WO2024251001A1 - 信用额度处理方法、装置、计算机设备和计算机程序产品 - Google Patents

信用额度处理方法、装置、计算机设备和计算机程序产品 Download PDF

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Publication number
WO2024251001A1
WO2024251001A1 PCT/CN2024/095974 CN2024095974W WO2024251001A1 WO 2024251001 A1 WO2024251001 A1 WO 2024251001A1 CN 2024095974 W CN2024095974 W CN 2024095974W WO 2024251001 A1 WO2024251001 A1 WO 2024251001A1
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Prior art keywords
credit limit
identity information
credit
initial
level
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Ceased
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PCT/CN2024/095974
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English (en)
French (fr)
Inventor
董晨
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Shenzhen TCL New Technology Co Ltd
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Shenzhen TCL New Technology Co Ltd
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Priority to EP24818534.0A priority Critical patent/EP4726635A1/en
Publication of WO2024251001A1 publication Critical patent/WO2024251001A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0609—Qualifying participants for shopping transactions

Definitions

  • the present application relates to the technical field of credit quota allocation, and in particular to a credit quota processing method, apparatus, computer equipment and computer program product.
  • a user When a user makes a purchase through a device such as a smart TV, the user can use the user's credit limit to make the purchase.
  • the user controls the device through a remote controller so that the device allocates a corresponding credit limit to the user.
  • the embodiments of the present application provide a credit limit processing method, apparatus, computer equipment, computer-readable storage medium, and computer program product, which can improve the efficiency and accuracy of generating user credit limits.
  • a credit limit processing method comprising:
  • the object is identified to obtain the identity information of the object;
  • an embodiment of the present application provides a credit limit processing device, including:
  • a first acquisition unit may be used to acquire biometric information of a subject for which a credit line is to be generated by the device
  • the identification unit can be used to identify the object according to the biometric information to obtain the identity information of the object;
  • the extraction unit may be specifically configured to obtain a credit limit level of the object according to the identity information; and extract an initial credit limit corresponding to the credit limit level to obtain an initial credit limit of the object for the device.
  • the extraction unit can be specifically used to determine whether the identity information matches the preset information in the cloud; if it matches, extract the preset credit limit level corresponding to the preset information; and determine the preset credit limit level as the credit limit level of the object.
  • the extraction unit can be specifically used to send a credit limit level query request to a data cache area corresponding to the credit limit processing server through the credit limit processing server, and the credit limit level query request carries identity information; based on the identity information in the credit limit query request, the credit limit level of the object is queried in the data cache area to obtain the credit limit level of the object.
  • the extraction unit may be specifically configured to retrieve the identity information in the credit level query request in the data cache.
  • the credit limit level of the object is queried and processed; if the credit limit level of the object is not queried in the data cache area, the credit limit level of the object is requested from the cloud through the credit limit processing server.
  • the extraction unit can be specifically used to extract the target consumption data of the object within a preset time period from the memory database corresponding to the credit limit processing server through the credit limit processing server; and request the credit limit level of the object from the cloud based on the target consumption data.
  • the fusion unit can be specifically used to obtain a mapping function for historical consumption data; according to the mapping function, the historical consumption data is mapped to obtain a credit limit parameter of the object; the credit limit parameter and the initial credit limit are fused to obtain the credit limit of the object.
  • an embodiment of the present application also provides a computer device, including a memory and a processor; the memory stores a computer program, and the processor is used to run the computer program in the memory to execute any credit limit processing method provided in the embodiment of the present application.
  • an embodiment of the present application further provides a computer-readable storage medium, which stores a computer program.
  • the computer program is suitable for loading by a processor to execute any credit limit processing method provided in the embodiment of the present application.
  • an embodiment of the present application also provides a computer program product, including a computer program, which implements any credit limit processing method provided in the embodiment of the present application when the computer program is executed by a processor.
  • the present application can obtain the biometric information of the object for which the device is to generate a credit line; identify the object based on the biometric information to obtain the object's identity information; extract the object's initial credit line for the device based on the identity information; obtain the object's historical consumption data for the device based on the identity information; and fuse the historical consumption data and the initial credit line to generate the object's credit line. Since the present application can identify the object's identity information based on the object's biometric information, the object's historical consumption data and initial credit line can be obtained based on the identity information, and thus the credit line can be accurately and automatically generated for the object based on the historical consumption data and the initial credit line, thereby improving the efficiency and accuracy of generating the user's credit line.
  • FIG1 is a scenario diagram of a credit limit processing method provided in an embodiment of the present application.
  • FIG2 is a flowchart of a credit limit processing method provided in an embodiment of the present application.
  • FIG3 is a schematic diagram of related equipment used in the credit limit processing method provided in an embodiment of the present application.
  • FIG4 is a second flow chart of a credit limit processing method provided in an embodiment of the present application.
  • FIG5 is a schematic diagram of the structure of a credit limit processing device provided in an embodiment of the present application.
  • FIG. 6 is a schematic diagram of the structure of a computer device provided in an embodiment of the present application.
  • the present invention provides a credit limit processing method, device, computer equipment, computer readable storage medium and computer
  • the credit limit processing device may be integrated in a computer device, which may be a server or a terminal.
  • the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, network acceleration services (Content Delivery Network, CDN), and big data and artificial intelligence platforms.
  • the terminal can be a smart phone, tablet computer, laptop computer, desktop computer, smart speaker, smart watch, etc., but is not limited to this.
  • the terminal and the server can be directly or indirectly connected by wired or wireless communication, and this application does not limit this.
  • the computer device can obtain the biometric information of an object for which a credit limit is to be generated by the device; based on the biometric information, the object is identified to obtain the identity information of the object; based on the identity information, the initial credit limit of the object for the device is extracted; based on the identity information, the historical consumption data of the object for the device is obtained; and the historical consumption data and the initial credit limit are integrated to generate the credit limit of the object.
  • the biometric information may refer to the biometric information of the object.
  • the initial credit limit may refer to a credit limit initially set for an object.
  • the historical consumption data may be the consumption data of the object within a historical period of time.
  • the device may refer to the aforementioned computer device.
  • a credit limit processing device which can be specifically integrated in a computer device, which can be a server or a terminal.
  • the terminal can include a tablet computer, a laptop computer, a personal computer (PC), a wearable device, a virtual reality device or other smart devices that can acquire data.
  • Step S201 to Step S205 the specific process of the credit limit processing method is as follows: Step S201 to Step S205:
  • S202 Perform identity recognition on the object based on the biometric information to obtain the identity information of the object.
  • S204 Obtain historical consumption data of the object for the device according to the identity information.
  • S205 Fusing the historical consumption data and the initial credit limit to generate the credit limit of the object.
  • the present application can obtain the biometric information of the object for which the device is to generate a credit line; identify the object based on the biometric information to obtain the object's identity information; extract the object's initial credit line for the device based on the identity information; obtain the object's historical consumption data for the device based on the identity information; and fuse the historical consumption data and the initial credit line to generate the object's credit line. Since the present application can identify the object's identity information based on the object's biometric information, the object's historical consumption data and initial credit line can be obtained based on the identity information, and thus the credit line can be accurately and automatically generated for the object based on the historical consumption data and the initial credit line, thereby improving the efficiency and accuracy of generating the user's credit line.
  • the credit limit processing device is specifically integrated into a computer device, and the computer device is a server.
  • the specific flow of the credit limit processing method is as follows: Step S201 to Step S205:
  • the object may refer to a user.
  • the biometric information may include but is not limited to at least one of the subject's voice, the subject's fingerprint, and the subject's face.
  • the biometric information in the embodiment of the present application may preferably be the subject's voice.
  • the method of obtaining the biometric information of the object for which the device is to generate a credit limit may be:
  • the biometric information acquisition device connected to the device acquires the biometric information of the object for which the device is to generate a credit line.
  • the biometric information acquisition device is a voice acquisition device
  • the biometric information acquisition device is a fingerprint acquisition device
  • the biometric information is a camera device.
  • the object is identified based on the biometric information of the object, and the object's identity information can be obtained by matching the biometric information with preset biometric information; if they match, the preset identity information corresponding to the preset biometric information is used as the identity information of the object.
  • the preset biometric information may refer to pre-set biometric information of an object.
  • this situation can be called that the biometric information matches the preset biometric information; when the biometric information is different from the preset biometric information, this situation can be called that the biometric information does not match the preset biometric information.
  • the biometric information when the similarity between the biometric information and the preset biometric information is greater than a preset similarity threshold, the biometric information can be said to match the preset biometric information; when the similarity between the biometric information and the preset biometric information is less than or equal to the preset similarity threshold, the biometric information can be said to not match the preset biometric information.
  • the object is identified based on the biometric information
  • the object's identity information is obtained by using an identity recognition model to identify the object based on the biometric information to obtain the object's identity information.
  • the identity recognition model may be a CNN neural network model, or a self-attention neural network model, etc.
  • S203 extracting the initial credit limit of the object for the device according to the identity information.
  • the method for extracting the initial credit limit of the object for the device based on the identity information can be: obtaining the credit limit level of the object based on the identity information; extracting the initial credit limit corresponding to the credit limit level to obtain the initial credit limit of the object for the device.
  • the method of obtaining the credit limit level of the object based on the identity information may be: obtaining the correspondence between the identity information and the credit limit level; obtaining the credit limit level corresponding to the identity information based on the identity information and the correspondence; and using the credit limit level corresponding to the identity information as the credit limit level of the object.
  • the method of extracting the initial credit limit corresponding to the credit limit level to obtain the initial credit limit of the object for the device may be: extracting the preset credit limit value corresponding to the credit limit level; using the mapping rule to map the preset credit limit value to obtain the initial credit limit corresponding to the credit limit level, so as to obtain the initial credit limit of the object for the device.
  • the mapping rule may refer to the rule for mapping the preset credit limit value, and the mapping rule may be specifically represented as a function or a table.
  • the initial credit limit corresponding to the credit limit level can be extracted through the correspondence between the initial credit limit and the credit limit level.
  • the credit limit level may refer to the level of the initial credit limit corresponding to the object.
  • the computer device obtains that the credit limit level of user A is level 2. Then, based on the correspondence between the credit limit level and the preset limit value, the computer device can extract that the corresponding preset limit value of user A under the credit limit level of level 2 is 100. Then, the computer device can use the mapping rule to map the preset limit value 100 to obtain a value 70, which is the initial credit limit of user A.
  • the method for obtaining the credit limit level of the object can be: determine whether the identity information matches the preset information in the cloud; if they match, extract the preset credit limit level corresponding to the preset information; and determine the preset credit limit level as the credit limit level of the object.
  • the present application stores the preset information in the cloud, which can reduce the storage capacity of the local storage space and does not need to rely on the local storage space.
  • it can be determined anytime and anywhere whether the identity information matches the preset information in the cloud.
  • this situation can be called that the identity information matches the preset information; when the identity information is different from the preset information, this situation can be called that the identity information does not match the preset information.
  • this situation can be called that the identity information matches the preset information; when the similarity between the identity information and the preset information is less than or equal to the preset similarity threshold, this situation can be called that the identity information does not match the preset information.
  • the credit limit processing server may refer to a server for processing the relevant information of the credit limit of the object.
  • the relevant information may include but is not limited to at least one of the credit limit level and the initial credit limit.
  • the identity information can be represented as the telephone number of user B.
  • the credit limit level of user B can be queried in the data cache area based on the telephone number of user B carried in the credit limit query request to obtain the credit limit level of user B.
  • the computer device can communicate with the credit limit processing server through the HTTPS protocol.
  • the data buffer area may be a storage area used to temporarily store the above-mentioned related information.
  • the method of requesting the credit limit level of an object from the cloud through a credit limit processing server can be: extracting the target consumption data of the object within a preset time period from the memory database corresponding to the credit limit processing server through the credit limit processing server; and requesting the credit limit level of the object from the cloud based on the target consumption data.
  • the present application utilizes the target consumption data of the object within the preset time period to improve the accuracy of obtaining the credit limit level.
  • the memory database may refer to a database used to store consumption data of an object for a long time.
  • the consumption data may include but is not limited to at least one of target consumption data and historical consumption data.
  • the method of requesting the credit level of the object from the cloud according to the target consumption data may be: sending the target consumption data to the cloud through the credit processing server, so that the cloud obtains the credit level of the object according to the target consumption data.
  • the cloud can determine the data interval where the target consumption data is located; map the data interval to obtain the credit limit level of the object.
  • the data interval may refer to an interval of data size.
  • the method of extracting the initial credit limit of the object for the device according to the identity information may be: Determine whether the identity information meets the preset requirements; if yes, extract the object's initial credit limit for the device based on the identity information.
  • the present application will then extract the object's initial credit limit for the device, which can improve the security of obtaining the initial credit limit.
  • the initial credit limit corresponding to the identity information can be extracted from the cloud according to the identity information; and the initial credit limit corresponding to the identity information is used as the initial credit limit of the object for the device.
  • the identity information when the identity information is bound to the mobile phone number, or the geographical location of the above-mentioned device logged in by the identity information is a preset valid geographical location, or the identity information is not in the blacklist, or the number of overdue repayments of all historical logged-in users in the device logged in by the identity information is not greater than the preset number threshold, in this case, the identity information can be said to meet the preset requirements.
  • the identity information When the identity information is not bound to the mobile phone number, or the geographical location of the above-mentioned device logged in by the identity information is not a preset valid geographical location, or the identity information is in the blacklist, or the number of overdue repayments of all historical logged-in users in the device logged in by the identity information is greater than the preset number threshold, in this case, the identity information can be said to not meet the preset requirements.
  • S204 Obtain historical consumption data of the object for the device according to the identity information.
  • the method for obtaining the historical consumption data of the object for the device based on the identity information can be: determining whether the initial credit limit is less than a preset credit limit threshold; if so, obtaining the historical consumption data of the object for the device based on the identity information.
  • the historical consumption data of the object for the device can be extracted from the aforementioned memory database according to the identity information.
  • the historical consumption data may include the object's voice consumption transaction information within the target time, credit fulfillment transaction information within the target time, offline cash transaction information within the target time, bank credit information within the target time, and other offline shopping transaction information within the target time.
  • the target time may be the last six months, or a set time period may be set according to circumstances.
  • the transaction information may include transaction amount information and total number of transactions.
  • mapping function for historical consumption data is obtained; according to the mapping function, the historical consumption data is mapped to obtain a credit limit parameter of the object; and the credit limit parameter and the initial credit limit are fused to obtain the credit limit of the object.
  • the present application utilizes the fusion of the credit limit parameter with the initial credit limit to more accurately obtain the credit limit of the object.
  • the method of performing a fusion operation on the credit limit parameter and the initial credit limit to obtain the credit limit of the object may be: obtaining a fusion function; and performing a fusion operation on the credit limit parameter and the initial credit limit through the fusion function to obtain the credit limit of the object.
  • the fusion function may be a function for performing a fusion operation on the credit limit parameter and the initial credit limit, and the fusion function may be a user-defined function.
  • the credit limit parameter and the initial credit limit can be added together through a fusion function to obtain the credit limit of the object.
  • the biometric information is the object's voice as an example. It can be understood that when the biometric information is the object's voice, the computer device can use the object's voice to quickly generate the object's credit limit, thereby avoiding manual operation of the object.
  • the present application may be provided with a computer device, an interface server, a credit limit processing server, a data buffer area, and a memory database.
  • the voice acquisition device may be integrated into the computer device, and the interface server may serve as an interface between the computer device and the credit limit processing server.
  • the computer device when the computer device acquires the voice of the object through the voice acquisition device, the computer device performs identity recognition on the object according to the biometric information to obtain the identity information of the object; then, the computer device sends the identity information to the credit limit processing server through the interface server; then, the credit limit processing server sends the identity information to the credit limit processing server.
  • the data cache area corresponding to the server sends a credit limit level query request, which carries identity information; based on the identity information in the credit limit level query request, the credit limit level of the object is queried in the data cache area.
  • the initial credit level of the object for the device is extracted from the data cache.
  • the credit level of the object is requested from the cloud through the credit processing server.
  • the computer device can extract the initial credit limit corresponding to the credit limit level through the cloud to obtain the initial credit limit of the object for the device.
  • the cloud can send the initial credit limit to the credit limit processing server.
  • the computer device can obtain the historical consumption data of the object for the device based on the identity information through the credit limit processing server; the computer device can integrate the historical consumption data and the initial credit limit through the credit limit processing server to generate the credit limit of the object.
  • the credit limit processing server can send the credit limit to the computer device through the interface server.
  • S402 Perform identity recognition on the object based on the biometric information to obtain the identity information of the object.
  • S403 Determine whether the identity information matches the preset information in the cloud.
  • step S404 If there is a match, execute step S404; if there is no match, execute step S409.
  • S405 Determine the preset credit limit level as the credit limit level of the object.
  • S406 Extract the initial credit limit corresponding to the credit limit level to obtain the initial credit limit of the object for the device.
  • S407 Obtain historical consumption data of the object for the device according to the identity information.
  • S408 The historical consumption data and the initial credit limit are integrated to generate the credit limit of the object.
  • S409 Sending failure information indicating failure in generating the initial credit limit to the object.
  • the present application can obtain the biometric information of the object for which the device is to generate a credit line; identify the object based on the biometric information to obtain the object's identity information; extract the object's initial credit line for the device based on the identity information; obtain the object's historical consumption data for the device based on the identity information; and fuse the historical consumption data and the initial credit line to generate the object's credit line. Since the present application can identify the object's identity information based on the object's biometric information, the object's historical consumption data and initial credit line can be obtained based on the identity information, and thus the credit line can be accurately and automatically generated for the object based on the historical consumption data and the initial credit line, thereby improving the efficiency and accuracy of generating the user's credit line.
  • an embodiment of the present application also provides a credit limit processing device, which can be integrated into a computer device, such as a server or a terminal, and the terminal can include a tablet computer, a laptop computer and/or a personal computer.
  • the credit limit processing device may include a first acquisition unit 301, an identification unit 302, an extraction unit 303, a second acquisition unit 304 and a fusion unit 305, as follows:
  • the acquisition unit can be used to acquire biometric information of an object for which a credit limit is to be generated by the device.
  • the identification unit can be used to identify the object according to the biometric information to obtain the identity information of the object.
  • the extraction unit can be used to extract the initial credit limit of the object for the device according to the identity information.
  • the extraction unit can be used to obtain the credit limit level of the object based on the identity information; extract the initial credit limit corresponding to the credit limit level to obtain the initial credit limit of the object for the device.
  • the extraction unit can be used to determine whether the identity information matches the preset information in the cloud; if it matches, the preset credit limit level corresponding to the preset information is extracted; and the preset credit limit level is determined as the credit limit level of the object.
  • the extraction unit can be used to send a credit limit level query request to a data cache area corresponding to the credit limit processing server through the credit limit processing server, and the credit limit level query request carries identity information; based on the identity information in the credit limit level query request, the credit limit level of the object is queried in the data cache area to obtain the credit limit level of the object.
  • the extraction unit can be used to query the credit limit level of the object in the data cache area based on the identity information in the credit limit level query request; if the credit limit level of the object is not found in the data cache area, the credit limit level of the object is requested from the cloud through the credit limit processing server.
  • the extraction unit can be used to extract the target consumption data of the object within a preset time period from the memory database corresponding to the credit limit processing server through the credit limit processing server; and request the credit limit level of the object from the cloud based on the target consumption data.
  • the extraction unit can be used to determine whether the identity information meets the preset requirements; if it does, the initial credit limit of the object for the device is extracted based on the identity information.
  • a second acquisition unit
  • the second acquisition unit may be configured to acquire historical consumption data of the object for the device according to the identity information.
  • the second acquisition unit may be used to determine whether the initial credit limit is less than a preset credit limit threshold
  • the fusion unit can be used to fuse the historical consumption data and the initial credit limit to generate the credit limit of the object.
  • the fusion unit can be used to obtain a mapping function for the historical consumption data; according to the mapping function, the historical consumption data is mapped to obtain the credit limit parameter of the object; and the credit limit parameter and the initial credit limit are fused to obtain the credit limit of the object.
  • the first acquisition unit of the present application can be used to acquire the biometric information of the object for which the device is to generate a credit line;
  • the identification unit can be used to identify the object based on the biometric information to obtain the identity information of the object;
  • the extraction unit can be used to extract the initial credit line of the object for the device based on the identity information;
  • the second acquisition unit can be used to acquire the historical consumption data of the object for the device based on the identity information;
  • the fusion unit can be used to fuse the historical consumption data and the initial credit line to generate the credit line of the object.
  • the present application can identify the identity information of the object based on the biometric information of the object, the historical consumption data and the initial credit line of the object can be acquired based on the identity information, so that the credit line can be accurately and automatically generated for the object based on the historical consumption data and the initial credit line, thereby improving the efficiency and accuracy of generating the user's credit line.
  • the embodiment of the present application further provides a computer device, as shown in FIG6 , which shows a schematic diagram of the structure of the computer device involved in the embodiment of the present application, specifically:
  • the processor 401 is the control center of the computer device, and uses various interfaces and lines to connect various parts of the entire computer device. By running or executing software programs and/or modules stored in the memory 402, and calling data stored in the memory 402, the processor 401 performs various functions of the computer device and processes data.
  • the processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and computer programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 401.
  • the memory 402 can be used to store software programs and modules.
  • the processor 401 executes various functional applications and data processing by running the software programs and modules stored in the memory 402.
  • the memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, a computer program required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc.
  • the memory 402 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 with access to the memory 402.
  • the computer device also includes a power supply 403 for supplying power to various components.
  • the power supply 403 can be logically connected to the processor 401 through a power management system, so as to manage charging, discharging, and power consumption through the power management system.
  • the power supply 403 can also include any components such as one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators.
  • the computer device may further include an input unit 404, which may be used to receive input digital or character information communications and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls.
  • an input unit 404 which may be used to receive input digital or character information communications and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls.
  • the computer device may further include a display unit, etc., which will not be described in detail herein.
  • the processor 401 in the computer device will load the executable files corresponding to the processes of one or more computer programs into the memory 402 according to the following instructions, and the processor 401 will run the computer programs stored in the memory 402, thereby realizing various functions, as follows:
  • an embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored.
  • the computer program can be loaded by a processor to execute any credit limit processing method provided in the embodiment of the present application.
  • the computer readable storage medium may include: read-only memory (ROM), random access memory (RAM), disk or CD, etc.
  • the instructions stored in the computer-readable storage medium can execute the steps in any one of the credit limit processing methods provided in the embodiments of the present application, the beneficial effects that can be achieved by any one of the credit limit processing methods provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

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Abstract

提供一种信用额度处理方法，获取对象的生物特征信息；根据生物特征信息进行身份识别，得到身份信息；根据身份信息，提取对象针对设备的初始信用额度（S203）；根据身份信息，获取对象针对设备的历史消费数据（S204）；对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度（S205）。提高信用额度生成效率和生成准确性。

Description

信用额度处理方法、装置、计算机设备和计算机程序产品
本申请要求申请日为2023年06月06日、申请号为202310664700.X、申请名称为“一种信用额度处理方法及相关设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及信用额度分配技术领域，具体涉及一种信用额度处理方法、装置、计算机设备和计算机程序产品。
背景技术
用户在通过设备如智能电视机进行购物时，可以采用用户的信用额度进行购物。其中，用户在通过设备进行购物时，是通过遥控器进行遥控，以使设备为用户分配相应的信用额度。
技术问题
但是，这种为用户分配信用额度的方式需要用户手动操作，分配效率不高；而且，这种为用户分配信用额度的方式，可能存在多人操控遥控器的情况，这样一来就无法准确地为用户分配信用额度。
综上，目前存在为用户信用额度的生成效率不高和生成准确性较低的问题。
技术解决方案
本申请实施例提供一种信用额度处理方法、装置、计算机设备、计算机可读存储介质及计算机程序产品，能够提高用户信用额度的生成效率和生成准确性。
一种信用额度处理方法，包括：
获取设备待生成信用额度的对象的生物特征信息；
根据生物特征信息，对对象进行身份识别，得到对象的身份信息；
根据身份信息，提取对象针对设备的初始信用额度；
根据身份信息，获取对象针对设备的历史消费数据；
对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。
相应地，本申请实施例提供一种信用额度处理装置，包括：
第一获取单元，可以用于获取设备待生成信用额度的对象的生物特征信息；
识别单元，可以用于根据生物特征信息，对对象进行身份识别，得到对象的身份信息；
提取单元，可以用于根据身份信息，提取对象针对设备的初始信用额度；
第二获取单元，可以用于根据身份信息，获取对象针对设备的历史消费数据；
融合单元，可以用于对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。
在一些实施例中，提取单元，具体可以用于根据身份信息，获取对象的信用额度等级；提取信用额度等级对应的初始信用额度，以得到对象针对设备的初始信用额度。
在一些实施例中，提取单元，具体可以用于判断身份信息与云端中的预设信息是否匹配；若匹配，则提取预设信息对应预设信用额度等级；将预设信用额度等级，确定为对象的信用额度等级。
在一些实施例中，提取单元，具体可以用于通过信用额度处理服务器，向信用额度处理服务器对应的数据缓存区发送额度等级查询请求，额度等级查询请求携带身份信息；根据额度等级查询请求中的身份信息，在数据缓存区中，对对象的信用额度等级进行查询处理，以得到对象的信用额度等级。
在一些实施例中，提取单元，具体可以用于根据额度等级查询请求中的身份信息，在数据缓 存区中，对对象的信用额度等级进行查询处理；若在数据缓存区中未查询到对象的信用额度等级，则通过信用额度处理服务器，向云端请求对象的信用额度等级。
在一些实施例中，提取单元，具体可以用于通过信用额度处理服务器，从信用额度处理服务器对应的内存数据库，提取对象在预设时间段内的目标消费数据；根据目标消费数据，向云端请求对象的信用额度等级。
在一些实施例中，第二获取单元，具体可以用于判断初始信用额度是否小于预设额度阈值；若是，则根据身份信息，获取对象针对设备的历史消费数据。
在一些实施例中，融合单元，具体可以用于获取针对历史消费数据的映射函数；根据映射函数，对历史消费数据进行映射处理，得到对象的信用额度参数；对信用额度参数和初始信用额度进行融合运算，得到对象的信用额度。
此外，本申请实施例还提供一种计算机设备，包括存储器和处理器；存储器存储有计算机程序，处理器用于运行存储器内的计算机程序，以执行本申请实施例提供的任一种信用额度处理方法。
此外，本申请实施例还提供一种计算机可读存储介质，计算机可读存储介质存储有计算机程序，计算机程序适于处理器进行加载，以执行本申请实施例提供的任一种信用额度处理方法。
此外，本申请实施例还提供一种计算机程序产品，包括计算机程序，计算机程序被处理器执行时实现本申请实施例所提供的任一种信用额度处理方法。
有益效果
本申请可以获取设备待生成信用额度的对象的生物特征信息；根据生物特征信息，对对象进行身份识别，得到对象的身份信息；根据身份信息，提取对象针对设备的初始信用额度；根据身份信息，获取对象针对设备的历史消费数据；对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。由于本申请可以基于对象的生物特征信息，识别出对象的身份信息，如此可以基于身份信息，获取得到对象的历史消费数据和初始信用额度，从而可以基于历史消费数据和初始信用额度，准确和自动地为对象生成信用额度，如此提高用户信用额度的生成效率和生成准确性。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请实施例提供的信用额度处理方法的场景示意图；
图2是本申请实施例提供的信用额度处理方法的流程示意一图；
图3是本申请实施例提供的信用额度处理方法所采用的相关设备的示意图；
图4是本申请实施例提供的信用额度处理方法的流程示意二图；
图5是本申请实施例提供的信用额度处理装置的结构示意图；
图6是本申请实施例提供的计算机设备的结构示意图。
本发明的实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请实施例提供一种信用额度处理方法、装置、计算机设备、计算机可读存储介质和计算 机程序产品。其中，该信用额度处理装置可以集成在计算机设备中，该计算机设备可以是服务器，也可以是终端等设备。
其中，服务器可以是独立的物理服务器，也可以是多个物理服务器构成的服务器集群或者分布式系统，还可以是提供云服务、云数据库、云计算、云函数、云存储、网络服务、云通信、中间件服务、域名服务、安全服务、网络加速服务(Content Delivery Network，CDN)、以及大数据和人工智能平台等基础云计算服务的云服务器。终端可以是智能手机、平板电脑、笔记本电脑、台式计算机、智能音箱、智能手表等，但并不局限于此。终端以及服务器可以通过有线或无线通信方式进行直接或间接地连接，本申请在此不做限制。
例如，参见图1，以信用额度处理装置集成在计算机设备中为例，计算机设备可以获取设备待生成信用额度的对象的生物特征信息；根据生物特征信息，对对象进行身份识别，得到对象的身份信息；根据身份信息，提取对象针对设备的初始信用额度；根据身份信息，获取对象针对设备的历史消费数据；对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。
其中，生物特征信息可以是指对象的生物特征的信息。
其中，初始信用额度可以是指初步为对象设置的信用额度。
其中，历史消费数据可以是在对象在历史时间内的消费数据。
其中，设备可以是指前述的计算机设备。
以下分别进行详细说明。需说明的是，以下实施例的描述顺序不作为对实施例优选顺序的限定。
本实施例将从信用额度处理装置的角度进行描述，该信用额度处理装置具体可以集成在计算机设备中，该计算机设备可以是服务器，也可以是终端等设备；其中，该终端可以包括平板电脑、笔记本电脑、以及个人计算机(PC，Personal Computer)、可穿戴设备、虚拟现实设备或其他可以获取数据的智能设备等设备。
如图2所示，该信用额度处理方法的具体流程如步骤S201至步骤S205：
S201、获取设备待生成信用额度的对象的生物特征信息。
S202、根据生物特征信息，对对象进行身份识别，得到对象的身份信息。
S203、根据身份信息，提取对象针对设备的初始信用额度。
S204、根据身份信息，获取对象针对设备的历史消费数据。
S205、对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。
本申请可以获取设备待生成信用额度的对象的生物特征信息；根据生物特征信息，对对象进行身份识别，得到对象的身份信息；根据身份信息，提取对象针对设备的初始信用额度；根据身份信息，获取对象针对设备的历史消费数据；对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。由于本申请可以基于对象的生物特征信息，识别出对象的身份信息，如此可以基于身份信息，获取得到对象的历史消费数据和初始信用额度，从而可以基于历史消费数据和初始信用额度，准确和自动地为对象生成信用额度，如此提高用户信用额度的生成效率和生成准确性。
根据上面实施例所描述的方法，以下将作进一步详细说明。
在本实施例中，将以该信用额度处理装置具体集成在计算机设备，计算机设备为服务器。如图2所示，该信用额度处理方法的具体流程如步骤S201至步骤S205：
S201、获取设备待生成信用额度的对象的生物特征信息。
其中，对象可以是指用户。
其中，生物特征信息可以包括但不限于对象语音、对象指纹、对象人脸中的至少一种。其中，本申请实施例的生物特征信息可以优选为对象语音。
在一些申请实施例中，获取设备待生成信用额度的对象的生物特征信息的方式可以为：通过 与设备连接的生物特征信息获取设备，获取设备待生成信用额度的对象的生物特征信息。其中，当生物特征信息为对象语音时，生物特征信息获取设备为语音获取设备；当生物特征信息为对象指纹时，生物特征信息获取设备为指纹获取设备；当生物特征信息为对象人脸时，生物特征信息为摄像设备。
S202、根据生物特征信息，对对象进行身份识别，得到对象的身份信息。
在一些申请实施例中，步骤S202中，根据上述对象的生物特征信息，对上述对象进行身份识别，得到对象的身份信息的方式可以为：将生物特征信息，与预设生物特征信息进行匹配；若匹配，则将预设生物特征信息对应的预设身份信息，作为该对象的身份信息。
其中，预设生物特征信息可以是指预先设置的、对象的生物特征信息。
在一示例中，当生物特征信息与预设生物特征信息相同时，此种情况可以称生物特征信息与预设生物特征信息匹配；当生物特征信息与预设生物特征信息不相同时，此种情况可以称生物特征信息与预设生物特征信息不匹配。
在一示例中，当生物特征信息与预设生物特征信息之间的相似度大于预设相似度阈值时，此种情况可以称生物特征信息与预设生物特征信息匹配；当生物特征信息与预设生物特征信息之间的相似度小于或等于预设相似度阈值时，此种情况可以称生物特征信息与预设生物特征信息不匹配。
在一申请实施例中，根据生物特征信息，对对象进行身份识别，得到对象的身份信息的方式可以为：采用身份识别模型，根据生物特征信息，对对象进行身份识别，得到对象的身份信息。
其中，身份识别模型可以为CNN神经网络模型，也可以为自注意力神经网络模型，等等。S203、根据身份信息，提取对象针对设备的初始信用额度。
在一些申请实施例中，根据身份信息，提取对象针对设备的初始信用额度的方式可以为：根据身份信息，获取对象的信用额度等级；提取信用额度等级对应的初始信用额度，以得到对象针对设备的初始信用额度。
例如，根据身份信息，获取对象的信用额度等级的方式可以为：获取身份信息和信用额度等级的对应关系；根据身份信息和对应关系，获取身份信息对应的信用额度等级；将身份信息对应的信用额度等级，作为对象的信用额度等级。
例如，提取信用额度等级对应的初始信用额度，以得到对象针对设备的初始信用额度的方式可以为：提取信用额度等级对应的预设额度数值；采用映射规则，对预设额度数值进行映射处理，得到信用额度等级对应的初始信用额度，以得到对象针对设备的初始信用额度。其中，映射规则可以是指对预设额度数值进行映射处理的规则，映射规则具体可以表征为函数，也可以表征为表格。
其中，映射规则可以为：初始信用额度＝预设额度数值×30％。
比如，初始信用额度与信用额度等级是一一对应的关系，基于此，可以通过初始信用额度与信用额度等级之间的对应关系，提取到信用额度等级对应的初始信用额度。
其中，信用额度等级可以是指对象所对应的初始信用额度的等级。
此处以具体例子进行解释，例如，当对象为用户A时，计算机设备获取到用户A的信用额度等级为二级，然后，计算机设备可以根据信用额度等级和预设额度数值之间的对应关系，提取到用户A在二级的信用额度等级下，对应的预设额度数值为100。然后，计算机设备可以采用映射规则，对预设额度数值100进行映射处理，得到数值70，该数值70即为用户A的初始信用额度。
比如，根据身份信息，获取对象的信用额度等级的方式可以为：判断身份信息与云端中的预设信息是否匹配；若匹配，则提取预设信息对应预设信用额度等级；将预设信用额度等级，确定为对象的信用额度等级。
此处可以理解的是，本申请将预设信息存储于云端，可以减少本地存储空间的存储量，还可以不必依赖本地存储空间，在有网络的情况下，可以随时随地可以判断身份信息与云端中的预设信息是否匹配。
其中，预设信息可以是指预先设置的、用于对身份信息进行判断的信息。例如，预设信息可以表征为预先设置的、对象的唯一标识符。
其中，当身份信息与预设信息相同时，此种情况，可以称身份信息与预设信息匹配；当身份信息与预设信息不相同时，此种情况，可以称身份信息与预设信息不匹配。
其中，当身份信息与预设信息之间的相似度大于预设相似度阈值时，此种情况可以称身份信息与预设信息匹配；当身份信息与预设信息之间的相似度小于或等于预设相似度阈值时，此种情况可以称身份信息与预设信息不匹配。
在一示例中，根据身份信息，获取对象的信用额度等级的方式可以为：通过信用额度处理服务器，向信用额度处理服务器对应的数据缓存区发送额度等级查询请求，额度等级查询请求携带身份信息；根据额度等级查询请求中的身份信息，在数据缓存区中，对对象的信用额度等级进行查询处理，以得到对象的信用额度等级。
其中，信用额度处理服务器可以是指用于对对象的信用额度的相关信息进行处理的服务器。其中，相关信息可以包括但不限于信用额度等级、初始信用额度中的至少一种。
例如，当对象为用户B时，身份信息可以表征为用户B的电话号码，基于此，当通过信用额度处理服务器，向信用额度处理服务器对应的数据缓存区发送额度等级查询请求后，可以基于额度等级查询请求携带的用户B的电话号码，在数据缓存区中，对用户B的信用额度等级进行查询处理，以得到用户B的信用额度等级。
其中，计算机设备可以与信用额度处理服务器通过HTTPS协议进行通信。
其中，数据缓存区可以是用于临时存储上述相关信息的存储区。
在一示例中，根据额度等级查询请求中的身份信息，在数据缓存区中，对对象的信用额度等级进行查询处理，以得到对象的信用额度等级的方式可以为：根据额度等级查询请求中的身份信息，在数据缓存区中，对对象的信用额度等级进行查询处理；若在数据缓存区中未查询到对象的信用额度等级，则通过信用额度处理服务器，向云端请求对象的信用额度等级。此处可以理解的是，本申请可以优先在数据缓存区中查询对象的信用额度等级，如此可以提高信用额度等级的获取效率。在数据缓存区中未查询到对象的信用额度等级的情况下，再选择采用新的方式来获取信用额度等级，如通过信用额度处理服务器，向云端请求对象的信用额度等级。
在一示例中，通过信用额度处理服务器，向云端请求对象的信用额度等级的方式可以为：通过信用额度处理服务器，从信用额度处理服务器对应的内存数据库，提取对象在预设时间段内的目标消费数据；根据目标消费数据，向云端请求对象的信用额度等级。
此处可以理解的是，本申请利用对象预设时间段内的目标消费数据，能够提高获取信用额度等级的准确性。
其中，内存数据库可以是指至少用于长时间存储对象的消费数据的数据库。其中，消费数据可以包括但不限于目标消费数据和历史消费数据中的至少一种。
在一示例中，根据目标消费数据，向云端请求对象的信用额度等级的方式可以为：通过信用额度处理服务器，向云端发送目标消费数据，以使云端根据目标消费数据，获取对象的信用额度等级。
基于上述，在一示例中，云端可以判断目标消费数据所处的数据区间；对数据区间进行映射处理，得到对象的信用额度等级。
其中，数据区间可以是指数据大小的区间。
在一些申请实施例中，根据身份信息，提取对象针对设备的初始信用额度的方式可以为：判 断身份信息是否符合预设要求；若符合，则根据身份信息，提取对象针对设备的初始信用额度。
此处可以理解的是，在身份信息符合预设要求的情况下，本申请再提取对象针对设备的初始信用额度，如此可以提高获取初始信用额度的安全性。
其中，可以根据身份信息，从云端中提取身份信息对应的初始信用额度；将身份信息对应的初始信用额度，作为对象针对设备的初始信用额度。
其中，当身份信息与手机号码绑定，或身份信息登录的上述设备所处的地理位置为预设有效地理位置，或身份信息不在黑名单内，或身份信息所登录的设备中所有历史登录用户的还款逾期次数均不大于预设次数阈值时，此种情况，可以称身份信息符合预设要求。当身份信息未与手机号码绑定，或身份信息登录的上述设备所处的地理位置不为预设有效地理位置，或身份信息在黑名单内，或身份信息所登录的设备中所有历史登录用户的还款逾期次数存在大于预设次数阈值时，此种情况，可以称身份信息不符合预设要求。
S204、根据身份信息，获取对象针对设备的历史消费数据。
在一些申请实施例中，根据身份信息，获取对象针对设备的历史消费数据的方式可以为：判断初始信用额度是否小于预设额度阈值；若是，则根据身份信息，获取对象针对设备的历史消费数据。
其中，可以根据身份信息，从前述的内存数据库中，提取对象针对设备的历史消费数据。其中，历史消费数据可以包括对象在目标时间内的语音消费交易信息、目标时间内的信用履约交易信息、目标时间内的线下现金方式交易信息、目标时间内的银行征信情况信息、目标时间内的其他线下购物交易信息。
其中，目标时间可以是近6个月，也可以根据情况设定时长。其中，交易信息可以包括交易金额信息和交易总笔数信息。
S205、对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。
具体地，获取针对历史消费数据的映射函数；根据映射函数，对历史消费数据进行映射处理，得到对象的信用额度参数；对信用额度参数和初始信用额度进行融合运算，得到对象的信用额度。
此处可以理解的是，本申请利用将信用额度参数与初始信用额度进行融合，能够更加精准地获取到对象的信用额度。
其中，映射函数可以为用于对历史消费数据进行映射处理的函数。
对信用额度参数和初始信用额度进行融合运算，得到对象的信用额度的方式可以为：获取融合函数；通过融合函数，对信用额度参数和初始信用额度进行融合运算，得到对象的信用额度。
其中，融合函数可以为用于对信用额度参数和初始信用额度进行融合运算的函数，该融合函数可以为自定义的函数。
例如，可以通过融合函数，将信用额度参数和初始信用额度进行相加，得到对象的信用额度。基于上述，此处进一步对本申请进行阐述。此处以生物特征信息是对象语音为例进行阐述，此处可以理解的是，当生物特征信息为对象语音时，计算机设备可以利用对象语音，快速生成对象的信用额度，从而可以避免对象的手动操作。
例如，如图3所示，本申请可以设置有计算机设备、接口服务器、信用额度处理服务器、数据缓存区和内存数据库。其中，语音获取设备可以集成于计算机设备上，接口服务器可以作为连接计算机设备和信用额度处理服务器之间的接口。
具体来说，当计算机设备通过语音获取设备，获取到对象的对象语音时，计算机设备根据生物特征信息，对对象进行身份识别，得到对象的身份信息；然后，计算机设备将身份信息通过接口服务器发送给信用额度处理服务器；接着，信用额度处理服务器，向信用额度处理服 务器对应的数据缓存区发送额度等级查询请求，额度等级查询请求携带身份信息；根据额度等级查询请求中的身份信息，在数据缓存区中，对对象的信用额度等级进行查询处理。
其中，若在数据缓存区中查询到对象的信用额度等级，则从数据缓存区中，提取对象针对设备的初始信用额度。
其中，若在数据缓存区中未查询到对象的信用额度等级，则通过信用额度处理服务器，向云端请求对象的信用额度等级。
然后，计算机设备可以通过云端，提取信用额度等级对应的初始信用额度，以得到对象针对设备的初始信用额度。接着，云端可以将初始信用额度发送到信用额度处理服务器。计算机设备可以通过信用额度处理服务器，根据身份信息，获取对象针对设备的历史消费数据；计算机设备可以通过信用额度处理服务器，对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。然后，信用额度处理服务器可以通过接口服务器，将信用额度发送给计算机设备。
基于上述，如图4所示，本申请进一步进行阐述，如步骤S401至步骤S409所示：
S401、获取设备待生成信用额度的对象的生物特征信息。
S402、根据生物特征信息，对对象进行身份识别，得到对象的身份信息。
S403、判断身份信息与云端中的预设信息是否匹配。
若匹配，则执行步骤S404；若不匹配，则执行步骤S409。
S404、提取预设信息对应预设信用额度等级。
S405、将预设信用额度等级，确定为对象的信用额度等级。
S406、提取信用额度等级对应的初始信用额度，以得到对象针对设备的初始信用额度。
S407、根据身份信息，获取对象针对设备的历史消费数据。
S408、对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。
S409、向对象发送初始信用额度生成失败的失败信息。
以上各个操作的具体实施可参见前面的实施例，在此不再赘述。
本申请可以获取设备待生成信用额度的对象的生物特征信息；根据生物特征信息，对对象进行身份识别，得到对象的身份信息；根据身份信息，提取对象针对设备的初始信用额度；根据身份信息，获取对象针对设备的历史消费数据；对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。由于本申请可以基于对象的生物特征信息，识别出对象的身份信息，如此可以基于身份信息，获取得到对象的历史消费数据和初始信用额度，从而可以基于历史消费数据和初始信用额度，准确和自动地为对象生成信用额度，如此提高用户信用额度的生成效率和生成准确性。
为了更好地实施以上方法，本申请实施例还提供一种信用额度处理装置，该信用额度处理装置可以集成在计算机设备，比如服务器或终端等设备中，该终端可以包括平板电脑、笔记本电脑和/或个人计算机等。
例如，如图5所示，该信用额度处理装置可以包括第一获取单元301、识别单元302、提取单元303、第二获取单元304和融合单元305，如下：
获取单元；
获取单元，可以用于获取设备待生成信用额度的对象的生物特征信息。
识别单元；
识别单元，可以用于根据生物特征信息，对对象进行身份识别，得到对象的身份信息。
提取单元；
提取单元，可以用于根据身份信息，提取对象针对设备的初始信用额度。
在一些申请实施例中，提取单元，可以用于根据身份信息，获取对象的信用额度等级；提取信用额度等级对应的初始信用额度，以得到对象针对设备的初始信用额度。
在一些申请实施例中，提取单元，可以用于判断身份信息与云端中的预设信息是否匹配；若匹配，则提取预设信息对应预设信用额度等级；将预设信用额度等级，确定为对象的信用额度等级。
在一些申请实施例中，提取单元，可以用于通过信用额度处理服务器，向信用额度处理服务器对应的数据缓存区发送额度等级查询请求，额度等级查询请求携带身份信息；根据额度等级查询请求中的身份信息，在数据缓存区中，对对象的信用额度等级进行查询处理，以得到对象的信用额度等级。
在一些申请实施例中，提取单元，可以用于根据额度等级查询请求中的身份信息，在数据缓存区中，对对象的信用额度等级进行查询处理；若在数据缓存区中未查询到对象的信用额度等级，则通过信用额度处理服务器，向云端请求对象的信用额度等级。
在一些申请实施例中，提取单元，可以用于通过信用额度处理服务器，从信用额度处理服务器对应的内存数据库，提取对象在预设时间段内的目标消费数据；根据目标消费数据，向云端请求对象的信用额度等级。
在一些申请实施例中，提取单元，可以用于判断身份信息是否符合预设要求；若符合，则根据身份信息，提取对象针对设备的初始信用额度。
第二获取单元；
第二获取单元，可以用于根据身份信息，获取对象针对设备的历史消费数据。
在一些申请实施例中，第二获取单元，可以用于判断初始信用额度是否小于预设额度阈值；
若是，则根据身份信息，获取对象针对设备的历史消费数据。
融合单元；
融合单元，可以用于对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。在一些申请实施例中，融合单元，可以用于获取针对历史消费数据的映射函数；根据映射函数，对历史消费数据进行映射处理，得到对象的信用额度参数；对信用额度参数和初始信用额度进行融合运算，得到对象的信用额度。
由上可知，本申请的第一获取单元可以用于获取设备待生成信用额度的对象的生物特征信息；识别单元可以用于根据生物特征信息，对对象进行身份识别，得到对象的身份信息；提取单元可以用于根据身份信息，提取对象针对设备的初始信用额度；第二获取单元可以用于根据身份信息，获取对象针对设备的历史消费数据；融合单元可以用于对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。由于本申请可以基于对象的生物特征信息，识别出对象的身份信息，如此可以基于身份信息，获取得到对象的历史消费数据和初始信用额度，从而可以基于历史消费数据和初始信用额度，准确和自动地为对象生成信用额度，如此提高用户信用额度的生成效率和生成准确性。
本申请实施例还提供一种计算机设备，如图6所示，其示出了本申请实施例所涉及的计算机设备的结构示意图，具体来讲：
该计算机设备可以包括一个或者一个以上处理核心的处理器401、一个或一个以上计算机可读存储介质的存储器402、电源403和输入单元404等部件。本领域技术人员可以理解，图6中示出的计算机设备结构并不构成对计算机设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。其中：
处理器401是该计算机设备的控制中心，利用各种接口和线路连接整个计算机设备的各个部分，通过运行或执行存储在存储器402内的软件程序和/或模块，以及调用存储在存储器402内的数据，执行计算机设备的各种功能和处理数据。可选的，处理器401可包括一个或多个处理核心；优选的，处理器401可集成应用处理器和调制解调处理器，其中，应用处理器主要处理操作系统、用户界面和计算机程序等，调制解调处理器主要处理无线通信。可以理解的是，上述调制解调处理器也可以不集成到处理器401中。
存储器402可用于存储软件程序以及模块，处理器401通过运行存储在存储器402的软件程序以及模块，从而执行各种功能应用以及数据处理。存储器402可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的计算机程序(比如声音播放功能、图像播放功能等)等；存储数据区可存储根据计算机设备的使用所创建的数据等。此外，存储器402可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。相应地，存储器402还可以包括存储器控制器，以提供处理器401对存储器402的访问。
计算机设备还包括给各个部件供电的电源403，优选的，电源403可以通过电源管理系统与处理器401逻辑相连，从而通过电源管理系统实现管理充电、放电、以及功耗管理等功能。电源403还可以包括一个或一个以上的直流或交流电源、再充电系统、电源故障检测电路、电源转换器或者逆变器、电源状态指示器等任意组件。
该计算机设备还可包括输入单元404，该输入单元404可用于接收输入的数字或字符信息通讯，以及产生与用户设置以及功能控制有关的键盘、鼠标、操作杆、光学或者轨迹球信号输入。
尽管未示出，计算机设备还可以包括显示单元等，在此不再赘述。具体在本实施例中，计算机设备中的处理器401会按照如下的指令，将一个或一个以上的计算机程序的进程对应的可执行文件加载到存储器402中，并由处理器401来运行存储在存储器402中的计算机程序，从而实现各种功能，如下：
获取设备待生成信用额度的对象的生物特征信息；根据生物特征信息，对对象进行身份识别，得到对象的身份信息；根据身份信息，提取对象针对设备的初始信用额度；根据身份信息，获取对象针对设备的历史消费数据；对历史消费数据和初始信用额度进行融合处理，以生成对象的信用额度。
以上各个操作的具体实施可参见前面的实施例，在此不再赘述。
本领域普通技术人员可以理解，上述实施例的各种方法中的全部或部分步骤可以通过计算机程序来完成，或通过计算机程序控制相关的硬件来完成，该计算机程序可以存储于一计算机可读存储介质中，并由处理器进行加载和执行。
为此，本申请实施例提供一种计算机可读存储介质，其中存储有计算机程序，该计算机程序能够被处理器进行加载，以执行本申请实施例所提供的任一种信用额度处理方法。
以上各个操作的具体实施可参见前面的实施例，在此不再赘述。
其中，该计算机可读存储介质可以包括：只读存储器(ROM，Read Only Memory)、随机存取记忆体(RAM，Random Access Memory)、磁盘或光盘等。
由于该计算机可读存储介质中所存储的指令，可以执行本申请实施例所提供的任一种信用额度处理方法中的步骤，因此，可以实现本申请实施例所提供的任一种信用额度处理方法所能实现的有益效果，详见前面的实施例，在此不再赘述。
其中，根据本申请的一个方面，提供了一种计算机程序产品或计算机程序，该计算机程序产品或计算机程序包括计算机指令，该计算机指令存储在计算机可读存储介质中。计算机设备的处理器从计算机可读存储介质读取该计算机指令，处理器执行该计算机指令，使得该计算机设备执行上述实施例提供的各种可选实现方式中提供的方法。
以上对本申请实施例所提供的一种信用额度处理方法、装置、计算机设备、计算机可读存储介质及计算机程序产品进行了详细介绍，本文中应用了具体个例对本申请的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本申请的方法及其核心思想；同时，对于本领域的技术人员，依据本申请的思想，在具体实施方式及应用范围上均会有改变之处，综上，本说明书内容不应理解为对本申请的限制。

Claims (20)

  1. 一种信用额度处理方法，其中，包括：
    获取设备待生成信用额度的对象的生物特征信息；
    根据所述生物特征信息，对所述对象进行身份识别，得到所述对象的身份信息；
    根据所述身份信息，提取所述对象针对所述设备的初始信用额度；
    根据所述身份信息，获取所述对象针对所述设备的历史消费数据；
    对所述历史消费数据和所述初始信用额度进行融合处理，以生成所述对象的信用额度。
  2. 根据权利要求1所述的信用额度处理方法，其中，所述根据所述身份信息，提取所述对象针对所述设备的初始信用额度，包括：
    根据所述身份信息，获取所述对象的信用额度等级；
    提取所述信用额度等级对应的初始信用额度，以得到所述对象针对所述设备的初始信用额度。
  3. 根据权利要求2所述的信用额度处理方法，其中，所述根据所述身份信息，获取所述对象的信用额度等级，包括：
    判断所述身份信息与云端中的预设信息是否匹配；
    若匹配，则提取所述预设信息对应预设信用额度等级；
    将所述预设信用额度等级，确定为所述对象的信用额度等级。
  4. 根据权利要求2所述的信用额度处理方法，其中，所述根据所述身份信息，获取所述对象的信用额度等级，包括：
    通过信用额度处理服务器，向所述信用额度处理服务器对应的数据缓 存区发送额度等级查询请求，所述额度等级查询请求携带所述身份信息；
    根据所述额度等级查询请求中的身份信息，在所述数据缓存区中，对所述对象的信用额度等级进行查询处理，以得到所述对象的信用额度等级。
  5. 根据权利要求4所述的信用额度处理方法，其中，所述根据所述额度等级查询请求中的身份信息，在所述数据缓存区中，对所述对象的信用额度等级进行查询处理，以得到所述对象的信用额度等级，包括：
    根据所述额度等级查询请求中的身份信息，在所述数据缓存区中，对所述对象的信用额度等级进行查询处理；
    若在所述数据缓存区中未查询到所述对象的信用额度等级，则通过所述信用额度处理服务器，向云端请求所述对象的信用额度等级。
  6. 根据权利要求5所述的信用额度处理方法，其中，所述通过所述信用额度处理服务器，向云端请求所述对象的信用额度等级，包括：
    通过所述信用额度处理服务器，从所述信用额度处理服务器对应的内存数据库，提取所述对象在预设时间段内的目标消费数据；
    根据所述目标消费数据，向云端请求所述对象的信用额度等级。
  7. 根据权利要求1所述的信用额度处理方法，其中，在所述根据所述对象身份信息，提取所述对象针对所述设备的初始信用额度，包括：
    判断所述身份信息是否符合预设要求；
    若符合，则根据所述身份信息，提取所述对象针对所述设备的初始信 用额度。
  8. 根据权利要求1所述的信用额度处理方法，其中，所述根据所述身份信息，获取所述对象针对所述设备的历史消费数据，包括：
    判断所述初始信用额度是否小于预设额度阈值；
    若是，则根据所述身份信息，获取所述对象针对所述设备的历史消费数据。
  9. 根据权利要求1至8任一项所述的信用额度处理方法，其中，所述对所述历史消费数据和所述初始信用额度进行融合处理，以生成所述对象的信用额度，包括：
    获取针对所述历史消费数据的映射函数；
    根据所述映射函数，对所述历史消费数据进行映射处理，得到所述对象的信用额度参数；
    对所述信用额度参数和所述初始信用额度进行融合运算，得到所述对象的信用额度。
  10. 根据权利要求1所述的信用额度处理方法，其中，所述根据所述生物特征信息，对所述对象进行身份识别，得到所述对象的身份信息，包括：
    采用身份识别模型，根据生物特征信息，对对象进行身份识别，得到对象的身份信息；
    所述身份识别模型包括CNN神经网络模型或者自注意力神经网络模型。
  11. 根据权利要求2所述的信用额度处理方法，其中，所述根据所述 身份信息，获取所述对象的信用额度等级，包括：
    获取身份信息和信用额度等级的对应关系；
    根据身份信息和对应关系，获取身份信息对应的信用额度等级；
    将身份信息对应的信用额度等级，作为对象的信用额度等级。
  12. 根据权利要求2所述的信用额度处理方法，其中，所述提取所述信用额度等级对应的初始信用额度，以得到所述对象针对所述设备的初始信用额度，包括：
    提取信用额度等级对应的预设额度数值；
    采用映射规则，对预设额度数值进行映射处理，得到信用额度等级对应的初始信用额度，以得到对象针对设备的初始信用额度。
  13. 根据权利要求9所述的信用额度处理方法，其中，所述对所述信用额度参数和所述初始信用额度进行融合运算，得到所述对象的信用额度，包括：
    获取融合函数；
    通过融合函数，对信用额度参数和初始信用额度进行融合运算，得到对象的信用额度。
  14. 根据权利要求1所述的信用额度处理方法，其中，所述获取设备待生成信用额度的对象的生物特征信息，包括：
    通过与设备连接的生物特征信息获取设备，获取设备待生成信用额度的对象的生物特征信息；
    其中，所述生物特征信息获取设备包括语音获取设备、指纹获取设备或者摄像设备中的至少一种。
  15. 根据权利要求1所述的信用额度处理方法，其中，所述根据所述生物特征信息，对所述对象进行身份识别，得到所述对象的身份信息，包括：
    将生物特征信息，与预设生物特征信息进行匹配；
    若匹配，则将预设生物特征信息对应的预设身份信息，作为该对象的身份信息。
  16. 一种信用额度处理装置，其中，包括：
    第一获取单元，用于获取设备待生成信用额度的对象的生物特征信息；识别单元，用于根据所述生物特征信息，对所述对象进行身份识别，得到所述对象的身份信息；
    提取单元，用于根据所述身份信息，提取所述对象针对所述设备的初始信用额度；
    第二获取单元，用于根据所述身份信息，获取所述对象针对所述设备的历史消费数据；
    融合单元，用于对所述历史消费数据和所述初始信用额度进行融合处理，以生成所述对象的信用额度。
  17. 根据权利要求16所述的信用额度处理装置，其中，所述提取单元具体用于：
    根据身份信息，获取对象的信用额度等级；
    提取信用额度等级对应的初始信用额度，以得到对象针对设备的初始信用额度。
  18. 一种计算机设备，其中，包括存储器和处理器；所述存储器存储 有计算机程序，所述处理器用于运行所述存储器内的计算机程序，以执行权利要求1至15任一项所述的信用额度处理方法。
  19. 一种计算机可读存储介质，其中，所述计算机可读存储介质存储有计算机程序，所述计算机程序适于处理器进行加载，以执行权利要求1至15任一项所述的信用额度处理方法。
  20. 一种计算机程序产品，其中，所述计算机程序产品存储有计算机程序，所述计算机程序适于处理器进行加载，以执行权利要求1至15任一项所述的信用额度处理方法。
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Publication number Priority date Publication date Assignee Title
CN117408768A (zh) * 2023-06-06 2024-01-16 深圳Tcl新技术有限公司 一种信用额度处理方法及相关设备
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104852966A (zh) * 2015-04-21 2015-08-19 小米科技有限责任公司 数值转移方法、终端及云端服务器
CN106600284A (zh) * 2016-12-22 2017-04-26 Tcl集团股份有限公司 一种信用额度的授权方法及装置
CN108573382A (zh) * 2018-03-27 2018-09-25 英业达科技有限公司 基于生物特征的信用支付系统及其方法
JP2019149025A (ja) * 2018-02-27 2019-09-05 三井住友カード株式会社 顔認証技術による与信管理及び自動決済システム
CN110969522A (zh) * 2018-09-30 2020-04-07 重庆小雨点小额贷款有限公司 一种贷款方法、装置、服务器及存储介质
CN114648344A (zh) * 2022-03-18 2022-06-21 中国建设银行股份有限公司 会员注册方法和装置
CN117408768A (zh) * 2023-06-06 2024-01-16 深圳Tcl新技术有限公司 一种信用额度处理方法及相关设备

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104852966A (zh) * 2015-04-21 2015-08-19 小米科技有限责任公司 数值转移方法、终端及云端服务器
CN106600284A (zh) * 2016-12-22 2017-04-26 Tcl集团股份有限公司 一种信用额度的授权方法及装置
JP2019149025A (ja) * 2018-02-27 2019-09-05 三井住友カード株式会社 顔認証技術による与信管理及び自動決済システム
CN108573382A (zh) * 2018-03-27 2018-09-25 英业达科技有限公司 基于生物特征的信用支付系统及其方法
CN110969522A (zh) * 2018-09-30 2020-04-07 重庆小雨点小额贷款有限公司 一种贷款方法、装置、服务器及存储介质
CN114648344A (zh) * 2022-03-18 2022-06-21 中国建设银行股份有限公司 会员注册方法和装置
CN117408768A (zh) * 2023-06-06 2024-01-16 深圳Tcl新技术有限公司 一种信用额度处理方法及相关设备

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