Bank card integrated management method and use method thereof

Abstract

The invention relates to the technical field of bank cards, in particular to a bank card integrated management method and a use method thereof, comprising a bank card information centralized storage module, a bill information generation module, a payment, transfer and account management module, a data analysis and suggestion module, a data security mechanism module and a personalized customer service and intelligent support module, the bank card information centralized storage module comprises bank card information, an encryption technology, key management, cloud storage and user identity verification, the encryption technology uses an advanced encryption standard in an AES algorithm, data transmission is carried out by adopting an HTTPS protocol, and an encryption mode based on quantum key distribution (QKD) is introduced. The method has the advantages of being intelligent and safe, the safety of user information and transaction data is ensured through multiple safety measures of multi-factor authentication, advanced encryption standard (AES), HTTPS protocol and QKD encryption mode, the geofence technology is introduced, an abnormal login site is monitored, and the login safety is further enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of bank cards, and in particular to a bank card integrated management method and a use method thereof. Background Art

[0002] As a card used to store user financial information and conduct financial transactions, bank cards have become an indispensable part of the modern financial system. They are closely linked to users' bank accounts and support users' withdrawals, deposits, transfers, payments and other financial activities. However, with the increasing complexity of the network environment and the increasing types and number of network threats, traditional bank card management methods have gradually revealed their limitations in ensuring user information security.

[0003] Traditional bank card management methods rely on a single authentication method, such as using only a password to log in. Although password authentication can protect user accounts to a certain extent, this single authentication method is insufficient in the face of increasingly complex network attacks. Hackers can easily steal users' passwords and obtain key bank card information through phishing attacks, malware, brute force cracking, etc., resulting in economic losses. With the development of quantum computing technology, the security of traditional cryptography has been challenged, and the security of a single password can no longer meet the needs of modern network security.

[0004] The traditional bank card management method has many inconveniences in actual operation. Users need to manage and operate bank cards on multiple different platforms or applications, such as logging in and managing accounts on different bank websites, third-party payment platforms or mobile applications. This decentralized management method increases the complexity of operations and leads to repeated entry and errors of information. Users need to enter the same bank card information on different platforms, which wastes time and increases the risk of information leakage. In addition, data synchronization problems between different platforms often lead to the inability of users to promptly reflect operations on one platform on other platforms, causing trouble for users.

[0005] Traditional bank card management methods lack personalized services. In the current financial market, users' personalized needs are growing, but traditional management methods cannot provide customized suggestions and solutions based on users' consumption habits, financial status, etc. For example, when users want to obtain expenditure analysis based on their own consumption patterns, or want the system to automatically generate budget suggestions, traditional management methods usually only provide basic transaction record query functions, which cannot deeply analyze users' financial behaviors, nor can they provide personalized financial suggestions, making it difficult for users to effectively manage their financial status.

[0006] Finally, the traditional bank card management method is relatively backward in terms of technological application, and cannot fully utilize big data analysis and artificial intelligence technologies to help financial institutions understand user needs, optimize product design and service processes, and provide users with financial advice and risk warnings. Summary of the invention

[0007] The purpose of the present invention is to provide a bank card integrated management method and a method of using the same, which has the advantages of intelligence and security and solves the problems raised by the above-mentioned background technology.

[0008] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a bank card integrated management method and its use method, including: a bank card information centralized storage module, a bill information generation module, a payment, transfer and account management module, a data analysis and suggestion module, a data security mechanism module and a personalized customer service and intelligent support module.

[0009] The bank card information centralized storage module includes bank card information, encryption technology, key management, cloud storage and user identity authentication.

[0010] The encryption technology uses the advanced encryption standard in the AES algorithm, adopts the HTTPS protocol for data transmission, and introduces an encryption method based on quantum key distribution (QKD).

[0011] The key management adopts dynamic key generation technology and uses hierarchical key management.

[0012] The cloud storage stores the encrypted bank card information in a dispersed manner in multiple servers in the cloud.

[0013] The bill information generation module includes data collection, data analysis, bill generation and bill query.

[0014] The data is collected by cooperating with major banks to obtain their API interfaces and using financial data aggregation platform analysis services.

[0015] The data analysis is based on an automatic classification and labeling system based on machine learning.

[0016] The bill generation uses charts or graphics to perform visual bill presentation.

[0017] The payment, transfer and account management modules are connected to major payment platforms, provide a one-click payment function, support multiple payment methods, use an integrated risk control engine to identify abnormal transactions, use the Secure File Transfer Protocol (SFTP) for transfers, support real-time or scheduled transfers, provide a balance query function, display the user's transaction history, provide an account setting function, and support multi-language account settings.

[0018] The data analysis and suggestion module includes data analysis and financial suggestions.

[0019] The data analysis integrates time series analysis and machine learning techniques, deep learning algorithms and graph theory algorithms.

[0020] The data security mechanism module includes data encryption technology, identity authentication mechanism and security audit.

[0021] The data encryption technology uses the asymmetric encryption algorithm RSA to encrypt sensitive information, uses a keyed message authentication code (HMAC) to verify the integrity of the data, and further encrypts it through quantum key distribution (QKD).

[0022] The identity authentication mechanism uses a login password as the first layer of identity authentication, two-factor authentication combining a dynamic password and an SMS verification code as the second layer of identity authentication, and biometrics as the third layer of identity authentication, and uses geo-fencing technology to automatically detect changes in the login location.

[0023] The personalized customer service and intelligent support module includes AI robots, personalized recommendations and multi-channel support.

[0024] The AI ​​robot integrates natural language processing (NLP) technology, sentiment analysis technology, knowledge base and GPT deep learning technology.

[0025] The personalized recommendation is based on an intelligent recommendation engine of machine learning.

[0026] Furthermore, as a preferred embodiment of the present invention, the bank card information includes card number, cardholder name, expiration date, security code, issuing institution, billing address, card type, card level and card status.

[0027] Furthermore, as a preferred embodiment of the present invention, the user identity authentication includes a login password, two-factor authentication combining a dynamic password and an SMS verification code, and biometric identification.

[0028] Furthermore, as a preferred embodiment of the present invention, the financial advice is provided through a dynamically adjusted budget advice system, which automatically adjusts the budget according to changes in user income and consumption, and provides saving strategies and investment advice based on the user's financial status and risk preferences.

[0029] Furthermore, as a preferred embodiment of the present invention, the security audit records detailed logs of all user operations, including timestamps, operation types, and operation object information, uses machine learning algorithms to automatically analyze large amounts of logs, quickly identify abnormal behaviors, and ensure system updates through an automatic update mechanism.

[0030] Furthermore, as a preferred embodiment of the present invention, the bill query provides an online query system, supports multi-dimensional query, provides bill printing or downloading functions, and allows users to set custom query conditions.

[0031] Furthermore, as a preferred embodiment of the present invention, the multi-channel support can be accessed collaboratively on multiple platforms, such as the Web, mobile application and desktop clients, and provides a voice assistant function for querying and managing accounts through voice.

[0032] The present invention provides a bank card integrated management method and a method of using the same, the method comprising the following steps:

[0033] Step 1: User authentication: Users enter through multi-factor authentication login password, dynamic password, SMS verification code or biometrics, encrypt bank card information using Advanced Encryption Standard (AES), use HTTPS protocol for data transmission to ensure the security of data during transmission, introduce QKD encryption method to further improve the security of data encryption, store the encrypted bank card information in multiple servers in the cloud to improve data security and recoverability, monitor the login location through geo-fencing technology, and if an abnormal location is detected, the user will be required to provide further identity verification to ensure login security;

[0034] Step 2: Synchronize users’ bank card transaction information in real time through the API interfaces of major banks, use the analysis services of the financial data aggregation platform to standardize the data, support the data synchronization function of mobile devices, ensure the real-time and consistency of the data, identify and classify the transaction types based on the automatic classification and labeling system of machine learning, clean and denoise the data returned by the bank, remove abnormal or irrelevant data, generate visual bills, and display transaction information in the form of charts or graphics. Users can query complete bill information and transaction records through voice or text input;

[0035] Step 3: Connect with major payment platforms, provide one-click payment function, identify abnormal transactions through integrated risk control engine, use secure file transfer protocol when transferring money to ensure the security of data during transmission, support real-time or scheduled transfer, provide multi-language account setting function, support balance inquiry and transaction history viewing;

[0036] Step 4: Use time series analysis and machine learning technology to predict the user's consumption trend. Use deep learning algorithms to improve the accuracy of consumption trend prediction. Use graph theory algorithms to find potential connections in user transactions to help users better manage capital flows. Use a dynamically adjusted budget suggestion system to automatically adjust the budget according to changes in user income and consumption. Provide savings strategies and investment suggestions based on the user's financial status and risk preferences to help users make better financial decisions.

[0037] Step 5: Bank card information is encrypted using the AES and RSA algorithms and stored in the HSM and distributed databases in the cloud. HMAC is used to verify the integrity of the data to prevent data tampering. All user operations are logged in detail and automatically analyzed to identify abnormal behaviors. The system security is ensured through an automatic update mechanism.

[0038] Step 6: Use AI robots to conduct natural language conversations with users, provide queries, settings, and suggestions, identify users' emotional states, provide corresponding support and comfort, recommend suitable products and services based on user preferences and transaction history, and support multiple methods of interaction and query through voice assistants, web terminals, and mobile applications.

[0039] Beneficial effects: The technical solution of the present application has the following technical effects: the present invention has the advantages of intelligent security. Through multiple security measures such as multi-factor authentication, Advanced Encryption Standard (AES), HTTPS protocol, and QKD encryption, the security of user information and transaction data is ensured. Geographical fence technology is introduced to monitor abnormal login locations to further enhance login security. Data is stored in multiple servers in the cloud to improve data security and recoverability. Real-time synchronization of user's bank card transaction information is performed to ensure real-time update of data. The financial data aggregation platform is used to standardize data, support data synchronization of mobile devices, and ensure data consistency between different platforms. Based on machine learning and deep learning algorithms, the user's consumption trend is predicted, and personalized budget suggestions and saving strategies are provided. Through natural language dialogue with users through AI robots, query, setting and suggestion functions are provided to enhance user experience. By providing a one-click payment function, the payment process is simplified, real-time or scheduled transfers are supported, as well as multi-language account settings, to meet the diverse operation needs of users. Through comprehensive risk management and monitoring, the integrated risk control engine can identify abnormal transactions and reduce transaction risks. Detailed log records and automatic analysis of all user operations are performed to identify abnormal behaviors and ensure the overall security of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0041] Figure 1 It is a flow chart of the system of the present invention. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. In order to better understand the technical content of the present invention, specific embodiments are cited and explained in conjunction with the drawings as follows. Various aspects of the present invention are described in this disclosure with reference to the drawings, in which many illustrative embodiments are shown. It should be understood that the various concepts and embodiments introduced above, as well as those described in more detail below, can be implemented in any of many ways. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0043] As attached Figure 1 :This embodiment provides a bank card integrated management method and a method of using the same, including:

[0044] Bank card information centralized storage module, bill information generation module, payment, transfer and account management module, data analysis and suggestion module, data security mechanism module and personalized customer service and intelligent support module.

[0045] The bank card information centralized storage module includes bank card information, encryption technology, key management, cloud storage and user identity authentication.

[0046] The encryption technology uses the advanced encryption standard in the AES algorithm, adopts the HTTPS protocol for data transmission, and introduces an encryption method based on quantum key distribution (QKD).

[0047] The key management adopts dynamic key generation technology and uses hierarchical key management.

[0048] The cloud storage stores the encrypted bank card information in a dispersed manner in multiple servers in the cloud.

[0049] The bill information generation module includes data collection, data analysis, bill generation and bill query.

[0050] The data is collected by cooperating with major banks to obtain their API interfaces and using financial data aggregation platform analysis services.

[0051] The data analysis is based on an automatic classification and labeling system based on machine learning.

[0052] The bill generation uses charts or graphics to perform visual bill presentation.

[0053] The payment, transfer and account management modules are connected to major payment platforms, provide a one-click payment function, support multiple payment methods, use an integrated risk control engine to identify abnormal transactions, use the Secure File Transfer Protocol (SFTP) for transfers, support real-time or scheduled transfers, provide a balance query function, display the user's transaction history, provide an account setting function, and support multi-language account settings.

[0054] The data analysis and suggestion module includes data analysis and financial suggestions.

[0055] The data analysis integrates time series analysis and machine learning techniques, deep learning algorithms and graph theory algorithms.

[0056] The data security mechanism module includes data encryption technology, identity authentication mechanism and security audit.

[0057] The data encryption technology uses the asymmetric encryption algorithm RSA to encrypt sensitive information, uses a keyed message authentication code (HMAC) to verify the integrity of the data, and further encrypts it through quantum key distribution (QKD).

[0058] The identity authentication mechanism uses a login password as the first layer of identity authentication, two-factor authentication combining a dynamic password and an SMS verification code as the second layer of identity authentication, and biometrics as the third layer of identity authentication, and uses geo-fencing technology to automatically detect changes in the login location.

[0059] The personalized customer service and intelligent support module includes AI robots, personalized recommendations and multi-channel support.

[0060] The AI ​​robot integrates natural language processing (NLP) technology, sentiment analysis technology, knowledge base and GPT deep learning technology.

[0061] The personalized recommendation is based on an intelligent recommendation engine of machine learning.

[0062] Specifically, the bank card information includes the card number, cardholder name, expiration date, security code, issuing institution, billing address, card type, card level and card status.

[0063] Specifically, the user identity verification includes a login password, two-factor authentication combining a dynamic password and a text message verification code, and biometric identification.

[0064] Specifically, the financial advice is provided through a dynamically adjusted budget advice system, which automatically adjusts the budget according to changes in the user's income and consumption, and provides savings strategies and investment advice based on the user's financial status and risk preferences.

[0065] Specifically, the security audit records detailed logs of all user operations, including timestamps, operation types, and operation object information, uses machine learning algorithms to automatically analyze large amounts of logs, quickly identify abnormal behaviors, and ensure system updates through an automatic update mechanism.

[0066] Specifically, the bill query provides an online query system, supports multi-dimensional query, provides bill printing or downloading functions, and allows users to set custom query conditions.

[0067] Specifically, the multi-channel support can be accessed through multiple platforms, such as the Web, mobile application and desktop client, and provides a voice assistant function to query and manage accounts through voice.

[0068] The present invention provides a bank card integrated management method and a method of using the same, the method comprising the following steps:

[0069] Step 1: User authentication: Users enter through multi-factor authentication login password, dynamic password, SMS verification code or biometrics, encrypt bank card information using Advanced Encryption Standard (AES), use HTTPS protocol for data transmission to ensure the security of data during transmission, introduce QKD encryption method to further improve the security of data encryption, store the encrypted bank card information in multiple servers in the cloud to improve data security and recoverability, monitor the login location through geo-fencing technology, and if an abnormal location is detected, the user will be required to provide further identity verification to ensure login security;

[0070] Step 2: Synchronize users’ bank card transaction information in real time through the API interfaces of major banks, use the analysis services of the financial data aggregation platform to standardize the data, support the data synchronization function of mobile devices, ensure the real-time and consistency of the data, identify and classify the transaction types based on the automatic classification and labeling system of machine learning, clean and denoise the data returned by the bank, remove abnormal or irrelevant data, generate visual bills, and display transaction information in the form of charts or graphics. Users can query complete bill information and transaction records through voice or text input;

[0071] Step 3: Connect with major payment platforms, provide one-click payment function, identify abnormal transactions through integrated risk control engine, use secure file transfer protocol when transferring money to ensure the security of data during transmission, support real-time or scheduled transfer, provide multi-language account setting function, support balance inquiry and transaction history viewing;

[0072] Step 4: Use time series analysis and machine learning technology to predict the user's consumption trend. Use deep learning algorithms to improve the accuracy of consumption trend prediction. Use graph theory algorithms to find potential connections in user transactions to help users better manage capital flows. Use a dynamically adjusted budget suggestion system to automatically adjust the budget according to changes in user income and consumption. Provide savings strategies and investment suggestions based on the user's financial status and risk preferences to help users make better financial decisions.

[0073] Step 5: Bank card information is encrypted using the AES and RSA algorithms and stored in the HSM and distributed databases in the cloud. HMAC is used to verify the integrity of the data to prevent data tampering. All user operations are logged in detail and automatically analyzed to identify abnormal behaviors. The system security is ensured through an automatic update mechanism.

[0074] Step 6: Use AI robots to conduct natural language conversations with users, provide queries, settings, and suggestions, identify users' emotional states, provide corresponding support and comfort, recommend suitable products and services based on user preferences and transaction history, and support multiple methods of interaction and query through voice assistants, web terminals, and mobile applications.

[0075] It should be noted that, in this document, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0076] Although the present invention has been disclosed as above with preferred embodiments, it is not intended to limit the present invention. A person with ordinary knowledge in the technical field to which the present invention belongs may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be determined by the definition of the claims.

Claims

1. A bank card integrated management method, characterized in that: include: Bank card information centralized storage module, bill information generation module, payment, transfer and account management module, data analysis and suggestion module, data security mechanism module and personalized customer service and intelligent support module; The bank card information centralized storage module includes bank card information, encryption technology, key management, cloud storage and user identity authentication; The encryption technology uses the Advanced Encryption Standard in the AES algorithm, adopts the HTTPS protocol for data transmission, and introduces an encryption method based on quantum key distribution (QKD); The key management adopts dynamic key generation technology and uses hierarchical key management; The cloud storage stores the encrypted bank card information in multiple servers in the cloud; The bill information generation module includes data collection, data analysis, bill generation and bill query; The data collection is carried out in cooperation with major banks to obtain their API interfaces and use financial data aggregation platform analysis services; The data analysis is based on an automatic classification and labeling system of machine learning; The bill generation uses charts or graphics to display the bill visually; The payment, transfer and account management modules are connected with major payment platforms, provide one-click payment function, support multiple payment methods, use integrated risk control engine, identify abnormal transactions, use secure file transfer protocol (SFTP) for transfer, support real-time or scheduled transfer, provide balance query function, display user's transaction history, provide account setting function, and support multi-language account setting; The data analysis and suggestion module includes data analysis and financial suggestions; The data analysis integrates time series analysis and machine learning techniques, deep learning algorithms and graph theory algorithms; The data security mechanism module includes data encryption technology, identity authentication mechanism and security audit; The data encryption technology uses the asymmetric encryption algorithm RSA to encrypt sensitive information, uses keyed message authentication code (HMAC) to verify the integrity of the data, and further encrypts it through quantum key distribution (QKD); The authentication mechanism uses a login password as the first layer of authentication, a two-factor authentication combining a dynamic password and a text message verification code as the second layer of authentication, and biometrics as the third layer of authentication, and uses geo-fencing technology to automatically detect changes in login locations; The personalized customer service and intelligent support module includes AI robots, personalized recommendations and multi-channel support; The AI ​​robot integrates natural language processing (NLP) technology, sentiment analysis technology, knowledge base and GPT deep learning technology; The personalized recommendation is based on an intelligent recommendation engine of machine learning.

2. A bank card integrated management method according to claim 1, characterized in that: The bank card information includes card number, cardholder name, expiration date, security code, issuing institution, billing address, card type, card level and card status.

3. A bank card integrated management method according to claim 1, characterized in that: The user identity authentication includes a login password, two-factor authentication combining a dynamic password and an SMS verification code, and biometrics.

4. A bank card integrated management method according to claim 1, characterized in that: The financial advice is provided by a dynamically adjusted budget advice system that automatically adjusts the budget according to changes in the user's income and consumption, and provides savings strategies and investment advice based on the user's financial status and risk preferences.

5. A bank card integrated management method according to claim 1, characterized in that: The security audit records all user operations in detail, including timestamps, operation types, and operation object information. It uses machine learning algorithms to automatically analyze large amounts of logs, quickly identify abnormal behaviors, and ensure system updates through an automatic update mechanism.

6. A bank card integrated management method according to claim 1, characterized in that: The bill query provides an online query system that supports multi-dimensional query, provides bill printing or downloading functions, and allows users to set custom query conditions.

7. A bank card integrated management method according to claim 1, characterized in that: The multi-channel support enables collaborative access across multiple platforms, such as the Web, mobile application, and desktop client, and provides a voice assistant function for querying and managing accounts through voice.

8. A bank card integrated management method and a method of using the same, characterized in that: The method comprises the following steps: Step 1: User authentication: Users enter through multi-factor authentication login password, dynamic password, SMS verification code or biometrics, encrypt bank card information using Advanced Encryption Standard (AES), use HTTPS protocol for data transmission to ensure the security of data during transmission, introduce QKD encryption method to further improve the security of data encryption, store the encrypted bank card information in multiple servers in the cloud to improve data security and recoverability, monitor the login location through geo-fencing technology, and if an abnormal location is detected, the user will be required to provide further identity verification to ensure login security; Step 2: Synchronize users’ bank card transaction information in real time through the API interfaces of major banks, use the analysis services of the financial data aggregation platform to standardize the data, support the data synchronization function of mobile devices, ensure the real-time and consistency of the data, identify and classify the transaction types based on the automatic classification and labeling system of machine learning, clean and denoise the data returned by the bank, remove abnormal or irrelevant data, generate visual bills, and display transaction information in the form of charts or graphics. Users can query complete bill information and transaction records through voice or text input; Step 3: Connect with major payment platforms, provide one-click payment function, identify abnormal transactions through integrated risk control engine, use secure file transfer protocol when transferring money to ensure the security of data during transmission, support real-time or scheduled transfer, provide multi-language account setting function, support balance inquiry and transaction history viewing; Step 4: Use time series analysis and machine learning technology to predict the user's consumption trend. Use deep learning algorithms to improve the accuracy of consumption trend prediction. Use graph theory algorithms to find potential connections in user transactions to help users better manage capital flows. Use a dynamically adjusted budget suggestion system to automatically adjust the budget according to changes in user income and consumption. Provide savings strategies and investment suggestions based on the user's financial status and risk preferences to help users make better financial decisions. Step 5: Bank card information is encrypted using the AES and RSA algorithms and stored in the HSM and distributed databases in the cloud. HMAC is used to verify the integrity of the data to prevent data tampering. All user operations are logged in detail and automatically analyzed to identify abnormal behaviors. The system security is ensured through an automatic update mechanism. Step 6: Use AI robots to conduct natural language conversations with users, provide queries, settings, and suggestions, identify users' emotional states, provide corresponding support and comfort, recommend suitable products and services based on user preferences and transaction history, and support multiple methods of interaction and query through voice assistants, web terminals, and mobile applications.

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