CN112669138A - Data processing method and related equipment - Google Patents
Data processing method and related equipment Download PDFInfo
- Publication number
- CN112669138A CN112669138A CN202011540112.8A CN202011540112A CN112669138A CN 112669138 A CN112669138 A CN 112669138A CN 202011540112 A CN202011540112 A CN 202011540112A CN 112669138 A CN112669138 A CN 112669138A
- Authority
- CN
- China
- Prior art keywords
- decision
- service
- determining
- information
- variables
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Finance (AREA)
- Databases & Information Systems (AREA)
- Accounting & Taxation (AREA)
- General Engineering & Computer Science (AREA)
- Quality & Reliability (AREA)
- Computer Hardware Design (AREA)
- Technology Law (AREA)
- Tourism & Hospitality (AREA)
- Health & Medical Sciences (AREA)
- Bioethics (AREA)
- General Health & Medical Sciences (AREA)
- Operations Research (AREA)
- Computer Security & Cryptography (AREA)
- Software Systems (AREA)
- Game Theory and Decision Science (AREA)
- Computing Systems (AREA)
- Educational Administration (AREA)
- Data Mining & Analysis (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to service security and provides a data processing method and related equipment. The method can determine a trigger user, acquire personal information, determine a decision service and acquire service variables if the personal information passes the audit, determine the decision priority of a plurality of service variables if the service variables are multiple, and acquire associated information corresponding to the plurality of service variables for decision analysis, and comprises the following steps: determining the business variable at the highest priority as a target variable according to the decision priority, acquiring information corresponding to the trigger user and the target variable simultaneously as associated information, performing decision analysis on the associated information, if the associated information passes the decision, repeatedly acquiring the associated information corresponding to a plurality of business variables for decision analysis until a preset condition is met, and outputting a decision result. The invention can not only avoid acquiring unnecessary information, but also improve the analysis efficiency. In addition, the invention also relates to a block chain technology, and the decision result can be stored in the block chain.
Description
Technical Field
The present invention relates to the field of service security technologies, and in particular, to a data processing method and related devices.
Background
In the field of internet finance, risk control refers to the risk manager taking various measures to eliminate or reduce the possibility of risk events. Risk decision-making refers to the process of selecting two or more action schemes under the influence of various uncertain factors.
In the traditional risk decision process, all relevant information of a user is analyzed and decided, and the mode is to analyze and check all relevant information of the user at one time, so that the decision result determining efficiency is low, and in addition, all relevant information of the user is collected in the early period, so that the data collecting time is too long, and the risk decision of the service is not facilitated.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a data processing method and related apparatus, which can not only avoid unnecessary information acquisition, but also improve analysis efficiency.
In one aspect, the present invention provides a data processing method, where the data processing method includes:
receiving a risk decision request and determining a triggering user of the risk decision request;
acquiring the personal information of the trigger user, and auditing the personal information;
if the personal information passes the verification, determining a decision service according to the risk decision request, and acquiring a service variable of the decision service;
if the number of the service variables is multiple, determining the decision priority of the service variables in the decision service;
obtaining the relevant information corresponding to the plurality of business variables for decision analysis, wherein the decision analysis comprises the following steps:
determining the service variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low;
acquiring information simultaneously corresponding to the trigger user and the target variable as associated information; performing decision analysis on the associated information;
and if the associated information passes the decision, repeatedly acquiring the associated information corresponding to the plurality of business variables for decision analysis until a preset condition is met, and outputting a decision result.
According to a preferred embodiment of the present invention, the determining the triggering user of the risk decision request comprises:
analyzing a message header of the risk decision request to obtain address information carried by the message header;
acquiring a preset label from a configuration library, wherein the preset label is used for indicating an address of a sending request;
acquiring information corresponding to the preset label from the address information as a sending address;
determining a terminal corresponding to the sending address as a sending terminal;
acquiring the receiving time of the risk decision request, and acquiring a request log from the sending terminal according to the receiving time;
and extracting a login identification code on the request log, and determining the trigger user according to the login identification code.
According to a preferred embodiment of the present invention, the auditing the personal information includes:
acquiring a configuration list, wherein the configuration list stores the mapping relation between a plurality of users and credit levels;
traversing the list users in the configuration list;
matching the traversed list users with the personal information, and determining the traversed list users successfully matched with the personal information as target users;
determining the credit level of the target user in the configuration list;
and if the credit grade is greater than or equal to the configuration grade, determining that the personal information passes the audit.
According to the preferred embodiment of the present invention, the acquiring the service variable of the decision service includes:
determining the service type of the decision service;
determining a decision rule according to the service type;
and extracting variables in the decision rule to obtain the business variables.
According to a preferred embodiment of the present invention, the performing decision analysis on the associated information includes:
extracting a target rule corresponding to the target variable from the decision rule;
analyzing the association information by using the target rule;
if the associated information meets the target rule, determining that the associated information passes a decision; or
And if the associated information does not meet the target rule, determining that the associated information fails to pass the decision.
According to a preferred embodiment of the present invention, the determining a decision priority of the plurality of service variables in the decision service includes:
determining an information variable to which the personal information belongs;
calculating the correlation strength of each business variable and the information variable;
determining the decision priority of the plurality of business variables according to the association strength.
According to a preferred embodiment of the invention, the method further comprises:
if the preset condition is that the associated information fails to pass the decision, determining that the risk decision request does not pass the audit; or
If the preset condition is that the plurality of business variables all complete decision analysis and the associated information corresponding to the business variable with the lowest decision priority fails to pass the decision, determining that the risk decision request fails to be audited; or
And if the preset condition is that the plurality of business variables all complete decision analysis and the associated information corresponding to the plurality of business variables all pass the decision, determining that the risk decision request passes the audit.
In another aspect, the present invention further provides a data processing apparatus, including:
the system comprises a determining unit, a judging unit and a judging unit, wherein the determining unit is used for receiving a risk decision request and determining a triggering user of the risk decision request;
the auditing unit is used for acquiring the personal information of the trigger user and auditing the personal information;
an obtaining unit, configured to determine a decision service according to the risk decision request if the personal information passes the audit, and obtain a service variable of the decision service;
the determining unit is further configured to determine a decision priority of the plurality of service variables in the decision service if the plurality of service variables are available;
an analysis unit, configured to obtain associated information corresponding to the multiple service variables for decision analysis, including:
determining the service variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low;
acquiring information simultaneously corresponding to the trigger user and the target variable as associated information; performing decision analysis on the associated information;
and the output unit is used for repeatedly acquiring the associated information corresponding to the plurality of business variables for decision analysis if the associated information passes a decision, until a preset condition is met, and outputting a decision result.
In another aspect, the present invention further provides an electronic device, including:
a memory storing computer readable instructions; and
a processor executing computer readable instructions stored in the memory to implement the data processing method.
In another aspect, the present invention also provides a computer-readable storage medium, in which computer-readable instructions are stored, and the computer-readable instructions are executed by a processor in an electronic device to implement the data processing method.
According to the technical scheme, the method can receive a risk decision request, determine a trigger user of the risk decision request, acquire personal information of the trigger user, audit the personal information, avoid processing related services of blacklist users by auditing the personal information of the trigger user, determine a decision service according to the risk decision request and acquire service variables of the decision service if the personal information passes the audit, acquire all service variables related to the decision service through the decision service, avoid omission of the service variables, determine decision priorities of a plurality of service variables in the decision service if the service variables are multiple, and acquire related information corresponding to the service variables for decision analysis, the method comprises the following steps: determining the business variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low, acquiring information simultaneously corresponding to the trigger user and the target variable as associated information, performing decision analysis on the associated information, acquiring the associated information corresponding to the multiple business variables according to high and low segments of the decision priorities, analyzing the associated information acquired by the segments, quickly determining an analysis result of the associated information, if the associated information passes the decision, repeatedly acquiring the associated information corresponding to the multiple business variables for decision analysis until a preset condition is met, outputting the decision result, and avoiding acquiring unnecessary information when the associated information fails the decision, thereby saving the acquisition time of unnecessary information. The method and the device adopt a sectional mode to obtain the associated information of the trigger user, and further carry out decision analysis on the associated information obtained by sections, and the information quantity of the associated information obtained by sections is less, so that the analysis efficiency of the associated information corresponding to each business variable is improved compared with the analysis of the whole user information. The plurality of business variables are important indicators for macro-economic research analysis.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of the data processing method of the present invention.
Fig. 2 is a flowchart of an embodiment of the present invention for auditing personal information.
FIG. 3 is a flow diagram of one embodiment of the present invention for determining decision priority for a plurality of business variables.
FIG. 4 is a functional block diagram of a preferred embodiment of a data processing apparatus according to the present invention.
FIG. 5 is a schematic structural diagram of an electronic device implementing a data processing method according to a preferred embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a flow chart of a data processing method according to a preferred embodiment of the present invention. The order of the steps in the flow chart may be changed and some steps may be omitted according to different needs.
The data processing method is applied to one or more electronic devices, which are devices capable of automatically performing numerical calculation and/or information processing according to computer readable instructions set or stored in advance, and the hardware thereof includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.
The electronic device may be any mobile electronic product capable of performing human-computer interaction with a user, for example, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), a game machine, an intelligent wearable device, and the like.
The electronic device may include a network device and/or a user device. Wherein the network device includes, but is not limited to, a single network electronic device, an electronic device group consisting of a plurality of network electronic devices, or a Cloud Computing (Cloud Computing) based Cloud consisting of a large number of hosts or network electronic devices.
The network in which 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 (VPN), and the like.
S10, receiving the risk decision request and determining the trigger user of the risk decision request.
In at least one embodiment of the invention, the risk decision request may be generated by any user trigger. The information carried by the risk decision request includes, but is not limited to: a transmission address, a service number, etc.
The triggering user refers to a user who triggers the generation of the risk decision request.
In at least one embodiment of the invention, the electronic device determining the triggering user of the risk decision request comprises:
analyzing a message header of the risk decision request to obtain address information carried by the message header;
acquiring a preset label from a configuration library, wherein the preset label is used for indicating an address of a sending request;
acquiring information corresponding to the preset label from the address information as a sending address;
determining a terminal corresponding to the sending address as a sending terminal;
acquiring the receiving time of the risk decision request, and acquiring a request log from the sending terminal according to the receiving time;
and extracting a login identification code on the request log, and determining the trigger user according to the login identification code.
Wherein the configuration library stores a plurality of predefined tags, and the tags further include an address for indicating a request to receive.
The login identification code may be a user login account, and the user login account is used for uniquely identifying the user.
By the implementation mode, the efficiency of acquiring the sending address can be improved because the message of the risk decision request does not need to be analyzed, and the login identification code associated with the risk decision request can be acquired from the sending terminal through the sending terminal and the receiving time of the risk decision request, so that the trigger user can be accurately determined according to the login identification code.
And S11, acquiring the personal information of the trigger user, and auditing the personal information.
In at least one embodiment of the present invention, the personal information may include: user name, user identification card, user mobile phone number, etc.
In at least one embodiment of the present invention, the electronic device acquiring the personal information of the trigger user includes:
determining the account type of the login identification code;
determining a user information table corresponding to the account type, wherein the user information table stores information of a plurality of users in the account type;
and acquiring information corresponding to the login identification code from the user information table as the personal information.
The account type refers to an application program registered by the login identification code, and may be, for example, QQ or the like.
The account type is determined through the login identification code, the user information table can be further determined, the personal information can be accurately determined from the user information table through the mapping relation between the login identification code and the personal information, and the personal information does not need to be screened from the information tables of all account types, so that the acquisition efficiency of the personal information can be improved.
Referring to fig. 2, fig. 2 is a flowchart of an embodiment of the process of auditing personal information according to the present invention. In at least one embodiment of the present invention, the auditing, by the electronic device, of the personal information includes:
s110, obtaining a configuration list, wherein the configuration list stores the mapping relation between a plurality of users and credit levels.
And S111, traversing the list users in the configuration list.
The list users are stored in the configuration list.
S112, matching the traversed list user with the personal information, and determining the traversed list user successfully matched with the personal information as a target user.
S113, determining the credit level of the target user in the configuration list.
And S114, if the credit level is greater than or equal to the configuration level, determining that the personal information passes the audit.
The configuration level can be set according to the service safety level, and the value of the configuration level is not limited by the invention.
Through the implementation mode, the credit level of the trigger user in the configuration list can be quickly determined, and whether the personal information passes the audit can be quickly determined according to the credit level.
And S12, if the personal information passes the audit, determining a decision service according to the risk decision request, and acquiring a service variable of the decision service.
In at least one embodiment of the invention, the decision-making service may include a home mortgage service or the like.
Correspondingly, the business variables may include borrower information, mortgage information, enterprise information, and the like.
In at least one embodiment of the present invention, if the personal information is not approved, a prompt message is generated according to the risk decision request, and the prompt message is sent to the terminal device of the trigger user.
Through the implementation mode, when the personal information is not approved, the auditing result can be fed back to the trigger user in time.
In at least one embodiment of the present invention, the electronic device determining a decision service according to the risk decision request includes:
analyzing the message of the risk decision request to obtain data information carried by the message;
acquiring information for indicating a service from the data information as a service number;
and determining the service corresponding to the service number as the decision service.
The service number can uniquely identify a service.
By the implementation mode, the service number can be accurately acquired from the data information, and the decision service can be accurately determined according to the mapping relation between the service number and the service.
In at least one embodiment of the present invention, the acquiring, by the electronic device, the service variable of the decision service includes:
determining the service type of the decision service;
determining a decision rule according to the service type;
and extracting variables in the decision rule to obtain the business variables.
For example, the business type may be a loan type.
The business variable refers to variable information in the decision rule.
Through the implementation mode, the business variable can be quickly determined by utilizing the business type to which the decision business belongs, and the determination efficiency of the business variable can be improved because the business attribute of the decision business does not need to be analyzed.
And S13, if the business variables are multiple, determining the decision priority of the business variables in the decision business.
In at least one embodiment of the present invention, 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 the most forward in the analysis order in the decision rule.
Referring to fig. 3, fig. 3 is a flow diagram of one embodiment of the present invention for determining decision priority for a plurality of business variables. In at least one embodiment of the present invention, the electronic device determining a decision priority of a plurality of the business variables in the decision business comprises:
s130, determining the information variable to which the personal information belongs.
The information variable refers to a variable corresponding to the personal information.
S131, calculating the correlation strength of each business variable and the information variable.
Specifically, 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 determines the calculated similarity as the association strength.
S132, determining the decision priority of the plurality of business variables according to the association strength.
For example: through calculation, the correlation strength of the business variable a and the information variable is 0.5, the correlation strength of the business variable B and the information variable is 0.7, the correlation strength of the business variable C and the information variable is 0.4, and the correlation strength of the business variable D and the information variable is 0.9, so that the order of the decision priority from high to low is as follows: 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 correlation strength of each business variable and the information variable.
S14, obtaining the relevant information corresponding to the plurality of business variables for decision analysis, including: determining the service variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low; acquiring information simultaneously corresponding to the trigger user and the target variable as associated information; and performing decision analysis on the associated information.
In at least one embodiment of the present invention, the performing, by the electronic device, decision analysis on the associated information includes:
extracting a target rule corresponding to the target variable from the decision rule;
analyzing the association information by using the target rule;
if the associated information meets the target rule, determining that the associated information passes a decision; or
And if the associated information does not meet the target rule, determining that the associated information fails to pass the decision.
For example: the target variable is the risk of the mortgage person, and the target rule extracted from the decision rule is as follows: and if the credit level of the mortgage is higher than the I5 level, determining that the associated information fails to be decided if the credit level of the mortgage is I4 level.
With the above embodiment, since it is not necessary to analyze the association information with all the rules in the decision rule, the efficiency of analyzing the association information can be improved.
And S15, if the associated information passes the decision, repeatedly acquiring the associated information corresponding to the plurality of business variables for decision analysis until a preset condition is met, and outputting a decision result.
It is emphasized that the decision result may also be stored in a node of a block chain in order to further ensure the privacy and security of the decision result.
In at least one embodiment of the present invention, the preset conditions include: and the associated information fails to pass the decision, or the plurality of business variables complete decision analysis.
The decision result comprises: the risk decision request passes the audit, and the risk decision request fails the audit.
Correspondingly, if the associated information fails to pass the decision, it is determined that the risk decision request fails to be audited, or if the plurality of business variables complete decision analysis and the associated information corresponding to the plurality of business variables passes the decision, it is determined that the risk decision request passes the audit.
In at least one embodiment of the invention, the method further comprises:
if the preset condition is that the associated information fails to pass the decision, determining that the risk decision request does not pass the audit; or
If the preset condition is that the plurality of business variables all complete decision analysis and the associated information corresponding to the business variable with the lowest decision priority fails to pass the decision, determining that the risk decision request fails to be audited; or
And if the preset condition is that the plurality of business variables all complete decision analysis and the associated information corresponding to the plurality of business variables all pass the decision, determining that the risk decision request passes the audit.
Through the implementation mode, the auditing result of the risk decision request can be determined.
According to the technical scheme, the method can receive a risk decision request, determine a trigger user of the risk decision request, acquire personal information of the trigger user, audit the personal information, avoid processing related services of blacklist users by auditing the personal information of the trigger user, determine a decision service according to the risk decision request and acquire service variables of the decision service if the personal information passes the audit, acquire all service variables related to the decision service through the decision service, avoid omission of the service variables, determine decision priorities of a plurality of service variables in the decision service if the service variables are multiple, and acquire related information corresponding to the service variables for decision analysis, the method comprises the following steps: determining the business variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low, acquiring information simultaneously corresponding to the trigger user and the target variable as associated information, performing decision analysis on the associated information, acquiring the associated information corresponding to the multiple business variables according to high and low segments of the decision priorities, analyzing the associated information acquired by the segments, quickly determining an analysis result of the associated information, if the associated information passes the decision, repeatedly acquiring the associated information corresponding to the multiple business variables for decision analysis until a preset condition is met, outputting the decision result, and avoiding acquiring unnecessary information when the associated information fails the decision, thereby saving the acquisition time of unnecessary information. The method and the device adopt a sectional mode to obtain the associated information of the trigger user, and further carry out decision analysis on the associated information obtained by sections, and the information quantity of the associated information obtained by sections is less, so that the analysis efficiency of the associated information corresponding to each business variable is improved compared with the analysis of the whole user information. The plurality of business variables are important indicators for macro-economic research analysis.
FIG. 4 is a functional block diagram of a data processing apparatus according to a preferred embodiment of the present invention. The data processing apparatus 11 includes a determination unit 110, an auditing unit 111, an acquisition unit 112, an analysis unit 113, and an output unit 114. The module/unit referred to herein is a series of computer readable instruction segments that can be accessed by the processor 13 and perform a fixed function and that are stored in the memory 12. In the present embodiment, the functions of the modules/units will be described in detail in the following embodiments.
The determining unit 110 receives a risk decision request and determines a triggering user of the risk decision request.
In at least one embodiment of the invention, the risk decision request may be generated by any user trigger. The information carried by the risk decision request includes, but is not limited to: a transmission address, a service number, etc.
The triggering user refers to a user who triggers the generation of the risk decision request.
In at least one embodiment of the present invention, the determining unit 110 determines the triggering user of the risk decision request includes:
analyzing a message header of the risk decision request to obtain address information carried by the message header;
acquiring a preset label from a configuration library, wherein the preset label is used for indicating an address of a sending request;
acquiring information corresponding to the preset label from the address information as a sending address;
determining a terminal corresponding to the sending address as a sending terminal;
acquiring the receiving time of the risk decision request, and acquiring a request log from the sending terminal according to the receiving time;
and extracting a login identification code on the request log, and determining the trigger user according to the login identification code.
Wherein the configuration library stores a plurality of predefined tags, and the tags further include an address for indicating a request to receive.
The login identification code may be a user login account, and the user login account is used for uniquely identifying the user.
By the implementation mode, the efficiency of acquiring the sending address can be improved because the message of the risk decision request does not need to be analyzed, and the login identification code associated with the risk decision request can be acquired from the sending terminal through the sending terminal and the receiving time of the risk decision request, so that the trigger user can be accurately determined according to the login identification code.
The auditing unit 111 acquires the personal information of the trigger user and performs auditing processing on the personal information.
In at least one embodiment of the present invention, the personal information may include: user name, user identification card, user mobile phone number, etc.
In at least one embodiment of the present invention, the acquiring, by the auditing unit 111, the personal information of the trigger user includes:
determining the account type of the login identification code;
determining a user information table corresponding to the account type, wherein the user information table stores information of a plurality of users in the account type;
and acquiring information corresponding to the login identification code from the user information table as the personal information.
The account type refers to an application program registered by the login identification code, and may be, for example, QQ or the like.
The account type is determined through the login identification code, the user information table can be further determined, the personal information can be accurately determined from the user information table through the mapping relation between the login identification code and the personal information, and the personal information does not need to be screened from the information tables of all account types, so that the acquisition efficiency of the personal information can be improved.
In at least one embodiment of the present invention, the auditing unit 111 performs auditing processing on the personal information, including:
and acquiring a configuration list, wherein the configuration list stores the mapping relation between a plurality of users and credit levels.
And traversing the list users in the configuration list.
The list users are stored in the configuration list.
Matching the traversed list users with the personal information, and determining the traversed list users successfully matched with the personal information as target users.
And determining the credit level of the target user in the configuration list.
And if the credit grade is greater than or equal to the configuration grade, determining that the personal information passes the audit.
The configuration level can be set according to the service safety level, and the value of the configuration level is not limited by the invention.
Through the implementation mode, the credit level of the trigger user in the configuration list can be quickly determined, and whether the personal information passes the audit can be quickly determined according to the credit level.
If the personal information passes the verification, the obtaining unit 112 determines a decision-making service according to the risk decision-making request, and obtains a service variable of the decision-making service.
In at least one embodiment of the invention, the decision-making service may include a home mortgage service or the like.
Correspondingly, the business variables may include borrower information, mortgage information, enterprise information, and the like.
In at least one embodiment of the present invention, if the personal information is not approved, a prompt message is generated according to the risk decision request, and the prompt message is sent to the terminal device of the trigger user.
Through the implementation mode, when the personal information is not approved, the auditing result can be fed back to the trigger user in time.
In at least one embodiment of the present invention, the obtaining unit 112 determining a decision service according to the risk decision request includes:
analyzing the message of the risk decision request to obtain data information carried by the message;
acquiring information for indicating a service from the data information as a service number;
and determining the service corresponding to the service number as the decision service.
The service number can uniquely identify a service.
By the implementation mode, the service number can be accurately acquired from the data information, and the decision service can be accurately determined according to the mapping relation between the service number and the service.
In at least one embodiment of the present invention, the obtaining unit 112 obtains the service variable of the decision service, including:
determining the service type of the decision service;
determining a decision rule according to the service type;
and extracting variables in the decision rule to obtain the business variables.
For example, the business type may be a loan type.
The business variable refers to variable information in the decision rule.
Through the implementation mode, the business variable can be quickly determined by utilizing the business type to which the decision business belongs, and the determination efficiency of the business variable can be improved because the business attribute of the decision business does not need to be analyzed.
If there are multiple business variables, the determining unit 110 determines the decision priorities of the multiple business variables in the decision business.
In at least one embodiment of the present invention, 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 the most forward in the analysis order in the decision rule.
In at least one embodiment of the present invention, the determining unit 110 determines the decision priority of the plurality of the service variables in the decision service includes:
and determining the information variable to which the personal information belongs.
The information variable refers to a variable corresponding to the personal information.
And calculating the association strength of each business variable and the information variable.
Specifically, 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 determines the calculated similarity as the association strength.
Determining the decision priority of the plurality of business variables according to the association strength.
For example: through calculation, the correlation strength of the business variable a and the information variable is 0.5, the correlation strength of the business variable B and the information variable is 0.7, the correlation strength of the business variable C and the information variable is 0.4, and the correlation strength of the business variable D and the information variable is 0.9, so that the order of the decision priority from high to low is as follows: 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 correlation strength of each business variable and the information variable.
The analyzing unit 113 obtains the relevant information corresponding to the plurality of business variables for performing decision analysis, and includes: determining the service variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low; acquiring information simultaneously corresponding to the trigger user and the target variable as associated information; and performing decision analysis on the associated information.
In at least one embodiment of the present invention, the analyzing unit 113 performing decision analysis on the association information includes:
extracting a target rule corresponding to the target variable from the decision rule;
analyzing the association information by using the target rule;
if the associated information meets the target rule, determining that the associated information passes a decision; or
And if the associated information does not meet the target rule, determining that the associated information fails to pass the decision.
For example: the target variable is the risk of the mortgage person, and the target rule extracted from the decision rule is as follows: and if the credit level of the mortgage is higher than the I5 level, determining that the associated information fails to be decided if the credit level of the mortgage is I4 level.
With the above embodiment, since it is not necessary to analyze the association information with all the rules in the decision rule, the efficiency of analyzing the association information can be improved.
If the associated information passes the decision, the output unit 114 repeatedly obtains the associated information corresponding to the plurality of business variables to perform decision analysis until a preset condition is met, and outputs a decision result.
In at least one embodiment of the present invention, the preset conditions include: and the associated information fails to pass the decision, or the plurality of business variables complete decision analysis.
The decision result comprises: the risk decision request passes the audit, and the risk decision request fails the audit.
Correspondingly, if the associated information fails to pass the decision, it is determined that the risk decision request fails to be audited, or if the plurality of business variables complete decision analysis and the associated information corresponding to the plurality of business variables passes the decision, it is determined that the risk decision request passes the audit.
In at least one embodiment of the present invention, if the preset condition is that the associated information fails to pass the decision, the determining unit 110 determines that the risk decision request fails to be audited; or
If the preset condition is that the plurality of business variables all complete decision analysis and the associated information corresponding to the business variable with the lowest decision priority fails to pass the decision, the determining unit 110 determines that the risk decision request fails to be audited; or
If the preset condition is that the plurality of business variables all complete decision analysis and the associated information corresponding to the plurality of business variables all pass a decision, the determining unit 110 determines that the risk decision request passes the audit.
Through the implementation mode, the auditing result of the risk decision request can be determined.
According to the technical scheme, the method can receive a risk decision request, determine a trigger user of the risk decision request, acquire personal information of the trigger user, audit the personal information, avoid processing related services of blacklist users by auditing the personal information of the trigger user, determine a decision service according to the risk decision request and acquire service variables of the decision service if the personal information passes the audit, acquire all service variables related to the decision service through the decision service, avoid omission of the service variables, determine decision priorities of a plurality of service variables in the decision service if the service variables are multiple, and acquire related information corresponding to the service variables for decision analysis, the method comprises the following steps: determining the business variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low, acquiring information simultaneously corresponding to the trigger user and the target variable as associated information, performing decision analysis on the associated information, acquiring the associated information corresponding to the multiple business variables according to high and low segments of the decision priorities, analyzing the associated information acquired by the segments, quickly determining an analysis result of the associated information, if the associated information passes the decision, repeatedly acquiring the associated information corresponding to the multiple business variables for decision analysis until a preset condition is met, outputting the decision result, and avoiding acquiring unnecessary information when the associated information fails the decision, thereby saving the acquisition time of unnecessary information. The method and the device adopt a sectional mode to obtain the associated information of the trigger user, and further carry out decision analysis on the associated information obtained by sections, and the information quantity of the associated information obtained by sections is less, so that the analysis efficiency of the associated information corresponding to each business variable is improved compared with the analysis of the whole user information. The plurality of business variables are important indicators for macro-economic research analysis.
Fig. 5 is a schematic structural diagram of an electronic device according to a preferred embodiment of the data processing method of the present invention.
In one embodiment of the present invention, the electronic device 1 includes, but is not limited to, a memory 12, a processor 13, and computer readable instructions, such as a data processing program, stored in the memory 12 and executable on the processor 13.
It will be appreciated by a person skilled in the art that the schematic diagram is only an example of the electronic device 1 and does not constitute a limitation of the electronic device 1, and that it may comprise more or less components than shown, or some components may be combined, or different components, e.g. the electronic device 1 may further comprise an input output device, a network access device, a bus, etc.
The Processor 13 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The processor 13 is an operation core and a control center of the electronic device 1, and is connected to each part of the whole electronic device 1 by various interfaces and lines, and executes an operating system of the electronic device 1 and various installed application programs, program codes, and the like.
Illustratively, the computer readable instructions may be partitioned into one or more modules/units that are stored in the memory 12 and executed by the processor 13 to implement the present invention. The one or more modules/units may be a series of computer readable instruction segments capable of performing specific functions, which are used for describing the execution process of the computer readable instructions in the electronic device 1. For example, the computer readable instructions may be divided into a determination unit 110, an auditing unit 111, an acquisition unit 112, an analysis unit 113, and an output unit 114.
The memory 12 may be used for storing the computer readable instructions and/or modules, and the processor 13 implements various functions of the electronic device 1 by executing or executing the computer readable instructions and/or modules stored in the memory 12 and invoking data stored in the memory 12. The memory 12 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to use of the electronic device, and the like. The memory 12 may include non-volatile and volatile memories, such as: a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a 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 memory 12 may be a memory having a physical form, such as a memory stick, a TF Card (Trans-flash Card), or the like.
The integrated modules/units of the electronic device 1 may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, all or part of the flow of the method according to the above embodiments may be implemented by hardware that is configured to be instructed by computer readable instructions, which may be stored in a computer readable storage medium, and when the computer readable instructions are executed by a processor, the steps of the method embodiments may be implemented.
Wherein the computer readable instructions comprise computer readable instruction code which may be in source code form, object code form, an executable file or some intermediate form, and the like. The computer-readable medium may include: any entity or device capable of carrying said computer readable instruction code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM).
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
In conjunction with fig. 1, the memory 12 in the electronic device 1 stores computer-readable instructions to implement a data processing method, and the processor 13 can execute the computer-readable instructions to implement:
receiving a risk decision request and determining a triggering user of the risk decision request;
acquiring the personal information of the trigger user, and auditing the personal information;
if the personal information passes the verification, determining a decision service according to the risk decision request, and acquiring a service variable of the decision service;
if the number of the service variables is multiple, determining the decision priority of the service variables in the decision service;
obtaining the relevant information corresponding to the plurality of business variables for decision analysis, wherein the decision analysis comprises the following steps:
determining the service variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low;
acquiring information simultaneously corresponding to the trigger user and the target variable as associated information; performing decision analysis on the associated information;
and if the associated information passes the decision, repeatedly acquiring the associated information corresponding to the plurality of business variables for decision analysis until a preset condition is met, and outputting a decision result.
Specifically, the processor 13 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the computer readable instructions, which is not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The computer readable storage medium has computer readable instructions stored thereon, wherein the computer readable instructions when executed by the processor 13 are configured to implement the steps of:
receiving a risk decision request and determining a triggering user of the risk decision request;
acquiring the personal information of the trigger user, and auditing the personal information;
if the personal information passes the verification, determining a decision service according to the risk decision request, and acquiring a service variable of the decision service;
if the number of the service variables is multiple, determining the decision priority of the service variables in the decision service;
obtaining the relevant information corresponding to the plurality of business variables for decision analysis, wherein the decision analysis comprises the following steps:
determining the service variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low;
acquiring information simultaneously corresponding to the trigger user and the target variable as associated information; performing decision analysis on the associated information;
and if the associated information passes the decision, repeatedly acquiring the associated information corresponding to the plurality of business variables for decision analysis until a preset condition is met, and outputting a decision result.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. The plurality of units or devices may also be implemented by one unit or device through software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A data processing method, characterized in that the data processing method comprises:
receiving a risk decision request and determining a triggering user of the risk decision request;
acquiring the personal information of the trigger user, and auditing the personal information;
if the personal information passes the verification, determining a decision service according to the risk decision request, and acquiring a service variable of the decision service;
if the number of the service variables is multiple, determining the decision priority of the service variables in the decision service;
obtaining the relevant information corresponding to the plurality of business variables for decision analysis, wherein the decision analysis comprises the following steps:
determining the service variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low;
acquiring information simultaneously corresponding to the trigger user and the target variable as associated information;
performing decision analysis on the associated information;
and if the associated information passes the decision, repeatedly acquiring the associated information corresponding to the plurality of business variables for decision analysis until a preset condition is met, and outputting a decision result.
2. The data processing method of claim 1, wherein the determining the triggering user of the risk decision request comprises:
analyzing a message header of the risk decision request to obtain address information carried by the message header;
acquiring a preset label from a configuration library, wherein the preset label is used for indicating an address of a sending request;
acquiring information corresponding to the preset label from the address information as a sending address;
determining a terminal corresponding to the sending address as a sending terminal;
acquiring the receiving time of the risk decision request, and acquiring a request log from the sending terminal according to the receiving time;
and extracting a login identification code on the request log, and determining the trigger user according to the login identification code.
3. The data processing method of claim 1, wherein the performing of the audit process on the personal information comprises:
acquiring a configuration list, wherein the configuration list stores the mapping relation between a plurality of users and credit levels;
traversing the list users in the configuration list;
matching the traversed list users with the personal information, and determining the traversed list users successfully matched with the personal information as target users;
determining the credit level of the target user in the configuration list;
and if the credit grade is greater than or equal to the configuration grade, determining that the personal information passes the audit.
4. The data processing method of claim 1, wherein the obtaining the business variables of the decision service comprises:
determining the service type of the decision service;
determining a decision rule according to the service type;
and extracting variables in the decision rule to obtain the business variables.
5. The data processing method of claim 4, wherein the decision analysis of the association information comprises:
extracting a target rule corresponding to the target variable from the decision rule;
analyzing the association information by using the target rule;
if the associated information meets the target rule, determining that the associated information passes a decision; or
And if the associated information does not meet the target rule, determining that the associated information fails to pass the decision.
6. The data processing method of claim 1, wherein said determining a decision priority for a plurality of said business variables in said decision business comprises:
determining an information variable to which the personal information belongs;
calculating the correlation strength of each business variable and the information variable;
determining the decision priority of the plurality of business variables according to the association strength.
7. The data processing method of claim 1, wherein the method further comprises:
if the preset condition is that the associated information fails to pass the decision, determining that the risk decision request does not pass the audit; or
If the preset condition is that the plurality of business variables all complete decision analysis and the associated information corresponding to the business variable with the lowest decision priority fails to pass the decision, determining that the risk decision request fails to be audited; or
And if the preset condition is that the plurality of business variables all complete decision analysis and the associated information corresponding to the plurality of business variables all pass the decision, determining that the risk decision request passes the audit.
8. A data processing apparatus, characterized in that the data processing apparatus comprises:
the system comprises a determining unit, a judging unit and a judging unit, wherein the determining unit is used for receiving a risk decision request and determining a triggering user of the risk decision request;
the auditing unit is used for acquiring the personal information of the trigger user and auditing the personal information;
an obtaining unit, configured to determine a decision service according to the risk decision request if the personal information passes the audit, and obtain a service variable of the decision service;
the determining unit is further configured to determine a decision priority of the plurality of service variables in the decision service if the plurality of service variables are available;
an analysis unit, configured to obtain associated information corresponding to the multiple service variables for decision analysis, including:
determining the service variable at the highest priority as a target variable according to the sequence of the decision priorities from high to low;
acquiring information simultaneously corresponding to the trigger user and the target variable as associated information;
performing decision analysis on the associated information;
and the output unit is used for repeatedly acquiring the associated information corresponding to the plurality of business variables for decision analysis if the associated information passes a decision, until a preset condition is met, and outputting a decision result.
9. An electronic device, characterized in that the electronic device comprises:
a memory storing computer readable instructions; and
a processor executing computer readable instructions stored in the memory to implement the data processing method of any of claims 1 to 7.
10. A computer-readable storage medium characterized by: the computer-readable storage medium has stored therein computer-readable instructions which are executed by a processor in an electronic device to implement the data processing method of any one of claims 1 to 7.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011540112.8A CN112669138B (en) | 2020-12-23 | 2020-12-23 | Data processing method and related equipment |
| PCT/CN2021/096635 WO2022134466A1 (en) | 2020-12-23 | 2021-05-28 | Data processing method and related device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011540112.8A CN112669138B (en) | 2020-12-23 | 2020-12-23 | Data processing method and related equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112669138A true CN112669138A (en) | 2021-04-16 |
| CN112669138B CN112669138B (en) | 2022-04-26 |
Family
ID=75408909
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011540112.8A Active CN112669138B (en) | 2020-12-23 | 2020-12-23 | Data processing method and related equipment |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN112669138B (en) |
| WO (1) | WO2022134466A1 (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022134466A1 (en) * | 2020-12-23 | 2022-06-30 | 平安科技（深圳）有限公司 | Data processing method and related device |
| CN115563657A (en) * | 2022-09-27 | 2023-01-03 | 冯淑芳 | Data information security processing method and system and cloud platform |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111597097B (en) * | 2020-04-21 | 2023-12-12 | 山西宇钶技术发展有限公司 | Big data processing method and system |
| CN115185923B (en) * | 2022-07-07 | 2023-03-07 | 中国气象局气象探测中心 | Method and system for managing meteorological observation metadata and intelligent terminal |
| CN115271933B (en) * | 2022-09-23 | 2023-02-03 | 天津金城银行股份有限公司 | Loan decision method and device, decision equipment and computer readable storage medium |
| CN116130096B (en) * | 2023-04-04 | 2023-11-21 | 安徽省立医院(中国科学技术大学附属第一医院) | System, method and electronic equipment for making auxiliary decision through core index |
| CN116777621B (en) * | 2023-06-25 | 2024-02-06 | 陕西西煤云商信息科技有限公司 | Trade business risk prevention and control method and prevention and control system thereof |
| CN117768150B (en) * | 2023-11-15 | 2024-06-07 | 安徽皖通高速公路股份有限公司 | Service system access method and service system access platform based on identity authentication |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102958105A (en) * | 2012-10-23 | 2013-03-06 | 大唐软件技术股份有限公司 | Internet of things terminal access method and device |
| CN103036960A (en) * | 2012-12-07 | 2013-04-10 | 中国联合网络通信集团有限公司 | Information push method and information push device and information push system |
| CN107316134A (en) * | 2017-06-16 | 2017-11-03 | 深圳乐信软件技术有限公司 | A kind of risk control method, device, server and storage medium |
| US20180101831A1 (en) * | 2016-10-10 | 2018-04-12 | AO Kaspersky Lab | System and method for performing secure online banking transactions |
| CN108090829A (en) * | 2017-12-21 | 2018-05-29 | 深圳市买买提信息科技有限公司 | A kind of data managing method, data administrator and electronic equipment |
| CN108418809A (en) * | 2018-02-07 | 2018-08-17 | 平安科技（深圳）有限公司 | Chat data processing method, device, computer equipment and storage medium |
| CN109857373A (en) * | 2018-12-18 | 2019-06-07 | 平安科技（深圳）有限公司 | Business data processing method, device, computer equipment and storage medium |
| CN111475144A (en) * | 2020-04-13 | 2020-07-31 | 深圳前海微众银行股份有限公司 | Wind control decision method, device, equipment and computer readable storage medium |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007127424A2 (en) * | 2006-04-28 | 2007-11-08 | Efunds Corporation | Methods and systems for opening and funding a financial account online |
| US20130346283A1 (en) * | 2012-06-22 | 2013-12-26 | Bank Of America Corporation | System and Method for Processing a Decision Engine Driven Integrated Consumer Credit Application |
| CN110390511A (en) * | 2019-06-20 | 2019-10-29 | 深圳壹账通智能科技有限公司 | The credit applications measures and procedures for the examination and approval, device, equipment and storage medium |
| CN110309205B (en) * | 2019-07-10 | 2021-12-07 | 上海诚数信息科技有限公司 | Credit decision data optimization extraction system and method |
| CN112669138B (en) * | 2020-12-23 | 2022-04-26 | 平安科技（深圳）有限公司 | Data processing method and related equipment |
-
2020
- 2020-12-23 CN CN202011540112.8A patent/CN112669138B/en active Active
-
2021
- 2021-05-28 WO PCT/CN2021/096635 patent/WO2022134466A1/en active Application Filing
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102958105A (en) * | 2012-10-23 | 2013-03-06 | 大唐软件技术股份有限公司 | Internet of things terminal access method and device |
| CN103036960A (en) * | 2012-12-07 | 2013-04-10 | 中国联合网络通信集团有限公司 | Information push method and information push device and information push system |
| US20180101831A1 (en) * | 2016-10-10 | 2018-04-12 | AO Kaspersky Lab | System and method for performing secure online banking transactions |
| CN107316134A (en) * | 2017-06-16 | 2017-11-03 | 深圳乐信软件技术有限公司 | A kind of risk control method, device, server and storage medium |
| CN108090829A (en) * | 2017-12-21 | 2018-05-29 | 深圳市买买提信息科技有限公司 | A kind of data managing method, data administrator and electronic equipment |
| CN108418809A (en) * | 2018-02-07 | 2018-08-17 | 平安科技（深圳）有限公司 | Chat data processing method, device, computer equipment and storage medium |
| CN109857373A (en) * | 2018-12-18 | 2019-06-07 | 平安科技（深圳）有限公司 | Business data processing method, device, computer equipment and storage medium |
| CN111475144A (en) * | 2020-04-13 | 2020-07-31 | 深圳前海微众银行股份有限公司 | Wind control decision method, device, equipment and computer readable storage medium |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022134466A1 (en) * | 2020-12-23 | 2022-06-30 | 平安科技（深圳）有限公司 | Data processing method and related device |
| CN115563657A (en) * | 2022-09-27 | 2023-01-03 | 冯淑芳 | Data information security processing method and system and cloud platform |
| CN115563657B (en) * | 2022-09-27 | 2023-12-01 | 国信金宏(成都)检验检测技术研究院有限责任公司 | Data information security processing method, system and cloud platform |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2022134466A1 (en) | 2022-06-30 |
| CN112669138B (en) | 2022-04-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112669138B (en) | Data processing method and related equipment | |
| CN111488363B (en) | Data processing method, device, electronic equipment and medium | |
| CN111475513B (en) | Form generation method and device, electronic equipment and medium | |
| CN113283675B (en) | Index data analysis method, device, equipment and storage medium | |
| CN111681091A (en) | Financial risk prediction method and device based on time domain information and storage medium | |
| CN111883251A (en) | Medical misdiagnosis detection method and device, electronic equipment and storage medium | |
| CN111666346A (en) | Information merging method, transaction query method, device, computer and storage medium | |
| CN112433705A (en) | Script generation method and device, electronic equipment and storage medium | |
| CN112363923A (en) | Test method, device, computer equipment and medium based on questionnaire system | |
| CN112711398A (en) | Method, device and equipment for generating buried point file and storage medium | |
| CN114510487A (en) | Data table merging method, device, equipment and storage medium | |
| CN115222443A (en) | Client group division method, device, equipment and storage medium | |
| CN113470775B (en) | Information acquisition method, device, equipment and storage medium | |
| CN113918467A (en) | Financial system testing method, device, equipment and storage medium | |
| CN112819305A (en) | Service index analysis method, device, equipment and storage medium | |
| CN112181482B (en) | Version verification method and device, electronic equipment and storage medium | |
| CN112947911A (en) | Interface script generation method, device, equipment and storage medium | |
| CN113283677B (en) | Index data processing method, device, equipment and storage medium | |
| CN113269179B (en) | Data processing method, device, equipment and storage medium | |
| CN114360732B (en) | Medical data analysis method, device, electronic equipment and storage medium | |
| CN114925033A (en) | Information uplink method, device, system and storage medium | |
| CN112527830A (en) | Data query method, device, equipment and storage medium | |
| CN115037790A (en) | Abnormal registration identification method, device, equipment and storage medium | |
| CN113065947A (en) | Data processing method, device, equipment and storage medium | |
| CN114692204A (en) | Data query method, device, equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |