CN111489255A - Data credit granting method, device, equipment and computer readable storage medium - Google Patents
Data credit granting method, device, equipment and computer readable storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of financial science and technology, and discloses a data credit granting method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring data to be evaluated in a credit system database, performing pre-credit processing on the data to be evaluated to obtain a pre-credit result, and determining a pre-credit limit according to the pre-credit result; acquiring verification data and user data corresponding to the data to be evaluated, and verifying the verification data and the user data to obtain a verification result; and determining a target credit line according to the pre-granted credit line and the auditing result. The invention realizes the pre-credit processing of the data to be evaluated by acquiring the data to be evaluated, determines the pre-credit line according to the pre-credit result, audits the checking data and the user data of the user, and determines the target credit line according to the audit result and the pre-credit line, thereby improving the credit accuracy and the evaluation reliability of the mortgage loan data.
Description
Technical Field
The invention relates to the technical field of credit granting of financial technology (Fintech) data, in particular to a method, a device and equipment for credit granting of data and a computer readable storage medium.
Background
With the development of computer technology, more and more technologies are applied in the financial field, and the traditional financial industry is gradually changing to financial technology (Fintech), but higher requirements are provided for the credit granting technology of data due to the requirements of security and real-time performance of the financial industry.
The existing mortgage loan data crediting method adopts an offline crediting method, and the method is used for crediting and evaluating house mortgages carried out by a user according to the investigation results of the mortgage house property and a borrowing user offline by the client, and finally determining a crediting result. When credit assessment is performed on the mortgage loan of the house property, the value of the house property is generally taken as an important credit assessment condition, and the assessment of the value of the house property is generally determined by the visit of a client manager, market research and the suggestion of an assessment company in comprehensive cooperation. Because the authorization process is heavy and needs a large amount of manual participation in the process of authorizing the house mortgage loan line, the trust granting process has operation risks. Furthermore, in the process of evaluating the home mortgage credit, the fusion institution usually only establishes cooperation with 1 evaluation company, and the evaluation company is easy to cause individual deviation, thereby causing errors of the home mortgage credit data. Therefore, the mortgage data crediting accuracy of the current mortgage data crediting method is low, and the mortgage data evaluation reliability is low.
Disclosure of Invention
The invention mainly aims to provide a data credit granting method, a device, equipment and a storage medium, and aims to solve the technical problems of low credit granting accuracy of existing mortgage data and low reliability of mortgage data evaluation.
In order to achieve the above object, the present invention provides a data trust method, which comprises the following steps:
acquiring data to be evaluated in a credit system database, performing pre-credit processing on the data to be evaluated to obtain a pre-credit result, and determining a pre-credit limit according to the pre-credit result;
acquiring verification data and user data corresponding to the data to be evaluated, and verifying the verification data and the user data to obtain a verification result;
and determining a target credit line according to the pre-granted credit line and the auditing result.
Preferably, the step of obtaining data to be evaluated in a credit system database, performing pre-credit processing on the data to be evaluated to obtain a pre-credit result, and determining a pre-credit limit according to the pre-credit result includes:
acquiring data to be evaluated in a credit granting system database, wherein the data to be evaluated comprises mortgage data, operation data and credit investigation data;
analyzing the mortgage data, the operation data and the credit investigation data to correspondingly obtain an evaluation result of the mortgage data, an evaluation result of the operation data and an evaluation result of the credit investigation data;
determining the pre-credit result according to the evaluation result of the mortgage data, the evaluation result of the operation data and the evaluation result of the credit investigation data;
and determining the pre-granted credit line according to the pre-granted credit result.
Preferably, the step of analyzing the mortgage data, the business data and the credit investigation data to obtain the evaluation result of the mortgage data, the evaluation result of the business data and the evaluation result of the credit investigation data correspondingly comprises:
the mortgage data are obtained, the mortgage data and the mortgage data in a credit system database are authenticated to obtain an authentication result, and the authentication result is calculated to obtain an evaluation result of the mortgage data;
acquiring the operation data, checking operation capacity data in the operation data to obtain a check result, and obtaining an evaluation result of the operation data according to the check result;
and acquiring the credit investigation data, inquiring the credit investigation data through a credit investigation system to obtain an inquiry result, and obtaining an evaluation result of the credit investigation data according to the inquiry result.
Preferably, the step of determining the pre-credit result according to the evaluation result of the mortgage data, the evaluation result of the business data and the evaluation result of the credit investigation data includes:
the assessment result of the mortgage data, the assessment result of the operation data and the assessment result of the credit investigation data are combined and determined to obtain a determination result, and whether the determination result meets the preset determination requirement is detected;
and if the confirmation result is detected to meet the preset confirmation requirement, the pre-credit result is confirmed through pre-credit.
Preferably, the step of determining the pre-credit amount according to the pre-credit result includes:
and acquiring the qualification coincidence degree in the pre-credit result, and determining the pre-credit line according to the qualification coincidence degree.
Preferably, the step of obtaining the verification data and the user data corresponding to the data to be evaluated, and verifying the verification data and the user data to obtain a verification result includes:
acquiring checking data under a subscriber line corresponding to the data to be evaluated and user data collected for the user on the line, wherein the checking data comprises property value information and property attribution information of the mortgage data, and the user data comprises operation information, financial information and credit investigation information of the user;
and analyzing the checking data and the user data to obtain an analysis result, and auditing the analysis result and preset comprehensive capacity data to obtain an auditing result.
Preferably, after the step of determining the target credit line according to the pre-credit line and the audit result, the method further includes:
storing the target credit line into the database;
and after receiving the query request, sending the target credit line to terminal equipment so that the terminal equipment can output the target credit line after receiving the target credit line.
In order to achieve the above object, the present invention also provides a data trust apparatus, including:
the acquisition module is used for acquiring data to be evaluated in the credit granting system database;
the pre-credit module is used for performing pre-credit processing on the data to be evaluated to obtain a pre-credit result;
the determining module is used for determining a pre-credit line according to the pre-credit result;
the acquisition module is further used for acquiring check data and user data corresponding to the data to be evaluated;
the auditing module is used for auditing the checking data and the user data to obtain an auditing result;
the determining module is also used for determining a target credit line according to the pre-credit line and the auditing result.
In order to achieve the above object, the present invention further provides a data granting device, including a memory, a processor, and a data granting program stored in the memory and running on the processor, wherein the data granting program, when executed by the processor, implements the steps of the data granting method.
In order to achieve the above object, the present invention further provides a computer-readable storage medium having stored thereon a data granting program, which when executed by a processor, implements the steps of the data granting method described above.
The method and the device realize pre-credit processing on the data to be evaluated by acquiring the data to be evaluated in the credit system database, determine the pre-credit line according to the pre-credit result, check the checking data of the user and the user data to obtain a check result, and determine the target credit line according to the check result and the pre-credit line. Therefore, in the mortgage loan data pre-credit process, the pre-credit of the data to be evaluated is processed to obtain the pre-credit line, the full online processing mode of the credit system is adopted, and manual pre-credit is not needed, so that the obtained pre-credit line is very accurate, and the credit accuracy of the mortgage loan data is improved. In the mortgage data evaluation process, the checking result is obtained by checking the checking data of the user and the user data, and then the checking result and the pre-granted credit line are combined to obtain the target granted credit line, so that manual evaluation is not needed through manual visiting and researching, the evaluation result is reasonable and credible, and the mortgage data evaluation reliability is improved.
Drawings
FIG. 1 is a flowchart illustrating a first embodiment of a method for granting trust of data according to the present invention;
FIG. 2 is a schematic diagram of a preferred structure of a data granting device according to the present invention;
fig. 3 is a schematic structural diagram of a hardware operating environment according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a data trust method, and referring to fig. 1, fig. 1 is a flow diagram of a first embodiment of the data trust method of the invention.
While a logical order is shown in the flowchart, in some data, the steps shown or described may be performed in a different order than shown.
The data trust method comprises the following steps:
step S10, obtaining the data to be evaluated in the credit system database, pre-granting the data to be evaluated to obtain a pre-granting result, and determining the pre-granting credit limit according to the pre-granting result.
Before a credit granting system acquires data to be evaluated, if a user wants to carry out mortgage loan, a corresponding request instruction needs to be selected from user terminal equipment, the request instruction is sent to the credit granting system after the user terminal equipment detects the request instruction, prompt information of the corresponding data to be submitted is returned according to the request instruction after the credit granting system receives the request instruction, the user submits the corresponding data to the credit granting system in an online mode according to the prompt information, and the data is stored in a database after the credit granting system receives the data submitted by the user. After the credit granting system receives a mortgage loan request of a user, the credit granting system obtains data to be evaluated of the user from a database, then carries out pre-granting processing on the data to be evaluated so as to obtain a pre-granting result of the data to be evaluated, and determines a pre-granting amount of the user according to the pre-granting result.
Wherein, the data to be evaluated is the corresponding data submitted by the user. The request command is a data command for representing mortgage loan types, each mortgage loan type corresponds to one request command, and the credit granting system presets the mapping relation between the request command and the mortgage loan types. The mortgage loan types include a personal house mortgage loan, a business house mortgage loan, and a trust mortgage loan, and the present embodiment does not limit the form of the mortgage loan type. The corresponding data is set in the credit granting system in advance by banking staff and is used for reminding the user of the data required to be submitted by the credit granting system when the user sends a mortgage loan to the credit granting system. Users include individual households, small and micro enterprises, medium and large enterprises, and the like. The online mode refers to various behaviors performed by relying on the internet.
It should be noted that after the user submits the corresponding data on line, the credit system can complete the pre-credit processing in a very short time and return the pre-credit amount, and the user can check the corresponding pre-credit amount on line.
In this embodiment, for example, if the user selects a mortgage loan on a personal property, the user may submit corresponding data, such as property information of the personal property of the user, financial information of the user, credit investigation information of the user, and the like, according to the prompt information returned by the credit granting system, and after receiving the data, the credit granting system performs pre-credit processing on the data to obtain a pre-credit result, and finally determines a pre-credit amount of the user according to the pre-credit result.
The step S10 includes:
step a, obtaining data to be evaluated in a credit granting system database, wherein the data to be evaluated comprises mortgage data, operation data and credit investigation data;
step b, analyzing the mortgage data, the operation data and the credit investigation data to correspondingly obtain an evaluation result of the mortgage data, an evaluation result of the operation data and an evaluation result of the credit investigation data;
c, determining the pre-credit result according to the evaluation result of the mortgage data, the evaluation result of the operation data and the evaluation result of the credit investigation data;
and d, determining the pre-credit line according to the pre-credit result.
Specifically, the credit granting system obtains data to be evaluated in a database, namely corresponding data submitted by a user, wherein the data to be evaluated comprises mortgage data, operation data and credit investigation data, then evaluates the mortgage value of the mortgage data, evaluates the financial data, the operation capacity and the operation range of the operation data and evaluates the credit value of the credit investigation data, thereby obtaining the evaluation result of the data to be evaluated, determines a pre-granting result, and finally obtains a pre-granting credit limit according to the pre-granting result.
The mortgage data comprise mortgage house information, mortgage vehicle information and the like, the operation data comprise financial data, operation capacity, operation range, unit information and the like, and the credit investigation data comprise credit value information, house credit data, public information and the like. The pre-granted credit line is the expected credit line.
Further, the step b comprises:
step e, obtaining the mortgage data, authenticating the mortgage data with the mortgage data in a credit system database to obtain an authentication result, and calculating the authentication result to obtain an evaluation result of the mortgage data;
specifically, the credit granting system acquires the property information of the mortgage data filled by the user, automatically calls investigation data of the property information, such as market heat information, community environment information, peripheral matching information and the like of the mortgage data, of a plurality of evaluation companies in the database, authenticates the property information filled by the user and the investigation data of the evaluation companies to obtain an authentication result, performs value weighting measurement on the authentication result, and calculates the property value of the mortgage data, wherein the property value of the mortgage data is the evaluation result of the mortgage data.
The employee of the evaluation company performs data investigation on the mortgage data in an online or/and offline manner in advance, and uploads the investigation data to the database of the credit system through the system corresponding to the evaluation company. The credit system calls a plurality of evaluation company investigation data to ensure that the mortgage data not only has certain market value, but also has certain market transaction degree and good matching environment, so that the mortgage data is prevented from generating high house property value, but has low market activity and low transaction amount. Or the total property value of the mortgage data is high, but the unit value of the mortgage data is obviously lower than that of the periphery of the mortgage data due to obvious defects of the periphery of the mortgage data, and the market activity is also low.
Step f, acquiring the operation data, checking the operation capacity data in the operation data to obtain a check result, and obtaining an evaluation result of the operation data according to the check result;
the credit granting system acquires the operation data of the user on line, and then acquires the operation capacity data in the operation data of the user, including operation range data, change performance data, long-term repayment capacity data, profit capacity data, cash flow capacity data and the like, and correspondingly checks the operation capacity data with the operation capacity data collected by the bank business personnel on line, thereby judging whether the operation data of the user is real and normal, obtaining a check result and obtaining an evaluation result of the operation data according to the check result.
Before the operation data is evaluated by the credit granting system, the credit granting system acquires the operation capacity data in the user operation data in an online manner, then inquires the operation capacity data, inquires the operation capacity conditions of the user, such as the size of an operation range, the strong and weak of the reappearance capacity, the good and bad of long-term repayment capacity, the strong and weak of cash flow capacity and the like, establishes an evaluation model of the financial data on the whole line according to the conditions, and directly uses the evaluation model to comprehensively evaluate the operation data when the credit granting system needs to evaluate the operation data.
And g, acquiring the credit investigation data, inquiring the credit investigation data through a credit investigation system to obtain an inquiry result, and obtaining an evaluation result of the credit investigation data according to the inquiry result.
The credit granting system acquires credit investigation data of the user in an online mode, automatically calls a credit investigation system to inquire the credit investigation conditions such as past loan record conditions and credit card record conditions of the user, inquires whether past loan records of the user are overdue or/and not, inquires whether credit cards of the user are overdriven or/and overdue and the like, and accordingly obtains an inquiry result, and obtains an evaluation result of the credit investigation data according to whether the past loan record conditions and the credit card record conditions of the user are normal or not.
The credit investigation system is a Chinese people bank credit investigation system and comprises an enterprise credit information basic database and a personal credit information basic database.
Before the credit investigation system evaluates the credit investigation data, the credit investigation system acquires the credit investigation data of the user in an online mode, then inquires the credit investigation data, inquires whether past loan records of the user are overdue or/and not, inquires whether credit cards of the user are overdriven or/and overdue or not, and the like, establishes an evaluation model of the credit investigation data on the whole line according to the conditions, and directly uses the evaluation model to comprehensively evaluate the credit investigation data when the credit investigation system needs to evaluate the credit investigation data.
Further, the step c includes:
step h, carrying out combined confirmation on the evaluation result of the mortgage data, the evaluation result of the operation data and the evaluation result of the credit investigation data to obtain a confirmation result, and detecting whether the confirmation result meets the preset confirmation requirement;
and i, if the confirmation result is detected to meet the preset confirmation requirement, the pre-credit confirmation result is the pre-credit confirmation.
Specifically, after the credit granting system obtains the evaluation result of the mortgage data, the evaluation result of the operation data and the evaluation result of the credit investigation data, the credit granting system combines the mortgage value in the evaluation result of the mortgage data, the operation range data, the long-term repayment capacity data and the like in the evaluation result of the operation capacity data of the operation data and the credit value in the evaluation result of the credit investigation data to further perform level confirmation to obtain a confirmation result, then detects whether the confirmation result meets the preset confirmation requirement in the credit granting system, if the confirmation result meets the preset confirmation requirement, the credit granting system passes the preset credit granting confirmation, and if the confirmation result does not meet the preset confirmation requirement, the credit granting system does not pass the preset credit granting confirmation.
The level identification means the mortgage value of the mortgage data, the financial data, the operational capacity and the operational range of the operational data, and the level coefficient of the credit value of the credit investigation data, and the manner of representing the level coefficient includes a percentage manner, a demarcation standard manner and a digital manner, and the present embodiment does not limit the manner of representing the level coefficient. The preset confirmation requirement is preset in the credit granting system by banking personnel, and can be set according to actual conditions.
In the present embodiment, for example, the rank assignment manner is expressed by a demarcation criteria manner, that is, the rank order is excellent, medium, and poor. The super-optimal condition means that the mortgage value of the mortgage data is extremely high, the operation capacity of the operation data is extremely excellent, the credit value of the credit investigation data is extremely excellent, the high-optimal condition means that the grade confirmation is simultaneously satisfied, that is, the mortgage value of the mortgage data is high, the operation capacity of the operation data is excellent, the credit value of the credit investigation data is good, the medium condition means that two items are satisfied, and the difference condition means that one item is not satisfied. The preset confirmation requirement is superior, in the mortgage value of the mortgage data in the data submitted by a certain user, the operation capacity of the operation data is superior and the credit value of the credit investigation data is good, the level of the credit granting system is confirmed to be moderate, and the preset confirmation requirement of the credit granting system is not met, so that the preset confirmation is not passed. The mortgage value of mortgage data in data submitted by a certain user is extremely high, the operation capacity of operation data is extremely excellent, the credit value of credit investigation data is extremely excellent, the level of a credit granting system is determined to be extremely excellent and the like, and the preset authentication requirement of the credit granting system is met, so the credit granting is determined in advance.
Further, the step d includes:
step j, acquiring the qualification coincidence degree in the pre-credit result, and determining the pre-credit line according to the qualification coincidence degree.
Specifically, the credit granting system obtains the qualification coincidence degree in the credit granting result, and then the qualification coincidence degree determines the corresponding pre-granted credit limit.
The confirmation conformity degree is the authentication level of the credit system for the user to submit corresponding data and the satisfaction degree of the preset confirmation requirement in the credit system. The expression mode of the satisfaction degree includes a scoring mode, a percentage mode, a description mode, and the like, and the present embodiment does not limit the expression of the satisfaction degree.
The pre-credit limit is automatically granted by the granting system, and does not need to be granted manually.
In this embodiment, for example, the expression of the satisfaction degree is a scoring manner, i.e. one to one hundred, and one conformity degree is equal to the preset qualification requirement. The level affirmation mode is expressed by a demarcation standard mode, the preset affirmation requirement in the credit system is excellent, and the user can mortgage the loan pre-awarded credit amount to be one million. The authentication level of the credit system for submitting corresponding data to a certain user is extremely high, the confirmation conformity degree of the credit system is very high, and the pre-credit limit of the credit system can be one hundred and fifty thousand.
Step S20, obtaining the checking data and the user data of the user corresponding to the data to be evaluated, and checking the checking data and the user data to obtain a checking result.
The credit granting system obtains the checking data of the user corresponding to the data to be evaluated, wherein the checking data comprises the property value information and the property attribution information of the mortgage data, and the user data comprises the information of the user, such as the operation information, the financial information and the credit investigation information, and then the checking data and the user data and the evaluation result of online pre-credit granting processing of the credit granting system are checked to obtain a checking result.
The step S20 includes:
step k, acquiring checking data under a subscriber line corresponding to the data to be evaluated and user data collected by the subscriber on the line, wherein the checking data comprises property value information and property attribution information of mortgage data, and the user data comprises operation information, financial information and credit investigation information of the subscriber;
and step l, analyzing the checking data and the user data to obtain an analysis result, and auditing the analysis result and preset comprehensive capacity data to obtain an auditing result.
Specifically, the credit granting system acquires authenticity of the property value of the mortgage data, whether the mortgage data belongs to the user, whether the current state of the mortgage data is available, whether the mortgage data has a property right dispute, and the like, correspondingly checks the property value of the mortgage data, the ownership of the mortgage data, the current available state condition of the mortgage data, the current property right dispute condition of the mortgage data, and the like collected by the bank service staff online to obtain a first checking result of the checking data, acquires user data, including user operation condition, user financial capacity range, user credit information, and the like, collected by the user on the line of an evaluation company, checks the data, whether the user normally operates, the user financial capacity range, the user credit information, and the like, collected by the bank service staff to obtain a second checking result of the user data, and obtaining analysis results of the checking data and the user data by combining the first checking result and the second checking result, then correspondingly matching the analysis results with the preset comprehensive capacity data in the credit granting system, and inquiring whether all the checking data and the user data in the analysis results are consistent with the preset comprehensive capacity data, thereby obtaining an auditing result.
The offline means user data collected manually online. The preset comprehensive capacity data is estimated data of the comprehensive capacity of the user according to submitted data in the process of pre-authorizing the submitted data of the user by the authorization system.
In this embodiment, for example, the credit system gives priority to the comprehensive capability estimation data of the user according to the submitted data, and the credit amount is one million. The credit granting system obtains offline checking data and real property value of evaluating the mortgage data of the company online collected user data of the user, all the property disputes are available to the user, the current state is available, and the property dispute does not exist currently, the user operates normally, the financial capacity is good, the credit investigation information is normal, the credit granting system estimates the comprehensive capacity of the user according to the submitted data, and the obtained auditing result is in accordance with the status.
And step S30, determining a target credit line according to the pre-credit line and the auditing result.
And the credit system combines the pre-granted credit line and the verification result to determine the target granted credit line of the user. The target credit line, namely the final amount of the mortgage loan of the user, is determined by the credit system and cannot be modified manually.
In this embodiment, for example, the pre-credit amount is one million, and if the user's audit result is in agreement, the target credit amount is one million. If the user does not meet the verification result, the target credit line is 0.
According to the method and the device, the data to be evaluated is subjected to pre-credit processing by acquiring the data to be evaluated in the credit system database, the pre-credit limit is determined according to the pre-credit result, the checking data of the user and the user data are checked to obtain the checking result, and the target credit limit is determined according to the checking result and the pre-credit limit. Therefore, in the mortgage loan data pre-credit process, the pre-credit of the data to be evaluated is processed to obtain the pre-credit line, the full online processing mode of the credit system is adopted, and manual pre-credit is not needed, so that the obtained pre-credit line is very accurate, and the credit accuracy of the mortgage loan data is improved. In the mortgage data evaluation process, the checking result is obtained by checking the checking data of the user and the user data, and then the checking result and the pre-granted credit line are combined to obtain the target granted credit line, so that manual evaluation is not needed through manual visiting and researching, the evaluation result is reasonable and credible, and the mortgage data evaluation reliability is improved.
Further, a second embodiment of the data trust method is provided.
The second embodiment of the data trust method is different from the first embodiment of the data trust method in that the data trust method further includes:
step l, storing the target credit line into the database, and after receiving the query request, sending the target credit line to a terminal device so that the terminal device can output the target credit line after receiving the target credit line.
Specifically, after determining a target credit line, the credit system stores the target credit line into a database of the credit system, after receiving an inquiry request sent by a user through a terminal device, the credit system sends the target credit line to the terminal device, and after receiving the target credit line, the terminal device outputs the target credit line, so that the user determines the target credit line of mortgage loan data provided by the user.
In this embodiment, the target credit line is stored in the database, and after receiving the query request, the target credit line is sent to the terminal device, so that the terminal device outputs the target credit line after receiving the target credit line. Therefore, the user can inquire the target credit line without submitting other mortgage data, and the efficiency of inquiring the mortgage data is improved.
In addition, the present invention also provides a data granting apparatus, referring to fig. 2, including:
the acquisition module 10 is used for acquiring data to be evaluated in a credit system database;
the pre-credit module 20 is configured to perform pre-credit processing on the data to be evaluated to obtain a pre-credit result;
the determining module 30 is used for determining a pre-credit line according to the pre-credit result;
the obtaining module 10 is further configured to obtain verification data and user data corresponding to the data to be evaluated;
the auditing module 40 is configured to audit the verification data and the user data to obtain an auditing result;
the determining module 30 is further configured to determine a target credit line according to the pre-granted credit line and the audit result.
Further, the obtaining module 10 is further configured to obtain data to be evaluated in a credit granting system database, where the data to be evaluated includes mortgage data, business data, and credit investigation data.
Further, the pre-trust module 20 further includes:
and the analysis unit is used for evaluating the mortgage data, the operation data and the credit investigation data and correspondingly obtaining the evaluation result of the mortgage data, the evaluation result of the operation data and the evaluation result of the credit investigation data.
Further, the determining module 30 is further configured to determine the credit pre-granting result according to the evaluation result of the mortgage data, the evaluation result of the business data, and the evaluation result of the credit investigation data; and determining the pre-granted credit line according to the pre-granted credit result.
Further, the analysis unit includes:
an acquisition subunit, configured to acquire the mortgage data;
the authentication subunit is used for authenticating the mortgage data and the mortgage data in the credit system database to obtain an authentication result;
the calculation subunit is used for calculating the authentication result to obtain an evaluation result of the mortgage data;
the obtaining subunit is further configured to obtain the operation data;
the checking subunit is used for obtaining a checking result by checking the operation capacity data in the operation data and obtaining an evaluation result of the operation data according to the checking result;
the obtaining subunit is further configured to obtain the credit investigation data;
and the inquiry subunit is used for inquiring the credit investigation data through the credit investigation system to obtain an inquiry result, and obtaining an evaluation result of the credit investigation data according to the inquiry result.
Further, the authentication unit includes:
the confirming subunit is used for carrying out combined confirmation on the evaluation results of the mortgage data, the operation data and the credit investigation data to obtain a confirmation result;
the detection subunit is used for detecting whether the identification result meets the preset identification requirement; and if the confirmation result is detected to meet the preset confirmation requirement, the pre-credit result is confirmed through pre-credit.
Further, the obtaining module 10 is further configured to obtain a determination conformity degree in the pre-trust result.
Further, the determining module 30 is further configured to determine the pre-granted credit line according to the confirmation conformity degree.
Further, the obtaining module 10 is further configured to obtain verification data of the data to be evaluated corresponding to the user line and user data collected by the user on the line, where the verification data includes property value information and property attribution information of mortgage data, and the user data includes operation information, financial information, and credit investigation information of the user.
Further, the auditing module 40 includes:
the analysis unit is used for analyzing the checking data and the user data to obtain an analysis result;
and the auditing unit is used for auditing the analysis result and preset comprehensive capacity data to obtain the auditing result.
Further, the data trust device further includes:
the storage module is used for storing the target credit line into the database;
and the sending module is used for sending the target credit line to terminal equipment after receiving the query request so as to output the target credit line after the terminal equipment receives the target credit line.
The specific implementation of the data-based credit granting device of the present invention is basically the same as that of the above-mentioned data-based credit granting method, and is not described herein again.
In addition, the invention also provides data credit granting equipment. As shown in fig. 3, fig. 3 is a schematic structural diagram of a hardware operating environment according to an embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a hardware operating environment of a data trust device.
Fig. 3 may be a schematic structural diagram of a hardware operating environment of the data trust device.
As shown, the data trust device may include: a processor 1001, such as a CPU, a memory 1005, a user interface 1003, a network interface 1004, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the data signaling device may further include an RF (Radio Frequency) circuit, a sensor, a WiFi module, and the like.
Those skilled in the art will appreciate that the data-trusted device architecture illustrated in FIG. 3 does not constitute a limitation on the data-trusted device, and may include more or fewer components than those illustrated, or some components may be combined, or a different arrangement of components.
As shown in fig. 3, a memory 1005, which is a kind of computer storage medium, may include an operating system, a network communication module, a user interface module, and a trust program for data. The operating system is a program for managing and controlling hardware and software resources of the data credit granting device, and supports the operation of the data credit granting program and other software or programs.
In the data credit granting device shown in the figure, the user interface 1003 is mainly used for a terminal device of a user, so that the user inputs a query request to the credit granting system and/or displays a target credit granting amount returned by the credit granting system; the network interface 1004 is mainly used for a credit granting system and performs data communication with a user terminal; the processor 1001 may be configured to call a trust program of data stored in the memory 1005 and execute the steps of the method for controlling the trust apparatus of data as described above.
The specific implementation of the data granting device of the present invention is basically the same as the embodiments of the data granting method, and is not described herein again.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where a data granting program is stored on the computer-readable storage medium, and when the data granting program is executed by a processor, the steps of the data granting method are implemented.
The specific implementation manner of the computer-readable storage medium of the present invention is substantially the same as that of the above-mentioned embodiments of the data granting method, and is not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation manner in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of software goods, which are stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and include instructions for enabling a data credit granting device to execute the methods according to the embodiments of the present invention.
Claims (10)
1. A data credit granting method is characterized by comprising the following steps:
acquiring data to be evaluated in a credit system database, performing pre-credit processing on the data to be evaluated to obtain a pre-credit result, and determining a pre-credit limit according to the pre-credit result;
acquiring verification data and user data corresponding to the data to be evaluated, and verifying the verification data and the user data to obtain a verification result;
and determining a target credit line according to the pre-granted credit line and the auditing result.
2. The method for granting credit to the data according to claim 1, wherein the step of obtaining the data to be evaluated in the credit granting system database, performing pre-granting processing on the data to be evaluated to obtain a pre-granting result, and determining the pre-granting credit limit according to the pre-granting result comprises:
acquiring data to be evaluated in a credit granting system database, wherein the data to be evaluated comprises mortgage data, operation data and credit investigation data;
analyzing the mortgage data, the operation data and the credit investigation data to correspondingly obtain an evaluation result of the mortgage data, an evaluation result of the operation data and an evaluation result of the credit investigation data;
determining the pre-credit result according to the evaluation result of the mortgage data, the evaluation result of the operation data and the evaluation result of the credit investigation data;
and determining the pre-granted credit line according to the pre-granted credit result.
3. The credit granting method for the data according to claim 2, wherein the step of analyzing the mortgage data, the business data and the credit investigation data to obtain the evaluation result of the mortgage data, the evaluation result of the business data and the evaluation result of the credit investigation data comprises:
the mortgage data are obtained, the mortgage data and the mortgage data in a credit system database are authenticated to obtain an authentication result, and an evaluation result of the mortgage data is obtained through calculation according to the authentication result;
acquiring the operation data, checking operation capacity data in the operation data to obtain a check result, and obtaining an evaluation result of the operation data according to the check result;
and acquiring the credit investigation data, inquiring the credit investigation data through a credit investigation system to obtain an inquiry result, and obtaining an evaluation result of the credit investigation data according to the inquiry result.
4. The method for granting credit to data according to claim 2, wherein the step of determining the pre-credit result according to the evaluation result of the mortgage data, the evaluation result of the business data and the evaluation result of the credit investigation data comprises:
the assessment result of the mortgage data, the assessment result of the operation data and the assessment result of the credit investigation data are combined and determined to obtain a determination result, and whether the determination result meets the preset determination requirement is detected;
and if the confirmation result is detected to meet the preset confirmation requirement, the pre-credit result is confirmed through pre-credit.
5. The method as claimed in claim 2, wherein the step of determining the pre-granted credit limit according to the pre-granted credit result comprises:
and acquiring the qualification coincidence degree in the pre-credit result, and determining the pre-credit line according to the qualification coincidence degree.
6. The method for granting credit to data according to claim 1, wherein the step of obtaining the verification data and the user data corresponding to the data to be evaluated, and verifying the verification data and the user data to obtain the verification result comprises:
acquiring checking data under a subscriber line corresponding to the data to be evaluated and user data collected for the user on the line, wherein the checking data comprises property value information and property attribution information of the mortgage data, and the user data comprises operation information, financial information and credit investigation information of the user;
and analyzing the checking data and the user data to obtain an analysis result, and auditing the analysis result and preset comprehensive capacity data to obtain an auditing result.
7. The method as claimed in any one of claims 1 to 6, wherein after the step of determining the target credit line based on the pre-granted credit line and the audit result, the method further comprises:
storing the target credit line into the database;
and after receiving the query request, sending the target credit line to the terminal equipment corresponding to the query request, so that the terminal equipment outputs the target credit line after receiving the target credit line.
8. A data credit granting device, comprising:
the acquisition module is used for acquiring data to be evaluated in the credit granting system database;
the pre-credit module is used for performing pre-credit processing on the data to be evaluated to obtain a pre-credit result;
the determining module is used for determining a pre-credit line according to the pre-credit result;
the acquisition module is further used for acquiring check data and user data corresponding to the data to be evaluated;
the auditing module is used for auditing the checking data and the user data to obtain an auditing result;
the determining module is also used for determining a target credit line according to the pre-credit line and the auditing result.
9. A data trust device, characterized in that the data trust device comprises a memory, a processor and a data trust program stored on the memory and running on the processor, wherein the data trust program realizes the steps of the data trust method according to any one of claims 1 to 7 when executed by the processor.
10. A computer-readable storage medium, having stored thereon a trust program for data, which when executed by a processor, performs the steps of the method for granting trust to data according to any one of claims 1 to 7.
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| CN202010289393.8A CN111489255A (en) | 2020-04-13 | 2020-04-13 | Data credit granting method, device, equipment and computer readable storage medium |
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| CN202010289393.8A CN111489255A (en) | 2020-04-13 | 2020-04-13 | Data credit granting method, device, equipment and computer readable storage medium |
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