CN117670510B - Small loan management system - Google Patents
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Abstract
The invention discloses a small loan management system, which relates to the technical field of small loan management, and comprises a basic information acquisition module, a loan information analysis module, a risk information analysis module, a credit information analysis module, a repayment interest analysis module, a display terminal and a database.
Description
Technical Field
The invention relates to the technical field of small loan management, in particular to a small loan management system.
Background
The small loan management technology is used for realizing comprehensive and automatic management of loans, effectively reducing complicated loan flows, enabling the loans to become efficient, relieving the burden of staff, improving the loan efficiency, and simultaneously, effectively reducing risks caused by loan of each user by evaluating basic information of each user and guaranteeing own interests and reputation of the user.
The current way of petty loan management is mainly operated by manual work, and the flow of the manual management loan is comparatively tedious, and consumes a great deal of time and energy, so that the loan efficiency is greatly reduced, the burden of staff is increased to a certain extent along with the increase of the user loan quantity, the satisfaction degree of user handling is reduced, and meanwhile, when the user handles the loan, accurate identification cannot be realized on the information filled by the user, so that the risk generated by the user loan is increased, and the benefit of the user is lost.
Disclosure of Invention
In view of the above-mentioned technical shortcomings, it is an object of the present invention to provide a small loan management system.
In order to solve the technical problems, the invention adopts the following technical scheme: the invention provides a small loan management system, comprising: the basic information acquisition module is used for acquiring basic information corresponding to each user, wherein the basic information comprises occupation, company name, working income and personal social security payment duration, further screening to obtain the information authenticity corresponding to each user, returning the application corresponding to a certain user if the basic information corresponding to the user is not authentic, enabling the user to refill a loan application until the basic information filled by the user is authentic, carrying out loan application filling, and analyzing to obtain the capability assessment coefficient corresponding to each user;
The loan information analysis module is used for obtaining loan information corresponding to each user, wherein the loan information comprises loan number, repayment duration and loan times, and further analyzing and obtaining loan assessment coefficients corresponding to each user;
The risk information analysis module is used for analyzing and obtaining the risk assessment coefficient corresponding to each user according to the capability assessment coefficient and the loan assessment coefficient corresponding to each user, judging the loan application limit corresponding to each user, if the loan application limit of a certain user is met, allowing the management system to pass through the loan approval of the user, and if the loan application limit of a certain user is not met, allowing the loan management system center to automatically analyze and generate an applicable loan limit interval for the user and feed back the applicable loan limit interval to the user for the user to select;
The credit information analysis module is used for acquiring repayment information corresponding to each user, wherein the repayment information comprises early repayment times, repayment speeds, overdue times and overdue time, further analyzing and obtaining credit evaluation coefficients corresponding to each user, judging credit states corresponding to each user according to the credit evaluation coefficients corresponding to each user, marking the user as a target user if the credit corresponding to a certain user is good, further marking the user as a correction user if the credit corresponding to the certain user is bad, and providing corresponding repayment interest amount for each correction user by the loan management system;
the repayment interest analysis module is used for further calculating repayment interest de-rating corresponding to each target user and repayment interest adjustment values corresponding to each correction user according to the credit evaluation coefficients corresponding to each user, and the loan management system sends calculation results to each target user and each correction user respectively;
and the display terminal is used for displaying all target users with good credit and all correction users with bad credit.
Preferably, the filtering obtains the information fidelity corresponding to each user, and the specific filtering process is as follows: based on the payroll income of each professional user corresponding to each company stored in the database, further calculating the average value of the payroll income of each professional user corresponding to each company stored in the database, so as to obtain the reference payroll income of each professional user corresponding to each company stored in the database, and marking the reference payroll income as K';
Comparing the payroll income corresponding to each company of each professional user with the reference payroll income interval corresponding to each company of each professional user stored in the database, if the payroll income corresponding to each company of a certain professional user is within the reference payroll income interval corresponding to a certain company of a certain professional user stored in the database, marking the payroll income corresponding to the company of the professional user as a reference payroll income allowance value, thereby obtaining a reference payroll income allowance value corresponding to each company of each professional user, and marking the reference payroll income allowance value as delta K;
By calculation formula And screening to obtain information fidelity BETA h corresponding to the h user, wherein h represents the number corresponding to each user, h=1, 2.
Preferably, the analysis obtains the capacity evaluation coefficient corresponding to each user, and the specific analysis process is as follows: by calculation formulaThe capacity evaluation coefficient lambda h corresponding to each user is obtained through analysis, wherein m' is the preset personal social security payment duration, m h is the personal social security payment duration corresponding to the h-th user, delta m is the preset personal social security payment duration permission difference value, q 1、q2 is the preset working income and the weight factor of the personal social security payment duration, and q 1＜1,0＜q2 is more than 0 and less than 1.
Preferably, the analysis obtains the loan assessment coefficient corresponding to each user, and the specific analysis process is as follows: by calculation formulaAnd further analyzing to obtain a loan evaluation coefficient phi h corresponding to the h user, wherein h represents the number corresponding to each user, h=1, 2.
Preferably, the analysis obtains risk assessment coefficients corresponding to each user, and the specific analysis process is as follows: the risk assessment coefficient beta h corresponding to the h user is obtained through analysis through a calculation formula beta h＝ν1*λh+ν2*Φh, h represents the number corresponding to each user, h=1, 2.
Preferably, the determining the loan application amount corresponding to each user includes the following specific determining process: and comparing the risk assessment coefficient corresponding to each user with a risk assessment coefficient threshold stored in a database, judging that the loan application amount corresponding to the user is not met if the risk assessment coefficient corresponding to a certain user is smaller than the risk assessment coefficient threshold stored in the database, and judging that the loan application amount corresponding to the user is met if the risk assessment coefficient corresponding to a certain user is larger than or equal to the risk assessment coefficient threshold stored in the database, so as to judge the loan application amount corresponding to each user.
Preferably, the analysis obtains credit evaluation coefficients corresponding to each user, and the specific analysis process is as follows: by calculation formula
And further analyzing to obtain the credit evaluation coefficient/>, corresponding to the h userH represents the number corresponding to each user, h=1, 2..y, y is any integer greater than 2, δ "is a preset advance payoff number,/>For the preset repayment speed, phi 'is the preset overdue number, gamma' is the preset overdue duration, delta h is the advanced repayment number corresponding to the h user,/>For the repayment speed corresponding to the h user, phi h is the overdue number corresponding to the h user, gamma h is the overdue duration corresponding to the h user, delta phi is the preset overdue number permission difference, delta gamma is the preset overdue duration permission difference, and c 1、c2、c3、c4 is the preset weight factors of the advanced repayment number, repayment speed, overdue number and overdue duration, wherein 0< c 1＜1,0＜c2＜1,0＜c3＜1,0＜c4 < 1.
Preferably, the specific judgment process for judging the credit status corresponding to each user is as follows: comparing the credit evaluation coefficient corresponding to each user with the credit evaluation coefficient threshold stored in the database, judging that the credit corresponding to a user is bad if the credit evaluation coefficient corresponding to the user is smaller than the credit evaluation coefficient threshold stored in the database, marking the user as a correction user, judging that the credit corresponding to the user is good if the credit evaluation coefficient corresponding to the user is larger than or equal to the credit evaluation coefficient threshold stored in the database, marking the user as a target user, judging the credit state corresponding to each user, and obtaining each target user and each correction user.
Preferably, the calculating obtains the repayment interest amount reduction corresponding to each target user and the repayment interest adjustment value when the repayment interest amount is increased corresponding to each correction user, and the specific analysis process is as follows: comparing the credit evaluation coefficient corresponding to each target user with the credit evaluation coefficient corresponding to each repayment interest amount stored in the database, and if the credit evaluation coefficient corresponding to a certain target user is the same as the credit evaluation coefficient corresponding to a certain repayment interest amount stored in the database, taking the repayment interest amount as the repayment interest amount corresponding to the target user, so as to obtain the repayment interest amount corresponding to each target user and taking the repayment interest amount as a repayment interest amount adjustment value corresponding to each target user;
And comparing the credit evaluation coefficient corresponding to each correction user with the credit evaluation coefficient corresponding to each repayment interest increment stored in the database, and if the credit evaluation coefficient corresponding to a certain correction user is the same as the credit evaluation coefficient corresponding to a certain repayment interest increment stored in the database, taking the repayment interest increment as the repayment interest increment corresponding to the correction user, so as to obtain the repayment interest increment corresponding to each correction user and taking the repayment interest increment as a repayment interest increment adjustment value corresponding to each correction user.
Preferably, the system further comprises a database for storing basic information, loan information, repayment information, risk assessment coefficient threshold values, credit assessment coefficient threshold values.
Compared with the prior art, the invention has the beneficial effects that: the invention provides a small loan management system, which better judges the loan application limit corresponding to each user by analyzing the risk assessment coefficient corresponding to each user, provides various selection schemes for non-conforming users, and further better monitors loan credits of each user, provides benefit lowering benefits for each target user with good loan credits, provides satisfied loan application service for each user, solves the defects existing in the prior art, provides comprehensive and automatic service, effectively simplifies complicated loan flow, improves the loan application handling efficiency, reduces the burden of staff, saves a great deal of time and energy, effectively presents convenience and intelligence of the loan management system, and simultaneously avoids risks generated by loan of each user in time by carefully knowing and analyzing each user, and effectively ensures own benefits.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the system structure 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.
Referring to fig. 1, a small loan management system includes a basic information acquisition module, a loan information analysis module, a risk information analysis module, a credit information analysis module, a repayment interest analysis module, a display terminal and a database.
The database is respectively connected with the basic information acquisition module, the loan information analysis module and the credit information analysis module, the basic information acquisition module is respectively connected with the loan information analysis module and the risk information analysis module, and the credit information analysis module is respectively connected with the repayment interest analysis module and the display terminal.
The basic information acquisition module is used for acquiring basic information corresponding to each user, wherein the basic information comprises occupation, company name, working income and personal social security payment duration, further screening to obtain the information authenticity corresponding to each user, returning the application corresponding to a certain user if the basic information corresponding to the user is not authentic, enabling the user to refill a loan application until the basic information filled by the user is authentic, carrying out loan application filling, and analyzing to obtain the capability assessment coefficient corresponding to each user;
when the user handles the small amount of loan, the loan management system enables each user to apply for filling the basic information of the loan when handling the loan, and the user submits the basic information after filling the basic information of the loan, and then uploads the basic information of the loan to the loan management system and stores the basic information in the database.
As an optional implementation manner, the filtering obtains the information fidelity corresponding to each user, and the specific filtering process is as follows: based on the payroll income of each professional user corresponding to each company stored in the database, further calculating the average value of the payroll income of each professional user corresponding to each company stored in the database, so as to obtain the reference payroll income of each professional user corresponding to each company stored in the database, and marking the reference payroll income as K';
Comparing the payroll income corresponding to each company of each professional user with the reference payroll income interval corresponding to each company of each professional user stored in the database, if the payroll income corresponding to each company of a certain professional user is within the reference payroll income interval corresponding to a certain company of a certain professional user stored in the database, marking the payroll income corresponding to the company of the professional user as a reference payroll income allowance value, thereby obtaining a reference payroll income allowance value corresponding to each company of each professional user, and marking the reference payroll income allowance value as delta K;
By calculation formula And screening to obtain information fidelity BETA h corresponding to the h user, wherein h represents the number corresponding to each user, h=1, 2.
As an optional implementation manner, the analysis obtains the capability assessment coefficient corresponding to each user, and the specific analysis process is as follows: by calculation formulaThe capacity evaluation coefficient lambda h corresponding to each user is obtained through analysis, wherein m' is the preset personal social security payment duration, m h is the personal social security payment duration corresponding to the h-th user, delta m is the preset personal social security payment duration permission difference value, q 1、q2 is the preset working income and the weight factor of the personal social security payment duration, and q 1＜1,0＜q2 is more than 0 and less than 1.
The loan information analysis module is used for obtaining loan information corresponding to each user, wherein the loan information comprises loan number, repayment duration and loan times, and further analyzing and obtaining loan assessment coefficients corresponding to each user;
When the user handles the small amount of loan, the loan management system makes the user submit the loan information application after the completion of the loan information application, and then uploads the loan information application to the loan management system and stores the loan information application in the database, and the loan application of each user is accumulated and added to obtain the corresponding loan times of each user and stored in the database.
As an alternative implementation manner, the analysis obtains the loan assessment coefficient corresponding to each user, and the specific analysis process is as follows: by calculation formulaAnd further analyzing to obtain a loan evaluation coefficient phi h corresponding to the h user, wherein h represents the number corresponding to each user, h=1, 2.
The risk information analysis module is used for analyzing and obtaining the risk assessment coefficient corresponding to each user according to the capability assessment coefficient and the loan assessment coefficient corresponding to each user, judging the loan application limit corresponding to each user, if the loan application limit of a certain user is met, allowing the management system to pass through the loan approval of the user, and if the loan application limit of a certain user is not met, allowing the loan management system center to automatically analyze and generate an applicable loan limit interval for the user and feed back the applicable loan limit interval to the user for the user to select;
As an optional implementation manner, the analysis obtains risk assessment coefficients corresponding to each user, and the specific analysis process is as follows: the risk assessment coefficient beta h corresponding to the h user is obtained through analysis through a calculation formula beta h＝ν1*λh+ν2*Φh, h represents the number corresponding to each user, h=1, 2.
As an optional implementation manner, the determining the loan application amount corresponding to each user specifically includes the following steps: and comparing the risk assessment coefficient corresponding to each user with a risk assessment coefficient threshold stored in a database, judging that the loan application amount corresponding to the user is not met if the risk assessment coefficient corresponding to a certain user is smaller than the risk assessment coefficient threshold stored in the database, and judging that the loan application amount corresponding to the user is met if the risk assessment coefficient corresponding to a certain user is larger than or equal to the risk assessment coefficient threshold stored in the database, so as to judge the loan application amount corresponding to each user.
The credit information analysis module is used for acquiring repayment information corresponding to each user, wherein the repayment information comprises early repayment times, repayment speeds, overdue times and overdue time, further analyzing and obtaining credit evaluation coefficients corresponding to each user, judging credit states corresponding to each user according to the credit evaluation coefficients corresponding to each user, marking the user as a target user if the credit corresponding to a certain user is good, further marking the user as a correction user if the credit corresponding to the certain user is bad, and providing corresponding repayment interest amount for each correction user by the loan management system;
Note that, the repayment information corresponding to each user is obtained from the database corresponding to the loan management system.
As an optional implementation manner, the analysis obtains the credit evaluation coefficient corresponding to each user, and the specific analysis process is as follows: by calculation formula
And further analyzing to obtain the credit evaluation coefficient/>, corresponding to the h userH represents the number corresponding to each user, h=1, 2..y, y is any integer greater than 2, δ "is a preset advance payoff number,/>For the preset repayment speed, phi 'is the preset overdue number, gamma' is the preset overdue duration, delta h is the advanced repayment number corresponding to the h user,/>For the repayment speed corresponding to the h user, phi h is the overdue number corresponding to the h user, gamma h is the overdue duration corresponding to the h user, delta phi is the preset overdue number permission difference, delta gamma is the preset overdue duration permission difference, and c 1、c2、c3、c4 is the preset weight factors of the advanced repayment number, repayment speed, overdue number and overdue duration, wherein 0< c 1＜1,0＜c2＜1,0＜c3＜1,0＜c4 < 1.
As an optional implementation manner, the specific judging process is as follows: comparing the credit evaluation coefficient corresponding to each user with the credit evaluation coefficient threshold stored in the database, judging that the credit corresponding to a user is bad if the credit evaluation coefficient corresponding to the user is smaller than the credit evaluation coefficient threshold stored in the database, marking the user as a correction user, judging that the credit corresponding to the user is good if the credit evaluation coefficient corresponding to the user is larger than or equal to the credit evaluation coefficient threshold stored in the database, marking the user as a target user, judging the credit state corresponding to each user, and obtaining each target user and each correction user.
The repayment interest analysis module is used for further calculating repayment interest de-rating corresponding to each target user and repayment interest adjustment values corresponding to each correction user according to the credit evaluation coefficients corresponding to each user, and the loan management system sends calculation results to each target user and each correction user respectively;
As an optional implementation manner, the calculating obtains the repayment interest amount reduction corresponding to each target user and the repayment interest adjustment value when the repayment interest amount is increased corresponding to each correction user, and the specific analysis process is as follows: comparing the credit evaluation coefficient corresponding to each target user with the credit evaluation coefficient corresponding to each repayment interest amount stored in the database, and if the credit evaluation coefficient corresponding to a certain target user is the same as the credit evaluation coefficient corresponding to a certain repayment interest amount stored in the database, taking the repayment interest amount as the repayment interest amount corresponding to the target user, so as to obtain the repayment interest amount corresponding to each target user and taking the repayment interest amount as a repayment interest amount adjustment value corresponding to each target user;
And comparing the credit evaluation coefficient corresponding to each correction user with the credit evaluation coefficient corresponding to each repayment interest increment stored in the database, and if the credit evaluation coefficient corresponding to a certain correction user is the same as the credit evaluation coefficient corresponding to a certain repayment interest increment stored in the database, taking the repayment interest increment as the repayment interest increment corresponding to the correction user, so as to obtain the repayment interest increment corresponding to each correction user and taking the repayment interest increment as a repayment interest increment adjustment value corresponding to each correction user.
The database is used for storing basic information, loan information, repayment information, risk assessment coefficient threshold values and credit assessment coefficient threshold values.
And the display terminal is used for displaying all target users with good credit and all correction users with bad credit.
The invention provides a small loan management system, which better judges the loan application limit corresponding to each user by analyzing the risk assessment coefficient corresponding to each user, provides various selection schemes for non-conforming users, and further better monitors loan credits of each user, provides benefit lowering benefits for each target user with good loan credits, provides satisfied loan application service for each user, solves the defects existing in the prior art, provides comprehensive and automatic service, effectively simplifies complicated loan flow, improves the loan application handling efficiency, reduces the burden of staff, saves a great deal of time and energy, effectively presents convenience and intelligence of the loan management system, and simultaneously avoids risks generated by loan of each user in time by carefully knowing and analyzing each user, and effectively ensures own benefits.
The foregoing is merely illustrative and explanatory of the principles of the invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of the invention or beyond the scope of the invention as defined in the description.
Claims (9)
1. A small loan management system, comprising:
The basic information acquisition module is used for acquiring basic information corresponding to each user, wherein the basic information comprises occupation, company name, working income and personal social security payment duration, further screening to obtain the information authenticity corresponding to each user, returning the application corresponding to a certain user if the basic information corresponding to the user is not authentic, enabling the user to refill a loan application until the basic information filled by the user is authentic, carrying out loan application filling, and analyzing to obtain the capability assessment coefficient corresponding to each user;
The loan information analysis module is used for obtaining loan information corresponding to each user, wherein the loan information comprises loan number, repayment duration and loan times, and further analyzing and obtaining loan assessment coefficients corresponding to each user;
The risk information analysis module is used for analyzing and obtaining the risk assessment coefficient corresponding to each user according to the capability assessment coefficient and the loan assessment coefficient corresponding to each user, judging the loan application limit corresponding to each user, if the loan application limit of a certain user is met, allowing the management system to pass through the loan approval of the user, and if the loan application limit of a certain user is not met, allowing the loan management system center to automatically analyze and generate an applicable loan limit interval for the user and feed back the applicable loan limit interval to the user for the user to select;
The credit information analysis module is used for acquiring repayment information corresponding to each user, wherein the repayment information comprises early repayment times, repayment speeds, overdue times and overdue time, further analyzing and obtaining credit evaluation coefficients corresponding to each user, judging credit states corresponding to each user according to the credit evaluation coefficients corresponding to each user, marking the user as a target user if the credit corresponding to a certain user is good, further marking the user as a correction user if the credit corresponding to the certain user is bad, and providing corresponding repayment interest amount for each correction user by the loan management system;
the credit evaluation coefficients corresponding to the users are obtained through analysis, and the specific analysis process is as follows:
By calculation formula And further analyzing to obtain the credit evaluation coefficient/>, corresponding to the h userH represents the number corresponding to each user, h=1, 2..y, y is any integer greater than 2, δ "is a preset advance payoff number,/>For the preset repayment speed, phi 'is the preset overdue number, gamma' is the preset overdue duration, delta h is the advanced repayment number corresponding to the h user,/>For the repayment speed corresponding to the h user, phi h is the overdue number corresponding to the h user, gamma h is the overdue duration corresponding to the h user, delta phi is the preset overdue number permission difference, delta gamma is the preset overdue duration permission difference, and c 1、c2、c3、c4 is the preset weight factors of the advanced repayment number, repayment speed, overdue number and overdue duration, wherein 0< c 1＜1,0＜c2＜1,0＜c3＜1,0＜c4 < 1;
the repayment interest analysis module is used for further calculating repayment interest de-rating corresponding to each target user and repayment interest adjustment values corresponding to each correction user according to the credit evaluation coefficients corresponding to each user, and the loan management system sends calculation results to each target user and each correction user respectively;
and the display terminal is used for displaying all target users with good credit and all correction users with bad credit.
2. The small loan management system of claim 1, wherein the filtering obtains the information fidelity corresponding to each user, and the specific filtering process is as follows:
Based on the payroll income of each professional user corresponding to each company stored in the database, further calculating the average value of the payroll income of each professional user corresponding to each company stored in the database, so as to obtain the reference payroll income of each professional user corresponding to each company stored in the database, and marking the reference payroll income as K';
Comparing the payroll income corresponding to each company of each professional user with the reference payroll income interval corresponding to each company of each professional user stored in the database, if the payroll income corresponding to each company of a certain professional user is within the reference payroll income interval corresponding to a certain company of a certain professional user stored in the database, marking the payroll income corresponding to the company of the professional user as a reference payroll income allowance value, thereby obtaining a reference payroll income allowance value corresponding to each company of each professional user, and marking the reference payroll income allowance value as delta K;
By calculation formula And screening to obtain information fidelity BETA h corresponding to the h user, wherein h represents the number corresponding to each user, h=1, 2.
3. The small loan management system of claim 2, wherein the analyzing obtains the ability evaluation coefficient corresponding to each user, and the specific analyzing process is as follows:
By calculation formula The capacity evaluation coefficient lambda h corresponding to each user is obtained through analysis, wherein m' is the preset personal social security payment duration, m h is the personal social security payment duration corresponding to the h-th user, delta m is the preset personal social security payment duration permission difference value, q 1、q2 is the preset working income and the weight factor of the personal social security payment duration, and q 1＜1,0＜q2 is more than 0 and less than 1.
4. The small loan management system of claim 1, wherein the analysis obtains the loan assessment coefficients corresponding to each user, and the specific analysis process is as follows:
By calculation formula And further analyzing to obtain a loan evaluation coefficient phi h corresponding to the h user, wherein h represents the number corresponding to each user, h=1, 2.
5. The small loan management system of claim 1, wherein the analyzing obtains risk assessment coefficients corresponding to each user, and the specific analyzing process is as follows:
The risk assessment coefficient beta h corresponding to the h user is obtained through analysis through a calculation formula beta h＝ν1*λh+ν2*Φh, h represents the number corresponding to each user, h=1, 2.
6. The small loan management system as recited in claim 1, wherein the determining the loan application amount corresponding to each user comprises the following steps:
And comparing the risk assessment coefficient corresponding to each user with a risk assessment coefficient threshold stored in a database, judging that the loan application amount corresponding to the user is not met if the risk assessment coefficient corresponding to a certain user is smaller than the risk assessment coefficient threshold stored in the database, and judging that the loan application amount corresponding to the user is met if the risk assessment coefficient corresponding to a certain user is larger than or equal to the risk assessment coefficient threshold stored in the database, so as to judge the loan application amount corresponding to each user.
7. The small loan management system of claim 1, wherein the determining the credit status corresponding to each user comprises the following steps:
comparing the credit evaluation coefficient corresponding to each user with the credit evaluation coefficient threshold stored in the database, judging that the credit corresponding to a user is bad if the credit evaluation coefficient corresponding to the user is smaller than the credit evaluation coefficient threshold stored in the database, marking the user as a correction user, judging that the credit corresponding to the user is good if the credit evaluation coefficient corresponding to the user is larger than or equal to the credit evaluation coefficient threshold stored in the database, marking the user as a target user, judging the credit state corresponding to each user, and obtaining each target user and each correction user.
8. The small loan management system of claim 1, wherein the calculating obtains the repayment interest amount reduction corresponding to each target user and the repayment interest adjustment value when the repayment interest amount increase corresponding to each correction user, and the specific analysis process is as follows:
Comparing the credit evaluation coefficient corresponding to each target user with the credit evaluation coefficient corresponding to each repayment interest amount stored in the database, and if the credit evaluation coefficient corresponding to a certain target user is the same as the credit evaluation coefficient corresponding to a certain repayment interest amount stored in the database, taking the repayment interest amount as the repayment interest amount corresponding to the target user, so as to obtain the repayment interest amount corresponding to each target user and taking the repayment interest amount as a repayment interest amount adjustment value corresponding to each target user;
And comparing the credit evaluation coefficient corresponding to each correction user with the credit evaluation coefficient corresponding to each repayment interest increment stored in the database, and if the credit evaluation coefficient corresponding to a certain correction user is the same as the credit evaluation coefficient corresponding to a certain repayment interest increment stored in the database, taking the repayment interest increment as the repayment interest increment corresponding to the correction user, so as to obtain the repayment interest increment corresponding to each correction user and taking the repayment interest increment as a repayment interest increment adjustment value corresponding to each correction user.
9. A small loan management system as recited in claim 1, further comprising a database for storing basic information, loan information, repayment information, risk assessment factor thresholds, credit assessment factor thresholds.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105512935A (en) * | 2015-12-01 | 2016-04-20 | 郑东东 | Borrowing and lending system based on mobile terminal |
| CN107464183A (en) * | 2017-07-03 | 2017-12-12 | 广州帝隆科技股份有限公司 | Debt-credit method, electronic equipment, storage medium and system based on internet |
| CN107993146A (en) * | 2018-01-25 | 2018-05-04 | 深圳市前海吉顺信科技发展有限公司 | The air control method and system of financial big data |
| CN108596773A (en) * | 2018-04-27 | 2018-09-28 | 中国太平洋保险（集团）股份有限公司 | A kind of control method for establishing subscriber household insurance cover combined system |
| CN109389491A (en) * | 2018-09-27 | 2019-02-26 | 深圳壹账通智能科技有限公司 | Loan product screening technique, device, equipment and storage medium based on big data |
| CN110223166A (en) * | 2019-06-14 | 2019-09-10 | 哈尔滨哈银消费金融有限责任公司 | The prediction technique and equipment of consumer finance user's overdue loan based on big data |
| CN112927071A (en) * | 2021-04-21 | 2021-06-08 | 顶象科技有限公司 | Post-loan behavior feature processing method and device |
| CN112991052A (en) * | 2021-04-25 | 2021-06-18 | 大箴(杭州)科技有限公司 | Repayment capability evaluation method and device |
| CN116258571A (en) * | 2023-01-12 | 2023-06-13 | 广东省中保小额贷款股份有限公司 | Loan inspection processing system and processing method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7734539B2 (en) * | 2007-04-25 | 2010-06-08 | Bank Of America Corporation | Calculating credit worthiness using transactional data |
-
2023
- 2023-11-30 CN CN202311620856.4A patent/CN117670510B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105512935A (en) * | 2015-12-01 | 2016-04-20 | 郑东东 | Borrowing and lending system based on mobile terminal |
| CN107464183A (en) * | 2017-07-03 | 2017-12-12 | 广州帝隆科技股份有限公司 | Debt-credit method, electronic equipment, storage medium and system based on internet |
| CN107993146A (en) * | 2018-01-25 | 2018-05-04 | 深圳市前海吉顺信科技发展有限公司 | The air control method and system of financial big data |
| CN108596773A (en) * | 2018-04-27 | 2018-09-28 | 中国太平洋保险（集团）股份有限公司 | A kind of control method for establishing subscriber household insurance cover combined system |
| CN109389491A (en) * | 2018-09-27 | 2019-02-26 | 深圳壹账通智能科技有限公司 | Loan product screening technique, device, equipment and storage medium based on big data |
| CN110223166A (en) * | 2019-06-14 | 2019-09-10 | 哈尔滨哈银消费金融有限责任公司 | The prediction technique and equipment of consumer finance user's overdue loan based on big data |
| CN112927071A (en) * | 2021-04-21 | 2021-06-08 | 顶象科技有限公司 | Post-loan behavior feature processing method and device |
| CN112991052A (en) * | 2021-04-25 | 2021-06-18 | 大箴(杭州)科技有限公司 | Repayment capability evaluation method and device |
| CN116258571A (en) * | 2023-01-12 | 2023-06-13 | 广东省中保小额贷款股份有限公司 | Loan inspection processing system and processing method |
Non-Patent Citations (3)
| Title |
|---|
| Alternative Scoring Factors using Non-Financial Data for Credit Decisions in Agricultural Microfinance;Naomi Simumba 等;《2018 IEEE International Systems Engineering Symposium (ISSE)》;20181129;第1-8页 * |
| What should lenders be more concerned about? Developing a profit-driven loan default prediction model;Lifang Zhang 等;《Expert Systems with Applications》;20230301;第213卷;第1-13页 * |
| 基于Cordova的微额快贷平台的设计与实现;吕丽粉;《中国优秀硕士学位论文全文数据库 信息科技辑》;20190215(第2期);第I138-524页 * |
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