WO2022134466A1 - 数据处理方法及相关设备 - Google Patents

数据处理方法及相关设备 Download PDF

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Publication number
WO2022134466A1
WO2022134466A1 PCT/CN2021/096635 CN2021096635W WO2022134466A1 WO 2022134466 A1 WO2022134466 A1 WO 2022134466A1 CN 2021096635 W CN2021096635 W CN 2021096635W WO 2022134466 A1 WO2022134466 A1 WO 2022134466A1
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decision
business
information
variables
request
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PCT/CN2021/096635
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English (en)
French (fr)
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颜赛云
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平安科技（深圳）有限公司
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Publication of WO2022134466A1 publication Critical patent/WO2022134466A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance

Definitions

  • the present application relates to the technical field of business security, and in particular, to a data processing method and related equipment.
  • risk control means that risk managers take various measures to eliminate or reduce the possibility of risk events.
  • Risk decision-making refers to the process of choosing two or more action plans under the action of various uncertain factors.
  • the inventor realized that in the traditional risk decision-making process, by analyzing and making decisions on all relevant information of the user, because this method is to analyze and verify all the relevant information of the user at one time, the efficiency of determining the decision-making result is low. , to collect all relevant information of users in the early stage, resulting in a long data collection time, which is not conducive to business risk decision-making.
  • a first aspect of the present application provides a data processing method, the data processing method comprising:
  • association information passes the decision, the association information corresponding to the plurality of business variables is repeatedly obtained for decision analysis until a preset condition is met, and a decision result is output.
  • a second aspect of the present application provides an electronic device, the electronic device includes a processor and a memory, the processor is configured to execute computer-readable instructions stored in the memory to implement the following steps:
  • association information passes the decision, the association information corresponding to the plurality of business variables is repeatedly obtained for decision analysis until a preset condition is met, and a decision result is output.
  • a third aspect of the present application provides a computer-readable storage medium on which at least one computer-readable instruction is stored, and the at least one computer-readable instruction is executed by a processor to implement the following steps:
  • association information passes the decision, the association information corresponding to the plurality of business variables is repeatedly acquired for decision analysis until a preset condition is met, and a decision result is output.
  • a fourth aspect of the present application provides a data processing device, the data processing comprising:
  • a determining unit configured to receive a risk decision request, and determine a trigger user of the risk decision request
  • an auditing unit configured to obtain the personal information of the triggering user, and conduct audit processing on the personal information
  • an acquisition unit configured to determine a decision-making business according to the risk decision request if the personal information passes the review, and obtain business variables of the decision-making business;
  • the determining unit is further configured to determine the decision priorities of the plurality of business variables in the decision-making business if there are multiple business variables;
  • An analysis unit configured to obtain the associated information corresponding to the plurality of business variables for decision analysis, including:
  • the output unit is configured to repeatedly obtain the associated information corresponding to the plurality of business variables for decision analysis if the associated information passes the decision, until a preset condition is satisfied, and output the decision result.
  • the present application can not only save the time spent on collecting information, but also reduce the analysis of unnecessary information and improve the analysis efficiency.
  • FIG. 1 is a flowchart of a preferred embodiment of the data processing method of the present application.
  • FIG. 2 is a flowchart of an embodiment of the application for reviewing personal information.
  • FIG. 3 is a flowchart of an embodiment of the present application for determining decision priorities for multiple business variables.
  • FIG. 4 is a functional block diagram of a preferred embodiment of the data processing apparatus of the present application.
  • FIG. 5 is a schematic structural diagram of an electronic device implementing a preferred embodiment of the data processing method of the present application.
  • FIG. 1 it is a flowchart of a preferred embodiment of the data processing method of the present application. According to different requirements, the order of the steps in this flowchart can be changed, and some steps can be omitted.
  • the data processing method is applied to one or more electronic devices, the electronic device is a device that can automatically perform numerical calculation and/or information processing according to pre-set or stored computer-readable instructions, and its hardware includes: But not limited to microprocessors, application specific integrated circuits (ASICs), programmable gate arrays (Field-Programmable Gate Arrays, FPGAs), digital processors (Digital Signal Processors, DSPs), embedded devices, etc.
  • ASICs application specific integrated circuits
  • FPGAs Field-Programmable Gate Arrays
  • DSPs Digital Signal Processors
  • embedded devices etc.
  • the electronic device may be any mobile electronic product that can interact with a user, such as a tablet computer, a smart phone, a Personal Digital Assistant (PDA), a game console, a smart wearable device, and the like.
  • a tablet computer such as a tablet computer, a smart phone, a Personal Digital Assistant (PDA), a game console, a smart wearable device, and the like.
  • PDA Personal Digital Assistant
  • the electronic equipment may include network equipment and/or user equipment.
  • the network device includes, but is not limited to, a single network electronic device, an electronic device group composed of multiple network electronic devices, or a cloud composed of a large number of hosts or network electronic devices based on cloud computing (Cloud Computing).
  • the network where the electronic device is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (Virtual Private Network, VPN), and the like.
  • VPN Virtual Private Network
  • S10 Receive a risk decision request, and determine a triggering user of the risk decision request.
  • the risk decision request may be triggered and generated by any user.
  • the information carried in the risk decision request includes, but is not limited to, sending address, service number, and the like.
  • the triggering user refers to a user who triggers the generation of the risk decision request.
  • determining, by the electronic device, the triggering user of the risk decision request includes:
  • the login identification code on the request log is extracted, and the triggering user is determined according to the login identification code.
  • a plurality of pre-defined tags are stored in the configuration library, and the tags further include an address for indicating a receiving request.
  • the login identification code may be a user login account, and the user login account is used to uniquely identify the user.
  • the efficiency of obtaining the sending address can be improved.
  • the login identification code associated with the risk decision request is acquired on the terminal, and then the triggering user can be accurately determined according to the login identification code.
  • S11 Acquire personal information of the triggering user, and perform audit processing on the personal information.
  • the personal information may include: user name, user ID card, user mobile phone number, and the like.
  • the obtaining, by the electronic device, the personal information of the triggering user includes:
  • the user information table determining a user information table corresponding to the account type, where the user information table stores information of multiple users in the account type;
  • Information corresponding to the login identification code is acquired from the user information table as the personal information.
  • the account type refers to the application program registered by the login identification code, for example, the account type may be QQ and the like.
  • the account type can be determined through the login identification code, and then the user information table can be determined. Through the mapping relationship between the login identification code and personal information, the individual can be accurately determined from the user information table. Since it is not necessary to filter out the personal information from the information tables of all account types, the efficiency of obtaining the personal information can be improved.
  • FIG. 2 is a flowchart of an embodiment of the application for reviewing personal information.
  • the electronic device auditing and processing the personal information includes:
  • S110 Acquire a configuration list, where the configuration list stores the mapping relationships between multiple users and credit levels.
  • the roster users are stored in the configuration roster.
  • S112 Match the traversed list users with the personal information, and determine the traversed list users who are successfully matched with the personal information as target users.
  • S113 Determine the credit level of the target user in the configuration list.
  • the configuration level may be set according to the service security level, and the present application does not limit the value of the configuration level.
  • the credit level of the triggering user in the configuration list can be quickly determined, and then whether the personal information has passed the review can be quickly determined according to the credit level.
  • the decision-making business may include a home mortgage loan business and the like.
  • the business variable may include co-borrower information, mortgagor information, enterprise information, and the like.
  • prompt information is generated according to the risk decision request, and the prompt information is sent to the terminal device of the triggering user.
  • the review result can be fed back to the triggering user in time.
  • the electronic device determining the decision service according to the risk decision request includes:
  • a service corresponding to the service number is determined as the decision service.
  • the service number can uniquely identify the service.
  • the service number can be accurately acquired from the data information, and then the decision-making service can be accurately determined according to the mapping relationship between the service number and the service.
  • obtaining the business variable of the decision-making business by the electronic device includes:
  • the variables in the decision rule are extracted to obtain the business variables.
  • the business type may be a loan type.
  • the business variable refers to variable information in the decision rule.
  • the business variable can be quickly determined by using the business type to which the decision-making business belongs, and since there is no need to analyze the business attribute of the decision-making business, the determination efficiency of the business variable can be improved.
  • the decision priority refers to an analysis order of the plurality of business variables in the decision rule. For example, the business variable with the highest decision priority is first in the analysis order in the decision rule.
  • FIG. 3 is a flowchart of an embodiment of the present application for determining decision priorities of multiple business variables.
  • determining, by the electronic device, decision priorities of a plurality of the business variables in the decision-making business includes:
  • the information variable refers to a variable corresponding to the personal information.
  • the electronic device converts each service variable into a service vector, converts the information variable into an information vector, calculates the similarity between each service vector and the information vector, and converts the calculated similarity to the information vector. degree is determined as the strength of the association.
  • the correlation strength between business variable A and the information variable is 0.5
  • the correlation strength between business variable B and the information variable is 0.7
  • the correlation strength between business variable C and the information variable is 0.4
  • the business variable The strength of the association between D and the information variable is 0.9. Therefore, the order of the decision priorities from high to low is: the business variable D, the business variable B, the business variable A, and the business variable C .
  • the decision priority can be quickly determined by the strength of the association between each business variable and the information variable.
  • S14 obtaining the association information corresponding to the plurality of business variables for decision analysis, including: according to the order of the decision priorities from high to low, determining the business variable currently at the highest priority as the target variable; Information corresponding to the triggering user and the target variable is used as associated information; decision analysis is performed on the associated information.
  • the electronic device performing decision analysis on the associated information includes:
  • association information If the association information satisfies the target rule, determine that the association information passes the decision; or
  • association information does not satisfy the target rule, it is determined that the association information fails the decision.
  • the target variable is the risk of the mortgagor
  • the target rule extracted from the decision rule is: the mortgagor's credit rating is greater than I5, and if the associated information is that the mortgagor's credit rating is I4, determine The associated information fails the decision.
  • association information passes the decision, repeatedly obtain the association information corresponding to the plurality of business variables for decision analysis until a preset condition is met, and output a decision result.
  • the above decision results can also be stored in a node of a blockchain.
  • the preset condition includes: the association information fails to pass the decision, or the multiple business variables all complete the decision analysis.
  • the decision result includes: the risk decision request passes the review, and the risk decision request fails the review.
  • the associated information fails the decision, it is determined that the risk decision request fails the review, or, if the multiple business variables have completed the decision analysis, and the associated information corresponding to the multiple business variables has passed the decision. , it is determined that the risk decision request has passed the review.
  • the method further includes:
  • the preset condition is that the associated information fails the decision, it is determined that the risk decision request fails the review.
  • the preset condition is that decision analysis has been completed for the plurality of business variables, and the associated information corresponding to the business variable with the lowest decision priority fails the decision, it is determined that the risk decision request has not passed the review; or
  • the preset condition is that decision analysis has been completed for the multiple business variables, and the associated information corresponding to the multiple business variables has passed the decision, it is determined that the risk decision request has passed the review.
  • the audit result of the risk decision request can be determined.
  • the present application can receive a risk decision request, determine the triggering user of the risk decision request, obtain the personal information of the triggering user, and conduct audit processing on the personal information. Triggering the user's personal information for review processing can avoid processing related services of blacklisted users. If the personal information passes the review, determine the decision-making service according to the risk decision request, and obtain the business variables of the decision-making service.
  • Decision-making business can obtain all business variables related to the decision-making business, avoid the omission of the business variables, if there are multiple business variables, determine the decision-making priority of multiple business variables in the decision-making business obtaining the associated information corresponding to the plurality of business variables for decision analysis, including: according to the order of the decision priorities from high to low, determining the business variable currently at the highest priority as the target variable, obtaining Trigger the information corresponding to the user and the target variable as the associated information, perform decision analysis on the associated information, obtain the associated information corresponding to the multiple business variables by segments according to the high and low decision priorities, and obtain the segmented
  • the obtained correlation information can be analyzed quickly, and the analysis result of the correlation information can be quickly determined.
  • the correlation information corresponding to the multiple business variables is repeatedly obtained for decision analysis until the preset conditions are met, and output As a result of the decision, when the associated information fails to pass the decision, it is possible to avoid acquiring unnecessary information, thereby saving the time for acquiring unnecessary information.
  • the present application acquires the associated information of the triggering user in a segmented manner, and then conducts decision analysis on the associated information obtained by segmentation. Since the associated information obtained by segmentation has a small amount of information, it is relatively easy to analyze the overall user information. In other words, the analysis efficiency of the related information corresponding to each business variable is improved. In addition, when the related information fails to pass the decision, the acquisition of the related information corresponding to the business variable is stopped. Therefore, it can not only save the time spent on collecting information, but also The analysis of unnecessary information is reduced, and the analysis efficiency is improved.
  • the plurality of business variables are important indicators for macroeconomic research and analysis.
  • the data processing device 11 includes a determination unit 110 , a review unit 111 , an acquisition unit 112 , an analysis unit 113 and an output unit 114 .
  • the module/unit referred to in this application refers to a series of computer-readable instruction segments that can be acquired by the processor 13 and can perform fixed functions, and are stored in the memory 12 . In this embodiment, the functions of each module/unit will be described in detail in subsequent embodiments.
  • the determination unit 110 receives the risk decision request, and determines the triggering user of the risk decision request.
  • the risk decision request may be triggered and generated by any user.
  • the information carried in the risk decision request includes, but is not limited to, sending address, service number, and the like.
  • the triggering user refers to a user who triggers the generation of the risk decision request.
  • the determining unit 110 determines the triggering user of the risk decision request includes:
  • the login identification code on the request log is extracted, and the triggering user is determined according to the login identification code.
  • a plurality of pre-defined tags are stored in the configuration library, and the tags further include an address for indicating a receiving request.
  • the login identification code may be a user login account, and the user login account is used to uniquely identify the user.
  • the efficiency of obtaining the sending address can be improved.
  • the login identification code associated with the risk decision request is acquired on the terminal, and then the triggering user can be accurately determined according to the login identification code.
  • the review unit 111 acquires the personal information of the triggering user, and performs review processing on the personal information.
  • the personal information may include: user name, user ID card, user mobile phone number, and the like.
  • the obtaining of the personal information of the triggering user by the review unit 111 includes:
  • the user information table determining a user information table corresponding to the account type, where the user information table stores information of multiple users in the account type;
  • Information corresponding to the login identification code is acquired from the user information table as the personal information.
  • the account type refers to the application program registered by the login identification code, for example, the account type may be QQ and the like.
  • the account type can be determined through the login identification code, and then the user information table can be determined. Through the mapping relationship between the login identification code and personal information, the individual can be accurately determined from the user information table. Since it is not necessary to filter out the personal information from the information tables of all account types, the efficiency of obtaining the personal information can be improved.
  • the review processing of the personal information by the review unit 111 includes:
  • a configuration list is obtained, where the configuration list stores the mapping relationship between multiple users and credit levels.
  • the roster users are stored in the configuration roster.
  • the traversed list users are matched with the personal information, and the traversed list users who are successfully matched with the personal information are determined as target users.
  • the configuration level may be set according to the service security level, and the present application does not limit the value of the configuration level.
  • the credit level of the triggering user in the configuration list can be quickly determined, and then whether the personal information has passed the review can be quickly determined according to the credit level.
  • the obtaining unit 112 determines a decision-making business according to the risk decision request, and obtains business variables of the decision-making business.
  • the decision-making business may include a home mortgage loan business and the like.
  • the business variable may include co-borrower information, mortgagor information, enterprise information, and the like.
  • prompt information is generated according to the risk decision request, and the prompt information is sent to the terminal device of the triggering user.
  • the review result can be fed back to the triggering user in time.
  • the obtaining unit 112 determines the decision-making service according to the risk decision request including:
  • a service corresponding to the service number is determined as the decision service.
  • the service number can uniquely identify the service.
  • the service number can be accurately obtained from the data information, and then the decision-making service can be accurately determined according to the mapping relationship between the service number and the service.
  • the acquiring unit 112 acquires the business variables of the decision-making business including:
  • the variables in the decision rule are extracted to obtain the business variables.
  • the business type may be a loan type.
  • the business variable refers to variable information in the decision rule.
  • the business variable can be quickly determined by using the business type to which the decision-making business belongs, and since it is unnecessary to analyze the business attribute of the decision-making business, the determination efficiency of the business variable can be improved.
  • the determining unit 110 determines the decision priorities of the multiple business variables in the decision-making business.
  • the decision priority refers to an analysis order of the plurality of business variables in the decision rule. For example, the business variable with the highest decision priority is first in the analysis order in the decision rule.
  • the determining unit 110 determines the decision priorities of a plurality of the business variables in the decision-making business, including:
  • An information variable to which the personal information belongs is determined.
  • the information variable refers to a variable corresponding to the personal information.
  • the strength of the association of each business variable with the information variable is calculated.
  • the determining unit 110 converts each service variable into a service vector, converts the information variable into an information vector, calculates the similarity between each service vector and the information vector, and converts the calculated The similarity is determined as the association strength.
  • the decision priority of the plurality of business variables is determined according to the correlation strength.
  • the correlation strength between business variable A and the information variable is 0.5
  • the correlation strength between business variable B and the information variable is 0.7
  • the correlation strength between business variable C and the information variable is 0.4
  • the business variable The strength of the association between D and the information variable is 0.9. Therefore, the order of the decision priorities from high to low is: the business variable D, the business variable B, the business variable A, and the business variable C .
  • the decision priority can be quickly determined by the strength of the association between each business variable and the information variable.
  • the analyzing unit 113 obtains the associated information corresponding to the plurality of business variables for decision analysis, including: according to the order of the decision priorities from high to low, determining the business variable currently at the highest priority as the target variable; The information corresponding to the triggering user and the target variable is used as associated information; decision analysis is performed on the associated information.
  • the analyzing unit 113 performs decision analysis on the associated information including:
  • association information If the association information satisfies the target rule, determine that the association information passes the decision; or
  • association information does not satisfy the target rule, it is determined that the association information fails the decision.
  • the target variable is the risk of the mortgagor
  • the target rule extracted from the decision rule is: the mortgagor's credit rating is greater than I5, and if the associated information is that the mortgagor's credit rating is I4, determine The associated information fails the decision.
  • the output unit 114 repeatedly acquires the correlation information corresponding to the plurality of business variables to perform decision analysis until the preset conditions are met, and outputs the decision result.
  • the preset condition includes: the association information fails to pass the decision, or the multiple business variables all complete the decision analysis.
  • the decision result includes: the risk decision request passes the review, and the risk decision request fails the review.
  • the associated information fails the decision, it is determined that the risk decision request fails the review, or, if the multiple business variables have completed the decision analysis, and the associated information corresponding to the multiple business variables has passed the decision. , it is determined that the risk decision request has passed the review.
  • the determining unit 110 determines that the risk decision request fails the review
  • the determining unit 110 determines that the risk decision request fails the review ;
  • the determining unit 110 determines that the risk decision request has passed the review.
  • the audit result of the risk decision request can be determined.
  • the present application can receive a risk decision request, determine the triggering user of the risk decision request, obtain the personal information of the triggering user, and conduct audit processing on the personal information. Triggering the user's personal information for review processing can avoid processing related services of blacklisted users. If the personal information passes the review, determine the decision-making service according to the risk decision request, and obtain the business variables of the decision-making service.
  • Decision-making business can obtain all business variables related to the decision-making business, avoid the omission of the business variables, if there are multiple business variables, determine the decision-making priority of multiple business variables in the decision-making business obtaining the associated information corresponding to the plurality of business variables for decision analysis, including: according to the order of the decision priorities from high to low, determining the business variable currently at the highest priority as the target variable, obtaining Trigger the information corresponding to the user and the target variable as the associated information, perform decision analysis on the associated information, obtain the associated information corresponding to the multiple business variables by segments according to the high and low decision priorities, and obtain the segmented
  • the obtained correlation information can be analyzed quickly, and the analysis result of the correlation information can be quickly determined.
  • the correlation information corresponding to the multiple business variables is repeatedly obtained for decision analysis until the preset conditions are met, and output As a result of the decision, when the associated information fails to pass the decision, it is possible to avoid acquiring unnecessary information, thereby saving the time for acquiring unnecessary information.
  • the present application acquires the associated information of the triggering user in a segmented manner, and then conducts decision analysis on the associated information obtained by segmentation. Since the associated information obtained by segmentation has a small amount of information, it is relatively easy to analyze the overall user information. In other words, the analysis efficiency of the related information corresponding to each business variable is improved. In addition, when the related information fails to pass the decision, the acquisition of the related information corresponding to the business variable is stopped. Therefore, it can not only save the time spent on collecting information, but also The analysis of unnecessary information is reduced, and the analysis efficiency is improved.
  • the plurality of business variables are important indicators for macroeconomic research and analysis.
  • FIG. 5 it is a schematic structural diagram of an electronic device according to a preferred embodiment of the data processing method of the present application.
  • the electronic device 1 includes, but is not limited to, a memory 12 , a processor 13 , and computer-readable instructions stored in the memory 12 and executable on the processor 13 , such as data handlers.
  • the schematic diagram is only an example of the electronic device 1, and does not constitute a limitation on the electronic device 1, and may include more or less components than the one shown, or combine some components, or different Components, for example, the electronic device 1 may also include input and output devices, network access devices, buses, and the like.
  • the processor 13 may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.
  • the processor 13 is the computing core and control center of the electronic device 1, and uses various interfaces and lines to connect the entire electronic device. 1, and the operating system that executes the electronic device 1, as well as various installed applications, program codes, and the like.
  • the computer-readable instructions may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 12 and executed by the processor 13 to Complete this application.
  • the one or more modules/units may be a series of computer-readable instruction segments capable of accomplishing specific functions, and the computer-readable instruction segments are used to describe the execution process of the computer-readable instructions in the electronic device 1 .
  • the computer readable instructions may be divided into a determination unit 110 , a review unit 111 , an acquisition unit 112 , an analysis unit 113 and an output unit 114 .
  • the memory 12 can be used to store the computer-readable instructions and/or modules, and the processor 13 executes or executes the computer-readable instructions and/or modules stored in the memory 12 and invokes the computer-readable instructions and/or modules stored in the memory 12.
  • the data in the electronic device 1 realizes various functions of the electronic device 1 .
  • the memory 12 may mainly include a stored program area and a stored data area, wherein the stored program area may store an operating system, an application program required for at least one function (such as a sound playback function, an image playback function, etc.), and the like; the storage data area may Data and the like created according to the use of the electronic device are stored.
  • the memory 12 may include non-volatile and volatile memory such as: hard disk, internal memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash memory card (Flash Card), at least one disk storage device, flash memory device, or other storage device.
  • non-volatile and volatile memory such as: hard disk, internal memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash memory card (Flash Card), at least one disk storage device, flash memory device, or other storage device.
  • the memory 12 may be an external memory and/or an internal memory of the electronic device 1 . Further, the storage 12 may be a storage in physical form, such as a memory stick, a TF card (Trans-flash Card) and the like.
  • TF card Trans-flash Card
  • modules/units integrated in the electronic device 1 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium, and the computer-readable storage medium may be a non-volatile storage medium.
  • a volatile storage medium can also be a volatile storage medium.
  • the computer-readable instructions include computer-readable instruction codes
  • the computer-readable instruction codes may be in source code form, object code form, executable file, or some intermediate form, and the like.
  • the computer-readable medium may include: any entity or device capable of carrying the computer-readable instruction code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only). Memory), random access memory (RAM, Random Access Memory).
  • the blockchain referred to in this application is a new application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm.
  • Blockchain essentially a decentralized database, is a series of data blocks associated with cryptographic methods. Each data block contains a batch of network transaction information to verify its Validity of information (anti-counterfeiting) and generation of the next block.
  • the blockchain can include the underlying platform of the blockchain, the platform product service layer, and the application service layer.
  • the memory 12 in the electronic device 1 stores computer-readable instructions to implement a data processing method
  • the processor 13 can execute the computer-readable instructions to implement:
  • association information passes the decision, the association information corresponding to the plurality of business variables is repeatedly obtained for decision analysis until a preset condition is met, and a decision result is output.
  • the computer-readable storage medium stores computer-readable instructions, wherein the computer-readable instructions are used to implement the following steps when executed by the processor 13:
  • association information passes the decision, the association information corresponding to the plurality of business variables is repeatedly obtained for decision analysis until a preset condition is met, and a decision result is output.
  • modules described as separate components may or may not be physically separated, and components shown as modules may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
  • each functional module in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units can be implemented in the form of hardware, or can be implemented in the form of hardware plus software function modules.

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Abstract

提供一种数据处理方法及相关设备。该方法能够确定触发用户，获取个人信息，若个人信息通过审核，确定决策业务，获取业务变量，若业务变量有多个，确定多个业务变量的决策优先级，获取多个业务变量对应的关联信息进行决策分析，包括：根据决策优先级确定当前处于最高优先级的业务变量为目标变量，获取同时与触发用户及目标变量对应的信息作为关联信息，对关联信息进行决策分析，若关联信息通过决策，重复获取多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。该方法不仅能够避免对非必要的信息进行获取，还能够提高分析效率。

Description

数据处理方法及相关设备
本申请要求于2020年12月23日提交中国专利局，申请号为202011540112.8，发明名称为“数据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
本申请涉及业务安全技术领域，尤其涉及一种数据处理方法及相关设备。
背景技术
在互联网金融领域中，风险控制是指风险管理者采取各种措施消灭或者减少风险事件发生的可能性。风险决策是指在多种不定因素作用下，对两个或者两个以上的行动方案进行选择的过程。
发明人意识到，在传统的风险决策过程中，通过对用户的所有相关信息进行分析决策，由于该方式是一次性对用户的所有相关信息进行分析校验，导致决策结果确定效率较低，此外，在前期对用户的所有相关进行收集，导致数据收集时间过长，不利于业务的风险决策。
发明内容
鉴于以上内容，有必要提供一种数据处理方法及相关设备，不仅能够避免对非必要的信息进行获取，还能够提高分析效率。
本申请的第一方面提供一种数据处理方法，所述数据处理方法包括：
接收风险决策请求，并确定所述风险决策请求的触发用户；
获取所述触发用户的个人信息，并对所述个人信息进行审核处理；
若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量；
若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级；
获取所述多个业务变量对应的关联信息进行决策分析，包括：
根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；
获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；
对所述关联信息进行决策分析；
若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
本申请的第二方面提供一种电子设备，所述电子设备包括处理器和存储器，所述处理器用于执行所述存储器中存储的计算机可读指令以实现以下步骤：
接收风险决策请求，并确定所述风险决策请求的触发用户；
获取所述触发用户的个人信息，并对所述个人信息进行审核处理；
若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量；
若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级；
获取所述多个业务变量对应的关联信息进行决策分析，包括：
根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；
获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；
对所述关联信息进行决策分析；
若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
本申请的第三方面提供一种计算机可读存储介质，所述计算机可读存储介质上存储有至少一个计算机可读指令，所述至少一个计算机可读指令被处理器执行以实现以下步骤：
接收风险决策请求，并确定所述风险决策请求的触发用户；
获取所述触发用户的个人信息，并对所述个人信息进行审核处理；
若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量；
若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级；
获取所述多个业务变量对应的关联信息进行决策分析，包括：
根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；
获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；
对所述关联信息进行决策分析；
若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
本申请的第四方面提供一种数据处理装置，所述数据处理包括：
确定单元，用于接收风险决策请求，并确定所述风险决策请求的触发用户；
审核单元，用于获取所述触发用户的个人信息，并对所述个人信息进行审核处理；
获取单元，用于若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量；
所述确定单元，还用于若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级；
分析单元，用于获取所述多个业务变量对应的关联信息进行决策分析，包括：
根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；
获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；
对所述关联信息进行决策分析；
输出单元，用于若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
由以上技术方案可以看出，本申请不仅能够节省收集信息所花费的时间，还能减少对非必要信息进行分析，提高了分析效率。
附图说明
图1是本申请数据处理方法的较佳实施例的流程图。
图2是本申请对个人信息进行审核处理的一实施例的流程图。
图3是本申请确定多个业务变量的决策优先级的一实施例的流程图。
图4是本申请数据处理装置的较佳实施例的功能模块图。
图5是本申请实现数据处理方法的较佳实施例的电子设备的结构示意图。
具体实施方式
为了使本申请的目的、技术方案和优点更加清楚，下面结合附图和具体实施例对本申请进行详细描述。
如图1所示，是本申请数据处理方法的较佳实施例的流程图。根据不同的需求，该流程图中步骤的顺序可以改变，某些步骤可以省略。
所述数据处理方法应用于一个或者多个电子设备中，所述电子设备是一种能够按照事先设定或存储的计算机可读指令，自动进行数值计算和/或信息处理的设备，其硬件包括但不限于微处理器、专用集成电路(Application Specific Integrated Circuit，ASIC)、可编程门阵列(Field－Programmable Gate Array，FPGA)、数字处理器(Digital Signal Processor，DSP)、嵌入式设备等。
所述电子设备可以是任何一种可与用户进行人机交互的移动电子产品，例如，平板电脑、智能手机、个人数字助理(Personal Digital Assistant，PDA)、游戏机、智能穿戴式设备等。
所述电子设备可以包括网络设备和/或用户设备。其中，所述网络设备包括，但不限于单个网络电子设备、多个网络电子设备组成的电子设备组或基于云计算(Cloud Computing)的由大量主机或网络电子设备构成的云。
所述电子设备所处的网络包括，但不限于：互联网、广域网、城域网、局域网、虚拟专用网络(Virtual Private Network，VPN)等。
S10，接收风险决策请求，并确定所述风险决策请求的触发用户。
在本申请的至少一个实施例中，所述风险决策请求可以由任意用户触发生成。所述风险决策请求携带的信息包括，但不限于：发送地址、业务编号等。
所述触发用户是指触发所述风险决策请求生成的用户。
在本申请的至少一个实施例中，所述电子设备确定所述风险决策请求的触发用户包括：
解析所述风险决策请求的报文头，得到所述报文头携带的地址信息；
从配置库中获取预设标签，所述预设标签用于指示发送请求的地址；
从所述地址信息中获取与所述预设标签对应的信息作为发送地址；
确定与所述发送地址对应的终端为发送终端；
获取所述风险决策请求的接收时间，并根据所述接收时间从所述发送终端上获取请求日志；
提取所述请求日志上的登录识别码，并根据所述登录识别码确定所述触发用户。
其中，所述配置库中存储多个预先定义好的标签，所述标签还包括用于指示接收请求的地址。
所述登录识别码可以是用户登录账号，所述用户登录账号用于唯一标识用户。
通过上述实施方式，由于无需解析所述风险决策请求的报文，因此能够提高所述发送地址的获取效率，通过所述发送终端及接收到所述风险决策请求的接收时间，能够从所述发送终端上获取到与所述风险决策请求相关联的登录识别码，进而根据所述登录识别码能够准确确定出所述触发用户。
S11，获取所述触发用户的个人信息，并对所述个人信息进行审核处理。
在本申请的至少一个实施例中，所述个人信息可以包括：用户姓名、用户身份证、用户手机号码等。
在本申请的至少一个实施例中，所述电子设备获取所述触发用户的个人信息包括：
确定所述登录识别码的账号类型；
确定与所述账号类型对应的用户信息表，所述用户信息表存储所述账号类型中多个用户的信息；
从所述用户信息表中获取与所述登录识别码对应的信息作为所述个人信息。
其中，所述账号类型是指所述登录识别码所注册的应用程序，例如，所述账号类型可以是QQ等。
通过所述登录识别码确定出所述账号类型，进而能够确定出所述用户信息表，通过所述登录识别码与个人信息的映射关系，能够从所述用户信息表中准确确定出所述个人信息，由于无需从所有账户类型的信息表中筛选出所述个人信息，因此，能够提高所述个人信息的获 取效率。
参见图2，图2是本申请对个人信息进行审核处理的一实施例的流程图。在本申请的至少一个实施例中，所述电子设备对所述个人信息进行审核处理包括：
S110，获取配置名单，所述配置名单中存储多个用户与信用等级的映射关系。
S111，遍历所述配置名单中的名单用户。
所述名单用户存储在所述配置名单中。
S112，将遍历到的名单用户与所述个人信息进行匹配，并将与所述个人信息匹配成功的所述遍历到的名单用户确定为目标用户。
S113，确定所述目标用户在所述配置名单中的信用等级。
S114，若所述信用等级大于或者等于配置等级，确定所述个人信息通过审核。
其中，所述配置等级可以根据业务安全等级设定，本申请对所述配置等级的取值不作限制。
通过上述实施方式，能够快速确定出所述触发用户在所述配置名单中的信用等级，进而根据所述信用等级能够快速确定出所述个人信息是否通过审核。
S12，若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量。
在本申请的至少一个实施例中，所述决策业务可以包括房屋抵押贷款业务等。
相对应地，所述业务变量可以包括共借人信息、抵押人信息、企业信息等。
在本申请的至少一个实施例中，若所述个人信息未通过审核，根据所述风险决策请求生成提示信息，并将所述提示信息发送至所述触发用户的终端设备。
通过上述实施方式，能够在所述个人信息未通过审核时，及时将审核结果反馈至所述触发用户。
在本申请的至少一个实施例中，所述电子设备根据所述风险决策请求确定决策业务包括：
解析所述风险决策请求的报文，得到所述报文携带的数据信息；
从所述数据信息中获取用于指示业务的信息作为业务编号；
确定与所述业务编号对应的业务作为所述决策业务。
其中，所述业务编号能够唯一标识业务。
通过上述实施方式，能够准确从所述数据信息中获取到所述业务编号，进而根据所述业务编号与业务的映射关系，能够准确确定出所述决策业务。
在本申请的至少一个实施例中，所述电子设备获取所述决策业务的业务变量包括：
确定所述决策业务所属的业务类型；
根据所述业务类型确定决策规则；
提取所述决策规则中的变量，得到所述业务变量。
例如，所述业务类型可以是贷款类型。
所述业务变量是指所述决策规则中的可变信息。
通过上述实施方式，能够利用所述决策业务所属的业务类型快速确定出所述业务变量，由于无需对所述决策业务的业务属性进行分析，因此，能够提高所述业务变量的确定效率。
S13，若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级。
在本申请的至少一个实施例中，所述决策优先级是指所述多个业务变量在所述决策规则中的分析顺序。例如，所述决策优先级最高的业务变量在所述决策规则中的分析顺序最前。
参见图3，图3是本申请确定多个业务变量的决策优先级的一实施例的流程图。在本申请的至少一个实施例中，所述电子设备确定多个所述业务变量在所述决策业务中的决策优先级包括：
S130，确定所述个人信息所属的信息变量。
所述信息变量是指所述个人信息对应的变量。
S131，计算每个业务变量与所述信息变量的关联强度。
具体地，所述电子设备将每个业务变量转换为业务向量，并将所述信息变量转换为信息向量，计算每个业务向量与所述信息向量的相似度，并将计算得到的所述相似度确定为所述关联强度。
S132，根据所述关联强度确定所述多个业务变量的所述决策优先级。
例如：经计算，得到业务变量A与所述信息变量的关联强度为0.5，业务变量B与所述信息变量的关联强度为0.7，业务变量C与所述信息变量的关联强度为0.4，业务变量D与所述信息变量的关联强度为0.9，因此，所述决策优先级从高到低的顺序为：所述业务变量D、所述业务变量B、所述业务变量A及所述业务变量C。
通过每个业务变量与所述信息变量的关联强度，能够快速确定出所述决策优先级。
S14，获取所述多个业务变量对应的关联信息进行决策分析，包括：根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；对所述关联信息进行决策分析。
在本申请的至少一个实施例中，所述电子设备对所述关联信息进行决策分析包括：
从所述决策规则中提取与所述目标变量对应的目标规则；
利用所述目标规则对所述关联信息进行分析；
若所述关联信息满足所述目标规则，确定所述关联信息通过决策；或者
若所述关联信息不满足所述目标规则，确定所述关联信息未通过决策。
例如：所述目标变量为抵押人的风险，从所述决策规则中提取到的所述目标规则为：抵押人的信用等级大于I5级，若关联信息为抵押人的信用等级为I4级，确定所述关联信息未通过决策。
通过上述实施方式，由于无需将所述关联信息与所述决策规则中的所有规则进行分析，因此，能够提高所述关联信息的分析效率。
S15，若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
需要强调的是，为进一步保证上述决策结果的私密和安全性，上述决策结果还可以存储于一区块链的节点中。
在本申请的至少一个实施例中，所述预设条件包括：所述关联信息未通过决策，或者所述多个业务变量均完成决策分析。
所述决策结果包括：所述风险决策请求通过审核，以及，所述风险决策请求未通过审核。
相应地，若所述关联信息未通过决策，确定所述风险决策请求未通过审核，或者，若所述多个业务变量均完成决策分析，且所述多个业务变量对应的关联信息均通过决策，确定所述风险决策请求通过审核。
在本申请的至少一个实施例中，所述方法还包括：
若所述预设条件为所述关联信息未通过决策，确定所述风险决策请求未通过审核；或者
若所述预设条件为所述多个业务变量均完成决策分析，且所述决策优先级最低的业务变量对应的关联信息未通过决策，确定所述风险决策请求未通过审核；或者
若所述预设条件为所述多个业务变量均完成决策分析，且所述多个业务变量对应的关联信息均通过决策，确定所述风险决策请求通过审核。
通过上述实施方式，能够确定出所述风险决策请求的审核结果。
由以上技术方案可以看出，本申请能够接收风险决策请求，并确定所述风险决策请求的触发用户，获取所述触发用户的个人信息，并对所述个人信息进行审核处理，通过对所述触发用户的个人信息进行审核处理，能够避免处理黑名单用户的相关业务，若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量，通过所述决策业务，能够获取到与所述决策业务有关的所有业务变量，避免所述业务变量的遗漏，若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级，获取所述多个业务变量对应的关联信息进行决策分析，包括：根据所述决策优先级从高到低的顺序，确 定当前处于最高优先级的业务变量为目标变量，获取同时与所述触发用户及所述目标变量对应的信息作为关联信息，对所述关联信息进行决策分析，根据所述决策优先级的高低分段获取所述多个业务变量对应的关联信息，并对分段获取到的关联信息进行分析，能够快速确定出所述关联信息的分析结果，若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果，能够在关联信息未通过决策时，避免对非必要的信息进行获取，节省了非必要信息的获取时间。本申请采用分段式方式获取所述触发用户的关联信息，进而对分段获取到的关联信息进行决策分析，由于分段获取到的关联信息的信息量较少，因此相对于分析整体用户信息而言，提高了每个业务变量对应的关联信息的分析效率，此外，在关联信息未通过决策时，停止获取业务变量对应的关联信息，因此，不仅能够节省收集信息所花费的时间，还能减少对非必要信息进行分析，提高了分析效率。所述多个业务变量是宏观经济研究分析的重要指标。
如图4所示，是本申请数据处理装置的较佳实施例的功能模块图。所述数据处理装置11包括确定单元110、审核单元111、获取单元112、分析单元113及输出单元114。本申请所称的模块/单元是指一种能够被处理器13所获取，并且能够完成固定功能的一系列计算机可读指令段，其存储在存储器12中。在本实施例中，关于各模块/单元的功能将在后续的实施例中详述。
确定单元110接收风险决策请求，并确定所述风险决策请求的触发用户。
在本申请的至少一个实施例中，所述风险决策请求可以由任意用户触发生成。所述风险决策请求携带的信息包括，但不限于：发送地址、业务编号等。
所述触发用户是指触发所述风险决策请求生成的用户。
在本申请的至少一个实施例中，所述确定单元110确定所述风险决策请求的触发用户包括：
解析所述风险决策请求的报文头，得到所述报文头携带的地址信息；
从配置库中获取预设标签，所述预设标签用于指示发送请求的地址；
从所述地址信息中获取与所述预设标签对应的信息作为发送地址；
确定与所述发送地址对应的终端为发送终端；
获取所述风险决策请求的接收时间，并根据所述接收时间从所述发送终端上获取请求日志；
提取所述请求日志上的登录识别码，并根据所述登录识别码确定所述触发用户。
其中，所述配置库中存储多个预先定义好的标签，所述标签还包括用于指示接收请求的地址。
所述登录识别码可以是用户登录账号，所述用户登录账号用于唯一标识用户。
通过上述实施方式，由于无需解析所述风险决策请求的报文，因此能够提高所述发送地址的获取效率，通过所述发送终端及接收到所述风险决策请求的接收时间，能够从所述发送终端上获取到与所述风险决策请求相关联的登录识别码，进而根据所述登录识别码能够准确确定出所述触发用户。
审核单元111获取所述触发用户的个人信息，并对所述个人信息进行审核处理。
在本申请的至少一个实施例中，所述个人信息可以包括：用户姓名、用户身份证、用户手机号码等。
在本申请的至少一个实施例中，所述审核单元111获取所述触发用户的个人信息包括：
确定所述登录识别码的账号类型；
确定与所述账号类型对应的用户信息表，所述用户信息表存储所述账号类型中多个用户的信息；
从所述用户信息表中获取与所述登录识别码对应的信息作为所述个人信息。
其中，所述账号类型是指所述登录识别码所注册的应用程序，例如，所述账号类型可以 是QQ等。
通过所述登录识别码确定出所述账号类型，进而能够确定出所述用户信息表，通过所述登录识别码与个人信息的映射关系，能够从所述用户信息表中准确确定出所述个人信息，由于无需从所有账户类型的信息表中筛选出所述个人信息，因此，能够提高所述个人信息的获取效率。
在本申请的至少一个实施例中，所述审核单元111对所述个人信息进行审核处理包括：
获取配置名单，所述配置名单中存储多个用户与信用等级的映射关系。
遍历所述配置名单中的名单用户。
所述名单用户存储在所述配置名单中。
将遍历到的名单用户与所述个人信息进行匹配，并将与所述个人信息匹配成功的所述遍历到的名单用户确定为目标用户。
确定所述目标用户在所述配置名单中的信用等级。
若所述信用等级大于或者等于配置等级，确定所述个人信息通过审核。
其中，所述配置等级可以根据业务安全等级设定，本申请对所述配置等级的取值不作限制。
通过上述实施方式，能够快速确定出所述触发用户在所述配置名单中的信用等级，进而根据所述信用等级能够快速确定出所述个人信息是否通过审核。
若所述个人信息通过审核，获取单元112根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量。
在本申请的至少一个实施例中，所述决策业务可以包括房屋抵押贷款业务等。
相对应地，所述业务变量可以包括共借人信息、抵押人信息、企业信息等。
在本申请的至少一个实施例中，若所述个人信息未通过审核，根据所述风险决策请求生成提示信息，并将所述提示信息发送至所述触发用户的终端设备。
通过上述实施方式，能够在所述个人信息未通过审核时，及时将审核结果反馈至所述触发用户。
在本申请的至少一个实施例中，所述获取单元112根据所述风险决策请求确定决策业务包括：
解析所述风险决策请求的报文，得到所述报文携带的数据信息；
从所述数据信息中获取用于指示业务的信息作为业务编号；
确定与所述业务编号对应的业务作为所述决策业务。
其中，所述业务编号能够唯一标识业务。
通过上述实施方式，能够准确从所述数据信息中获取到所述业务编号，进而根据所述业务编号与业务的映射关系，能够准确确定出所述决策业务。
在本申请的至少一个实施例中，所述获取单元112获取所述决策业务的业务变量包括：
确定所述决策业务所属的业务类型；
根据所述业务类型确定决策规则；
提取所述决策规则中的变量，得到所述业务变量。
例如，所述业务类型可以是贷款类型。
所述业务变量是指所述决策规则中的可变信息。
通过上述实施方式，能够利用所述决策业务所属的业务类型快速确定出所述业务变量，由于无需对所述决策业务的业务属性进行分析，因此，能够提高所述业务变量的确定效率。
若所述业务变量有多个，所述确定单元110确定多个所述业务变量在所述决策业务中的决策优先级。
在本申请的至少一个实施例中，所述决策优先级是指所述多个业务变量在所述决策规则中的分析顺序。例如，所述决策优先级最高的业务变量在所述决策规则中的分析顺序最前。
在本申请的至少一个实施例中，所述确定单元110确定多个所述业务变量在所述决策业 务中的决策优先级包括：
确定所述个人信息所属的信息变量。
所述信息变量是指所述个人信息对应的变量。
计算每个业务变量与所述信息变量的关联强度。
具体地，所述确定单元110将每个业务变量转换为业务向量，并将所述信息变量转换为信息向量，计算每个业务向量与所述信息向量的相似度，并将计算得到的所述相似度确定为所述关联强度。
根据所述关联强度确定所述多个业务变量的所述决策优先级。
例如：经计算，得到业务变量A与所述信息变量的关联强度为0.5，业务变量B与所述信息变量的关联强度为0.7，业务变量C与所述信息变量的关联强度为0.4，业务变量D与所述信息变量的关联强度为0.9，因此，所述决策优先级从高到低的顺序为：所述业务变量D、所述业务变量B、所述业务变量A及所述业务变量C。
通过每个业务变量与所述信息变量的关联强度，能够快速确定出所述决策优先级。
分析单元113获取所述多个业务变量对应的关联信息进行决策分析，包括：根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；对所述关联信息进行决策分析。
在本申请的至少一个实施例中，所述分析单元113对所述关联信息进行决策分析包括：
从所述决策规则中提取与所述目标变量对应的目标规则；
利用所述目标规则对所述关联信息进行分析；
若所述关联信息满足所述目标规则，确定所述关联信息通过决策；或者
若所述关联信息不满足所述目标规则，确定所述关联信息未通过决策。
例如：所述目标变量为抵押人的风险，从所述决策规则中提取到的所述目标规则为：抵押人的信用等级大于I5级，若关联信息为抵押人的信用等级为I4级，确定所述关联信息未通过决策。
通过上述实施方式，由于无需将所述关联信息与所述决策规则中的所有规则进行分析，因此，能够提高所述关联信息的分析效率。
若所述关联信息通过决策，输出单元114重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
在本申请的至少一个实施例中，所述预设条件包括：所述关联信息未通过决策，或者所述多个业务变量均完成决策分析。
所述决策结果包括：所述风险决策请求通过审核，以及，所述风险决策请求未通过审核。
相应地，若所述关联信息未通过决策，确定所述风险决策请求未通过审核，或者，若所述多个业务变量均完成决策分析，且所述多个业务变量对应的关联信息均通过决策，确定所述风险决策请求通过审核。
在本申请的至少一个实施例中，若所述预设条件为所述关联信息未通过决策，所述确定单元110确定所述风险决策请求未通过审核；或者
若所述预设条件为所述多个业务变量均完成决策分析，且所述决策优先级最低的业务变量对应的关联信息未通过决策，所述确定单元110确定所述风险决策请求未通过审核；或者
若所述预设条件为所述多个业务变量均完成决策分析，且所述多个业务变量对应的关联信息均通过决策，所述确定单元110确定所述风险决策请求通过审核。
通过上述实施方式，能够确定出所述风险决策请求的审核结果。
由以上技术方案可以看出，本申请能够接收风险决策请求，并确定所述风险决策请求的触发用户，获取所述触发用户的个人信息，并对所述个人信息进行审核处理，通过对所述触发用户的个人信息进行审核处理，能够避免处理黑名单用户的相关业务，若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量，通过所述决策业务，能够获取到与所述决策业务有关的所有业务变量，避免所述业务变量的遗漏，若 所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级，获取所述多个业务变量对应的关联信息进行决策分析，包括：根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量，获取同时与所述触发用户及所述目标变量对应的信息作为关联信息，对所述关联信息进行决策分析，根据所述决策优先级的高低分段获取所述多个业务变量对应的关联信息，并对分段获取到的关联信息进行分析，能够快速确定出所述关联信息的分析结果，若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果，能够在关联信息未通过决策时，避免对非必要的信息进行获取，节省了非必要信息的获取时间。本申请采用分段式方式获取所述触发用户的关联信息，进而对分段获取到的关联信息进行决策分析，由于分段获取到的关联信息的信息量较少，因此相对于分析整体用户信息而言，提高了每个业务变量对应的关联信息的分析效率，此外，在关联信息未通过决策时，停止获取业务变量对应的关联信息，因此，不仅能够节省收集信息所花费的时间，还能减少对非必要信息进行分析，提高了分析效率。所述多个业务变量是宏观经济研究分析的重要指标。
如图5所示，是本申请实现数据处理方法的较佳实施例的电子设备的结构示意图。
在本申请的一个实施例中，所述电子设备1包括，但不限于，存储器12、处理器13，以及存储在所述存储器12中并可在所述处理器13上运行的计算机可读指令，例如数据处理程序。
本领域技术人员可以理解，所述示意图仅仅是电子设备1的示例，并不构成对电子设备1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，例如所述电子设备1还可以包括输入输出设备、网络接入设备、总线等。
所述处理器13可以是中央处理单元(Central Processing Unit，CPU)，还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现场可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等，所述处理器13是所述电子设备1的运算核心和控制中心，利用各种接口和线路连接整个电子设备1的各个部分，及执行所述电子设备1的操作系统以及安装的各类应用程序、程序代码等。
示例性的，所述计算机可读指令可以被分割成一个或多个模块/单元，所述一个或者多个模块/单元被存储在所述存储器12中，并由所述处理器13执行，以完成本申请。所述一个或多个模块/单元可以是能够完成特定功能的一系列计算机可读指令段，该计算机可读指令段用于描述所述计算机可读指令在所述电子设备1中的执行过程。例如，所述计算机可读指令可以被分割成确定单元110、审核单元111、获取单元112、分析单元113及输出单元114。
所述存储器12可用于存储所述计算机可读指令和/或模块，所述处理器13通过运行或执行存储在所述存储器12内的计算机可读指令和/或模块，以及调用存储在存储器12内的数据，实现所述电子设备1的各种功能。所述存储器12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应用程序(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电子设备的使用所创建的数据等。存储器12可以包括非易失性和易失性存储器，例如：硬盘、内存、插接式硬盘，智能存储卡(Smart Media Card，SMC)，安全数字(Secure Digital，SD)卡，闪存卡(Flash Card)、至少一个磁盘存储器件、闪存器件、或其他存储器件。
所述存储器12可以是电子设备1的外部存储器和/或内部存储器。进一步地，所述存储器12可以是具有实物形式的存储器，如内存条、TF卡(Trans-flash Card)等等。
所述电子设备1集成的模块/单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中，所述计算机可读存储介质可以是非易失性的存储介质，也可以是易失性的存储介质。基于这样的理解，本申请实现上述实施例方 法中的全部或部分流程，也可以通过计算机可读指令来指令相关的硬件来完成，所述的计算机可读指令可存储于一计算机可读存储介质中，该计算机可读指令在被处理器执行时，可实现上述各个方法实施例的步骤。
其中，所述计算机可读指令包括计算机可读指令代码，所述计算机可读指令代码可以为源代码形式、对象代码形式、可执行文件或某些中间形式等。所述计算机可读介质可以包括：能够携带所述计算机可读指令代码的任何实体或装置、记录介质、U盘、移动硬盘、磁碟、光盘、计算机存储器、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)。
本申请所指区块链是分布式数据存储、点对点传输、共识机制、加密算法等计算机技术的新型应用模式。区块链(Blockchain)，本质上是一个去中心化的数据库，是一串使用密码学方法相关联产生的数据块，每一个数据块中包含了一批次网络交易的信息，用于验证其信息的有效性(防伪)和生成下一个区块。区块链可以包括区块链底层平台、平台产品服务层以及应用服务层等。
结合图1，所述电子设备1中的所述存储器12存储计算机可读指令实现一种数据处理方法，所述处理器13可执行所述计算机可读指令从而实现：
接收风险决策请求，并确定所述风险决策请求的触发用户；
获取所述触发用户的个人信息，并对所述个人信息进行审核处理；
若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量；
若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级；
获取所述多个业务变量对应的关联信息进行决策分析，包括：
根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；
获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；
对所述关联信息进行决策分析；
若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
具体地，所述处理器13对上述计算机可读指令的具体实现方法可参考图1对应实施例中相关步骤的描述，在此不赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统，装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述模块的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式。
所述计算机可读存储介质上存储有计算机可读指令，其中，所述计算机可读指令被处理器13执行时用以实现以下步骤：
接收风险决策请求，并确定所述风险决策请求的触发用户；
获取所述触发用户的个人信息，并对所述个人信息进行审核处理；
若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量；
若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级；
获取所述多个业务变量对应的关联信息进行决策分析，包括：
根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；
获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；
对所述关联信息进行决策分析；
若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
所述作为分离部件说明的模块可以是或者也可以不是物理上分开的，作为模块显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能模块可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能模块的形式实现。
因此，无论从哪一点来看，均应将实施例看作是示范性的，而且是非限制性的，本申请的范围由所附权利要求而不是上述说明限定，因此旨在将落在权利要求的等同要件的含义和范围内的所有变化涵括在本申请内。不应将权利要求中的任何附关联图标记视为限制所涉及的权利要求。
此外，显然“包括”一词不排除其他单元或步骤，单数不排除复数。所述的多个单元或装置也可以由一个单元或装置通过软件或者硬件来实现。第一、第二等词语用来表示名称，而并不表示任何特定的顺序。
最后应说明的是，以上实施例仅用以说明本申请的技术方案而非限制，尽管参照较佳实施例对本申请进行了详细说明，本领域的普通技术人员应当理解，可以对本申请的技术方案进行修改或等同替换，而不脱离本申请技术方案的精神和范围。

Claims (20)

  1. 一种数据处理方法，其中，所述数据处理方法包括：
    接收风险决策请求，并确定所述风险决策请求的触发用户；
    获取所述触发用户的个人信息，并对所述个人信息进行审核处理；
    若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量；
    若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级；
    获取所述多个业务变量对应的关联信息进行决策分析，包括：
    根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；
    获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；
    对所述关联信息进行决策分析；
    若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
  2. 根据权利要求1所述的数据处理方法，其中，所述确定所述风险决策请求的触发用户包括：
    解析所述风险决策请求的报文头，得到所述报文头携带的地址信息；
    从配置库中获取预设标签，所述预设标签用于指示发送请求的地址；
    从所述地址信息中获取与所述预设标签对应的信息作为发送地址；
    确定与所述发送地址对应的终端为发送终端；
    获取所述风险决策请求的接收时间，并根据所述接收时间从所述发送终端上获取请求日志；
    提取所述请求日志上的登录识别码，并根据所述登录识别码确定所述触发用户。
  3. 根据权利要求1所述的数据处理方法，其中，所述对所述个人信息进行审核处理包括：
    获取配置名单，所述配置名单中存储多个用户与信用等级的映射关系；
    遍历所述配置名单中的名单用户；
    将遍历到的名单用户与所述个人信息进行匹配，并将与所述个人信息匹配成功的所述遍历到的名单用户确定为目标用户；
    确定所述目标用户在所述配置名单中的信用等级；
    若所述信用等级大于或者等于配置等级，确定所述个人信息通过审核。
  4. 根据权利要求1所述的数据处理方法，其中，所述获取所述决策业务的业务变量包括：
    确定所述决策业务所属的业务类型；
    根据所述业务类型确定决策规则；
    提取所述决策规则中的变量，得到所述业务变量。
  5. 根据权利要求4所述的数据处理方法，其中，所述对所述关联信息进行决策分析包括：
    从所述决策规则中提取与所述目标变量对应的目标规则；
    利用所述目标规则对所述关联信息进行分析；
    若所述关联信息满足所述目标规则，确定所述关联信息通过决策；或者
    若所述关联信息不满足所述目标规则，确定所述关联信息未通过决策。
  6. 根据权利要求1所述的数据处理方法，其中，所述确定多个所述业务变量在所述决策业务中的决策优先级包括：
    确定所述个人信息所属的信息变量；
    计算每个业务变量与所述信息变量的关联强度；
    根据所述关联强度确定所述多个业务变量的所述决策优先级。
  7. 根据权利要求1所述的数据处理方法，其中，所述方法还包括：
    若所述预设条件为所述关联信息未通过决策，确定所述风险决策请求未通过审核；或者
    若所述预设条件为所述多个业务变量均完成决策分析，且所述决策优先级最低的业务变量对应的关联信息未通过决策，确定所述风险决策请求未通过审核；或者
    若所述预设条件为所述多个业务变量均完成决策分析，且所述多个业务变量对应的关联信息均通过决策，确定所述风险决策请求通过审核。
  8. 一种数据处理装置，其中，所述数据处理装置包括：
    确定单元，用于接收风险决策请求，并确定所述风险决策请求的触发用户；
    审核单元，用于获取所述触发用户的个人信息，并对所述个人信息进行审核处理；
    获取单元，用于若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量；
    所述确定单元，还用于若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级；
    分析单元，用于获取所述多个业务变量对应的关联信息进行决策分析，包括：
    根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；
    获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；
    对所述关联信息进行决策分析；
    输出单元，用于若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
  9. 一种电子设备，其中，所述电子设备包括处理器和存储器，所述处理器用于执行存储器中存储的至少一个计算机可读指令以实现以下步骤：
    接收风险决策请求，并确定所述风险决策请求的触发用户；
    获取所述触发用户的个人信息，并对所述个人信息进行审核处理；
    若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量；
    若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级；
    获取所述多个业务变量对应的关联信息进行决策分析，包括：
    根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；
    获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；
    对所述关联信息进行决策分析；
    若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
  10. 根据权利要求9所述的电子设备，其中，在所述确定所述风险决策请求的触发用户时，所述处理器执行所述至少一个计算机可读指令以实现以下步骤：
    解析所述风险决策请求的报文头，得到所述报文头携带的地址信息；
    从配置库中获取预设标签，所述预设标签用于指示发送请求的地址；
    从所述地址信息中获取与所述预设标签对应的信息作为发送地址；
    确定与所述发送地址对应的终端为发送终端；
    获取所述风险决策请求的接收时间，并根据所述接收时间从所述发送终端上获取请求日志；
    提取所述请求日志上的登录识别码，并根据所述登录识别码确定所述触发用户。
  11. 根据权利要求9所述的电子设备，其中，在所述对所述个人信息进行审核处理时，所述处理器执行所述至少一个计算机可读指令以实现以下步骤：
    获取配置名单，所述配置名单中存储多个用户与信用等级的映射关系；
    遍历所述配置名单中的名单用户；
    将遍历到的名单用户与所述个人信息进行匹配，并将与所述个人信息匹配成功的所述遍历到的名单用户确定为目标用户；
    确定所述目标用户在所述配置名单中的信用等级；
    若所述信用等级大于或者等于配置等级，确定所述个人信息通过审核。
  12. 根据权利要求9所述的电子设备，其中，在所述获取所述决策业务的业务变量时，所述处理器执行所述至少一个计算机可读指令以实现以下步骤：
    确定所述决策业务所属的业务类型；
    根据所述业务类型确定决策规则；
    提取所述决策规则中的变量，得到所述业务变量。
  13. 根据权利要求12所述的电子设备，其中，在所述对所述关联信息进行决策分析时，所述处理器执行所述至少一个计算机可读指令以实现以下步骤：
    从所述决策规则中提取与所述目标变量对应的目标规则；
    利用所述目标规则对所述关联信息进行分析；
    若所述关联信息满足所述目标规则，确定所述关联信息通过决策；或者
    若所述关联信息不满足所述目标规则，确定所述关联信息未通过决策。
  14. 根据权利要求9所述的电子设备，其中，在所述确定多个所述业务变量在所述决策业务中的决策优先级时，所述处理器执行所述至少一个计算机可读指令以实现以下步骤：
    确定所述个人信息所属的信息变量；
    计算每个业务变量与所述信息变量的关联强度；
    根据所述关联强度确定所述多个业务变量的所述决策优先级。
  15. 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至少一个计算机可读指令，所述至少一个计算机可读指令被处理器执行时实现以下步骤：
    接收风险决策请求，并确定所述风险决策请求的触发用户；
    获取所述触发用户的个人信息，并对所述个人信息进行审核处理；
    若所述个人信息通过审核，根据所述风险决策请求确定决策业务，并获取所述决策业务的业务变量；
    若所述业务变量有多个，确定多个所述业务变量在所述决策业务中的决策优先级；
    获取所述多个业务变量对应的关联信息进行决策分析，包括：
    根据所述决策优先级从高到低的顺序，确定当前处于最高优先级的业务变量为目标变量；
    获取同时与所述触发用户及所述目标变量对应的信息作为关联信息；
    对所述关联信息进行决策分析；
    若所述关联信息通过决策，重复获取所述多个业务变量对应的关联信息进行决策分析，直至满足预设条件，输出决策结果。
  16. 根据权利要求15所述的存储介质，其中，在所述确定所述风险决策请求的触发用户时，所述至少一个计算机可读指令被处理器执行以实现以下步骤：
    解析所述风险决策请求的报文头，得到所述报文头携带的地址信息；
    从配置库中获取预设标签，所述预设标签用于指示发送请求的地址；
    从所述地址信息中获取与所述预设标签对应的信息作为发送地址；
    确定与所述发送地址对应的终端为发送终端；
    获取所述风险决策请求的接收时间，并根据所述接收时间从所述发送终端上获取请求日志；
    提取所述请求日志上的登录识别码，并根据所述登录识别码确定所述触发用户。
  17. 根据权利要求15所述的存储介质，其中，在所述对所述个人信息进行审核处理时，所述至少一个计算机可读指令被处理器执行以实现以下步骤：
    获取配置名单，所述配置名单中存储多个用户与信用等级的映射关系；
    遍历所述配置名单中的名单用户；
    将遍历到的名单用户与所述个人信息进行匹配，并将与所述个人信息匹配成功的所述遍历到的名单用户确定为目标用户；
    确定所述目标用户在所述配置名单中的信用等级；
    若所述信用等级大于或者等于配置等级，确定所述个人信息通过审核。
  18. 根据权利要求15所述的存储介质，其中，在所述获取所述决策业务的业务变量时，所述至少一个计算机可读指令被处理器执行以实现以下步骤：
    确定所述决策业务所属的业务类型；
    根据所述业务类型确定决策规则；
    提取所述决策规则中的变量，得到所述业务变量。
  19. 根据权利要求18所述的存储介质，其中，在所述对所述关联信息进行决策分析时，所述至少一个计算机可读指令被处理器执行时以实现以下步骤：
    从所述决策规则中提取与所述目标变量对应的目标规则；
    利用所述目标规则对所述关联信息进行分析；
    若所述关联信息满足所述目标规则，确定所述关联信息通过决策；或者
    若所述关联信息不满足所述目标规则，确定所述关联信息未通过决策。
  20. 根据权利要求15所述的存储介质，其中，在所述确定多个所述业务变量在所述决策业务中的决策优先级时，所述至少一个计算机可读指令被处理器执行以实现以下步骤：
    确定所述个人信息所属的信息变量；
    计算每个业务变量与所述信息变量的关联强度；
    根据所述关联强度确定所述多个业务变量的所述决策优先级。
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