Asset query method and device

Abstract

The invention provides an asset query method and device, which can be used in the financial field or other fields. The method comprises the following steps: acquiring a first query request sent by a query terminal, and processing the first query request sent by the query terminal by using a preset asset query strong authentication dual-algorithm model to obtain a customer identifier; obtaining first effective verification information and second effective verification information corresponding to the customer identifier in a preset aging region; and obtaining customer asset information sent by the generative artificial intelligence server through an asset query encryption packaging interface by using the first effective verification information and the second effective verification information, and feeding back the customer asset information to a customer through a query terminal. According to the method, convenient and brand-new asset and liability management services are provided for clients, the clients do not need to open all electronic banks to inquire assets and then carry out single superposition, all assets under the name can be inquired clearly at a glance, and the convenience of asset inquiry is improved while data safety is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of data query technology, and in particular to an asset query method and device. Background Art

[0002] With the development of electronic technology and network technology, electronic banking such as mobile banking, online banking, and telephone banking has been widely used in daily life, bringing convenience to customers' lives.

[0003] In the prior art, when a customer wants to check the assets under his name, he usually needs to check the assets in a bank through the electronic banking of a bank. He can only obtain a single piece of information and cannot check all the assets in all banks under his name. If the customer loses his mobile phone and forgets which bank assets and account passwords he has, he may miss some asset management. Therefore, how to propose an asset query method so that customers can check all assets under their name at a glance without opening the electronic banking has become an important issue that needs to be solved in this field. Summary of the invention

[0004] In view of the problems existing in the prior art, the main purpose of the embodiments of the present invention is to provide an asset query method and device, so as to improve the convenience of asset query while ensuring data security.

[0005] In order to achieve the above object, an embodiment of the present invention provides an asset query method, the method comprising:

[0006] Obtaining a first query request sent by the query terminal, and processing the first query request sent by the query terminal using a preset asset query strong authentication dual algorithm model to obtain a customer identifier;

[0007] Acquire the first valid verification information and the second valid verification information corresponding to the customer identification within the preset time validity area;

[0008] Utilizing the first valid verification information and the second valid verification information, the customer asset information sent by the generative artificial intelligence server is obtained through the asset query encryption encapsulation interface, and the customer asset information is fed back to the customer through the query terminal.

[0009] Optionally, in an embodiment of the present invention, the method further includes: obtaining customer identity information corresponding to the customer identifier based on the customer identifier, and verifying the customer identity information corresponding to the customer identifier.

[0010] Optionally, in one embodiment of the present invention, obtaining the customer asset information sent by the generative artificial intelligence server through the asset query encryption encapsulation interface includes:

[0011] Obtain all the customer's asset information through the asset query encryption encapsulation interface, and encrypt all the customer's asset information using encryption algorithms;

[0012] The encrypted customer's entire asset information is desensitized using a preset information desensitization model, and the desensitized customer's entire asset information is sent to a generative artificial intelligence server to obtain the customer asset information sent by the generative artificial intelligence server.

[0013] Optionally, in one embodiment of the present invention, desensitizing all encrypted customer asset information using a preset information desensitization model includes:

[0014] By using the preset information desensitization model, the real customer data in all the encrypted customer asset information is replaced with deformed data, and the desensitization process has been completed.

[0015] Optionally, in one embodiment of the present invention, the method further includes:

[0016] Obtaining a first query request sent by the acquisition terminal, and determining a client login status according to the first query request sent by the acquisition terminal;

[0017] If the customer's login status is not logged in, the collection terminal is used to display the preset generative artificial intelligence login page to the customer and obtain the account information entered by the customer;

[0018] Encrypt the account information using an asymmetric encryption algorithm, and send the encrypted account information to the generative artificial intelligence server via a third-party server to obtain first valid verification information fed back by the generative artificial intelligence server;

[0019] After obtaining the first valid authentication information, using asset query strong authentication processing to obtain second valid authentication information;

[0020] The first valid verification information and the second valid authentication information are processed using a preset structural equation model to obtain a processing result, and the processing result is sent to a third-party server to complete the customer login registration.

[0021] Optionally, in an embodiment of the present invention, obtaining the account information input by the customer includes:

[0022] Obtain account information entered by the customer based on the generative AI login page;

[0023] Perform format verification on the account information and obtain the format verification result.

[0024] Optionally, in an embodiment of the present invention, using asset query strong authentication processing, obtaining the second valid authentication information includes:

[0025] Use the collection terminal to display the strong authentication page to the customer and obtain the login information entered by the customer;

[0026] Using the login information, obtaining multiple asset information authorized by the customer, and sending the multiple asset information to a third-party server;

[0027] The customer identity information authorized by the customer is obtained by using the collection terminal, and the customer identity information is verified to obtain the second valid authentication information.

[0028] The embodiment of the present invention further provides an asset query device, the device comprising:

[0029] A customer identification module is used to obtain a first query request sent by the query terminal, and process the first query request sent by the query terminal using a preset asset query strong authentication dual algorithm model to obtain a customer identification;

[0030] A verification information module, used to obtain first valid verification information and second valid verification information corresponding to the customer identifier within a preset time limit;

[0031] The query result module is used to use the first valid verification information and the second valid verification information to obtain the customer asset information sent by the generative artificial intelligence server through the asset query encryption encapsulation interface, and feed back the customer asset information to the customer through the query terminal.

[0032] Optionally, in an embodiment of the present invention, the device further includes: an identity authentication module, configured to obtain customer identity information corresponding to the customer identifier based on the customer identifier, and verify the customer identity information corresponding to the customer identifier.

[0033] Optionally, in one embodiment of the present invention, the query result module includes:

[0034] The encryption processing unit is used to obtain all the customer's asset information through the asset query encryption encapsulation interface, and encrypt all the customer's asset information using an encryption algorithm;

[0035] The desensitizing processing unit is used to use a preset information desensitizing model to desensitize all the encrypted customer asset information, and send the desensitized customer asset information to the generative artificial intelligence server to obtain the customer asset information sent by the generative artificial intelligence server.

[0036] Optionally, in one embodiment of the present invention, the desensitizing processing unit is also used to use a preset information desensitizing model to replace the real customer data in all the encrypted customer asset information with deformed data, thereby completing the desensitizing processing.

[0037] Optionally, in one embodiment of the present invention, the device further includes:

[0038] A login status module, used to obtain a first query request sent by the acquisition terminal, and determine a customer login status according to the first query request sent by the acquisition terminal;

[0039] The account information module is used to display a preset generative artificial intelligence login page to the customer using the acquisition terminal if the customer's login status is not logged in, and obtain the account information entered by the customer;

[0040] A first verification information module, used to encrypt the account information using an asymmetric encryption algorithm, and send the encrypted account information to the generative artificial intelligence server via a third-party server to obtain first valid verification information fed back by the generative artificial intelligence server;

[0041] A second verification information module is used to obtain the second valid authentication information by using the asset query strong authentication process after obtaining the first valid authentication information;

[0042] The login and registration module is used to process the first valid verification information and the second valid authentication information using a preset structural equation model, obtain a processing result, and send the processing result to a third-party server to complete the customer login and registration.

[0043] Optionally, in one embodiment of the present invention, the account information module includes:

[0044] An account information unit, used to obtain the account information entered by the customer based on the generative artificial intelligence login page;

[0045] The format verification unit is used to perform format verification on the account information and obtain a format verification result.

[0046] Optionally, in one embodiment of the present invention, the second verification information module includes:

[0047] A login information unit, used to display a strong authentication page to the customer using a collection terminal and obtain login information entered by the customer;

[0048] An information sending unit, used to obtain multiple asset information authorized by the customer using the login information, and send the multiple asset information to a third-party server;

[0049] The second verification information unit is used to obtain the customer identity information authorized by the customer through the collection terminal, verify the customer identity information, and obtain the second valid authentication information.

[0050] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the above method is implemented when the processor executes the program.

[0051] The present invention also provides a computer-readable storage medium, which stores a computer program for executing the above method by a computer.

[0052] The present invention also provides a computer program product, comprising a computer program / instruction, which implements the steps of the above method when the computer program / instruction is executed by a processor.

[0053] The present invention provides customers with a convenient and new asset-liability management service. Customers do not need to open all electronic banking to query assets and then perform a single overlay. All assets under their name can be queried at a glance, helping customers to grasp the status of all assets under their name in real time, thereby ensuring data security while improving the convenience of asset query. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 A flowchart of an asset query method according to an embodiment of the present invention;

[0056] Figure 2 A flowchart of obtaining customer asset information in an embodiment of the present invention;

[0057] Figure 3 A flowchart of customer login and registration in an embodiment of the present invention;

[0058] Figure 4 A flowchart of obtaining account information input by a customer in an embodiment of the present invention;

[0059] Figure 5 A flowchart of obtaining second valid authentication information in an embodiment of the present invention;

[0060] Figure 6 A schematic diagram of the system structure of the asset query method applied in the embodiment of the present invention;

[0061] Figure 7 A schematic diagram of system interaction in an embodiment of the present invention;

[0062] Figure 8 A flowchart of a customer login in an embodiment of the present invention;

[0063] Fig. 9 This is a flowchart of asset query in an embodiment of the present invention;

[0064] Fig.10This is a schematic diagram of the structure of an asset query device according to an embodiment of the present invention;

[0065] Fig.11 It is a structural schematic diagram of an asset query device in another embodiment of the present invention;

[0066] Fig.12 This is a schematic diagram of the structure of a query result module in an embodiment of the present invention;

[0067] Fig.13 This is a schematic diagram of the structure of an asset query device in another embodiment of the present invention;

[0068] Fig.14 This is a schematic diagram of the structure of an account information module in an embodiment of the present invention;

[0069] Fig.15 Schematic diagram of the structure of the second verification information module in an embodiment of the present invention;

[0070] Fig.16 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0071] The embodiments of the present invention provide an asset query method and device, which can be used in the financial field and other fields. It should be noted that the asset query method and device of the present invention can be used in the financial field, and can also be used in any field other than the financial field. The application field of the asset query method and device of the present invention is not limited.

[0072] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0073] like Figure 1 The flowchart of an asset query method according to an embodiment of the present invention is shown. The execution subject of the asset query method provided by the embodiment of the present invention includes but is not limited to a computer, such as a bank intelligent terminal, etc. The present invention provides customers with a convenient and brand-new asset-liability management service. Customers do not need to open all electronic banking to query assets and then perform a single overlay. Only through an open platform, customer data is encrypted, modeled, etc., so that all assets under the name can be queried at a glance, helping customers to grasp the status of all assets under their name in real time, and improving the convenience of asset query while ensuring data security. The method shown in the figure includes:

[0074] Step S1, obtaining a first query request sent by a query terminal, and using a preset asset query strong authentication dual algorithm model to process the first query request sent by the query terminal to obtain a customer identifier.

[0075] The collection terminal and the query terminal may be intelligent mobile terminals that can be used by customers. A first query request sent by the query terminal is received. Specifically, the first query request sent by the query terminal includes the words "query all assets under the name" in the customer input field when the customer is talking to the generative artificial intelligence (AI).

[0076] Further, it is determined whether the first query request sent by the query terminal hits the generative AI and the preset asset query strong authentication dual algorithm model, and the customer identification can be obtained after the hit. Specifically, the conventional method and model used to determine whether the first query request hits the generative AI and the preset asset query strong authentication dual algorithm model and the preset asset query strong authentication dual algorithm model are not repeated here.

[0077] Step S2: obtaining first valid verification information and second valid verification information corresponding to the customer identification within a preset time limit.

[0078] The first and second valid verification information are obtained by the customer during the login and registration process.

[0079] Step S3, using the first valid verification information and the second valid verification information, obtains the customer asset information sent by the generative artificial intelligence server through the asset query encryption encapsulation interface, and feeds back the customer asset information to the customer through the query terminal.

[0080] Among them, the bank asset query encryption and encapsulation interface is called, and the interface encrypts and encapsulates all the bank assets under the customer's name using the AES encryption algorithm and then provides them to the preset information desensitization model SDM (this model can deform the customer's real information to avoid customer data leakage). Specifically, the encryption algorithm is used for encryption processing and the information desensitization model uses conventional methods and models, which will not be repeated again.

[0081] Furthermore, after the customer data enters the information desensitization model, it will search for each node data in the queue to be desensitized, and identify whether each node data exists in the preset modified data list. If so, the data to be desensitized will be desensitized by data replacement, replacing the customer's real data with the deformed data formulated by the model. After the data is successfully desensitized, it will be transmitted to the generative AI server. After the generative AI server re-decrypts the desensitized data, it will return the customer's asset information. In this way, the customer's asset information is fed back to the customer as the query result.

[0082] As an embodiment of the present invention, the method further includes: obtaining customer identity information corresponding to the customer identifier according to the customer identifier, and verifying the customer identity information corresponding to the customer identifier.

[0083] After obtaining the customer identifier, the corresponding customer identity information is identified, and the security of the customer information is verified using a double encryption model authentication. After the verification is passed, the first and second valid verification information are obtained. Specifically, the customer identifier can be composed of numbers, letters, etc. The customer identity information can be pre-stored when the customer logs in and registers, and the customer identifier corresponds to the customer identity information one by one. In addition, the security of customer information can be verified using a double encryption model authentication in a conventional manner, which will not be repeated here.

[0084] As an embodiment of the present invention, Figure 2 As shown, the customer asset information sent by the generative artificial intelligence server obtained through the asset query encryption encapsulation interface includes:

[0085] Step S31, obtaining all the customer's asset information through the asset query encryption encapsulation interface, and encrypting all the customer's asset information using an encryption algorithm;

[0086] Step S32, using a preset information desensitization model, desensitizes all the encrypted customer asset information, and sends the desensitized customer asset information to the generative artificial intelligence server to obtain the customer asset information sent by the generative artificial intelligence server.

[0087] Among them, the bank asset query encryption and encapsulation interface is called, and the interface encrypts and encapsulates all the bank assets under the customer's name using the AES encryption algorithm and provides them to the preset information desensitization model SDM. Specifically, the encryption algorithm is used for encryption processing and the information desensitization model uses conventional methods and models, which will not be repeated again.

[0088] In this embodiment, desensitizing the encrypted customer's entire asset information using a preset information desensitizing model includes: replacing the customer's real data in the encrypted customer's entire asset information with deformed data using a preset information desensitizing model, thereby completing the desensitizing process.

[0089] Among them, after the customer data enters the information desensitization model, it will search for the data of each node in the queue to be desensitized, and identify whether the data of each node exists in the preset modified data list. If so, the data to be desensitized will be desensitized by data replacement, and the customer's real data will be replaced with the deformed data prepared by the model. After the data is successfully desensitized, it will be transmitted to the generative AI server. After the generative AI server re-decrypts the desensitized data, it will return the customer asset information.

[0090] As an embodiment of the present invention, Figure 3 As shown, the method also includes:

[0091] Step S4, obtaining a first query request sent by the acquisition terminal, and determining the customer login status according to the first query request sent by the acquisition terminal;

[0092] Step S5: If the customer login status is not logged in, the acquisition terminal is used to display a preset generative artificial intelligence login page to the customer and obtain the account information entered by the customer;

[0093] Step S6, encrypting the account information using an asymmetric encryption algorithm, and sending the encrypted account information to the generative artificial intelligence server via the third-party server to obtain first valid verification information fed back by the generative artificial intelligence server;

[0094] Step S7, after obtaining the first valid authentication information, using asset query strong authentication processing to obtain second valid authentication information;

[0095] Step S8, using a preset structural equation model, the first valid verification information and the second valid authentication information are processed to obtain a processing result, and the processing result is sent to a third-party server to complete the customer login registration.

[0096] Among them, a first query request sent by the collection terminal is received. Specifically, the first query request sent by the collection terminal includes the words "query all assets under the name" in the customer input field when the customer is talking with the generative AI.

[0097] Furthermore, the customer login status is determined based on the first query request sent by the acquisition terminal. If it is determined that the customer has not logged in to the generative AI, a generative AI login page pops up and the customer enters the account information.

[0098] In this embodiment, if Figure 4 As shown, obtaining the account information entered by the customer includes:

[0099] Step S51, obtaining the account information input by the customer based on the generative artificial intelligence login page;

[0100] Step S52, performing format verification on the account information to obtain a format verification result.

[0101] The correctness of the format of the account information is determined to obtain a format verification result. If the format verification result is correct, the account information is processed through the RSA encryption algorithm. If the format verification result is incorrect, the customer is prompted to re-enter.

[0102] Furthermore, the account information entered by the customer is encrypted and intelligently packaged and then transmitted to a third-party server. The third-party server decrypts the data and transmits it to the generative AI server for successful login. After successful login, the customer needs to sign a privacy disclaimer and agree to query the asset information under his name through generative AI. After successful signing, it becomes the first valid verification information (i.e., SEM structural equation model factor a).

[0103] In this embodiment, if Figure 5 As shown, by using asset query strong authentication processing, the second valid authentication information obtained includes:

[0104] Step S71, using the acquisition terminal to display a strong authentication page to the customer and obtain the login information entered by the customer;

[0105] Step S72, using the login information, obtaining multiple asset information authorized by the customer, and sending the multiple asset information to a third-party server;

[0106] Step S73, using the collection terminal to obtain the customer identity information authorized by the customer, verifying the customer identity information, and obtaining the second valid authentication information.

[0107] Among them, after the first valid verification information is successfully obtained, the strong authentication page for bank asset query is entered, which is the second valid verification information. The strong authentication method is for the customer to enter the online banking login information of any bank under his name. For example, the customer enters the online banking login information of Bank A. After the background verifies that the information is correct, the customer's asset information in other banks B, C, D, etc. is searched layer by layer through the association rules in the Apriori algorithm, and encrypted and packaged, and transmitted to the third-party server, without the need for the customer to manually enter the account number of each bank in turn. After the strong authentication is successful, the customer needs to perform face recognition authentication (collection terminal) to confirm the authenticity of the customer's identity. After the face recognition authentication is passed, the second valid verification information (i.e., SEM structural equation model factor b) is successfully obtained.

[0108] Further, when the first valid verification information and the second valid verification information are both obtained, factor a and factor b are successfully obtained. When factor a and factor b are obtained, they can be calculated through the SEM structural equation model. If only factor a or only factor b exists or there are other non-a and non-b factors, the SEM structural equation model cannot be used; after factor a and factor b are modeled through the SEM structural equation model, the final processing results are transmitted to the third-party server, which means that the customer identification can be successfully obtained, and the asset query can be successfully logged in. Among them, the calculation and modeling using the SEM structural equation model are all carried out in a conventional manner, which will not be repeated here.

[0109] In a specific embodiment of the present invention, the system structure diagram of applying the above asset query method is as follows: Figure 6 As shown, the system shown in the figure can specifically be a query terminal used for asset query. The present invention is based on the integration mechanism and method of generative AI (i.e., a type of artificial intelligence technology that can generate content, solutions or new concepts, such as GAN, OpenAI, Magenta, etc.) and bank asset linkage, which can at least partially solve the problems existing in the prior art.

[0110] In this embodiment, if Figure 7 The system interaction diagram shown includes a collection terminal 2, a third-party server 3 and a query terminal 1.

[0111] Among them, Figure 8 As shown, the login and registration process of the generative AI and bank assets linkage in the present invention includes:

[0112] Receive the first query request sent by the collection terminal, where the first query request includes the words "query all assets under the name" in the customer input field when the customer is talking to the generative AI; the security protection model of the dual algorithm of logging in to the generative AI and strong authentication of bank asset query must be met.

[0113] Step S101, determining the client login status according to a first query request sent by a collection terminal.

[0114] Step S102: If it is determined that the customer has not logged in to the generative AI, a generative AI login page will pop up, and the customer will enter the account information to determine whether the account information format is correct. If it is correct, the account information will be processed through the RSA encryption algorithm. If it is incorrect, the customer will be prompted to re-enter the information. The customer information is encrypted and intelligently packaged and transmitted to a third-party server. The third-party server decrypts the data and transmits it to the generative AI server. The customer can log in successfully after the login is successful. After the login is successful, the customer needs to sign a privacy disclaimer and agree to query the asset information under his name through generative AI. After the signing is successful, it becomes the first valid verification information (SEM structural equation model factor a).

[0115] Step S103, after the first valid verification information is successfully obtained, enter the bank asset query strong authentication page, which is the second valid verification information. The strong authentication method is for the customer to enter the online banking login information of any bank under his name. For example, the customer enters the online banking login information of Bank A. After the background verifies that the information is correct, the customer's asset information in other banks B, C, D, etc. is searched layer by layer through the association rules in the Apriori algorithm, and encrypted and packaged, and transmitted to the third-party server, without the customer manually entering the account number of each bank in turn. After the strong authentication is successful, the customer needs to perform face recognition authentication (collection terminal) to confirm the authenticity of the customer's identity. After the face recognition authentication is passed, the second valid verification information (SEM structural equation model factor b) is successfully obtained.

[0116] Step S104, when the first valid verification information and the second valid verification information are both obtained, factor a and factor b are successfully obtained; when factor a and factor b are obtained, they can be calculated through the SEM structural equation model. If only factor a or only factor b exists or there are other non-a, non-b factors, the SEM structural equation model cannot be used; after factor a and factor b are modeled through the SEM structural equation model, the final processing results are transmitted to the third-party server, which means that the first customer identification can be successfully obtained, and the login can be successfully performed to query the assets.

[0117] In this embodiment, if Figure 6 The query terminal shown in the figure has a specific workflow as follows Fig. 9 As shown, specifically including:

[0118] Step S201, the receiving module 101 is used to receive a first query request sent by a query terminal (non-collection terminal), and the first query request includes the customer input field containing the words "query all assets under the name" when the customer is talking to the generative AI.

[0119] In step S202, the identification module 102 is used to determine whether the generative AI and bank asset query strong authentication dual algorithm model is hit. If hit, the first customer identifier can be obtained to identify the customer identity information. The double encryption model authentication ensures the security of customer information.

[0120] Step S203, the query module 103 is used to identify and obtain the first valid verification information and the second valid verification information (factor a and factor b) corresponding to the customer identifier of the first customer in the time limit area (stored for only 10 minutes) according to the customer identifier of the first customer, thereby entering the customer information query module, calling the bank asset query encryption and encapsulation interface, and the interface encrypts and encapsulates all the bank assets under the customer's name using the AES encryption algorithm and provides them to the information desensitization model SDM (this model can deform the customer's real information to avoid customer data leakage). After the customer data enters the information desensitization model, the model will search for each node data in the queue to be desensitized, and identify whether each node data exists in the preset modified data list. If so, the data to be desensitized will be desensitized by data replacement, and the customer's real data will be replaced with the deformed data formulated by the model. After the data is successfully desensitized, it will be transmitted to the generative AI server. After the generative AI server re-decrypts the desensitized data, the customer asset information query result can be returned to the customer.

[0121] Step S204, the information storage module 104 is used to ensure the timeliness of information storage. Specifically, in order to improve the security of the query, the valid verification information stored in the timeliness area has a time limit. When the storage time of the valid verification information in the timeliness area exceeds the time limit, the valid verification information that exceeds the time limit will be deleted from the timeliness area.

[0122] Among them, the valid verification information includes the first valid verification information and the second valid verification information. After the customer information query is successful, it will only be stored for 10 minutes. If the customer has no other query operations after 10 minutes, the customer’s second valid verification information will be deleted from the time limit area. If the customer has no other generative AI operations after 20 minutes, the customer’s first valid verification information will be deleted from the time limit area.

[0123] In a specific embodiment of the present invention, the asset query method of the present invention can receive a first query request sent by a query terminal, the first query request includes the customer input field containing the words "query all assets under the name" when the customer is talking to the generative AI; the customer login status is judged according to the first query request, if it is judged that the customer has not logged in to the generative AI, the generative AI login page pops up, and the login is successful after hitting the generative AI and the bank asset query strong authentication double encryption model authentication, and the first customer identifier is identified after the login is successful.

[0124] Furthermore, after the first customer is successfully identified, the bank asset query encryption and encapsulation interface is called up. The interface encrypts and encapsulates all the bank assets under the customer's name using the AES encryption algorithm and provides them to the information desensitizing model. The information desensitizing model will search for each node data in the model to be desensitized, and identify whether the data of each node exists in the preset modified data list. If so, the data to be desensitized will be desensitized by data replacement, and the normal data will be replaced with the specified data. After the data is successfully desensitized, it will be transmitted to the generative AI server, and all the assets and asset details corresponding to the first customer can be successfully queried.

[0125] Specifically, for example, customer A has assets in banks A, B, C, and D. After customer A opens any generative AI platform and starts a conversation, he enters "I want to see all my assets". Generative AI displays the login page. After logging in, the customer enters the bank asset query strong authentication page. After entering the electronic banking account and password of bank B, he can view all his assets. Click on the details to query the asset list, which is 500,000 assets in bank A, 1.6 million assets in bank B, 800,000 assets in bank C, and 200,000 assets in bank D, totaling 3.1 million. If customer A exits generative AI and does not return to view within 10 minutes, he will automatically log out of the bank asset query page. In the asset query process, customer-related information can only be obtained after user authorization.

[0126] The present invention provides customers with a convenient and brand-new asset-liability management service. Customers do not need to open all electronic banking to query assets and then perform a single overlay. By simply encrypting and modeling customer data through an open platform, all assets under their name can be queried at a glance, helping customers to grasp the status of all assets under their name in real time. While ensuring data security, the convenience of financial services is improved.

[0127] The present invention provides customers with a convenient and brand-new asset-liability management service. Customers do not need to open all electronic banking to query assets and then perform a single superposition. Only through an open platform, customer data is encrypted, modeled, and other processing is performed, so that all assets under the name can be queried at a glance, helping customers to grasp the status of all assets under their name in real time, thereby ensuring data security while improving the convenience of asset query.

[0128] like Fig.10 FIG. 1 is a schematic diagram of the structure of an asset query device according to an embodiment of the present invention. The device shown in the figure includes:

[0129] The client identification module 10 is used to obtain the first query request sent by the query terminal, and process the first query request sent by the query terminal using the preset asset query strong authentication dual algorithm model to obtain the client identification;

[0130] The verification information module 20 is used to obtain the first valid verification information and the second valid verification information corresponding to the customer identification within a preset time limit;

[0131] The query result module 30 is used to use the first valid verification information and the second valid verification information to obtain the customer asset information sent by the generative artificial intelligence server through the asset query encryption encapsulation interface, and feed back the customer asset information to the customer through the query terminal.

[0132] As an embodiment of the present invention, Fig.11 As shown, the device further includes: an identity authentication module 40, which is used to obtain the customer identity information corresponding to the customer identification according to the customer identification, and verify the customer identity information corresponding to the customer identification.

[0133] As an embodiment of the present invention, Fig.12 As shown, the query result module 30 includes:

[0134] The encryption processing unit 31 is used to obtain all the asset information of the customer through the asset query encryption encapsulation interface, and encrypt all the asset information of the customer using an encryption algorithm;

[0135] The desensitizing processing unit 32 is used to use a preset information desensitizing model to desensitize all the encrypted customer asset information, and send the desensitized customer asset information to the generative artificial intelligence server to obtain the customer asset information sent by the generative artificial intelligence server.

[0136] In this embodiment, the desensitizing processing unit is also used to use a preset information desensitizing model to replace the customer's real data in all the encrypted customer asset information with deformed data, thereby completing the desensitizing processing.

[0137] As an embodiment of the present invention, Fig.13 As shown, the device also includes:

[0138] The login status module 50 is used to obtain the first query request sent by the acquisition terminal, and determine the customer login status according to the first query request sent by the acquisition terminal;

[0139] The account information module 60 is used to display a preset generative artificial intelligence login page to the customer using the acquisition terminal if the customer login status is not logged in, and obtain the account information entered by the customer;

[0140] A first verification information module 70 is used to encrypt the account information using an asymmetric encryption algorithm, and send the encrypted account information to the generative artificial intelligence server via a third-party server to obtain first valid verification information fed back by the generative artificial intelligence server;

[0141] The second verification information module 80 is used to obtain the second valid authentication information by using the asset query strong authentication process after obtaining the first valid authentication information;

[0142] The login registration module 90 is used to process the first valid verification information and the second valid authentication information using a preset structural equation model, obtain a processing result, and send the processing result to a third-party server to complete the customer login registration.

[0143] In this embodiment, if Fig.14 As shown, the account information module 60 includes:

[0144] An account information unit 61, used to obtain account information input by the customer according to the generative artificial intelligence login page;

[0145] The format verification unit 62 is used to perform format verification on the account information and obtain a format verification result.

[0146] In this embodiment, if Fig.15 As shown, the second verification information module 80 includes:

[0147] The login information unit 81 is used to display a strong authentication page to the customer using the acquisition terminal and obtain the login information input by the customer;

[0148] An information sending unit 82 is used to obtain multiple asset information authorized by the customer using the login information, and send the multiple asset information to a third-party server;

[0149] The second verification information unit 83 is used to obtain the customer identity information authorized by the customer through the collection terminal, verify the customer identity information, and obtain the second valid authentication information.

[0150] Based on the same application concept as the above-mentioned asset query method, the present invention also provides the above-mentioned asset query device. Since the principle of solving the problem by the asset query device is similar to that of the asset query method, the implementation of the asset query device can refer to the implementation of the asset query method, and the repeated parts will not be repeated.

[0151] The present invention provides customers with a convenient and brand-new asset-liability management service. Customers do not need to open all electronic banking to query assets and then perform a single superposition. Only through an open platform, customer data is encrypted, modeled, and other processing is performed, so that all assets under the name can be queried at a glance, helping customers to grasp the status of all assets under their name in real time, thereby ensuring data security while improving the convenience of asset query.

[0152] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the above method is implemented when the processor executes the program.

[0153] The present invention also provides a computer program product, comprising a computer program / instruction, which implements the steps of the above method when the computer program / instruction is executed by a processor.

[0154] The present invention also provides a computer-readable storage medium, which stores a computer program for executing the above method by a computer.

[0155] like Fig.16 As shown, the electronic device 600 may further include: a communication module 110, an input unit 120, an audio processor 130, a display 160, and a power supply 170. It is worth noting that the electronic device 600 does not necessarily have to include Fig.16 In addition, the electronic device 600 may also include Fig.16 For components not shown, reference may be made to the prior art.

[0156] like Fig.16 As shown, the central processor 100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor devices and / or logic devices. The central processor 100 receives inputs and controls the operations of various components of the electronic device 600.

[0157] The memory 140 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices. The above-mentioned information related to the failure may be stored, and a program for executing the relevant information may also be stored. The CPU 100 may execute the program stored in the memory 140 to implement information storage or processing.

[0158] The input unit 120 provides input to the CPU 100. The input unit 120 is, for example, a key or a touch input device. The power supply 170 is used to provide power to the electronic device 600. The display 160 is used to display display objects such as images and text. The display may be, for example, an LCD display, but is not limited thereto.

[0159] The memory 140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 140 may also be some other type of device. The memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application / function storage unit 142, which is used to store application programs and function programs or processes for executing the operation of the electronic device 600 through the central processor 100.

[0160] The memory 140 may also include a data storage unit 143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 144 of the memory 140 may include various drivers for communication functions of the electronic device and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0161] The communication module 110 is a transmitter / receiver 110 that transmits and receives signals via an antenna 111. The communication module (transmitter / receiver) 110 is coupled to the central processor 100 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0162] Based on different communication technologies, multiple communication modules 110 may be provided in the same electronic device, such as a cellular network module, a Bluetooth module and / or a wireless LAN module. The communication module (transmitter / receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide an audio output via the speaker 131 and receive an audio input from the microphone 132, thereby realizing a common telecommunication function. The audio processor 130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 130 is also coupled to the central processor 100, so that the sound can be recorded on the local machine through the microphone 132, and the sound stored on the local machine can be played through the speaker 131.

[0163] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0164] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0165] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0166] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0167] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An asset query method, characterized in that: The method comprises: Acquire a first query request sent by the query terminal, and process the first query request sent by the query terminal using a preset asset query strong authentication dual algorithm model to obtain a customer identifier; Acquire first valid verification information and second valid verification information corresponding to the customer identifier within a preset time validity area; Utilizing the first valid verification information and the second valid verification information, the customer asset information sent by the generative artificial intelligence server is obtained through the asset query encryption encapsulation interface, and the customer asset information is fed back to the customer through the query terminal.

2. The method according to claim 1, characterized in that The method further includes: obtaining customer identity information corresponding to the customer identifier according to the customer identifier, and verifying the customer identity information corresponding to the customer identifier.

3. The method according to claim 1, characterized in that The method of obtaining the customer asset information sent by the generative artificial intelligence server through the asset query encryption encapsulation interface includes: Obtain all the customer's asset information through the asset query encryption encapsulation interface, and encrypt all the customer's asset information using encryption algorithms; The encrypted customer's entire asset information is desensitized using a preset information desensitization model, and the desensitized customer's entire asset information is sent to a generative artificial intelligence server to obtain the customer's asset information sent by the generative artificial intelligence server.

4. The method according to claim 3, characterized in that The method of using a preset information desensitization model to desensitize all encrypted customer asset information includes: By using the preset information desensitization model, the real customer data in all the encrypted customer asset information is replaced with deformed data, and the desensitization process has been completed.

5. The method according to claim 1, characterized in that The method further comprises: Obtaining a first query request sent by the acquisition terminal, and determining a client login status according to the first query request sent by the acquisition terminal; If the customer login status is not logged in, the acquisition terminal is used to display a preset generative artificial intelligence login page to the customer and obtain the account information entered by the customer; Encrypting the account information using an asymmetric encryption algorithm, and sending the encrypted account information to the generative artificial intelligence server via a third-party server to obtain first valid verification information fed back by the generative artificial intelligence server; After obtaining the first valid authentication information, using asset query strong authentication processing to obtain second valid authentication information; The first valid verification information and the second valid authentication information are processed using a preset structural equation model to obtain a processing result, and the processing result is sent to a third-party server to complete the customer login registration.

6. The method according to claim 5, characterized in that The step of obtaining the account information input by the customer includes: Obtaining account information entered by the customer based on the generative artificial intelligence login page; Perform format verification on the account information to obtain a format verification result.

7. The method according to claim 5, characterized in that Using asset query strong authentication processing, the second valid authentication information obtained includes: Using the acquisition terminal to display a strong authentication page to the customer and obtain login information entered by the customer; Using the login information, obtaining multiple asset information authorized by the customer, and sending the multiple asset information to a third-party server; The customer identity information authorized by the customer is obtained by using the collection terminal, and the customer identity information is verified to obtain the second valid authentication information.

8. An asset query device, characterized in that: The device comprises: A customer identification module, used to obtain a first query request sent by a query terminal, and process the first query request sent by the query terminal using a preset asset query strong authentication dual algorithm model to obtain a customer identification; A verification information module, used to obtain first valid verification information and second valid verification information corresponding to the customer identifier within a preset time limit; The query result module is used to use the first valid verification information and the second valid verification information to obtain the customer asset information sent by the generative artificial intelligence server through the asset query encryption encapsulation interface, and feed back the customer asset information to the customer through the query terminal.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for causing a computer to execute the method according to any one of claims 1 to 7.

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