CN116308736A - Loan money early warning management system - Google Patents
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Abstract
The invention discloses a loan deposit early-warning management system, and relates to the field of loan early-warning management. In order to solve the problem that the black list user cannot be carefully checked when the conventional early warning management system checks the data of the loan user, and misjudgment of the black list is easily caused. A loan money early warning management system, comprising: the system comprises an information acquisition module, a list library management service module, an information verification module and a risk early warning management module. The loan deposit early warning management system provided by the invention avoids the situation that information submitted by a user is irrelevant to information of blacklist related audit information, so that misjudgment occurs, ensures the accuracy of applying for loan by the user, further ensures the reliability of loan by the user, avoids the situation that repayment is difficult due to mismatching of income and expense of the user, ensures that the user can normally repay, improves the experience of use of the user, and avoids the overdue situation due to insufficient repayment amount.
Description
Technical Field
The invention relates to the field of loan early warning management, in particular to a loan money early warning management system.
Background
With the rapid development of socioeconomic performance, it is possible for both businesses and individuals to apply loans to banks or financial institutions. For example, in order to expand the production and operation scale, enterprises need to introduce advanced technologies and devices, however, the technologies and devices generally need to spend a lot of money, millions and tens of millions of yuan. During the use period after the user obtains the loan, the bank obtains fewer loan information channels of the related user, is not updated timely, can not timely inform related personnel and institutions, triggers a risk processing flow, and has poor loan risk control capability. The invention of application number CN202011168361.9 discloses a credit management system supporting automatic early warning, which realizes the simultaneous return of result data of inquiry data request and risk early warning to clients by adopting an asynchronous operation mode, solves the problem that new scenes and new services are difficult to access quickly by a scene inquiry configuration module and a derivative variable processing service module, increases the judgment of the relevance between clients by a credit early warning engine module, enhances the early warning capability, but the system cannot carefully audit blacklist users when auditing the data of loan users, and easily causes the situation that the user information is not updated timely, so that misjudgment occurs to the blacklist.
Disclosure of Invention
The invention aims to provide a loan money early warning management system, which firstly confirms the black-and-white list condition of a user through a list management service library module, converts information submitted by a secondary blacklist user into information of auditing information related to the blacklist, considers the blacklist if the converted information and the auditing information related to the blacklist have a certain repetition rate, and if the converted information and the auditing information do not accord with the judgment of the blacklist, the user is converted into the white list, so that the information submitted by the user is not related to the auditing information of the blacklist, the situation of misjudgment is further avoided, the accuracy of the loan application of the user is ensured, the corresponding risk early warning is determined through comparing the cash income and the cash expenditure of the user, the reliability of the loan of the user is further ensured, the situation that repayment is difficult due to mismatching of the income and expenditure of the user is avoided, the repayment signal is sent to the user according to the adjustment of the residual value of the user, the user can normally repayment, the experience of the user is improved, the situation of repayment amount is avoided due to the fact that the repayment amount is insufficient, and the problem is solved in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a loan money early warning management system, comprising:
the information acquisition module is used for acquiring user identity information, assets, liability information and income conditions, establishing a database, acquiring user information at the same time through identification in the database, dividing the user into a plurality of grades, wherein each grade corresponds to a score segment, and determining whether the user reaches a blacklist standard according to the score segments.
The list base management service module is used for accessing the business blacklist database according to the identity authorization information of the user, matching the business blacklist database, judging whether the user is a blacklist user, determining whether the user can handle the loan business according to the judging result, entering a loan approval process if the user is a whitelist user, not handling the loan business if the user is a blacklist user, and uploading the information to the information verification module for verification.
The information verification module is used for inputting and reading identity information, assets, liability information and income conditions submitted by the user, automatically matching the information with the information of the user in the database, determining the user as a blacklist user if the matching is consistent, rejecting a loan request of the user, removing the user from the blacklist database if the matching is inconsistent, and rechecking.
The risk early warning management module is used for setting early warning indexes, early warning functions and early warning thresholds of various risk projects, setting constituent elements of the early warning indexes, calculating the risk degree of account funds of users, sending early warning to blacklist users, refusing loan application, and sending repayment early warning signals to users according to adjustment of residual values of loan users.
Further, the information acquisition module includes:
and the information receiving and reading module is used for inputting and reading the identity information, the assets, the liability information and the income condition submitted by the user.
And the retrieval module is used for retrieving the data provided by the user and the related audit information of the black-and-white list, screening out different information and transmitting the information to the grading module for grading.
And the grading module is used for dividing the user into a plurality of grades, each grade corresponds to one fractional segment, determining the blacklist grade standard of the user according to the fractional segment, and determining whether to approve the loan according to the grade standard of the blacklist, wherein the lower the grade is, the higher the passing rate of the loan is.
Further, the information receiving and reading module includes:
and the information receiving module is used for receiving the identity information, the assets, the liability information and the income situation submitted by the user.
And the conversion module is used for collecting and identifying the information uploaded by the user, converting the collected information into characters, and uploading the characters to the retrieval module for retrieving the black-and-white list.
Further, the information verification module includes:
and the information calling module is used for calling the user identity information, the assets, the liability information and the income situation out of the database.
And the information automatic matching module is used for automatically matching the user information acquired by the information acquisition module with the information called out from the database by the information calling-out module.
And the information auditing module is used for rechecking the information which is matched by the information automatic matching module and is different from the auditing information related to the blacklist, refusing the loan application if the blacklist standard is met, classifying the user as a white list if the blacklist standard is not met, storing the white list into a white list database and correspondingly updating the black list database.
Further, the information auditing module includes:
and re-auditing the information which is searched by the search module and is different from the auditing information related to the blacklist.
And converting different information into information of the auditing information related to the blacklist, if the converted information and the auditing information related to the blacklist have a certain repetition rate, considering the blacklist, refusing the loan application and adding the blacklist database.
If the repetition rate does not exist between the converted information and the blacklist related audit information, classifying the user as a white list, storing the white list into a white list database, and correspondingly updating the black list database to grant loan approval to the user.
Further, the list library management service module includes:
and the black-and-white list information base is used for storing auditing information for confirming the black-and-white list.
The list confirmation module is used for carrying out batch confirmation on the information of the loan users to be confirmed, which is acquired by the information acquisition module, by utilizing the black-and-white list information base, adding the users confirmed to be white lists into a white list base list, setting the lists outside the white lists as primary black list users and secondary black list users, adding the primary black list users into the black list database, and simultaneously carrying out rechecking on the secondary black list users.
And the list checking module is used for checking the user confirmed as the primary blacklist, and transmitting the user confirmed as the secondary blacklist to the information verification module for checking again.
Further, the list confirmation module includes:
and matching the information submitted by the user with the information in the black-and-white list information base.
If the coincidence rate of the information submitted by the user and the information in the blacklist database exceeds 70%, confirming that the user is a first-level blacklist user, adding the risk to the blacklist database, and refusing the loan application.
If the coincidence rate of the information submitted by the user and the information in the blacklist database is smaller than 70% and larger than 20%, the information is confirmed to be a secondary blacklist user, and the next examination is carried out.
If the coincidence rate of the information submitted by the user and the information in the blacklist database is less than 20%, confirming the information as a whitelist, applying for loan, and adding the list into the whitelist database.
Further, the risk early warning management module includes:
and the fund risk early warning module is used for setting early warning indexes, early warning functions and early warning thresholds of various risk items, setting constituent elements of the early warning indexes, setting the early warning functions and the early warning thresholds according to the constituent elements, and calculating the risk degree of account fund of a user.
And the black-and-white list early warning module is used for sending the user confirmed as the black list to the black list database, and sending the black list early warning to the user so as to reject the loan application.
And the money early warning module is used for performing digital redundancy processing on the user fund data and the preset user fund to obtain a user residual value of the user, and sending a repayment early warning signal to the user according to adjustment of the user residual value.
Further, the fund risk early warning module includes:
and calculating the ratio of the cash income to the cash expenditure of the user, and reflecting the ratio relation of the cash income to the cash expenditure of the user.
If the ratio is smaller than 1, the cash income of the user is smaller than the cash expenditure, triggering a first-level risk early warning, and further auditing the loan application of the user;
if the proportion is greater than 1, the cash income of the user is greater than the cash expenditure, and balance exists in the user account, the secondary risk early warning is triggered, and the loan application of the user is approved.
Further, the money early warning module includes:
and presetting repayment funds of the user.
And performing data redundancy processing on the balance fund data of the user account and the preset user repayment fund to obtain a user residual value.
And calculating a corresponding repayment difference according to the residual value of the user, and sending a repayment early warning signal to the user according to the repayment difference.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the loan deposit early warning management system, a list management service library module is used for firstly confirming the black and white list condition of a user, screening out corresponding white list users, setting a primary black list user and a secondary black list user, directly adding the primary black list user to a black list database, simultaneously conducting rechecking on the secondary black list user, converting information submitted by the secondary black list user into information of checking information related to the black list, considering the black list if the converted information and the checking information related to the black list have a certain repetition rate, refusing to apply for the loan and adding the black list database, and if the converted information and the checking information related to the black list do not accord with the judgment of the black list, converting the information submitted by the user into the white list, avoiding the situation that the information submitted by the user is irrelevant to the information related to the black list and further guaranteeing the accuracy of applying for the loan by the user.
2. According to the loan money early warning management system, the corresponding risk early warning is determined by comparing the cash income and cash expenditure of the user, and whether the loan is approved or not is further guaranteed according to the corresponding risk level, so that the reliability of the loan of the user is further guaranteed, the situation that repayment is difficult due to mismatching of the income and expenditure of the user is avoided, the fund data of the loan user and the preset user fund are subjected to digital redundancy processing, and a repayment early warning signal is sent to the user according to adjustment of the user residual value, so that the user can normally repay, the experience of the user is improved, and the overdue situation due to insufficient repayment amount is avoided.
Drawings
FIG. 1 is a schematic diagram of a loan deposit early warning management system;
FIG. 2 is a workflow diagram of a loan deposit early warning management system of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the technical problem that the prior early warning management system cannot carefully audit the blacklist user when auditing the data of the loan user, and is easy to cause the situation that misjudgment occurs in the blacklist due to untimely updating of the user information, please refer to fig. 1-2, the embodiment provides the following technical scheme:
a loan money early warning management system, comprising:
the information acquisition module is used for acquiring user identity information, assets, liability information and income conditions, establishing a database, acquiring user information at the same time through identification in the database, dividing the user into a plurality of grades, wherein each grade corresponds to a score segment, and determining whether the user reaches a blacklist standard according to the score segments.
An information acquisition module comprising:
and the information receiving and reading module is used for inputting and reading the identity information, the assets, the liability information and the income condition submitted by the user.
And the retrieval module is used for retrieving the data provided by the user and the related audit information of the black-and-white list, screening out different information and transmitting the information to the grading module for grading.
And the grading module is used for dividing the user into a plurality of grades, each grade corresponds to one fractional segment, determining the blacklist grade standard of the user according to the fractional segment, and determining whether to approve the loan according to the grade standard of the blacklist, wherein the lower the grade is, the higher the passing rate of the loan is.
An information receiving and reading module, comprising:
and the information receiving module is used for receiving the identity information, the assets, the liability information and the income situation submitted by the user.
And the conversion module is used for collecting and identifying the information uploaded by the user, converting the collected information into characters, and uploading the characters to the retrieval module for retrieving the black-and-white list.
The list base management service module is used for accessing the business blacklist database according to the identity authorization information of the user, matching the business blacklist database, judging whether the user is a blacklist user, determining whether the user can handle the loan business according to the judging result, entering a loan approval process if the user is a whitelist user, not handling the loan business if the user is a blacklist user, and uploading the information to the information verification module for verification.
A roster vault management service module comprising:
and the black-and-white list information base is used for storing auditing information for confirming the black-and-white list.
The list confirmation module is used for carrying out batch confirmation on the information of the loan users to be confirmed, which is acquired by the information acquisition module, by utilizing the black-and-white list information base, adding the users confirmed to be white lists into a white list base list, setting the lists outside the white lists as primary black list users and secondary black list users, adding the primary black list users into the black list database, and simultaneously carrying out rechecking on the secondary black list users.
And the list checking module is used for checking the user confirmed as the primary blacklist, and transmitting the user confirmed as the secondary blacklist to the information verification module for checking again.
A list validation module comprising:
and matching the information submitted by the user with the information in the black-and-white list information base.
If the coincidence rate of the information submitted by the user and the information in the blacklist database exceeds 70%, confirming that the user is a first-level blacklist user, adding the risk to the blacklist database, and refusing the loan application.
If the coincidence rate of the information submitted by the user and the information in the blacklist database is smaller than 70% and larger than 20%, the information is confirmed to be a secondary blacklist user, and the next examination is carried out.
If the coincidence rate of the information submitted by the user and the information in the blacklist database is less than 20%, confirming the information as a whitelist, applying for loan, and adding the list into the whitelist database.
The information verification module is used for inputting and reading identity information, assets, liability information and income conditions submitted by the user, automatically matching the information with the information of the user in the database, determining the user as a blacklist user if the matching is consistent, rejecting a loan request of the user, removing the user from the blacklist database if the matching is inconsistent, and rechecking.
An information verification module comprising:
and the information calling module is used for calling the user identity information, the assets, the liability information and the income situation out of the database.
And the information automatic matching module is used for automatically matching the user information acquired by the information acquisition module with the information called out from the database by the information calling-out module.
And the information auditing module is used for rechecking the information which is matched by the information automatic matching module and is different from the auditing information related to the blacklist, refusing the loan application if the blacklist standard is met, classifying the user as a white list if the blacklist standard is not met, storing the white list into a white list database and correspondingly updating the black list database.
An information auditing module, comprising:
and re-auditing the information which is searched by the search module and is different from the auditing information related to the blacklist.
Different information is converted into information of the auditing information related to the blacklist, if the converted information and the auditing information related to the blacklist have certain repetition rate, the blacklist is considered, the loan application is refused and the blacklist database is added, so that the situation that the information submitted by the user is irrelevant to the information of the auditing information related to the blacklist, and misjudgment occurs is avoided, and the accuracy of the user for applying the loan is ensured.
If the repetition rate does not exist between the converted information and the blacklist related audit information, classifying the user as a white list, storing the white list into a white list database, and correspondingly updating the black list database to grant loan approval to the user.
And comparing the information required by blacklist auditing after each item of information of the loan user is converted by the information verification module, if the converted information has a certain repetition rate with blacklist related auditing information, considering the blacklist, refusing the loan application and adding the blacklist database.
The risk early warning management module is used for setting early warning indexes, early warning functions and early warning thresholds of various risk projects, setting constituent elements of the early warning indexes, calculating the risk degree of account funds of users, sending early warning to blacklist users, refusing loan application, and sending repayment early warning signals to users according to adjustment of residual values of loan users.
A risk early warning management module comprising:
and the fund risk early warning module is used for setting early warning indexes, early warning functions and early warning thresholds of various risk items, setting constituent elements of the early warning indexes, setting the early warning functions and the early warning thresholds according to the constituent elements, and calculating the risk degree of account fund of a user.
And the black-and-white list early warning module is used for sending the user confirmed as the black list to the black list database, and sending the black list early warning to the user so as to reject the loan application.
And the money early warning module is used for performing digital redundancy processing on the user fund data and the preset user fund to obtain a user residual value of the user, and sending a repayment early warning signal to the user according to adjustment of the user residual value.
A fund risk early warning module comprising:
and calculating the ratio of the cash income to the cash expenditure of the user, and reflecting the ratio relation of the cash income to the cash expenditure of the user.
If the ratio is smaller than 1, the cash income of the user is smaller than the cash expenditure, triggering a first-level risk early warning, and further auditing the loan application of the user;
if the proportion is greater than 1, the cash income of the user is greater than the cash expenditure, and balance exists in the user account, the secondary risk early warning is triggered, and the loan application of the user is approved.
The corresponding risk early warning is determined by comparing the user cash income with the cash expenditure of the user, and whether the loan is approved or not is carried out according to the corresponding risk level, so that the reliability of the user loan is further ensured, and the situation that the repayment is difficult due to unmatched user income and expenditure is avoided.
Money early warning module includes:
and presetting repayment funds of the user.
And performing data redundancy processing on the balance fund data of the user account and the preset user repayment fund to obtain a user residual value.
And calculating a corresponding repayment difference according to the residual value of the user, and sending a repayment early warning signal to the user according to the repayment difference.
Through carrying out the redundant processing of the data of the funds of the loan user and the funds of the preset user, the user's remainder value is obtained, and a repayment early warning signal is sent to the user according to the adjustment of the user's remainder value, so that the user can pay normally, the user's experience is improved, and the overdue situation caused by insufficient repayment amount is avoided.
In order to better realize the use method of the loan money early warning management system, the method comprises the following steps:
step one: the method comprises the steps of collecting identity information, assets, liability information and income conditions of a user through an information collecting module, inputting and reading the identity information, the assets, liability information and income conditions submitted by the user, establishing a corresponding user database, searching information provided by the user and related audit information of a black-and-white list, screening out different information, transmitting the information to a grading module for grading, wherein each grade corresponds to one fractional segment, and determining blacklist grade standards of the user according to the fractional segments.
Step two: establishing a black-and-white list information base, carrying out batch confirmation on the information of the loan users to be confirmed, which is acquired by the information acquisition module, by utilizing the black-and-white list information base, adding the users which are confirmed to be white lists into a white list base list, setting the lists outside the white lists as primary black list users and secondary black list users, adding the primary black list users into a black list database, and simultaneously, carrying out rechecking on the secondary black list users.
Step three: and calling out the user identity information, the assets, the liability information and the income situation from the database, automatically matching the user information acquired by the information acquisition module with the information called out from the database by the information calling-out module, rechecking the information which is matched by the information automatic matching module and is different from the verification information related to the blacklist, if the blacklist standard is met, refusing the loan application, if the blacklist standard is not met, classifying the user as a white list, storing the white list into the white list database, and correspondingly updating the black list database.
Step four: setting early warning indexes, early warning functions and early warning thresholds of various risk items, setting constituent elements of the early warning indexes, calculating the risk degree of account funds of a user, simultaneously sending the user confirmed as a blacklist to a blacklist database, sending blacklist early warning to the user, refusing a loan application, approving a permitted loan to the whitelist user, performing digital data redundancy processing on the fund data of the loan user and preset user funds to obtain the user residual value of the user, and sending a repayment early warning signal to the user according to the adjustment of the user residual value.
In summary, according to the loan deposit early warning management system disclosed by the invention, different information is converted into the information of the audit information related to the blacklist, if the converted information and the blacklist related audit information have a certain repetition rate, the blacklist is considered, the loan application is refused and added into the blacklist database, so that the situation that the information submitted by a user is irrelevant to the information of the blacklist related audit information, further misjudgment occurs, the accuracy of the loan application of the user is ensured, the corresponding risk early warning is determined by comparing the cash income and the cash expenditure of the user, and whether the loan is approved or not is performed according to the corresponding risk level, the reliability of the user loan is further ensured, the situation that difficulty occurs due to mismatching of income and expenditure of the user is avoided, the user residue value of the user is obtained by carrying out a number redundancy processing on the fund data of the loan user and the preset user funds, the user is ensured to be normally carried out repayment according to the adjustment of the user residue value, the user is prevented from experiencing sense of use of the user, and the condition that the overdue deposit is avoided.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should be covered by the protection scope of the present invention by making equivalents and modifications to the technical solution and the inventive concept thereof.
Claims (10)
1. A loan money early-warning management system, characterized by comprising:
the information acquisition module is used for acquiring user identity information, assets, liability information and income conditions, establishing a database, acquiring user information at the same time through identifiers in the database, dividing the user into a plurality of grades, wherein each grade corresponds to a fraction segment, and determining whether the user reaches a blacklist standard according to the fraction segment;
the list base management service module is used for accessing the business blacklist database according to the identity authorization information of the user, matching the business blacklist database, judging whether the user is a blacklist user, determining whether the user can handle loan business according to the judging result, entering a loan approval process if the user is a whitelist user, not handling loan business if the user is a blacklist user, and uploading information to the information verification module for verification;
the information verification module is used for inputting and reading identity information, assets, liability information and income conditions submitted by a user, automatically matching the information with the information of the user in the database, determining the information as a blacklist user if the information is matched with the information of the user in the database, rejecting a loan request of the user, removing the user from the blacklist database if the information is matched with the information in the database, and rechecking the user if the information is not matched with the information;
the risk early warning management module is used for setting early warning indexes, early warning functions and early warning thresholds of various risk projects, setting constituent elements of the early warning indexes, calculating the risk degree of account funds of users, sending early warning to blacklist users, refusing loan application, and sending repayment early warning signals to users according to adjustment of residual values of loan users.
2. The loan money early warning management system of claim 1, wherein the information acquisition module comprises:
the information receiving and reading module is used for inputting and reading identity information, assets, liability information and income conditions submitted by a user;
the searching module is used for searching the data provided by the user and the related auditing information of the black-white list, screening out different information and transmitting the information to the grading module for grading;
and the grading module is used for dividing the user into a plurality of grades, each grade corresponds to one fractional segment, determining the blacklist grade standard of the user according to the fractional segment, and determining whether to approve the loan according to the grade standard of the blacklist, wherein the lower the grade is, the higher the passing rate of the loan is.
3. The loan money early warning management system of claim 2, wherein the information receiving and reading module comprises:
the information receiving module is used for receiving identity information, assets, liability information and income conditions submitted by the user;
and the conversion module is used for collecting and identifying the information uploaded by the user, converting the collected information into characters, and uploading the characters to the retrieval module for retrieving the black-and-white list.
4. The loan money early warning management system of claim 1, wherein the information verification module comprises:
the information calling module is used for calling out the user identity information, the assets, the liability information and the income situation from the database;
the information automatic matching module is used for automatically matching the user information acquired by the information acquisition module with the information called out by the information calling-out module from the database;
and the information auditing module is used for rechecking the information which is matched by the information automatic matching module and is different from the auditing information related to the blacklist, refusing the loan application if the blacklist standard is met, classifying the user as a white list if the blacklist standard is not met, storing the white list into a white list database and correspondingly updating the black list database.
5. The loan money early warning management system of claim 4, wherein the information auditing module comprises:
rechecking the information which is searched by the search module and is different from the information related to the blacklist;
converting different information into information of auditing information related to a blacklist, if the converted information and the auditing information related to the blacklist have a certain repetition rate, considering the blacklist, refusing the loan application and adding the blacklist database;
if the repetition rate does not exist between the converted information and the blacklist related audit information, classifying the user as a white list, storing the white list into a white list database, and correspondingly updating the black list database to grant loan approval to the user.
6. The loan money early warning management system of claim 1, wherein the list bank management service module comprises:
the black-and-white list information base is used for storing auditing information for confirming the black-and-white list;
the list confirmation module is used for carrying out batch confirmation on the information of the loan users to be confirmed, which is acquired by the information acquisition module, by utilizing the black-and-white list information base, adding the users confirmed to be white lists into a white list base list, setting the lists outside the white lists as primary black list users and secondary black list users, adding the primary black list users into the black list database, and simultaneously carrying out rechecking on the secondary black list users;
and the list checking module is used for checking the user confirmed as the primary blacklist, and transmitting the user confirmed as the secondary blacklist to the information verification module for checking again.
7. The loan money early warning management system of claim 6, wherein the list confirmation module comprises:
matching the information submitted by the user with the information in the black-and-white list information base;
if the coincidence rate of the information submitted by the user and the information in the blacklist database exceeds 70%, confirming that the user is a first-level blacklist user, adding the risk to the blacklist database and refusing the loan application;
if the coincidence rate of the information submitted by the user and the information in the blacklist database is less than 70% and greater than 20%, confirming the information as a secondary blacklist user, and entering the next examination;
if the coincidence rate of the information submitted by the user and the information in the blacklist database is less than 20%, confirming the information as a whitelist, applying for loan, and adding the list into the whitelist database.
8. The loan money early-warning management system of claim 1, wherein the risk early-warning management module comprises:
the fund risk early warning module is used for setting early warning indexes, early warning functions and early warning thresholds of various risk items, setting constituent elements of the early warning indexes, setting the early warning functions and the early warning thresholds according to the constituent elements, and calculating the risk degree of account funds of a user;
the black-and-white list early warning module is used for sending the user confirmed as the black list to the black list database, and sending out black list early warning for the user so as to reject the loan application;
and the money early warning module is used for performing digital redundancy processing on the user fund data and the preset user fund to obtain a user residual value of the user, and sending a repayment early warning signal to the user according to adjustment of the user residual value.
9. The loan money early-warning management system of claim 7, wherein the fund risk early-warning module comprises:
calculating the ratio of the cash income to the cash expenditure of the user, and reflecting the ratio relation of the cash income to the cash expenditure of the user;
if the ratio is smaller than 1, the cash income of the user is smaller than the cash expenditure, triggering a first-level risk early warning, and further auditing the loan application of the user;
if the proportion is greater than 1, the cash income of the user is greater than the cash expenditure, and balance exists in the user account, the secondary risk early warning is triggered, and the loan application of the user is approved.
10. The loan funds warning management system of claim 7, wherein the funds warning module comprises:
presetting repayment funds of a user;
performing a digital redundancy process on the balance fund data of the user account and the preset user repayment fund to obtain a user residual value;
and calculating a corresponding repayment difference according to the residual value of the user, and sending a repayment early warning signal to the user according to the repayment difference.
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Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003090134A2 (en) * | 2002-04-19 | 2003-10-30 | Intersolve Limited | Computer system for the management of loans |
| US20030229581A1 (en) * | 2000-03-03 | 2003-12-11 | Green Timothy T. | System and Method for Automated Loan Compliance Assessment |
| WO2010022155A1 (en) * | 2008-08-19 | 2010-02-25 | Alibaba Group Holding Limited | Credit risk control |
| US20100332410A1 (en) * | 2009-06-25 | 2010-12-30 | Robert Scott Brown | Microfinance funds aggregation for a retail investor |
| US20120246060A1 (en) * | 2011-03-25 | 2012-09-27 | LoanHD, Inc. | Loan management, real-time monitoring, analytics, and data refresh system and method |
| CN107730377A (en) * | 2017-09-30 | 2018-02-23 | 平安科技（深圳）有限公司 | Qualification of providing a loan screening technique, device and computer-readable recording medium |
| CN109670929A (en) * | 2018-09-13 | 2019-04-23 | 深圳壹账通智能科技有限公司 | Control method, device, equipment and the computer readable storage medium of loan early warning |
| WO2019079708A1 (en) * | 2017-10-20 | 2019-04-25 | Idm Global, Inc. | Enhanced system and method for identity evaluation using a global score value |
| CN110210702A (en) * | 2019-04-24 | 2019-09-06 | 深圳融信网金信息科技有限公司 | Big data intelligent excavating analysis method, system, terminal device based on block chain |
| CN112348664A (en) * | 2020-10-28 | 2021-02-09 | 富邦华一银行有限公司 | Credit credit information management system supporting automatic early warning |
| CN113327161A (en) * | 2021-06-24 | 2021-08-31 | 国槐(上海)信息科技有限公司 | Intelligent wind control decision system for credit business |
| CN113935822A (en) * | 2021-09-24 | 2022-01-14 | 四川享宇金信金融科技有限公司 | Loan verification method, system and equipment based on agriculture and animal husbandry |
| CN113989017A (en) * | 2021-10-20 | 2022-01-28 | 中国农业银行股份有限公司河北省分行 | Post-loan risk early warning device and method for public clients |
| CN114219604A (en) * | 2021-11-09 | 2022-03-22 | 中国建设银行股份有限公司 | House loan service processing method, device, equipment and storage medium |
| CN114331692A (en) * | 2021-12-31 | 2022-04-12 | 中科柏诚科技（北京）股份有限公司 | Loan black intermediary prediction method and system based on social relationship |
| CN114463112A (en) * | 2021-12-31 | 2022-05-10 | 中科柏诚科技（北京）股份有限公司 | Loan risk prediction method and system |
| CN114493843A (en) * | 2022-01-27 | 2022-05-13 | 中国建设银行股份有限公司 | Business approval method and device, electronic equipment and computer readable medium |
| CN115564564A (en) * | 2022-09-30 | 2023-01-03 | 中国农业银行股份有限公司贵州省分行 | Public accumulation fund credit loan risk monitoring system |
-
2023
- 2023-02-15 CN CN202310125949.3A patent/CN116308736B/en active Active
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030229581A1 (en) * | 2000-03-03 | 2003-12-11 | Green Timothy T. | System and Method for Automated Loan Compliance Assessment |
| WO2003090134A2 (en) * | 2002-04-19 | 2003-10-30 | Intersolve Limited | Computer system for the management of loans |
| WO2010022155A1 (en) * | 2008-08-19 | 2010-02-25 | Alibaba Group Holding Limited | Credit risk control |
| US20100332410A1 (en) * | 2009-06-25 | 2010-12-30 | Robert Scott Brown | Microfinance funds aggregation for a retail investor |
| US20120246060A1 (en) * | 2011-03-25 | 2012-09-27 | LoanHD, Inc. | Loan management, real-time monitoring, analytics, and data refresh system and method |
| CN107730377A (en) * | 2017-09-30 | 2018-02-23 | 平安科技（深圳）有限公司 | Qualification of providing a loan screening technique, device and computer-readable recording medium |
| WO2019079708A1 (en) * | 2017-10-20 | 2019-04-25 | Idm Global, Inc. | Enhanced system and method for identity evaluation using a global score value |
| CN109670929A (en) * | 2018-09-13 | 2019-04-23 | 深圳壹账通智能科技有限公司 | Control method, device, equipment and the computer readable storage medium of loan early warning |
| CN110210702A (en) * | 2019-04-24 | 2019-09-06 | 深圳融信网金信息科技有限公司 | Big data intelligent excavating analysis method, system, terminal device based on block chain |
| CN112348664A (en) * | 2020-10-28 | 2021-02-09 | 富邦华一银行有限公司 | Credit credit information management system supporting automatic early warning |
| CN113327161A (en) * | 2021-06-24 | 2021-08-31 | 国槐(上海)信息科技有限公司 | Intelligent wind control decision system for credit business |
| CN113935822A (en) * | 2021-09-24 | 2022-01-14 | 四川享宇金信金融科技有限公司 | Loan verification method, system and equipment based on agriculture and animal husbandry |
| CN113989017A (en) * | 2021-10-20 | 2022-01-28 | 中国农业银行股份有限公司河北省分行 | Post-loan risk early warning device and method for public clients |
| CN114219604A (en) * | 2021-11-09 | 2022-03-22 | 中国建设银行股份有限公司 | House loan service processing method, device, equipment and storage medium |
| CN114331692A (en) * | 2021-12-31 | 2022-04-12 | 中科柏诚科技（北京）股份有限公司 | Loan black intermediary prediction method and system based on social relationship |
| CN114463112A (en) * | 2021-12-31 | 2022-05-10 | 中科柏诚科技（北京）股份有限公司 | Loan risk prediction method and system |
| CN114493843A (en) * | 2022-01-27 | 2022-05-13 | 中国建设银行股份有限公司 | Business approval method and device, electronic equipment and computer readable medium |
| CN115564564A (en) * | 2022-09-30 | 2023-01-03 | 中国农业银行股份有限公司贵州省分行 | Public accumulation fund credit loan risk monitoring system |
Non-Patent Citations (2)
| Title |
|---|
| 刘扬;姬建华;: "大数据在传统贷款风控中的应用", 科技传播, no. 03, 10 February 2018 (2018-02-10), pages 119 - 120 * |
| 湛韬;张晖;: "政银合作扶持新型农业经营主体发展模式探讨――以南京市"金陵惠农贷"为例", 新疆农垦经济, no. 08, 15 August 2020 (2020-08-15), pages 68 - 74 * |
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