CN116109401A - Data request processing method and system based on artificial intelligence - Google Patents
Data request processing method and system based on artificial intelligence Download PDFInfo
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Abstract
The invention relates to a processing method and a system of a data request based on artificial intelligence, wherein the method comprises the steps of submitting user request information; acquiring historical data from a data platform according to identity information in user request information; calculating first processing data volume according to the first request data volume of the user and the user processing mode, and analyzing whether the user has processing capacity according to the first processing data volume and the acquired data volume information; the method comprises the steps that a user with processing capacity carries out processing capacity grade classification on the user according to request records, overtime processing records and unprocessed data volume information of the user, and a processing capacity grade list is output; evaluating the processing capacity grade list and users without processing capacity, and outputting an evaluation result; and after the request protocol takes effect, the request data platform requests for response. The response risk of the request data platform is reduced by analyzing the user processing capacity and the processing capacity level and making relevant risk decisions.
Description
Technical Field
The invention relates to the field of data processing, in particular to a data request processing method and system based on artificial intelligence.
Background
With the rise of artificial intelligence, users acquire data, especially important data and even confidential data, from a data platform, the data platform is more and more important for the users to apply for auditing of acquiring the data, and the users are evaluated by means of the artificial intelligence, so that the risk of the data platform is effectively reduced.
Loan risk assessment method and server disclosed in patent application number 201810457323.1, the method comprises the following steps: collecting facial expression images of a user at intervals of a preset time period in a preset time period; extracting facial expression features in the facial expression image; matching the extracted facial expression features with facial expression features prestored in a database to determine facial expression categories corresponding to the extracted facial expression features; obtaining a corresponding preset loan coefficient according to the determined facial expression categories, wherein each facial expression category corresponds to one preset loan coefficient; and determining a final loan coefficient according to each preset loan coefficient obtained in the preset time period, and determining a loan risk according to the final loan coefficient and according to preset user credit information.
In the prior art, the facial expression characteristics of a user are analyzed according to the data request of the user to determine the data request coefficient of the user, but the user is not accurately analyzed, so that the data is inaccurate and the data request processing efficiency is low.
Disclosure of Invention
Therefore, the invention provides a processing method and a processing system for data requests based on artificial intelligence, which can solve the problems of inaccurate data and low efficiency of processing the data requests caused by inaccurate analysis of users.
To achieve the above object, the present invention provides a method for processing a data request based on artificial intelligence, the method comprising:
submitting user request information, wherein the user request information comprises basic information, first request data volume and user processing mode, and the basic information comprises identity information and acquired data volume information;
acquiring historical data from a data platform according to the identity information, wherein the historical data comprises the identity information, a request record, a timeout processing record, unprocessed data volume information and owned data volume information;
calculating first processing data volume according to the first request data volume of the user and the user processing mode, and analyzing whether the user has processing capacity according to the first processing data volume and the acquired data volume information;
the method comprises the steps that a user with processing capacity carries out processing capacity grade classification on the user according to request records, overtime processing records and unprocessed data volume information of the user, and a processing capacity grade list is output;
Evaluating the users according to the processing capacity grade list of the users, evaluating the users without processing capacity, and outputting an evaluation result;
generating a request protocol according to the evaluation result, wherein the request protocol comprises identity information, a second request data volume, a user processing mode and a second processing data volume;
and after the request protocol is validated, the request data platform performs request response.
Further, when analyzing whether the user has processing capability, calculating first processing data amount according to the first request data amount of the user and the processing mode of the user, analyzing whether the user has processing capability according to the first processing data amount and the acquired data amount information, acquiring the data amount information for periodically acquiring the data amount for the user during analysis,
when the data volume acquired by the user periodically is more than or equal to the first processing data volume, determining that the user has processing capacity;
when the user periodically acquires the data quantity < the first processing data quantity, determining that the user has no processing capability.
Further, when the user has processing capability, the user is classified into processing capability classes according to the request record, the timeout processing record and the unprocessed data volume information,
if the unprocessed data amount information of the user has no unprocessed data amount, the processing capability level of the user is in level A, specifically:
When the user does not request the record, the processing capacity level of the user is A1 level;
when the user has a request record and does not have a timeout processing record, the processing capacity level of the user is A2 level;
when the user has a timeout processing record and the processing is completed, the processing capacity level of the user is A3 level;
when the user has a timeout processing record and does not finish processing, the processing capacity level of the user is A4 level;
if the unprocessed data volume exists in the unprocessed data volume information of the user, the processing capacity level of the user is in level B, specifically:
when the user does not request recording, the processing capacity level of the user is B1 level;
when the user has a request record and does not have a timeout processing record, the processing capacity level of the user is B2 level;
when the user has a timeout processing record and the processing is completed, the processing capacity level of the user is B3 level;
when the user has a timeout processing record and does not finish processing, the processing capacity level of the user is B4 level;
after the processing capacity level of the user is divided, the request record, the overtime processing record and the unprocessed data volume information of the user are continuously tracked and monitored in a preset period, the processing capacity level of the user is timely adjusted,
When the user finishes processing the unprocessed data volume within a preset period, the processing capacity grade of the user is improved to the grade A, and the specific processing capacity grade dividing method is the same;
when the user finishes overtime processing within a preset period, the processing capacity level of the user is improved to A3 level or B3 level;
when the user eliminates the overtime processing record in a preset period, the processing capacity level of the user is improved to A2 level or B2 level;
when the user has unprocessed data quantity in a preset period, the processing capacity grade of the user is reduced to B grade, and the specific processing capacity grade dividing method is the same;
when the user has overtime processing records in a preset period and the processing is completed, the processing capacity level of the user is reduced to A3 level or B3 level;
and when the user has timeout processing record in a preset period and the timeout processing is not completed, the processing capacity level of the user is increased to A4 level or B4 level.
Further, in evaluating a user having processing capability, the evaluation is performed according to the processing capability level of the user,
when the processing capacity level of the user is A1 level, taking 100% of the first request data amount of the user as the second request data amount;
When the processing capacity level of the user is A2 level, 87.5% of the first request data amount of the user is used as the second request data amount;
when the processing capacity level of the user is A3 level, 75% of the first request data amount of the user is used as the second request data amount;
when the processing capacity level of the user is A4 level, 62.5% of the first request data volume of the user is used as the second request data volume;
when the processing capacity level of the user is B1 level, 50% of the first request data amount of the user is used as the second request data amount;
when the processing capacity level of the user is B2 level, taking 37.5% of the first request data amount of the user as the second request data amount;
when the processing capacity level of the user is B3 level, 25% of the first request data amount of the user is used as the second request data amount;
when the user's processing power level is level B4, then 12.5% of the user's first requested data amount is taken as the second requested data amount.
Further, when the user without processing capability is evaluated, if the user does not have processing capability, the user will obtain a second request data volume through the value information mortgage, the second request data volume is calculated according to the preset rule of the value information, and if the user cannot process during the processing, the value information of the user mortgage will not be received.
Further, after the request protocol is validated, batch request response is carried out according to a preset period, when the batch request response is carried out, the owned data volume information of the user is obtained from the data platform in real time for detection and analysis, when the owned data volume information of the user is detected and analyzed to change before any batch request response, the next batch request response is delayed, and when the obtained data volume information and the owned data volume information of the user are detected and analyzed to be unable to counteract the second request data volume within a preset delay time, the request response of the residual request data volume is stopped.
Further, before the user submits the user request information, real-name authentication is required, face recognition is carried out on the user according to the identity card photo uploaded when the user fills in the basic information, the user needs to carry out synchronous actions according to dynamic indication of face recognition, the dynamic indication comprises nodding, blinking, head rotation and mouth opening, and whether the user is operating is confirmed by comparing the identity card photo of the user with the face recognition.
Further, the present invention also provides a processing system for data request based on artificial intelligence, the system comprising:
The application module is used for submitting user request information, wherein the user request information comprises basic information, first request data quantity and user processing mode, and the basic information comprises identity information and acquired data quantity information;
the acquisition module is used for acquiring historical data from the data platform according to the identity information, wherein the historical data comprises the identity information, a request record, a timeout processing record, unprocessed data volume information and owned data volume information;
the analysis module is used for calculating the first processing data volume according to the first request data volume of the user and the user processing mode, and analyzing whether the user has processing capacity according to the first processing data volume and the acquired data volume information;
the dividing module is used for dividing the processing capacity level of the user with the processing capacity according to the request record, the overtime processing record and the unprocessed data volume information of the user, and outputting a processing capacity level list;
the evaluation module is used for evaluating the user according to the processing capacity grade list of the user, evaluating the user without processing capacity and outputting an evaluation result;
the generating module is used for generating a request protocol according to the evaluation result, wherein the request protocol comprises identity information, a second request data volume, a user processing mode and a second processing data volume;
And the request response module is used for requesting the data platform to respond to the request after the request protocol is validated.
Further, the analysis module comprises a calculation unit and an analysis unit, wherein the calculation unit is used for calculating the first processing data volume according to the first request data volume of the user and the processing mode of the user, and the analysis unit is used for analyzing whether the user has processing capacity according to the first processing data volume and the acquired data volume information;
the evaluation module comprises a first evaluation unit and a second evaluation unit, wherein the first evaluation unit is used for evaluating the user according to the processing capability level list of the user, and the second evaluation unit is used for evaluating the user without processing capability.
Further, the request response module comprises a first detection unit, a second detection unit and a request response unit, wherein the first detection unit is used for acquiring the owned data volume information of the user from the data platform in real time for detection and analysis, detecting and analyzing whether the owned data volume information of the user fluctuates, and outputting a first detection result, the second detection unit is used for detecting and analyzing whether the acquired data volume information of the user and the owned data volume information can counteract the second request data volume again when the first detection unit detects and analyzes that the owned data volume information of the user fluctuates, and outputting a second detection result, and the request response unit is used for carrying out request response in batches and delaying or stopping the request response according to the results of the first detection unit and the second detection unit.
Compared with the prior art, the method has the advantages that the user submits the user request information, the history data is acquired from the data platform according to the identity information in the user request information, then the first processing data amount is calculated according to the first request data amount of the user and the user processing mode, whether the user has processing capacity or not is analyzed according to the first processing data amount and the acquired data amount information, the processing capacity of the user with the processing capacity is classified, the user without the processing capacity is evaluated according to the user processing capacity, the user without the processing capacity is directly evaluated, relevant measures are timely made through the data analysis of the user processing capacity and the processing capacity, the user information is comprehensively and accurately analyzed and timely wind-controlled, and therefore the analysis data is more comprehensive and accurate, and the efficiency of processing the data request is improved.
In particular, the first processing data amount is calculated according to the first request data amount of the user and the user processing mode, whether the user has processing capacity or not is analyzed according to the first processing data amount and the acquired data amount information, the user with processing capacity is higher than the user without processing capacity and has low risk, whether the user has processing capacity or not is determined through analysis, so that the information data of the analyzed user is more comprehensive and accurate, and the efficiency of processing the data request is improved.
Particularly, when the user has processing capacity, the processing capacity of the user is classified according to the user request record, the overtime processing record and the unprocessed data volume information, the higher the rating is, the better the processing capacity of the user is, the processing capacity of the user is analyzed through the classification of the processing capacity, the response risk of the request data platform can be effectively reduced, the processing capacity of the user is timely adjusted through the tracking monitoring in a period, the satisfaction degree of the user can be improved through the improvement of the processing capacity of the user, the information data of the user is analyzed more comprehensively and accurately, and the efficiency of processing the data request is further improved.
In particular, when a user with processing capability is evaluated, corresponding measures are taken according to the processing capability level of the user, the higher the processing capability level of the user is, the higher the data volume of the request is, the request data volume requested by the user is adjusted through the user processing capability level, the problem that the response risk is high due to the fact that the corresponding processing of the user can not be obtained by the request data platform can be effectively avoided, in addition, the data request is processed according to the user processing capability level, the information data of the user is analyzed more comprehensively and accurately, and the efficiency of processing the data request is improved.
In particular, when the user has no processing capability, the user can bear the response risk of the request data platform by performing mortgage on the value information of the user, so that the response risk of the request data platform is reduced, and the user can also obtain response under the condition that the user has no data request by performing mortgage on the value information of the user, so that the user is satisfied, and the efficiency of processing the data request is improved.
Particularly, when the user's own data volume information is analyzed and determined to change during the request response, the request response is delayed within the preset time, if the user's acquired data volume information and the own data volume information are determined to be unable to be counteracted within the preset delay time, the request response of the rest batch is stopped immediately, whether the user can counteract the second request data volume is determined by analyzing the user's acquired data volume information or the own data volume information in real time, the data volume which the user cannot process the request can be effectively avoided, and the analysis data is more accurate by accurately monitoring the user's information, so that the efficiency of processing the data request is improved.
In particular, identity card information uploaded by a user is compared with face recognition through real-name authentication to confirm identity card identity, the situation that the identity is stolen by a bad user is prevented through dynamic indication, the user is accurately verified, analysis data is more comprehensive, analysis is more accurate, and therefore the efficiency of processing data requests is improved.
The user request information comprises basic information, first request data quantity and user processing mode, the basic information comprises identity information and acquired data quantity information, the acquired module acquires historical data from the data platform according to the identity information, the analysis module calculates first processing data quantity according to the first request data quantity of the user and the user processing mode, whether the user has processing capacity or not is analyzed according to the first processing data quantity and the acquired data quantity information, the division module is used for classifying the processing capacity of the user according to request records and overtime processing records of the user with the processing capacity, the evaluation module evaluates the user according to a processing capacity grade list of the user, and evaluates the user without the processing capacity at the same time, then the generation module generates a request protocol according to an evaluation result, finally, the request response module requests the data platform to respond after the request protocol is validated, analyzes according to the user request information of the user and makes corresponding measures, and through the all-round accurate analysis and timely wind control of the user information, the analysis data is more comprehensive and accurate, and the efficiency of processing data requests is further improved.
Particularly, the first processing data quantity is calculated according to the first request data quantity of the user and the user processing mode through the calculation unit in the analysis module, then the analysis unit analyzes whether the user has processing capacity according to the first processing data quantity and the acquired data quantity information, and through analysis, whether the user has processing capacity is determined, so that the response risk of the request data platform caused by the fact that the user does not have the processing capacity is avoided, and the response risk is effectively reduced; the first evaluation unit and the second evaluation unit in the evaluation module respectively evaluate the users with the processing capacity according to the processing capacity grades of the users and evaluate the users without the processing capacity, and respectively take different measures according to the users with different conditions, so that the information data of the analyzed users are more comprehensive and accurate through analyzing the processing capacity of the users, and further the efficiency of processing the data requests is improved.
In particular, the first detection unit in the request response module acquires the owned data amount information of the user from the data platform in real time to detect and analyze whether the owned data amount information of the user changes, and outputs a first detection result, wherein the second detection unit is used for detecting and analyzing whether the acquired data amount information and the owned data amount information of the user can offset the residual second request data amount again when the first detection unit detects and analyzes that the owned data amount information of the user changes, and outputting a second detection result.
Drawings
FIG. 1 is a flow chart of a method for processing an artificial intelligence based data request according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a processing system for data requests based on artificial intelligence according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of an analysis module in an artificial intelligence-based data request processing system according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an evaluation module in an artificial intelligence based data request processing system according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a request response module in an artificial intelligence based data request processing system according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, the method for processing an artificial intelligence-based data request according to the embodiment of the present invention includes:
step S110, submitting user request information, wherein the user request information comprises basic information, first request data quantity and user processing mode, and the basic information comprises identity information and acquired data quantity information;
Step S120, acquiring historical data from a data platform according to the identity information, wherein the historical data comprises the identity information, a request record, a timeout processing record, unprocessed data volume information and owned data volume information;
step S130, calculating a first processing data amount according to a first request data amount of a user and a user processing mode, and analyzing whether the user has processing capacity according to the first processing data amount and acquired data amount information;
step S140, the users with processing capacity are classified according to the request record, the overtime processing record and the unprocessed data volume information, and a processing capacity class list is output;
step S150, evaluating the users according to the processing capability level list of the users, evaluating the users without processing capability, and outputting an evaluation result;
step S160, generating a request protocol according to the evaluation result, wherein the request protocol comprises identity information, a second request data volume, a user processing mode and a second processing data volume;
step S170, the request data platform requests a request response after the request protocol is validated.
Specifically, the application scenario of the method can be that the user requests important data or confidential data, the data platform carries out risk decision on the user to determine the data volume of the responding user, or the user carries out risk decision on the user to determine the loan amount, for example, when the user carries out loan, the user submits the user request information after filling in identity information, acquiring data volume information, first request data volume and user processing mode, wherein the acquired data volume is income information, the first request data volume is first loan amount, the user processing mode is user repayment mode, then the request record and overtime processing record corresponding to the identity information are called by the user request information, namely name and identity card number, to a central bank, a commercial bank, a security company, an insurance company and a financing company, the request record is a overdue record, when the user history data is acquired, the user request information and the history data of the user are started to be processed, the user request information is calculated according to the first request data volume and the user processing mode, the user processing mode is the second request data volume is calculated according to the first request volume and the user processing mode, the user processing mode is the user repayment volume is the user volume, if the user has the second request volume is the user volume is not estimated to have the capability, the capability is evaluated according to the capability, the capability is evaluated according to the capability is obtained, and the capability is evaluated according to the capability of the user processing data is estimated after the capability is evaluated, and finally, the request data platform responds to the request according to the identity information, the second request data volume, the user processing mode and the second processing data volume after the request protocol is validated, wherein the request protocol is a loan protocol, and the second request data volume is the second-period repayment amount.
Specifically, the embodiment of the invention submits user request information, acquires historical data from a data platform according to identity information in the user request information, calculates first processing data amount according to first request data amount of the user and a user processing mode, analyzes whether the user has processing capacity according to the first processing data amount and the acquired data amount information, classifies the processing capacity of the user with the processing capacity, evaluates the user according to the processing capacity of the user, directly evaluates the user without the processing capacity, analyzes the processing capacity of the user and the processing capacity of the user through data, makes relevant measures, and analyzes and timely and wind-controls the user information and the omnibearing accuracy, so that the analysis data is more comprehensive and accurate, and the efficiency of processing the data request is further improved.
Specifically, before a user submits user request information, real-name authentication is required, face recognition is carried out on the user according to an identity card photo uploaded when the user fills in basic information, the user needs to carry out synchronous actions according to dynamic instructions of face recognition, the dynamic instructions comprise nodding, blinking, head rotation and mouth opening, and whether the user is operating is confirmed by comparing the identity card photo of the user with the face recognition.
Specifically, the embodiment of the invention compares the identity card information uploaded by the user with the face recognition through real-name authentication to confirm that the identity card is consistent with the identity, and prevents the situation of fraudulent use of the identity by bad users through dynamic indication, and through accurately verifying the user, analysis data is more comprehensive, so that analysis is more accurate, and the efficiency of processing data requests is improved.
Specifically, when analyzing whether the user has processing capability, calculating first processing data amount according to first request data amount of the user and the processing mode of the user, analyzing whether the user has processing capability according to the first processing data amount and acquired data amount information, acquiring data amount information for a period of the user during analysis,
when the data volume acquired by the user periodically is more than or equal to the first processing data volume, determining that the user has processing capacity;
when the user periodically acquires the data quantity < the first processing data quantity, determining that the user has no processing capability.
Specifically, taking a user loan as an example, if the data amount acquired by the user cycle, i.e. the income, is 10000 yuan per month, the user repayment mode is divided into three periods, three months and one period, the first requested data amount, i.e. the first loan amount, is 60000 yuan, the first period repayment amount is 20000 yuan, and the data amount acquired by the user cycle, i.e. the income per period, is 30000 yuan, and as 30000 is more than 20000, the repayment capability of the user, i.e. the processing capability of the user, is analyzed.
Specifically, the embodiment of the invention calculates the first processing data volume according to the first request data volume of the user and the user processing mode, analyzes whether the user has processing capacity according to the first processing data volume and the acquired data volume information, and determines whether the user has processing capacity or not according to the analysis that the user has processing capacity higher than that of the user without processing capacity and lower risk, so that the information data of the analyzed user is more comprehensive and accurate, and the efficiency of processing the data request is further improved.
Specifically, when the user has processing capability, the user is classified into processing capability classes according to request record, timeout processing record and unprocessed data volume information,
if the unprocessed data amount information of the user has no unprocessed data amount, the processing capability level of the user is in level A, specifically:
when the user does not request the record, the processing capacity level of the user is A1 level;
when the user has a request record and does not have a timeout processing record, the processing capacity level of the user is A2 level;
when the user has a timeout processing record and the processing is completed, the processing capacity level of the user is A3 level;
when the user has a timeout processing record and does not finish processing, the processing capacity level of the user is A4 level;
If the unprocessed data volume exists in the unprocessed data volume information of the user, the processing capacity level of the user is in level B, specifically:
when the user does not request recording, the processing capacity level of the user is B1 level;
when the user has a request record and does not have a timeout processing record, the processing capacity level of the user is B2 level;
when the user has a timeout processing record and the processing is completed, the processing capacity level of the user is B3 level;
when the user has a timeout processing record and does not finish processing, the processing capacity level of the user is B4 level;
after the processing capacity level of the user is divided, the request record, the overtime processing record and the unprocessed data volume information of the user are continuously tracked and monitored in a preset period, the processing capacity level of the user is timely adjusted,
when the user finishes processing the unprocessed data volume within a preset period, the processing capacity grade of the user is improved to the grade A, and the specific processing capacity grade dividing method is the same;
when the user finishes overtime processing within a preset period, the processing capacity level of the user is improved to A3 level or B3 level;
when the user eliminates the overtime processing record in a preset period, the processing capacity level of the user is improved to A2 level or B2 level;
When the user has unprocessed data quantity in a preset period, the processing capacity grade of the user is reduced to B grade, and the specific processing capacity grade dividing method is the same;
when the user has overtime processing records in a preset period and the processing is completed, the processing capacity level of the user is reduced to A3 level or B3 level;
and when the user has timeout processing record in a preset period and the timeout processing is not completed, the processing capacity level of the user is increased to A4 level or B4 level.
Specifically, when the user has processing capacity, the processing capacity grade of the user is classified according to the user request record, the overtime processing record and the unprocessed data volume information, the higher the rating is, the better the processing capacity of the user is, the response risk of the request data platform can be effectively reduced through analyzing the processing capacity of the user through the processing capacity grade classification, and the processing capacity grade of the user can be timely adjusted through tracking and monitoring in a period, so that the processing capacity grade of the user can be improved, the satisfaction degree of the user can be improved, and the response risk of the request data platform is further reduced.
In particular, in evaluating a user having processing power, the user is evaluated according to the user's processing power level,
When the processing capacity level of the user is A1 level, taking 100% of the first request data amount of the user as the second request data amount;
when the processing capacity level of the user is A2 level, 87.5% of the first request data amount of the user is used as the second request data amount;
when the processing capacity level of the user is A3 level, 75% of the first request data amount of the user is used as the second request data amount;
when the processing capacity level of the user is A4 level, 62.5% of the first request data volume of the user is used as the second request data volume;
when the processing capacity level of the user is B1 level, 50% of the first request data amount of the user is used as the second request data amount;
when the processing capacity level of the user is B2 level, taking 37.5% of the first request data amount of the user as the second request data amount;
when the processing capacity level of the user is B3 level, 25% of the first request data amount of the user is used as the second request data amount;
when the user's processing power level is level B4, then 12.5% of the user's first requested data amount is taken as the second requested data amount.
Specifically, when the user with processing capability is evaluated, corresponding measures are taken according to the processing capability level of the user, the higher the processing capability level of the user is, the higher the data volume of the request is, the request data volume requested by the user is adjusted through the user processing capability level, the problem that the response risk is high due to the fact that the corresponding processing of the user cannot be obtained by the request data platform can be effectively avoided, in addition, the data request is processed according to the user processing capability level, the information data of the analysis user is more comprehensive and accurate, and the efficiency of processing the data request is improved.
Specifically, when a user without processing capability is evaluated, if the user does not have processing capability, the user will obtain a second request data volume through the value information mortgage, the second request data volume is calculated according to a preset rule of the value information, and if the user cannot process during processing, the value information of the user mortgage will not be received.
Specifically, taking a user loan as an example, when evaluating a user without processing capability, if the user does not have processing capability, i.e., repayment capability, the user will obtain a second requested data amount, i.e., a second loan amount, through a property mortgage, the property being a property, an automobile, a stock, a policy, and a value, the second requested data amount being calculated according to a preset rule of the property, such as a preset percentage of a cash value of the property, and if during processing, the user cannot process, i.e., repayment, the user will not receive the property of the user mortgage.
Specifically, in the embodiment of the invention, when the user has no processing capability, the user bears the response risk of the request data platform by performing mortgage on the value information of the user, so that the response risk of the request data platform is reduced, and the user can also obtain response under the condition of no data request by performing mortgage on the value information of the user, so that the user is satisfied, and the efficiency of processing the data request is improved.
Specifically, after the request protocol is validated, batch request response is carried out according to a preset period, when the batch request response is carried out, the owned data volume information of the user is obtained from the data platform in real time for detection and analysis, when the owned data volume information of the user is detected and analyzed to change before any batch request response, the next batch request response is delayed, and when the detection and analysis of the obtained data volume information of the user and the owned data volume information in the preset delay time can not offset the second request data volume, the request response of the remaining second request data volume is stopped.
Specifically, if it is analyzed that the data amount information owned by the user varies, the processing capability of the user is likely to be affected, so that the risk is reduced by delaying the request response, and then whether the user has the capability of canceling the second request data amount is determined by analyzing both the acquired data amount information and the owned data amount information of the user.
Specifically, taking a user loan as an example, if the second request data amount, that is, the second loan amount is 20000 yuan, is paid out in two batches for one week in a preset period, 10000 yuan are paid out every week, if the property information, that is, the owned data amount information of the user is analyzed to be not available before the second batch is paid out in response to the second batch, the payment is delayed for 5 days, and if the income information or the owned data amount information and the property information of the user are analyzed to be unable to be returned to the second loan amount during 5 days, the payment of the remaining 10000 yuan is stopped.
Specifically, in the embodiment of the invention, request response is carried out on users through batches, when the change of the information of the data quantity owned by the users is analyzed and determined during the request response period, delay request response is carried out in preset time, if the information of the data quantity acquired by the users and the information of the data quantity owned by the users are judged to be unable to be counteracted in the preset delay time, the request response of the rest batches is stopped immediately, whether the users can counteract the second request data quantity is judged by analyzing the information of the data quantity acquired by the users or the information of the data quantity owned by the users in real time, the situation that the data quantity which cannot be processed by the users is accurately monitored by the users can be effectively avoided, the analysis data is more accurate, and the efficiency of processing the data request is improved.
Specifically, referring to fig. 2, an embodiment of the present invention further provides a system for processing a data request based on artificial intelligence, where the system includes:
the application module 210 is configured to submit user request information, where the user request information includes basic information, a first request data volume, and a user processing manner, and the basic information includes identity information and acquired data volume information;
the obtaining module 220 is configured to obtain, according to the identity information, historical data from the data platform, where the historical data includes identity information, a request record, a timeout processing record, and unprocessed data volume information and has data volume information;
An analysis module 230, configured to calculate a first processing data amount according to a first request data amount of a user and a user processing manner, and analyze whether the user has processing capability according to the first processing data amount and the acquired data amount information;
a dividing module 240, configured to divide the processing capability of the user with processing capability according to the request record, the timeout processing record and the unprocessed data volume information, and output a processing capability level list;
the evaluation module 250 is configured to evaluate the user according to the processing capability level list of the user, and evaluate the user without processing capability at the same time, and output an evaluation result;
a generating module 260, configured to generate a request protocol according to the evaluation result, where the request protocol includes identity information, a second request data volume, a user processing manner, and a second processing data volume;
the request response module 270 is configured to request the data platform to perform a request response after the request protocol is validated.
Specifically, the embodiment of the invention submits user request information through an application module, wherein the user request information comprises basic information, first request data volume and user processing mode, the basic information comprises identity information and acquired data volume information, an acquisition module acquires historical data from a data platform according to the identity information, an analysis module calculates first processing data volume according to the first request data volume of a user and the user processing mode, analyzes whether the user has processing capacity according to the first processing data volume and the acquired data volume information, a division module is used for dividing the processing capacity of the user according to request records and overtime processing records of the user with processing capacity, an evaluation module evaluates the user according to a processing capacity grade list of the user, evaluates the user without processing capacity at the same time, then a generation module generates a request protocol according to an evaluation result, and finally a request response module requests the data platform to respond after the request protocol is validated, analyzes and makes corresponding measures according to the user request information of the user, and performs all-round accurate analysis and timely wind control on the user information, so that the analysis data is more comprehensive and accurate, and the efficiency of processing data requests is improved.
Specifically, the analysis module comprises a calculation unit and an analysis unit, wherein the calculation unit is used for calculating the first processing data amount according to the first request data amount of the user and the processing mode of the user, and the analysis unit is used for analyzing whether the user has processing capacity according to the first processing data amount and the acquired data amount information.
Specifically, the first processing data amount is calculated by the calculation unit of the analysis module according to the first request data amount of the user and the user processing mode, then the analysis unit analyzes whether the user has processing capacity according to the first processing data amount and the acquired data amount information, analyzes and determines whether the user has the processing capacity, avoids the response risk of the request data platform caused by the fact that the user does not have the processing capacity, and enables the information data of the analysis user to be more comprehensive and accurate by analyzing the processing capacity of the user, so that the efficiency of processing the data request is improved.
Specifically, the evaluation module includes a first evaluation unit for evaluating a user according to a processing capability level list of the user, and a second evaluation unit for evaluating a user without processing capability.
Specifically, in the embodiment of the invention, the first evaluation unit and the second evaluation unit in the evaluation module respectively evaluate users with processing capacity according to the processing capacity level and evaluate users without processing capacity, and respectively take different measures according to different conditions, so that the information data of the analyzed users are more comprehensive and accurate by analyzing the processing capacity of the users, and the efficiency of processing data requests is further improved.
Specifically, the request response module comprises a first detection unit, a second detection unit and a request response unit, wherein the first detection unit is used for acquiring the owned data volume information of the user from the data platform in real time for detection and analysis, detecting and analyzing whether the owned data volume information of the user fluctuates, outputting a first detection result, the second detection unit is used for detecting and analyzing whether the acquired data volume information of the user and the owned data volume information can offset the second request data volume again when the first detection unit detects and analyzes that the owned data volume information of the user fluctuates, outputting a second detection result, and the request response unit is used for carrying out request response in batches and delaying or stopping the request response according to the results of the first detection unit and the second detection unit.
Specifically, the first detection unit in the request response module acquires the owned data amount information of the user from the data platform in real time to detect and analyze, detect and analyze whether the owned data amount information of the user changes, and output a first detection result, wherein the second detection unit is used for detecting and analyzing whether the acquired data amount information of the user and the owned data amount information can offset the remaining second request data amount again when the first detection unit detects and analyzes that the owned data amount information of the user changes, and outputting a second detection result.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the invention; various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for processing an artificial intelligence based data request, comprising:
submitting user request information, wherein the user request information comprises basic information, first request data volume and user processing mode, and the basic information comprises identity information and acquired data volume information;
acquiring historical data from a data platform according to the identity information, wherein the historical data comprises the identity information, a request record, a timeout processing record, unprocessed data volume information and owned data volume information;
calculating first processing data volume according to the first request data volume of the user and the user processing mode, and analyzing whether the user has processing capacity according to the first processing data volume and the acquired data volume information;
the method comprises the steps that a user with processing capacity carries out processing capacity grade classification on the user according to request records, overtime processing records and unprocessed data volume information of the user, and a processing capacity grade list is output;
Evaluating the users according to the processing capacity grade list of the users, evaluating the users without processing capacity, and outputting an evaluation result;
generating a request protocol according to the evaluation result, wherein the request protocol comprises identity information, a second request data volume, a user processing mode and a second processing data volume;
and after the request protocol is validated, the request data platform performs request response.
2. The method according to claim 1, wherein when analyzing whether the user has processing capability, the first processing data amount is calculated based on the first request data amount of the user and the processing mode of the user, whether the user has processing capability is analyzed based on the first processing data amount and the acquired data amount information, the acquired data amount information is the user periodically acquired data amount,
when the data volume acquired by the user periodically is more than or equal to the first processing data volume, determining that the user has processing capacity;
when the user periodically acquires the data quantity < the first processing data quantity, determining that the user has no processing capability.
3. The method of claim 2, wherein when the user has processing capability, the user is ranked according to request record, timeout processing record and unprocessed data volume information,
If the unprocessed data amount information of the user has no unprocessed data amount, the processing capability level of the user is in level A, specifically:
when the user does not request the record, the processing capacity level of the user is A1 level;
when the user has a request record and does not have a timeout processing record, the processing capacity level of the user is A2 level;
when the user has a timeout processing record and the processing is completed, the processing capacity level of the user is A3 level;
when the user has a timeout processing record and does not finish processing, the processing capacity level of the user is A4 level;
if the unprocessed data volume exists in the unprocessed data volume information of the user, the processing capacity level of the user is in level B, specifically:
when the user does not request recording, the processing capacity level of the user is B1 level;
when the user has a request record and does not have a timeout processing record, the processing capacity level of the user is B2 level;
when the user has a timeout processing record and the processing is completed, the processing capacity level of the user is B3 level;
when the user has a timeout processing record and does not finish processing, the processing capacity level of the user is B4 level;
after the processing capacity level of the user is divided, the request record, the overtime processing record and the unprocessed data volume information of the user are continuously tracked and monitored in a preset period, the processing capacity level of the user is timely adjusted,
When the user finishes processing the unprocessed data volume within a preset period, the processing capacity grade of the user is improved to the grade A, and the specific processing capacity grade dividing method is the same;
when the user finishes overtime processing within a preset period, the processing capacity level of the user is improved to A3 level or B3 level;
when the user eliminates the overtime processing record in a preset period, the processing capacity level of the user is improved to A2 level or B2 level;
when the user has unprocessed data quantity in a preset period, the processing capacity grade of the user is reduced to B grade, and the specific processing capacity grade dividing method is the same;
when the user has overtime processing records in a preset period and the processing is completed, the processing capacity level of the user is reduced to A3 level or B3 level;
and when the user has timeout processing record in a preset period and the timeout processing is not completed, the processing capacity level of the user is increased to A4 level or B4 level.
4. The method for processing an artificial intelligence based data request according to claim 3, wherein when evaluating a user having processing power, the evaluation is performed according to the processing power level of the user,
when the processing capacity level of the user is A1 level, taking 100% of the first request data amount of the user as the second request data amount;
When the processing capacity level of the user is A2 level, 87.5% of the first request data amount of the user is used as the second request data amount;
when the processing capacity level of the user is A3 level, 75% of the first request data amount of the user is used as the second request data amount;
when the processing capacity level of the user is A4 level, 62.5% of the first request data volume of the user is used as the second request data volume;
when the processing capacity level of the user is B1 level, 50% of the first request data amount of the user is used as the second request data amount;
when the processing capacity level of the user is B2 level, taking 37.5% of the first request data amount of the user as the second request data amount;
when the processing capacity level of the user is B3 level, 25% of the first request data amount of the user is used as the second request data amount;
when the user's processing power level is level B4, then 12.5% of the user's first requested data amount is taken as the second requested data amount.
5. The method of claim 4, wherein when evaluating a user without processing capability, if the user does not have processing capability, the user will obtain a second requested data amount by the value information mortgage, the second requested data amount is calculated according to a preset rule of the value information, and if the user cannot process during the processing, the value information of the user mortgage will not be received.
6. The method according to claim 5, wherein after the request protocol is validated, the batch request response is performed according to a preset period, the user's own data amount information is acquired from the data platform in real time for detection and analysis during the batch request response, when the user's own data amount information is detected and analyzed to change before any batch request response, the next batch request response is delayed, and when the user's acquired data amount information and the own data amount information are detected and analyzed to fail to cancel the second request data amount within a preset delay time, the request response of the remaining request data amount is stopped.
7. The method for processing data request based on artificial intelligence according to claim 6, wherein before the user submits the user request information, real-name authentication is required, face recognition is performed on the user according to the uploaded identification card photo when the user fills in the basic information, the user needs to perform synchronous actions according to dynamic indication of face recognition, the dynamic indication comprises nodding, blinking, head rotation and mouth opening, and whether the user is operating is confirmed by comparing the identification card photo of the user with the face recognition.
8. An artificial intelligence based data request processing system applying the artificial intelligence based data request processing method of any one of claims 1 to 7, comprising:
the application module is used for submitting user request information, wherein the user request information comprises basic information, first request data quantity and user processing mode, and the basic information comprises identity information and acquired data quantity information;
the acquisition module is used for acquiring historical data from the data platform according to the identity information, wherein the historical data comprises the identity information, a request record, a timeout processing record, unprocessed data volume information and owned data volume information;
the analysis module is used for calculating the first processing data volume according to the first request data volume of the user and the user processing mode, and analyzing whether the user has processing capacity according to the first processing data volume and the acquired data volume information;
the dividing module is used for dividing the processing capacity level of the user with the processing capacity according to the request record, the overtime processing record and the unprocessed data volume information of the user, and outputting a processing capacity level list;
the evaluation module is used for evaluating the user according to the processing capacity grade list of the user, evaluating the user without processing capacity and outputting an evaluation result;
The generating module is used for generating a request protocol according to the evaluation result, wherein the request protocol comprises identity information, a second request data volume, a user processing mode and a second processing data volume;
and the request response module is used for requesting the data platform to respond to the request after the request protocol is validated.
9. The system of claim 8, wherein the analysis module comprises a calculation unit and an analysis unit, the calculation unit is used for calculating a first processed data volume according to a first requested data volume of a user and a processing mode of the user, and the analysis unit is used for analyzing whether the user has processing capability according to the first processed data volume and acquired data volume information;
the evaluation module comprises a first evaluation unit and a second evaluation unit, wherein the first evaluation unit is used for evaluating the user according to the processing capability level list of the user, and the second evaluation unit is used for evaluating the user without processing capability.
10. The system according to claim 9, wherein the request response module comprises a first detection unit, a second detection unit and a request response unit, the first detection unit is configured to acquire the user's own data volume information from the data platform in real time for detection and analysis, detect and analyze whether the user's own data volume information fluctuates, output a first detection result, and the second detection unit is configured to, when the first detection unit detects and analyzes that the user's own data volume information fluctuates, re-detect and analyze whether the user's acquired data volume information and the own data volume information can cancel the second request data volume, output a second detection result, and the request response unit is configured to perform request response in batches and delay or stop the request response according to the results of the first detection unit and the second detection unit.
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