial device in related technologies has problems such as complicated business processing flow, low business processing efficiency, slow response speed, etc., which affects the user's experience. SUMMARY

[0005] The embodiments of the present application provide a business processing method, device, equipment, storage medium and program product, which can optimize the business processing flow, improve the business processing efficiency and response speed.

[0006] In a first aspect, the embodiments of the present application provide a business processing method, comprising:

[0007] After receiving the start instruction, real-time environment data is acquired, and a target adjustment operation is performed according to the environment data;

[0008] According to the user's body feature information, the identity transaction information corresponding to the user is determined, and a target recommendation service is performed according to the identity transaction information;

[0009] The transaction request of the user is received, the transaction request is preprocessed, and the target transaction data corresponding to the transaction request is obtained;

[0010] According to the target transaction data, the environment data and the body feature information, target risk information and a risk processing mode corresponding to the target risk information are determined;

[0011] According to the target risk information and the risk processing mode, the business processing flow is adjusted to obtain a target business processing flow, and the transaction request is processed according to the target business processing flow;

[0012] The target processing result corresponding to the transaction request is output.

[0013] In a second aspect, an embodiment of the present application provides a service processing device, including:

[0014] A first execution module is configured to obtain environmental data in real time after receiving a start instruction, and perform a target adjustment operation according to the environmental data;

[0015] A second execution module is configured to determine the identity transaction information corresponding to the user based on the user's body feature information, and execute a target recommendation service based on the identity transaction information;

[0016] a preprocessing module, configured to receive a transaction request from the user, preprocess the transaction request information, and obtain target transaction data corresponding to the transaction request;

[0017] a determination module, configured to determine target risk information and a risk handling method corresponding to the target risk information based on the target transaction data, the environmental data, and the human characteristic information;

[0018] an adjustment module, configured to adjust the business processing flow to obtain a target business processing flow according to the target risk information and the risk handling method, and process the transaction request according to the target business processing flow;

[0019] The output module is used to output the target processing result corresponding to the transaction request.

[0020] In a third aspect, an embodiment of the present application provides a service processing device, including: a memory, a processor;

[0021] The memory stores computer-executable instructions;

[0022] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the business processing method as described in any one of the first aspect or the second aspect above.

[0023] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by a processor, they are used to implement the business processing method described in any one of the first aspect or the second aspect above.

[0024] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the business processing method as described in any one of the first aspect or the second aspect above.

[0025] The business processing method, apparatus, device, storage medium, and program product provided in the embodiments of the present application, after receiving a start instruction, obtains environmental data in real time and performs a target adjustment operation based on the environmental data; determines the user's corresponding identity transaction information based on the user's human body characteristic information, and performs a target recommendation service based on the identity transaction information; receives a transaction request from the user, pre-processes the transaction request, and obtains target transaction data corresponding to the transaction request; determines target risk information and a risk treatment method corresponding to the target risk information based on the target transaction data, environmental data, and human body characteristic information; adjusts the business processing flow based on the target risk information and the risk treatment method to obtain a target business processing flow, and processes the transaction request according to the target business processing flow; and outputs a target processing result corresponding to the transaction request. In the present application, after receiving a start instruction, the financial transaction device obtains environmental data in real time and performs a target adjustment operation based on the target, thereby avoiding the negative impact of environmental factors on business processing; determines the user's identity transaction information based on the user's human body characteristic information, performs a target recommendation service based on the identity transaction information, and adjusts the business processing flow through pre-processing and risk assessment, and finally processes the transaction request according to the adjusted and optimized target business processing flow, thereby simplifying the business processing flow, improving business processing efficiency and response speed, and improving user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] 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.

[0027] Figure 1 Schematic diagram of the application scenario provided for this application;

[0028] Figure 2 A flowchart of a business processing method provided for this application;

[0029] Figure 3 A schematic diagram of the process of obtaining environmental data and executing target adjustment operations provided by this application;

[0030] Figure 4 A schematic diagram of the execution flow of a target recommendation service provided by this application;

[0031] Figure 5 A schematic diagram of the pre-processing process of a transaction request provided in this application;

[0032] Figure 6 A schematic diagram of the risk assessment process for a transaction request provided in this application;

[0033] Figure 7 A flowchart of a business process optimization and adjustment provided for this application;

[0034] Figure 8 A schematic diagram of the feedback process of a target processing result provided in this application;

[0035] Figure 9 A schematic diagram of the structure of a business processing device provided in this application;

[0036] Figure 10 A schematic diagram of the structure of a business processing device provided in this application.

[0037] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0038] To enable those skilled in the art to better understand the technical solution of the present application, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments and drawings described herein are only used to explain the present application and are not intended to limit the present application.

[0039] 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 relevant data comply with the relevant laws, regulations and standards of 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.

[0040] In addition, this application involves artificial intelligence analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.), and the use of artificial intelligence technology for automated decision-making, and a technical solution for making decisions that have a significant impact on personal rights and interests based on the results of automated decision-making. The application provides users with corresponding operation entrances for users to choose to agree or reject the results of automated decision-making; if the user chooses to reject, the expert decision-making process will be entered.

[0041] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0042] It should be noted that the business processing methods, devices, equipment, storage media and program products of this application can be used in the field of artificial intelligence technology, and can also be used in any field other than the field of artificial intelligence technology. This application does not limit the specific application fields of the business processing methods, devices, equipment, storage media and program products.

[0043] With the continuous development of technologies such as the internet and artificial intelligence, financial technology (FinTech) has also experienced rapid growth. Financial transaction devices such as ATMs and self-service terminals have not only seen significant functional enrichment and enhancement, but also seen a greater breadth and depth in their application scenarios, user experience, and integration with other FinTech products. This has facilitated the digital transformation and intelligent upgrade of the financial industry.

[0044] In related technologies, although traditional financial transaction devices have played a significant role in promoting the popularization and convenience of financial services, they suffer from significant shortcomings in actual applications, such as complex procedures, cumbersome operations, and slow response speeds. Specifically, traditional financial transaction devices often require users to follow a series of preset, relatively complex operational processes, from inserting a card and entering a password to selecting a business type and confirming transaction information. Each step requires the user to perform accurately and without error. For users who are not familiar with the operation, this undoubtedly increases the difficulty and time cost of use. In addition, due to reasons such as system architecture design, hardware performance, or network latency, traditional financial transaction devices have a slow response speed, resulting in long waiting times for users, affecting the user experience. Especially during emergency or peak hours, users have to wait in line for a long time, resulting in high service pressure and a poor user experience.

[0045] It can be seen that traditional financial transaction equipment in related technologies has problems such as cumbersome business processing procedures, low business processing efficiency, and slow response speed, which affects the user experience.

[0046] To solve the above problems, the application provides a business processing method, device, equipment, storage medium and program product. After receiving a starting instruction, the financial transaction device acquires environment data in real time, and performs target adjustment operation according to the environment data. Then, the financial transaction device determines user identity transaction information according to user body feature information, and performs target recommendation service according to the identity transaction information. The transaction request of the user is received, and the transaction request is preprocessed to obtain target transaction data corresponding to the transaction request. According to the target transaction data, the environment data and the body feature information, target risk information and a risk processing mode corresponding to the target risk information are determined. According to the target risk information and the risk processing mode, the business processing flow is adjusted to obtain a target business processing flow, and the transaction request is processed according to the target business processing flow. The target processing result corresponding to the transaction request is output. In this way, the financial transaction device can perform adaptive adjustment operation based on the environment data, can ensure the stability of the device, can perform personalized recommendation according to the user identity transaction information, and can optimize and adjust the business processing flow through preprocessing and risk assessment of the transaction request, can simplify the business processing flow, improve the business processing efficiency, can improve the response speed, and can improve the user experience.

[0047] Figure 1 An application scenario provided by the application is shown. As shown in Figure 1 The financial transaction device 102 processes the transaction request of the user 101, and finally outputs the transaction result to the user 101.

[0048] The schemes shown by the application are described in detail through specific embodiments. It should be noted that the following embodiments can exist independently, or can be combined with each other. For the same or similar content, the description is not repeated in different embodiments.

[0049] Figure 2 A flowchart of a business processing method provided by the application is shown. Please refer to Figure 2 The business processing method can include:

[0050] S201, after receiving a starting instruction, environment data is acquired in real time, and target adjustment operation is performed according to the environment data.

[0051] The execution subject of the embodiment of the application can be a financial transaction device, such as an ATM, a self-service terminal or a computer, etc. It can also be a business processing device arranged in the financial transaction device. The business processing device can be realized by software, or realized by the combination of software and hardware. In order to facilitate understanding, in the following, the execution subject is taken as the financial transaction device as an example for description.

[0052] In the embodiments of the present application, a startup instruction may refer to a startup operation instruction for a financial transaction device. Environmental data may refer to environmental data related to the environment in which the financial transaction device is located, such as temperature, humidity, light intensity, air pressure, air quality, and noise level. Target adjustment operations may refer to device adjustment operations determined by the financial transaction device based on the environmental data, such as activating the cooling system, adjusting screen brightness, and adjusting volume.

[0053] In this step, after receiving the activation command, the financial transaction device can activate its corresponding environmental monitoring devices, such as various sensors and environmental monitoring devices. The financial transaction device can obtain real-time environmental data through the environmental monitoring devices and then perform corresponding target adjustment operations based on this environmental data. For example, if the temperature in the environmental data is greater than a preset temperature threshold, the financial transaction device can activate the cooling system; if the light intensity in the environmental data is greater than a preset light intensity threshold, the device can adjust the screen brightness to increase the screen brightness; and if the noise level in the environmental data is greater than a preset noise threshold, the device can adjust the volume to increase the output volume of the financial transaction device. In this way, by performing corresponding target adjustment operations based on environmental data, the financial transaction device can achieve adaptive device adjustments, improve device stability and reliability, and mitigate the negative impact of environmental factors on business processing.

[0054] S202: Determine the identity transaction information corresponding to the user according to the user's body feature information, and perform a target recommendation service according to the identity transaction information.

[0055] In the embodiments of the present application, human characteristic information may refer to information related to the human characteristics of the user currently using the financial transaction device, and may specifically include facial information, expression information, or behavioral information. Identity transaction information may refer to the user's identity information and historical transaction information. Target recommendation services may refer to personalized recommendation content that matches the current user, such as recommending personalized information to the user (such as financial products, financial services, or promotional information), generating a personalized transaction process, or displaying a personalized interactive interface.

[0056] In this step, the financial transaction device can obtain the user's biometric information and then, through methods such as facial recognition, determine the user's identity and transaction information based on this biometric information. Based on the preferences and historical transaction information contained in the identity and transaction information, the device can then predict the user's transaction needs and habits and provide targeted service recommendations. This can improve the security of business processing by determining the identity and transaction information, while also enabling personalized recommendations for the current user based on the identity and transaction information, improving business processing efficiency and simplifying user operations.

[0057] S203: Receive a transaction request from the user, pre-process the transaction request, and obtain target transaction data corresponding to the transaction request.

[0058] In the embodiments of the present application, a transaction request may refer to a user's request for a financial transaction, specifically a transaction request message. Preprocessing may refer to processes such as message verification, key information extraction, and data validation. Target transaction data may refer to key transaction information included in the transaction request, such as account number, transaction amount, transaction type, timestamp, and customer ID.

[0059] In this step, after the user performs an interactive operation on the financial transaction device based on actual needs, the financial transaction device responds to the user's interactive operation, receives the user's transaction request, and may pre-process the transaction request. For example, the financial transaction device may verify the format of the transaction request message and extract key information from the transaction request. It may then perform data verification on the values ​​within the key information, ultimately obtaining the target transaction data corresponding to the transaction request. Subsequently, business processing may be performed based on this target transaction data. In this way, by receiving the transaction request and performing pre-processing to obtain the target transaction data, the financial transaction device can improve the integrity and accuracy of the transaction data, accelerate the processing of the transaction data, and thereby improve overall business processing efficiency.

[0060] S204: Determine target risk information and a risk handling method corresponding to the target risk information based on the target transaction data, environmental data, and human characteristic information.

[0061] In the embodiment of the present application, the target risk information may refer to the risk information that may exist in the current user during the business processing process. The risk handling method may refer to the handling strategy for the target risk information.

[0062] In this step, after acquiring the target transaction data, environmental data, and the user's anthropomorphic information, the financial transaction device can identify the user's behavioral patterns based on the anthropomorphic information, obtaining behavioral analysis results. The financial transaction device can then input the risk assessment dataset, consisting of the target transaction data, environmental data, and behavioral analysis results, into a target risk identification model to determine the target risk information corresponding to the risk assessment dataset. Furthermore, the device can determine the corresponding risk treatment method based on the target risk information. In this way, by performing a risk assessment on the user's business processing and determining the target risk information and risk treatment method, the financial transaction device can improve the security and reliability of business transactions.

[0063] S205: Adjust the business processing flow to obtain a target business processing flow according to the target risk information and the risk handling method, and process the transaction request according to the target business processing flow.

[0064] In the embodiments of the present application, the target service processing flow can refer to an adjusted and optimized service processing flow. Specifically, after determining the target risk information and the risk processing manner existing in the current service processing process, the financial transaction device can perform adjustment and optimization processing on the service processing flow according to the risk processing manner, for example, can increase the verification step, adjust the parameter threshold, or introduce a new transaction path, and the like, to obtain the target service processing flow, and process the transaction request according to the target service processing flow. In this way, the financial transaction device can dynamically adjust and optimize the service processing flow according to the risk assessment result, and can improve the security and response speed of the service processing.

[0065] S206, output the target processing result corresponding to the transaction request.

[0066] In the embodiments of the present application, the target processing result can refer to the processing result corresponding to the transaction request of the user. The target processing result can include a transaction result and corresponding description information. The description information can include transaction interpretation information, personalized suggestion information, or reminder information generated by the financial transaction device for the current user, and the like. The specific content of the description information is not limited in the embodiments of the present application.

[0067] In this step, after processing the transaction request of the user, the financial transaction device can generate the target processing result corresponding to the transaction request, and then can feed back the target processing result to the user. The feedback can be performed through a display screen, voice output, or short message prompt, and the like, to realize real-time reminding of the user.

[0068] The service processing method provided in the embodiments of the present application can obtain environment data in real time after receiving a starting instruction, and perform target adjustment operation according to the environment data; determine identity transaction information corresponding to a user according to human feature information of the user, and perform target recommendation service according to the identity transaction information; receive a transaction request of the user, pre-process the transaction request, and obtain target transaction data corresponding to the transaction request; determine target risk information and a risk processing mode corresponding to the target risk information according to the target transaction data, the environment data and the human feature information; adjust a service processing flow to obtain a target service processing flow according to the target risk information and the risk processing mode, and process the transaction request according to the target service processing flow; and output a target processing result corresponding to the transaction request. In the present application, the financial transaction device can obtain environment data in real time and perform target adjustment operation after receiving a starting instruction, so that negative influence of environmental factors on service processing can be avoided; identity transaction information of a user can be determined according to human feature information of the user, target recommendation service can be performed according to the identity transaction information, and service processing flow can be adjusted through pre-processing and risk assessment, so that transaction request can be processed according to the adjusted and optimized target service processing flow, service processing flow can be simplified, service processing efficiency and response speed can be improved, and user experience is improved.

[0069] On the basis of the above embodiments, Figure 3 A flowchart of environment data acquisition and target adjustment operation execution is provided in the present application. Please refer to Figure 3 , which comprises:

[0070] S301, initialize the environment detection device, and obtain environment data in real time through the environment detection device.

[0071] In the embodiments of the present application, the environment detection device can be an environment data detection device associated with the financial transaction device, and can specifically comprise built-in sensors and external environment monitoring devices, wherein the built-in sensors can comprise temperature sensors, humidity sensors and illumination sensors, and the external environment monitoring devices can comprise weather station interfaces and air quality monitors.

[0072] In this step, the financial transaction device can first perform initialization processing on the environment detection device after starting. Specifically, the financial transaction device can perform device state confirmation on the environment detection device, so that each environment detection device enters a normal working state; and then can load and initialize sensor drivers and environment monitoring software, and automatically configure detection parameters such as data acquisition frequency and accuracy. Of course, the financial transaction device can also perform other initialization processing operations, which are not limited in the embodiments of the present application.

[0073] After the initialization process is completed, the financial transaction device can start data collection, obtain real-time environmental data through the environmental detection device, and store the collected environmental data in the local cache or memory of the financial transaction device, facilitating subsequent processing and analysis.

[0074] In S302, a target adjustment operation corresponding to the environmental data is determined and executed according to a preset mapping relationship. The preset mapping relationship includes preset adjustment operations corresponding to different values of the environmental data.

[0075] In an embodiment of the present application, the preset mapping relationship can refer to the correspondence between different values of the environmental data and the preset adjustment operation. For example, when the light intensity is lower than a first light intensity threshold, the screen brightness is reduced; when the light intensity is higher than a second light intensity threshold, the screen brightness is increased.

[0076] Specifically, the financial transaction device can preprocess the environmental data, such as data cleaning and standardization, to remove noise and outliers in the environmental data, thereby ensuring the accuracy and reliability of the environmental data. Then, the financial transaction device can perform statistical analysis, trend prediction, etc. on the preprocessed environmental data based on data analysis algorithms such as statistical analysis algorithms and machine learning algorithms, to obtain data analysis results that can reflect the specific impact of the current environment reflected by the environmental data on the device operation.

[0077] Then, the financial transaction can determine the matching relationship between the environmental data and the preset mapping relationship based on the data analysis results, and further determine the target adjustment operation corresponding to the environmental data. For example, the financial transaction device can determine whether a certain environmental data exceeds a preset safety or performance threshold. For environmental data exceeding the threshold, the corresponding target adjustment operation can be determined in the preset mapping relationship. For example, when the temperature in the environmental data is higher than a preset temperature threshold, the financial transaction device determines the target adjustment operation as starting the cooling system and adjusting the working frequency; when the light intensity in the environmental data is higher than a second light intensity threshold, the financial transaction device determines the target adjustment operation as increasing the screen brightness, etc.

[0078] After the financial transaction device determines the target adjustment operation corresponding to the current environmental data, it can convert the target adjustment operation into specific control instructions and send them to the corresponding device or system component, and can detect the feedback information of the corresponding device or system component to ensure the effective execution of the target adjustment operation. Then, the financial transaction device can continuously monitor the changes in environmental data and device state. If the target adjustment operation fails to effectively respond to environmental changes or produces adverse effects such as increased energy consumption due to excessive cooling, the financial transaction device can dynamically adjust the target adjustment operation based on the environmental data and device state feedback, such as reducing the speed of the cooling system, etc.

[0079] In the embodiments of the present application, financial transaction devices ensure stable operation under various environmental conditions by detecting environmental data in real time and adaptively executing target adjustment operations. Initialization of the environmental detection device ensures the readiness of all hardware devices and software components, laying the foundation for subsequent data collection and analysis. Real-time acquisition of environmental data and preprocessing and data analysis improve the accuracy and reliability of environmental data. Subsequently, determining and executing target adjustment operations enables the financial transaction device to maintain optimal operating conditions under adverse environmental conditions. Continuous monitoring and feedback adjustments continuously optimize the target adjustment operations, ensuring that the financial transaction device can continuously adapt to environmental changes.

[0080] Through real-time data collection and pre-processing analysis, financial trading equipment can accurately assess the impact of the environment on equipment operation, providing a scientific basis for taking effective adaptive measures (i.e., target adjustment operations), helping to reduce equipment failure rates caused by environmental factors and improve equipment reliability and stability. The decision-making and execution of target adjustment operations enable financial trading equipment to flexibly respond to various complex environments and maintain optimal operating conditions, thereby improving user experience and service quality. In addition, through continuous monitoring and feedback adjustment mechanisms, financial trading equipment can continuously optimize its adaptive strategies, improve the efficiency and accuracy of responding to environmental changes, and enhance its environmental adaptability, thereby improving the scenario adaptability of financial trading equipment.

[0081] S303: Acquire historical environmental data and determine an environmental change model based on the historical environmental data; the environmental change model is used to predict the changing trend of environmental data.

[0082] In the embodiment of the present application, the historical environmental data may refer to the environmental changes experienced by the financial transaction device in different historical time periods. The environmental change model may refer to a pre-trained model for predicting environmental change trends.

[0083] In an embodiment of the present application, the financial transaction device may include an environmental factor warning system, which can analyze historical environmental data and real-time environmental data, predict the changing trend of environmental data in the future, and issue a warning in advance when it is predicted that the preset threshold may be exceeded so that preventive measures can be taken.

[0084] Specifically, the environmental factor warning system in a financial transaction device can collect and store a large amount of historical environmental data, such as temperature, humidity, and light intensity. This historical environmental data reflects the environmental changes experienced by the financial transaction device over different time periods. The environmental factor warning system can be trained based on data analysis techniques, such as time series analysis and machine learning algorithms, to obtain an environmental change model that can identify and predict the periodic changes and trends in environmental data. The environmental change model can also use other algorithms, and the embodiments of this application do not limit the specific type of environmental change model and the training process.

[0085] S304: Determine environmental prediction information corresponding to the environmental data based on the environmental data and the environmental change model; and output warning information when the environmental prediction information meets a preset threshold condition.

[0086] In embodiments of the present application, environmental prediction information may refer to prediction information corresponding to the current environmental data of the financial transaction device, such as a trend or a specific value at a specific moment. Preset threshold conditions may refer to pre-set threshold conditions for abnormal environmental data. Early warning information may refer to environmental abnormality warning information.

[0087] During this step, while the financial transaction device is collecting real-time environmental data, the environmental factor warning system continuously monitors the current environmental data and performs predictive processing using an environmental change model. For example, it can compare and integrate current environmental data with historical environmental data to predict the changing trends of environmental data over a period of time, generating environmental forecast information. If one or more environmental data points in this forecast information meet preset threshold conditions, the environmental factor warning system triggers a warning mechanism and outputs warning information to administrators or users via display screens, audio prompts, or remote notifications, allowing them to take preventive measures, such as adjusting the device's operating mode, increasing heat dissipation, or implementing other countermeasures, to ensure the stability and security of the financial transaction device.

[0088] In an embodiment of the present application, a financial transaction device uses an environmental factor early warning system to predict environmental data, obtain environmental prediction information, and output a warning message when the environmental prediction information meets preset threshold conditions. This enables the financial transaction device to foresee the risks associated with environmental changes and promptly notify users or managers to take preventive measures, thereby avoiding equipment failures or service interruptions caused by environmental factors and improving the reliability and stability of the device. Furthermore, through real-time data analysis and prediction, the financial transaction device can more accurately assess the impact of environmental data on device operation, providing a scientific basis for determining target adjustment operations, further enhancing the device's intelligence level and user experience.

[0089] In addition, in the embodiments of the present application, the financial transaction device can use data encryption technology to protect data security and user privacy during the process of collecting, transmitting, and storing environmental data, ensuring that sensitive information is not accessed or leaked without authorization. In one possible implementation, the business processing method may also include the following steps:

[0090] In the process of collecting environmental data, the environmental data is encrypted; the environmental data is transmitted based on a secure communication protocol and an encrypted channel, and the environmental data is encrypted and stored.

[0091] In the embodiment of the present application, the financial transaction device can encrypt the environmental data during the environmental data collection process. Specifically, this can be achieved based on data encryption technology. The data encryption technology converts sensitive information into a form that is difficult for unauthorized users to understand and access through specific algorithms and keys. The embodiment of the present application does not limit the specific type of data encryption technology. Encryption processing is performed during the environmental data collection stage to ensure that its content cannot be easily obtained even if it is intercepted during the transmission process; during the data transmission process, the financial transaction device adopts a secure communication protocol and an encrypted channel to ensure that the data is not tampered with or leaked during the transmission process; during the data storage stage, the encrypted environmental data is stored in a secure storage medium and regularly backed up, audited, and other processes are performed to prevent data loss or illegal access. Of course, in addition to environmental data, the financial transaction device in the embodiment of the present application can use encryption processing for other types of data, such as human feature information, during data collection, transmission, and storage to ensure data security.

[0092] In the embodiment of the present application, the financial transaction device can effectively protect the security of environmental data and user privacy by encrypting the environmental data during collection, transmission and storage, which is conducive to enhancing the user's trust and satisfaction with the financial transaction device. During the data transmission and storage process, data encryption technology can ensure the security of sensitive information and prevent the risk of data leakage and illegal access.

[0093] Based on the above embodiments, Figure 4 This is a schematic diagram of the execution flow of a target recommendation service provided by this application. Figure 4 Shown, including:

[0094] S401. Obtaining the user's body feature information through a camera; the body feature information includes facial information, expression information, and behavior information.

[0095] S402: Determine the identity transaction information corresponding to the user based on the facial information.

[0096] In the embodiment of the present application, the shooting device may refer to a video or image acquisition device corresponding to the financial transaction device, such as a camera. Specifically, the financial transaction device may activate the shooting device to collect real-time human feature information of users entering the field of view of the shooting device, which may specifically include facial information, expression information, and behavioral information (such as body movements, gestures, etc.). Afterwards, the financial transaction device may search the facial information of the user in a known customer facial database stored in the financial transaction device based on the facial information of the user. Specifically, a 1:1 or 1:N (N is a positive integer greater than 1) comparison method may be used to confirm the user's identity information based on face recognition algorithms such as deep learning and convolutional neural networks to ensure that the operation is indeed the user himself. After determining the identity information, the financial transaction device reads the user's historical transaction information based on the identity information to determine the user's identity transaction information. If the facial information fails to match successfully, the financial transaction device may authenticate the user, such as prompting the user to enter a password or prompting the user to answer preset questions, to ensure the security of business processing.

[0097] In this way, financial transaction equipment can quickly verify customer identities by capturing user facial information in real time and using facial recognition algorithms to compare it with a database of known customer faces. This can not only improve the accuracy and speed of user identity recognition, but also ensure the authenticity and security of transactions.

[0098] S403: Determine the predicted transaction information corresponding to the user based on the identity transaction information, expression information, and behavior information.

[0099] In the embodiments of the present application, predicted transaction information may refer to information about the current user's potential transaction needs and points of interest. Specifically, the financial transaction device may collect user facial expressions, such as smiles, frowns, and surprise, and determine the user's emotional state based on an emotion recognition algorithm. Furthermore, the device may collect behavioral information such as body movements and postures, and analyze the user's behavioral patterns using a behavioral analysis algorithm, including body posture, movement smoothness, and gaze direction, to determine the user's behavioral patterns.

[0100] In addition, financial transaction devices can determine the user's historical transaction information based on the user's identity information, which may specifically include the user's historical transaction records, preference settings, browsing behavior and other data. Based on this historical transaction information, and combined with the emotional state determined based on the expression information and the behavioral pattern determined based on the behavioral information, through machine learning or deep learning models, the current user's predicted transaction information is predicted to determine the user's possible transaction needs or points of interest, which can facilitate personalized recommendations for users.

[0101] S404: Output target recommendation information based on the predicted transaction information and determine the business processing flow corresponding to the predicted transaction information.

[0102] In the embodiment of the present application, the target recommendation information may refer to personalized information corresponding to the current user, such as financial products, financial services, or promotional information. In this step, the financial transaction device may perform the target recommendation service after determining the user's predicted transaction information. Specifically, the financial transaction device outputs the target recommendation information through a display screen or voice prompt, and may automatically generate an adjusted business transaction process. For example, according to the user's behavior pattern and preference settings, the conventional transaction process is automatically adjusted, and the business transaction process and personalized interactive interface (layout) corresponding to the user are determined. This can simplify unnecessary operation links and improve transaction efficiency and customer experience.

[0103] It should be noted that financial transaction equipment can encrypt the collected human feature information to ensure data security, strictly abide by relevant laws, regulations and privacy policies, and clearly inform customers of the purpose, method and scope of data collection, use and processing. Only after obtaining the user's explicit consent will operations such as facial recognition and behavioral analysis be performed, thereby ensuring the security and privacy of customer information.

[0104] In an embodiment of the present application, a financial transaction device determines a user's identity transaction information by collecting human feature information, and determines the user's predicted transaction information based on facial expression information, behavioral information, and identity transaction information. Based on this predicted transaction information, the device outputs target recommendation information and generates a simplified and adjusted business processing flow. In this way, the financial transaction device effectively prevents fraudulent behavior and illegal transactions through efficient and accurate customer identity identification, thereby improving the security and reliability of financial transactions. In-depth analysis of customer emotions and behaviors enables the financial transaction device to more accurately meet customer needs, provide personalized services, and enhance the user experience. By determining predicted transaction information, the device can predict the user's transaction needs, enabling personalized recommendations and improving transaction efficiency and success rates. Furthermore, based on strict data encryption and privacy protection measures, the financial transaction device can ensure privacy and security, enhancing user trust and user experience.

[0105] Based on the above embodiments, Figure 5 This is a schematic diagram of the pre-processing process of a transaction request provided by this application. Figure 5 Shown, including:

[0106] S501: Obtain a transaction request message corresponding to a transaction request.

[0107] In an embodiment of the present application, a financial transaction device may continuously monitor a network port or a specific communication interface, waiting to receive a transaction request message from a client. Upon receiving the transaction request message, the financial transaction device may first perform an integrity check, specifically using a checksum, hash value, or other method, to ensure that the transaction request message has not been tampered with or damaged during transmission.

[0108] The financial transaction device may then perform format verification on the transaction request message based on target message format conditions. The target message format conditions may be dynamically adjusted message format specifications that may include message length, field delimiters, and the integrity of required fields. If the transaction request message format does not meet the target message format conditions, the financial transaction device may record an error message and return a format error prompt to the client, prompting the client to resend a corrected transaction request message.

[0109] In an embodiment of the present application, the financial transaction device continuously monitors the network port or specific communication interface to ensure that the system can promptly receive the transaction request message from the client, and performs an integrity check after receiving the transaction request message to ensure that the message has not been tampered with or damaged during transmission; then, the transaction request message is format verified based on the target message format conditions to ensure the compliance and processability of the transaction request message.

[0110] S502: If the transaction request message meets the target message format condition, parse the transaction request message to obtain key transaction information corresponding to the transaction request message.

[0111] In embodiments of the present application, key transaction information may refer to key information in a transaction message request, such as the account number, transaction amount, transaction type, timestamp, and customer identifier. Specifically, upon determining that a transaction request message meets target message format requirements, the financial transaction device may determine a corresponding parsing algorithm or parsing tool based on the specific type of the transaction request message, such as Extensible Markup Language (XML), JavaScript Object Notation (JSON), or binary, to quickly identify and extract the key transaction information from the transaction request message. Furthermore, after determining the key transaction information, the financial transaction device may perform data verification on the key transaction information, such as to determine whether the account number is valid and whether the transaction amount is within a reasonable range.

[0112] In this way, after confirming that the format of the transaction request message is correct, the financial transaction device selects an appropriate parsing algorithm or parsing tool according to the type of transaction request message, quickly identifies and extracts key transaction information from the transaction data, and performs basic data verification to ensure the accuracy and rationality of the key transaction information.

[0113] S503: When the key transaction information is verified, the key transaction information is formatted and processed to obtain target transaction data corresponding to the transaction request.

[0114] In the embodiment of the present application, if the key transaction information passes verification (or validation), the financial transaction device can format the key transaction information according to a preset data standard to ensure consistency in subsequent processing. At the same time, the data types of certain fields can be converted according to business needs, such as converting a string-type amount to a numeric type, to obtain the target transaction data corresponding to the transaction request. In this way, the financial transaction device formats the key transaction information according to the preset data standard and performs the necessary data type conversion to obtain the target transaction data, thereby ensuring consistency in subsequent processing and improving business processing efficiency.

[0115] S504: Store the target transaction data and send the target transaction data to other business components.

[0116] In an embodiment of the present application, the financial transaction device can store the key transaction information obtained by pre-processing the transaction request, specifically in a temporary storage area such as an in-memory database, cache, etc., to facilitate quick access for subsequent business processing; at the same time, the financial transaction device can also record the key steps and results of the pre-processing process, including the reception time, parsing results, any abnormal or error information, etc., to facilitate subsequent problem tracking and performance analysis.

[0117] Afterwards, the financial transaction device can pass the target transaction data and related metadata to other business processing components, including subsequent business processing modules or system components, such as transaction verification, account processing, and risk control checks. Regarding the method of transmitting the target transaction data, the target transaction data can be transmitted synchronously to other business processing components or asynchronously through methods such as message queues. This can meet different system architecture design requirements. The embodiments of this application do not limit the specific method of transmitting the target transaction data.

[0118] In an embodiment of the present application, after receiving a transaction request initiated by a user, the financial transaction device performs efficient and accurate pre-processing on the transaction request and determines the target transaction data corresponding to the transaction request. Specifically, the financial transaction device ensures the integrity and accuracy of the transaction data through a strict message reception and verification mechanism, effectively prevents the risk of data tampering and damage, and improves the security of the transaction; through efficient message parsing and data standardization, it speeds up the processing of transaction data, reduces system latency, and improves the user experience; by formatting key transaction information and converting data types, it ultimately stores the target transaction data, providing convenience for subsequent business processing and reducing the complexity of data conversion and processing. In addition, recording the key steps and results of the pre-processing process facilitates problem tracking and performance analysis, provides strong support for system optimization and improvement, and adapts to the needs of different system architecture designs through flexible target transaction data delivery methods, improving the scalability and flexibility of the system.

[0119] In the embodiment of the present application, when performing format verification on the transaction request message in step S502, the financial transaction device can dynamically adjust the target message format conditions based on the client or transaction type, thereby implementing a flexible format verification mechanism and improving the ability to handle complex transaction requests. In one possible implementation, the target message format conditions in step S502 can be dynamically adjusted in the following manner:

[0120] Determine the source information and type information of the transaction request; and update the target message format condition based on the source information and type information.

[0121] In this embodiment of the present application, upon receiving a new transaction request message, the financial transaction device first identifies the source and type information of the transaction request. The source information may include a specific client, and the type information may include transaction type information such as transfer or payment. The financial transaction device then performs verification based on the currently valid target message format conditions.

[0122] If a financial transaction device detects new source information or new type of information, such as a new client connection or a change in transaction type, it can automatically query and obtain the new message format specifications and update these message format specifications into the target message format conditions. The financial transaction device then performs format verification on the updated target message format conditions. This allows the financial transaction device to dynamically adjust the target message format conditions, either in real time or periodically, based on client characteristics, transaction type differences, or changes in business rules. This allows the financial transaction device to flexibly respond to a variety of complex transaction requests, improving processing flexibility and accuracy.

[0123] The financial transaction device in the embodiments of the present application improves the ability of the system to process complex transaction requests by dynamically adjusting the target message format conditions, so that the financial transaction device can flexibly cope with the needs of different clients and transaction types, helps to reduce errors and rejection rates caused by message format mismatch, and improves the success rate of transaction processing and customer satisfaction. In addition, the dynamic adjustment mechanism of the target message format conditions also enhances the scalability and adaptability of the financial transaction device, so that the financial transaction device can easily integrate new clients or support new transaction types without the need for large-scale code modification or system reconstruction.

[0124] In the embodiments of the present application, during the storage process of the target transaction data in step S504, the financial transaction device can adopt an intelligent caching strategy to dynamically adjust the cache size and validity period according to the frequency and importance of the transaction request, thereby improving the data access speed and system response capability. In one possible implementation, the target transaction data in step S504 can be stored in the following manner:

[0125] (1) Determine the target frequency parameter corresponding to the transaction request.

[0126] (2) If the target frequency parameter is greater than a first preset frequency threshold, store the target transaction data according to a first storage space and a first validity period.

[0127] In the embodiments of the present application, the target frequency parameter can be used to represent the frequency and importance of the transaction request. The first preset frequency threshold can be a high threshold of the frequency parameter. If the target frequency parameter of the transaction request is greater than the first preset frequency threshold, the financial transaction device can determine that the frequency and importance of the target transaction data in the transaction request are high, and can use a larger first storage space and a larger first validity period to store the target transaction data.

[0128] (3) If the target frequency parameter is less than a second preset frequency threshold, store the target transaction data according to a second storage space and a second validity period; the first storage space is greater than the second storage space, and the first validity period is greater than the second validity period.

[0129] In the embodiments of the present application, the second preset frequency threshold can be a low threshold of the frequency parameter. If the target frequency parameter of the transaction request is less than the first preset frequency threshold, the financial transaction device can determine that the frequency and importance of the target transaction data in the transaction request are low, and can use a smaller second storage space and a smaller second validity period to store the target transaction data.

[0130] In an embodiment of the present application, a financial transaction device monitors and analyzes the access patterns of transaction requests to identify the target frequency parameter corresponding to the transaction requests. If the target frequency parameter of the transaction request is greater than a first preset frequency threshold, the financial transaction device may increase storage space and extend the cache validity period. Specifically, a larger first storage space and a longer first validity period may be used to store the target transaction data. This reduces the number of accesses to the backend database and improves data access speed. If the target frequency parameter of the transaction request is less than a second preset frequency threshold, the system reduces cache resource allocation. Specifically, a smaller second storage space and a shorter second validity period may be used to store the target transaction data. This optimizes cache utilization. Furthermore, the financial transaction device regularly clears expired cache to ensure the timeliness and accuracy of cached data.

[0131] In an embodiment of the present application, a financial transaction device dynamically manages cache resources used for target transaction data based on an intelligent caching strategy, based on the frequency and importance of transaction requests. This significantly improves data access speed, reduces system latency, and enhances user experience by reducing the number of backend database accesses. It also optimizes cache resource usage by dynamically adjusting cache size and expiration time, ensuring the timeliness and accuracy of cached data while avoiding waste of cache resources. Furthermore, the intelligent caching strategy used by the financial transaction device helps reduce the burden on the backend database and improve the overall performance and stability of the system.

[0132] Based on the above embodiments, Figure 6 This is a risk assessment process diagram for a transaction request provided by this application. Figure 6 Shown, including:

[0133] S601: Determine the behavior analysis result corresponding to the user according to the human body feature information.

[0134] S602: Input the target transaction data, environmental data, and behavior analysis results into the target risk prediction model to obtain target risk information corresponding to the transaction request.

[0135] In the embodiments of the present application, the behavioral analysis results may refer to analysis results obtained by integrating the user's facial expression information, behavioral information, and historical transaction information. The financial transaction device may collect target transaction data, environmental data, and behavioral analysis results, and may also collect other environmental information such as network status, geographic location, and time to form a risk assessment dataset.

[0136] Then, the financial transaction device can obtain a historical risk assessment data set, train an initial risk assessment model to enable it to identify potential risk patterns. The initial risk assessment model can be determined according to actual business requirements and data characteristics, and can be a neural network, decision tree, random forest, support vector machine, etc. Then, the financial transaction device can optimize the parameters of the initial risk assessment model in the training process through cross-validation, grid search, etc. to improve the accuracy and stability of risk assessment, and finally obtain a target risk assessment model.

[0137] Then, the financial transaction device can determine that the risk assessment data set is input into the target risk identification model according to the target transaction data, environmental data and human feature information, and perform real-time risk assessment. The target risk identification model predicts potential risk points in the transaction process, such as fraud risk, credit risk, operational risk, etc. according to the input risk assessment data set, and generates target risk information, which can include risk type, risk level, possible impact range and countermeasures, etc.

[0138] In the embodiments of the present application, the financial transaction device combines environmental data, target transaction data and behavior analysis results to build a comprehensive and rich risk assessment data set, ensuring the comprehensiveness and accuracy of risk assessment and providing an accurate data basis for subsequent analysis; using the historical risk assessment data set for model training and optimizing parameters through cross-validation, grid search, etc. can improve the accuracy and stability of risk assessment, and also improve the deep learning and intelligent identification capabilities of the financial transaction device for complex data patterns; the financial transaction device inputs the risk assessment data set into the trained target risk identification model, which can accurately and in real time assess the risk of the transaction process.

[0139] S603, determining a risk processing method corresponding to the target risk information.

[0140] In an embodiment of the present application, a financial transaction device can determine a risk identification method based on the target risk information output by a target risk identification model. Specifically, based on the risk assessment results, the financial transaction device can determine a corresponding risk response strategy, such as adding verification steps, limiting the transaction amount, or rejecting the transaction. From multiple possible risk response strategies, the financial transaction device selects a strategy using an optimization algorithm, such as a genetic algorithm or simulated annealing, to determine a risk handling method. The selected risk handling method is then converted into specific operational instructions and passed to subsequent business processing components (or modules) for execution. Furthermore, during the subsequent execution of the risk handling method, the financial transaction device can monitor changes in risk assessment-related factors, such as transaction status and environmental data, in real time to facilitate timely adjustment of decision-making plans. After the transaction is completed, the financial transaction device can evaluate the effectiveness of the decision, including risk control effectiveness and customer satisfaction. Based on the evaluation results, the target risk identification model and risk handling method are then optimized through feedback, thereby continuously improving the intelligence level and decision-making capabilities of the financial transaction device.

[0141] In an embodiment of the present application, before processing a transaction, a financial transaction device can perform a risk assessment based on target transaction data, environmental data, and human characteristics to determine target risk information and risk management methods. In this way, by integrating multi-dimensional data, the financial transaction device can more comprehensively assess transaction risks, improving the accuracy and comprehensiveness of risk assessments, helping to reduce misjudgments and missed judgments caused by information asymmetry or data loss, and enhancing the system's risk prevention and control capabilities. Simultaneously, by training risk assessment models and performing parameter optimization, the financial transaction device can identify potential risks in complex data patterns, improving the intelligence and stability of risk assessments, and helping the financial transaction device maintain a high degree of sensitivity and adaptability when faced with rapidly changing transaction environments and complex and ever-changing fraudulent methods. In addition, determining the risk handling method based on target risk information can not only effectively deal with different types of risks, but also screen strategies among multiple possible response strategies, thereby achieving precise and efficient risk control, helping to improve customer experience, reduce losses and maintain market order. Moreover, through real-time monitoring and feedback optimization mechanisms, financial trading equipment can continuously adjust and optimize risk assessment models and risk handling method determination mechanisms, adapt to the ever-changing market environment and business needs, and achieve continuous learning and self-optimization.

[0142] Based on the above embodiments, Figure 7 This is a flow chart of a business process optimization and adjustment provided by this application. Figure 7 Shown, including:

[0143] S701, adjust the key parameters, transaction path or business processing mode corresponding to the business processing flow according to the target risk information and the risk processing mode, and obtain a target business processing flow.

[0144] In the embodiments of the present application, after the target risk information and the risk processing mode are determined, the financial transaction device can optimize and adjust the business processing flow. Specifically, the corresponding key parameters, transaction path or business processing mode, etc. can be adjusted to obtain the target business processing flow. Subsequently, the target transaction request can be processed according to the target business processing flow, and the target processing result can be output.

[0145] Specifically, the financial transaction device can analyze the target risk information to determine the risk type, risk level and countermeasures, and then determine the link or parameter that needs to be optimized in the business processing flow. Then, the financial transaction device can adjust the key parameters in the business processing flow, such as transaction limit, verification threshold, etc., to reduce the risk and improve the processing efficiency; the financial transaction device can also re-plan the transaction processing path corresponding to the business processing flow, select a safer and more efficient path for transaction processing, and reduce unnecessary links and delays; for specific risk types or business needs, the financial transaction device can use other business processing modes, such as the alternative business processing modes pre-configured in the financial transaction device, etc. Of course, the financial transaction device can add new processing strategies or technical means according to the configuration of the management personnel, such as machine learning models, automated approval processes, etc. The embodiments of the present application are not limited in this regard.

[0146] Then, the financial transaction device can perform specific business processing flow adjustment and optimization operations. Specifically, the configuration file or parameter setting of the system can be updated to ensure that the system can process transactions according to the new processing flow; the system code or algorithm can also be adjusted and optimized as necessary to support new processing strategies or technical means. In addition, the financial transaction device can also test and verify the optimized target business processing flow in a small-scale range to ensure the effectiveness and stability of the optimization measures.

[0147] After the target business processing flow is obtained through optimization and adjustment, the financial transaction device can monitor the changes and effects of the transaction processing flow in real time during the process of processing transaction requests according to the target business processing flow. The transaction data before and after optimization is collected and analyzed, and the processing efficiency, accuracy, risk control effect and other indicators are compared. According to the data analysis result, the effect of the optimization measure is evaluated to determine whether the expected target is achieved. In addition, the financial transaction device can also collect feedback information about the optimization effect through user feedback, system log, etc. Analyze the feedback information to identify problems or deficiencies in the optimization process. For the identified problems or deficiencies, iterative optimization is performed to continuously improve the business processing flow and improve the optimization and adjustment performance of the financial transaction device.

[0148] In an embodiment of the present application, a financial transaction device conducts an in-depth analysis of target risk information and subsequently improves the security and efficiency of the financial transaction device by adjusting and optimizing the business processing process. Specifically, the financial transaction device analyzes the target risk information to determine the risk type, risk level, and response measures. This allows it to identify potential weaknesses in the business processing process or parameters that need adjustment. The financial transaction device then develops specific optimization strategies based on the target risk information and risk management approach. These strategies may include adjusting key parameters in the transaction processing process to better control risk and improve processing efficiency; replanning transaction processing paths to select safer and more efficient ones to reduce unnecessary steps and delays; and introducing new processing strategies or technical means to enhance the system's intelligence and automation level based on specific risk types or business needs. The financial transaction device then executes specific optimization measures based on the developed optimization strategies, including updating system configuration files or parameter settings to ensure the system can process transactions according to the new processing flow; making necessary adjustments and optimizations to system code or algorithms to support the new processing strategies or technical means; and testing and verifying the optimized system on a small scale to ensure the effectiveness and stability of the optimization measures.

[0149] In an embodiment of the present application, a financial transaction device dynamically optimizes the business processing flow based on target risk information and risk handling methods to obtain a target business processing flow. By analyzing and processing target risk information, the financial transaction device can more accurately identify and control potential risks, thereby reducing the probability of adverse events such as fraud and credit risk, and improving the security of the overall business processing flow. By adjusting key parameters in the transaction processing process and replanning the processing path, the financial transaction device can reduce unnecessary links and delays, speed up transaction processing, and improve user experience and satisfaction. The introduction of new technical means enables the financial transaction device to adapt to the ever-changing market environment and business needs, improving the accuracy and efficiency of decision-making. Furthermore, through monitoring and optimization effect evaluation, continuous optimization and iteration mechanisms, and by collecting user feedback and system log information, the financial transaction device can further improve the continuous optimization and iterative upgrade of business processing flows.

[0150] Based on the above embodiments, Figure 8 This is a schematic diagram of the feedback process of a target processing result provided by this application. Figure 8 Shown, including:

[0151] S801: When the transaction request processing is completed, determine the transaction result corresponding to the transaction request.

[0152] In the embodiments of the present application, after the transaction request processing is completed, the financial transaction device can determine the transaction result corresponding to the transaction request, which can include success prompt (whether the transaction is successful), transaction details (such as transaction amount, transaction time, etc.) and other information.

[0153] S802, format conversion is performed on the transaction result, and description information corresponding to the transaction result is added to obtain a target processing result.

[0154] In the embodiments of the present application, the financial transaction device can perform format conversion on the transaction result, for example, can convert it into an image or text format that is easy for the user to understand, and at the same time can add corresponding description information to obtain a target processing result.

[0155] Specifically, the financial transaction device can determine the user's preference habits according to the user's feedback history, historical transaction information and other data. Then the financial transaction device can interpret the transaction result according to the customer's preference habits, such as explaining the significance of transaction success, providing chart analysis of transaction data, etc., and generate subsequent service suggestions according to the transaction result and customer preference habits, such as recommending related products, providing financial planning suggestions, inviting participation in preferential activities, etc. The financial transaction device can integrate the personalized interpretation and subsequent service suggestions as description information with the transaction result to generate a personalized target processing result corresponding to the user's transaction request.

[0156] S803, output the target processing result according to the target output mode, and obtain the user's feedback information.

[0157] In the embodiments of the present application, the target output mode can refer to the target processing result feedback mode corresponding to the current business processing process. Specifically, for customers who transact on site or use terminal devices, the target output mode can be to directly display the target processing result on the display screen; for scenarios that require voice feedback, the target output mode can be to convert the target processing result into voice information through voice synthesis technology for playing; for customers who transact off-site or require asynchronous notification, the target output mode can be to send the target processing result through the short message service. In addition, according to the customer's preference settings, the target output mode can also be to send the target output mode through the email or application program push notification mode.

[0158] It should be noted that the financial transaction device can determine the target feedback mode according to the user's preference settings, for example, customers who prefer short message notifications can choose to receive only short messages and not receive notifications from other channels, so the financial transaction device can take short messages as the target feedback mode. Of course, the financial transaction device can dynamically update the user's preference settings according to the user's interaction operation, and the customer can update his own feedback preferences in the system at any time, and the target feedback mode is determined according to the user's latest preference settings, which is not limited in the embodiments of the present application.

[0159] Finally, the financial transaction device can collect feedback information of the customer on the target processing result through questionnaires, evaluation systems, etc. The financial transaction device can analyze the feedback information of the customer, evaluate the effect of different target output modes and the acceptance of the description information, and optimize and adjust the generation algorithm of the description text and the target output mode according to the analysis result of the feedback information, and continuously improve the quality of the output mode and the personalized service.

[0160] In the embodiments of the present application, the financial transaction device first obtains the final result of the transaction request, then performs format adjustment and adds personalized description information to obtain the target processing result, which can improve the user experience; then the financial transaction device outputs the target processing result according to the target output mode by using a multi-channel feedback mechanism according to the transaction scene and the preference of the customer; finally, the feedback information of the user is obtained and analyzed, which can continuously optimize the target output mode and the personalized description information, and further improve the user experience.

[0161] In the embodiments of the present application, the financial transaction device outputs the target processing result by using a multi-channel and personalized target output mode, which can ensure that the customer obtains the transaction result information in time and accurately, and provides personalized description information according to the preference and demand of the customer, which not only helps the customer to better understand the transaction result, but also can recommend related products or services according to the interest points of the customer, and increase the customer satisfaction. In addition, by collecting and analyzing the feedback information of the user, the financial transaction device can continuously optimize the feedback mechanism, ensure the effectiveness and pertinence of the target output mode and the generation of the description information, and improve the user experience.

[0162] On the basis of the various embodiments described above, the financial transaction device, after starting, collects environmental data in real time through the environmental detection device and timely takes corresponding target adjustment operations to ensure that the device operates in the best state. Subsequently, the financial transaction device executes target recommendation services by obtaining human feature information and further determining user identity transaction information, which can improve user experience. Upon receiving a transaction request, the financial transaction device can preprocess the transaction request to obtain target transaction data, providing a solid data foundation for subsequent business processing. Before business processing, the financial transaction device performs risk assessment based on target transaction data, environmental data, and human feature information to determine target risk information and risk processing methods to ensure the security of subsequent business processing. Subsequently, the financial transaction device can dynamically adjust the business processing flow according to the target risk information and risk processing methods, and process the transaction request according to the adjusted target business processing flow, which can ensure the efficiency and accuracy of transaction processing. After the transaction request is completed, the financial transaction device converts the transaction result format and adds personalized description text to generate a target processing result; the target processing result is output according to the target output method, and feedback information of the user is obtained for continuous optimization to further enhance customer satisfaction.

[0163] In the embodiments of the present application, the financial transaction device provides a more convenient, safe, and personalized financial transaction experience for customers through multiple links such as environmental perception, customer identification, transaction request preprocessing, business processing flow adjustment, and result feedback, effectively solving the defects of traditional financial transaction devices such as complex procedures, tedious operations, and slow response speed, and can optimize business processes, simplify operation steps, and improve response speed, thereby improving user experience, service efficiency, and security performance.

[0164] Figure 9 A structural schematic diagram of a business processing device provided in the present application is shown in FIG. 9. Figure 9 The business processing device 90 can include:

[0165] A first execution module 91 is configured to, after receiving a start instruction, obtain environmental data in real time and perform target adjustment operations according to the environmental data.

[0166] A second execution module 92 is configured to determine identity transaction information corresponding to a user according to human feature information of the user, and perform target recommendation services according to the identity transaction information.

[0167] A preprocessing module 93 is configured to receive a transaction request of a user, preprocess transaction request information, and obtain target transaction data corresponding to the transaction request.

[0168] Determination module 94, for determining target risk information and a risk handling method corresponding to the target risk information based on target transaction data, environmental data, and human characteristic information;

[0169] An adjustment module 95 is configured to adjust the business processing flow to obtain a target business processing flow based on the target risk information and the risk handling method, and process the transaction request according to the target business processing flow;

[0170] The output module 96 is used to output the target processing result corresponding to the transaction request.

[0171] In a possible implementation, the first execution module 91 is specifically configured to:

[0172] Initialize environmental detection equipment and obtain environmental data in real time through the environmental detection equipment;

[0173] According to the environmental data and the preset mapping relationship, the target adjustment operation corresponding to the environmental data is determined and executed; the preset mapping relationship includes preset adjustment operations corresponding to environmental data of different values.

[0174] In one possible implementation, the device 90 is further configured to:

[0175] Obtain historical environmental data and determine an environmental change model based on the historical environmental data; the environmental change model is used to predict the trend of environmental data changes;

[0176] Determine environmental prediction information corresponding to the environmental data based on the environmental data and the environmental change model;

[0177] When the environmental prediction information meets the preset threshold conditions, the warning information is output.

[0178] In one possible implementation, the device 90 is further configured to:

[0179] In the process of collecting environmental data, the environmental data is encrypted;

[0180] Environmental data is transmitted based on secure communication protocols and encrypted channels, and is stored in encrypted form.

[0181] In a possible implementation, the second execution module 92 is specifically configured to:

[0182] Acquire the user's body feature information through a camera; the body feature information includes facial information, expression information, and behavior information;

[0183] Determine the user's corresponding identity transaction information based on facial information;

[0184] Determine the user's corresponding predicted transaction information based on identity transaction information, expression information, and behavior information;

[0185] Based on the predicted transaction information, output target recommendation information and determine the business processing flow corresponding to the predicted transaction information.

[0186] In a possible implementation, the preprocessing module 93 is specifically configured to:

[0187] Obtain the transaction request message corresponding to the transaction request;

[0188] If the transaction request message meets the target message format conditions, the transaction request message is parsed to obtain the transaction key information corresponding to the transaction request message;

[0189] If the key transaction information is verified, the key transaction information is formatted and processed to obtain the target transaction data corresponding to the transaction request;

[0190] Stores target transaction data and sends it to other business components.

[0191] In a possible implementation, the preprocessing module 93 is specifically configured to:

[0192] Determine the target frequency parameters corresponding to the transaction request;

[0193] When the target frequency parameter satisfies a preset frequency threshold, storing the target transaction data according to the first storage space and the first validity period;

[0194] When the target frequency parameter does not meet the preset frequency threshold, the target transaction data is stored according to the second storage space and the second validity period; the first storage space is larger than the second storage space, and the first validity period is larger than the second validity period.

[0195] In one possible implementation, the device 90 is further configured to:

[0196] Determine the source and type of transaction request;

[0197] Update the target message format condition based on the source information and type information.

[0198] In a possible implementation, the determination module 94 is specifically configured to:

[0199] Determine the user's corresponding behavior analysis results based on human feature information;

[0200] Input the target transaction data, environmental data, and behavior analysis results into the target risk prediction model to obtain the target risk information corresponding to the transaction request;

[0201] Determine the risk processing mode corresponding to the target risk information.

[0202] In a possible implementation, the adjusting module 95 is specifically configured to:

[0203] According to the target risk information and the risk processing mode, adjust the key parameter, the transaction path, or the business processing mode corresponding to the business processing flow, to obtain a target business processing flow.

[0204] In a possible implementation, the output module 96 is specifically configured to:

[0205] In the case where the transaction request processing is completed, determine a transaction result corresponding to the transaction request;

[0206] Format-convert the transaction result and add description information corresponding to the transaction result, to obtain a target processing result;

[0207] Output the target processing result according to a target output mode, and obtain feedback information of the user.

[0208] The business processing apparatus 90 provided in the embodiments of the present application can execute the technical solutions shown in the method embodiments, and the implementation principles and beneficial effects are similar, which will not be repeated here.

[0209] Figure 10 A structural schematic diagram of a business processing device provided in the present application is shown in FIG. 1. Figure 10 The business processing device 100 can include a memory 1001 and a processor 1002. The memory 1001 and the processor 1002 are connected to each other through a bus 1003.

[0210] The memory 1001 is configured to store program instructions.

[0211] The processor 1002 is configured to execute the program instructions stored in the memory, to implement the business processing method shown in the above embodiments.

[0212] Figure 10 The business processing device 100 shown in the embodiments of the present application can execute the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects are similar, which will not be repeated here.

[0213] The embodiments of the present application provide a computer readable storage medium, and the computer readable storage medium stores computer execution instructions. When the computer execution instructions are executed by a processor, the computer execution instructions are configured to implement the above business processing method.

[0214] The embodiments of the present application can also provide a computer program product, which includes a computer program. When the computer program is executed by a processor, the computer program can implement the above business processing method.

[0215] It should be noted that the processor mentioned in the embodiments of the present application can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0216] It should be understood that the memory mentioned in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM) used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct memory bus random access memory (DRAM). It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, the memory (storage module) is integrated in the processor. It should be noted that the memory described herein is intended to include but not limited to these and any other suitable types of memory.

[0217] It should be understood that the size of the sequence number of each process described above in various embodiments of the present application does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0218] Embodiments of the present application are described with reference to flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processing unit of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the processing unit of the computer or other programmable data processing devices produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for performing the functions specified in the flow or flows and / or block or blocks.

[0219] These computer program instructions can also be stored in a computer-readable memory that can guide the computer or other programmable data processing devices to work in a specific way, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction means, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for performing the functions specified in the flow or flows and / or block or blocks.

[0220] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are performed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide a process for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for performing the functions specified in the flow or flows and / or block or blocks.

[0221] Regarding each module / unit contained in each device / product described in the above embodiments, it can be a software module / unit, or a hardware module / unit, or part of a software module / unit and part of a hardware module / unit. Each device / product can be applied to or integrated into a chip, a chip module, or a terminal device. Illustratively, for each device / product applied to or integrated into a chip, each module / chip contained therein can be realized in the form of hardware such as a circuit, or at least part of the modules / units can be realized in the form of a software program running on a processor integrated in the chip, and the remaining part of the modules / units can be realized in the form of hardware such as a circuit.

[0222] In this application, the term "comprising" and its variants can refer to non-limiting inclusion; the term "or" and its variants can refer to "and / or". In this application, the terms "first", "second" and the like are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. In this application, "multiple" refers to two or more. "And / or", which describes the relationship between the associated objects, means that there can be three relationships, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone. The character " / " generally represents a "or" relationship between the front and rear associated objects.

[0223] The above is only part of the embodiments of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which should also be considered as the protection scope of the present application.

Claims

1. A business processing method, characterized in that: include: After receiving the start command, the system acquires environmental data in real time and performs target adjustment operations based on the environmental data; Determining the identity transaction information corresponding to the user based on the user's body feature information, and performing target recommendation services based on the identity transaction information; receiving a transaction request from the user, preprocessing the transaction request, and obtaining target transaction data corresponding to the transaction request; Determining target risk information and a risk handling method corresponding to the target risk information based on the target transaction data, the environmental data, and the human characteristic information; Adjusting the business processing flow to obtain a target business processing flow based on the target risk information and the risk handling method, and processing the transaction request according to the target business processing flow; Outputting the target processing result corresponding to the transaction request; The determining of the identity transaction information corresponding to the user based on the user's body feature information, and performing a target recommendation service based on the identity transaction information, includes: Acquire the user's body feature information through a camera; the body feature information includes facial information, expression information, and behavior information; Determining the identity transaction information corresponding to the user based on the facial information; Determining predicted transaction information corresponding to the user based on the identity transaction information, the expression information, and the behavior information; Output target recommendation information based on the predicted transaction information and determine the business processing flow corresponding to the predicted transaction information; The determining, based on the target transaction data, the environmental data, and the human characteristic information, target risk information and a risk handling method corresponding to the target risk information includes: Determining a behavior analysis result corresponding to the user based on the human body feature information; Inputting the target transaction data, the environmental data, and the behavior analysis results into a target risk prediction model to obtain target risk information corresponding to the transaction request; Determine the risk handling method corresponding to the target risk information.

2. The method according to claim 1, characterized in that The acquiring of environmental data and performing target adjustment operations according to the environmental data includes: Initializing an environmental detection device and acquiring the environmental data in real time through the environmental detection device; According to the environmental data and the preset mapping relationship, a target adjustment operation corresponding to the environmental data is determined and executed; the preset mapping relationship includes preset adjustment operations corresponding to environmental data of different values.

3. The method according to claim 1, characterized in that The method further comprises: Acquire historical environmental data and determine an environmental change model based on the historical environmental data; the environmental change model is used to predict the trend of environmental data changes; Determining environmental prediction information corresponding to the environmental data based on the environmental data and the environmental change model; When the environmental prediction information meets a preset threshold condition, an early warning message is output.

4. The method according to any one of claims 1 to 3, characterized in that The method further comprises: In the process of collecting the environmental data, encrypting the environmental data; The environmental data is transmitted based on a secure communication protocol and an encrypted channel, and the environmental data is encrypted and stored.

5. The method according to claim 1, wherein The receiving the transaction request from the user, pre-processing the transaction request, and obtaining target transaction data corresponding to the transaction request includes: Obtaining a transaction request message corresponding to the transaction request; If the transaction request message meets the target message format condition, the transaction request message is parsed to obtain the transaction key information corresponding to the transaction request message; If the transaction key information is verified, the transaction key information is formatted and processed to obtain target transaction data corresponding to the transaction request; The target transaction data is stored and sent to other business components.

6. The method according to claim 5, characterized in that The storing of the target transaction data includes: determining a target frequency parameter corresponding to the transaction request; When the target frequency parameter satisfies a preset frequency threshold, storing the target transaction data according to the first storage space and the first validity period; When the target frequency parameter does not meet the preset frequency threshold, the target transaction data is stored according to the second storage space and the second validity period; the first storage space is larger than the second storage space, and the first validity period is larger than the second validity period.

7. The method according to claim 5 or 6, characterized in that The method further comprises: Determining source information and type information of the transaction request; The target message format condition is updated according to the source information and type information.

8. The method according to claim 1, characterized in that The step of adjusting the business processing flow to obtain a target business processing flow according to the target risk information and the risk handling method includes: According to the target risk information and the risk handling method, key parameters, transaction paths or business handling methods corresponding to the business handling process are adjusted to obtain the target business handling process.

9. The method according to claim 1, characterized in that Outputting the target processing result corresponding to the transaction request includes: When the transaction request is processed, determining a transaction result corresponding to the transaction request; Convert the transaction result into a new format and add the corresponding description information to obtain the target processing result. The target processing result is output according to the target output mode, and feedback information from the user is obtained.

10. A business processing device, characterized in that: include: A first execution module is configured to obtain environmental data in real time after receiving a start instruction, and perform a target adjustment operation according to the environmental data; A second execution module is configured to determine the identity transaction information corresponding to the user based on the user's body feature information, and execute a target recommendation service based on the identity transaction information; a preprocessing module, configured to receive a transaction request from the user, preprocess the transaction request information, and obtain target transaction data corresponding to the transaction request; a determination module, configured to determine target risk information and a risk handling method corresponding to the target risk information based on the target transaction data, the environmental data, and the human characteristic information; an adjustment module, configured to adjust the business processing flow to obtain a target business processing flow according to the target risk information and the risk handling method, and process the transaction request according to the target business processing flow; An output module, configured to output a target processing result corresponding to the transaction request; The second execution module is specifically configured to: Acquire the user's body feature information through a camera; the body feature information includes facial information, expression information, and behavior information; Determining the identity transaction information corresponding to the user based on the facial information; Determining predicted transaction information corresponding to the user based on the identity transaction information, the expression information, and the behavior information; Output target recommendation information based on the predicted transaction information and determine the business processing flow corresponding to the predicted transaction information; The determining module is specifically configured to: Determining a behavior analysis result corresponding to the user based on the human body feature information; Inputting the target transaction data, the environmental data, and the behavior analysis results into a target risk prediction model to obtain target risk information corresponding to the transaction request; Determine the risk handling method corresponding to the target risk information.

11. A business processing device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the business processing method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the business processing method according to any one of claims 1 to 9.

13. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the service processing method according to any one of claims 1 to 9 is implemented.

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