CN116258571A - Loan inspection processing system and processing method - Google Patents
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Abstract
The invention belongs to the technical field of loan inspection, and discloses a loan inspection processing method, which comprises the following steps: acquiring credit investigation information of a borrower according to the identity information of the borrower; comparing the credit investigation information of the borrower with the preset credit investigation conditions for analysis, and rejecting the loan application of the borrower if the credit investigation information of the borrower does not accord with the preset credit investigation conditions; if the credit investigation information of the borrower accords with the preset credit investigation condition, generating a credit investigation information depth analysis signal; collecting borrower repayment information and borrower employment information, wherein the borrower employment information comprises a borrower employment prospect value and a borrower employment willingness value; carrying out formulated analysis on the foreground value of the career employment unit and the career employment wish value according to the foreground value of the career employment unit to obtain a career employment coefficient, and generating different risk employment marks for corresponding careers according to the size of the career employment coefficient; and grading the quality of the corresponding borrower according to the different risk repayment marks and the different risk employment marks.
Description
Technical Field
The invention relates to the technical field of loan inspection, in particular to a loan inspection processing system and a loan inspection processing method.
Background
The loan is an important financial business of a financial institution, and information of a borrower needs to be checked before loan release, wherein the two important checks comprise credit investigation of the borrower and fund running line inspection of the borrower, in a real situation, the fund running line of the borrower does not reach the standard, and the borrower is fake by the fund running line in order to meet the approval condition of the loan, so that the later-period default risk is increased, and therefore, the two checks cannot truly reflect the actual income condition and the actual repayment capability of the borrower, so that the quality grading accuracy of the existing loan check is low and the later-period default risk is large.
In view of this, the present inventors have discovered a loan inspection processing system and processing method.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide a loan inspection processing system and processing method.
In order to achieve the above purpose, the present invention provides the following technical solutions: a loan inspection processing method, comprising:
acquiring credit investigation information of a borrower according to the identity information of the borrower;
comparing the credit investigation information of the borrower with the preset credit investigation conditions for analysis, and rejecting the loan application of the borrower if the credit investigation information of the borrower does not accord with the preset credit investigation conditions; if the credit investigation information of the borrower accords with the preset credit investigation condition, generating a credit investigation information depth analysis signal;
Collecting borrow repayment information and borrow employment information according to a borrow information depth analysis signal, wherein the borrow repayment information comprises a borrow repayment pressure value and a borrow mortgage change value, and the borrow employment information comprises a borrow employment unit prospect value and a borrow employment willingness value;
carrying out formulated analysis on the loan repayment pressure value and the mortgage change value of the loan to obtain a loan repayment coefficient, and generating different risk repayment marks for corresponding loans according to the size of the loan repayment coefficient; carrying out formulated analysis on the foreground value of the career employment unit and the career employment wish value according to the foreground value of the career employment unit to obtain a career employment coefficient, and generating different risk employment marks for corresponding careers according to the size of the career employment coefficient;
and grading the quality of the corresponding borrower according to the different risk repayment marks and the different risk employment marks.
In a preferred embodiment, the borrower repayment pressure value obtaining step includes marking hyz the borrower repayment pressure value, and obtaining a total income value, a total expense value and a total surplus value n months before the borrower at the current moment, wherein the total surplus value is equal to a result value obtained by subtracting the total expense value from the total income value; the total income value comprises a bank card income value, a WeChat income value and a Payment device income value;
The total payout value comprises a total fixed payout value and a total floating payout, and the total fixed payout value obtaining process comprises the following steps: analyzing the n-month total expenditure value data, marking the names of the payees with the occurrence times equal to n as fixed payees, and marking the payees of the fixed payees for n months as total fixed expenditure values; the total floating payout value is equal to a result value of the total payout value minus the total fixed payout value;
dividing the total floating payment value by n to obtain a total floating payment average value, marking the total floating payment average value as y1, calculating to obtain a monthly payment value according to the loan amount, the payment period and the payment mode of the borrower, marking the monthly payment value as y2, and marking the sum of y1 and y2 as y3;
wherein y4 is a total surplus mean value, and the total surplus mean value is a result value obtained by dividing the total surplus value by n;
the present value of the borrower mortgage is calculated according to the formula if the borrower mortgage value is marked as 0 and if the borrower is a business
Where bxz is the borrower mortgage present value and the corporate mobile liabilities include the monthly repayment value for the present loan.
In a preferred embodiment, the step of obtaining the prospect value of the borrower employment unit includes obtaining the latest month social security payment unit name of the borrower, obtaining the latest N unit time tax payment amounts corresponding to the current unit name according to the unit name, arranging the N time tax payment amounts according to time sequence, calculating two adjacent tax payment amount difference values in sequence, marking the two adjacent tax payment amount difference values as p1, marking the result value of dividing the p1 by the tax payment amount with the adjacent two tax payment amounts with the time sequence front as p2, and marking the sum of all p2 in the N unit time as the prospect value of the borrower employment unit;
The step of obtaining the employment willingness value of the borrower comprises the steps of obtaining the name of a social security payment unit in k unit time of the borrower, marking the employment willingness value of the borrower as 1 if the name of the social security payment unit is consistent in k unit time, and marking the actual value of the employment willingness value of the borrower as r if the name of the social security payment unit is inconsistent in k unit time.
In a preferred embodiment, the low risk repayment signature, the stroke risk repayment signature, and the high risk repayment signature are generated by marking a borrower repayment pressure value and a borrower mortgage change value as hyzi and bxzi respectively, and performing formulated analysis to obtain a borrower repayment coefficient hkxi;
the low risk employment marking, the medium risk employment marking and the high risk employment marking generating steps include: marking the foreground value of the borrower employment unit and the value of the borrower employment willingness as jdzi and jyzi respectively, carrying out formulated analysis to obtain the borrower employment coefficient jyxi
Setting gradient thresholds Yz1 and Yz2 of a borrower repayment coefficient hkxi, wherein Yz2 is larger than Yz1, and setting gradient thresholds Yz3 and Yz4 of the borrower repayment coefficient hkxi, and Yz4 is larger than Yz3; substituting the borrower repayment coefficient hkxi into gradient thresholds Yz1 and Yz2 for analysis;
If the borrower repayment coefficient hkxi is larger than Yz2, generating a high risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than or equal to Yz2 and the borrower repayment coefficient hkxi is larger than or equal to Yz1, generating an intermediate risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than Yz1, generating a low risk repayment mark for the corresponding borrower;
substituting the borrower employment coefficient jyxi into gradient threshold values Yz3 and Yz4 for analysis, and if the borrower employment coefficient jyxi is larger than Yz4, generating a low risk employment mark for the corresponding borrower; if the career employment coefficient jyxi is smaller than or equal to Yz4 and larger than or equal to Yz3, generating an intermediate risk employment mark for the corresponding career; if the borrower employment coefficient jyxi is less than Yz3, a high risk employment indicia is generated for the respective borrower.
In a preferred embodiment, the quality rankings include a top-level borrower, a sub-top-level borrower, and a sub-level borrower, the generating step includes obtaining different risk repayment signatures and different risk employment signatures for the same borrower at the same time,
if the same borrower has both a low risk repayment signature and a low risk employment signature, generating a premium borrower for the corresponding borrower;
If the same borrower has both a low risk repayment signature and a medium risk employment signature, the low risk employment signature and the medium risk repayment signature, generating a suboptimal borrower for the corresponding borrower;
if the same borrower has both a medium-risk repayment sign and a medium-risk repayment sign, a medium-risk repayment sign and a high-risk repayment sign, a high-risk repayment sign and a high-risk repayment sign, a low-risk repayment sign and a high-risk repayment sign, and a low-risk repayment sign and a high-risk repayment sign, then generating a secondary borrower for the corresponding borrower.
A loan inspection processing system, comprising:
the credit investigation acquisition module acquires credit investigation information of the borrower according to the identity information of the borrower;
the credit investigation comparison module compares and analyzes the credit investigation information of the borrower with the preset credit investigation conditions, and refuses the loan application of the borrower if the credit investigation information of the borrower does not accord with the preset credit investigation conditions; if the credit investigation information of the borrower accords with the preset credit investigation condition, generating a credit investigation information depth analysis signal;
the data acquisition module acquires borrow repayment information and borrow employment information according to the borrow information depth analysis signal, wherein the borrow repayment information comprises a borrow repayment pressure value and a borrow mortgage change value, and the borrow employment information comprises a borrow employment prospect value and a borrow employment willingness value;
The data analysis module is used for carrying out formulated analysis on the borrower repayment pressure value and the borrower mortgage change value to obtain a borrower repayment coefficient, and generating different risk repayment marks for corresponding borrowers according to the size of the borrower repayment coefficient; carrying out formulated analysis on the foreground value of the career employment unit and the career employment wish value according to the foreground value of the career employment unit to obtain a career employment coefficient, and generating different risk employment marks for corresponding careers according to the size of the career employment coefficient;
and the risk rating module is used for quality rating of corresponding borrowers according to different risk repayment marks and different risk employment marks.
In a preferred embodiment, the borrower repayment pressure value obtaining step includes marking hyz the borrower repayment pressure value, and obtaining a total income value, a total expense value and a total surplus value n months before the borrower at the current moment, wherein the total surplus value is equal to a result value obtained by subtracting the total expense value from the total income value; the total income value comprises a bank card income value, a WeChat income value and a Payment device income value;
the total payout value comprises a total fixed payout value and a total floating payout, and the total fixed payout value obtaining process comprises the following steps: analyzing the n-month total expenditure value data, marking the names of the payees with the occurrence times equal to n as fixed payees, and marking the payees of the fixed payees for n months as total fixed expenditure values; the total floating payout value is equal to a result value of the total payout value minus the total fixed payout value;
Dividing the total floating payment value by n to obtain a total floating payment average value, marking the total floating payment average value as y1, calculating to obtain a monthly payment value according to the loan amount, the payment period and the payment mode of the borrower, marking the monthly payment value as y2, and marking the sum of y1 and y2 as y3;
wherein y4 is a total surplus mean value, and the total surplus mean value is a result value obtained by dividing the total surplus value by n;
the present value of the borrower mortgage is calculated according to the formula if the borrower mortgage value is marked as 0 and if the borrower is a business
Bxz is the present value of the borrower mortgage, and the mobile liability package of the enterpriseThe monthly repayment value of the loan is included.
In a preferred embodiment, the step of obtaining the prospect value of the borrower employment unit includes obtaining the latest month social security payment unit name of the borrower, obtaining the latest N unit time tax payment amounts corresponding to the current unit name according to the unit name, arranging the N time tax payment amounts according to time sequence, calculating two adjacent tax payment amount difference values in sequence, marking the two adjacent tax payment amount difference values as p1, marking the result value of dividing the p1 by the tax payment amount with the adjacent two tax payment amounts with the time sequence front as p2, and marking the sum of all p2 in the N unit time as the prospect value of the borrower employment unit;
The step of obtaining the employment willingness value of the borrower comprises the steps of obtaining the name of a social security payment unit in k unit time of the borrower, marking the employment willingness value of the borrower as 1 if the name of the social security payment unit is consistent in k unit time, and marking the actual value of the employment willingness value of the borrower as r if the name of the social security payment unit is inconsistent in k unit time.
In a preferred embodiment, the low risk repayment signature, the stroke risk repayment signature, and the high risk repayment signature are generated by marking a borrower repayment pressure value and a borrower mortgage change value as hyzi and bxzi respectively, and performing formulated analysis to obtain a borrower repayment coefficient hkxi;
the low risk employment marking, the medium risk employment marking and the high risk employment marking generating steps include: marking the foreground value of the borrower employment unit and the value of the borrower employment willingness as jdzi and jyzi respectively, carrying out formulated analysis to obtain the borrower employment coefficient jyxi
Setting gradient thresholds Yz1 and Yz2 of a borrower repayment coefficient hkxi, wherein Yz2 is larger than Yz1, and setting gradient thresholds Yz3 and Yz4 of the borrower repayment coefficient hkxi, and Yz4 is larger than Yz3; substituting the borrower repayment coefficient hkxi into gradient thresholds Yz1 and Yz2 for analysis;
If the borrower repayment coefficient hkxi is larger than Yz2, generating a high risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than or equal to Yz2 and the borrower repayment coefficient hkxi is larger than or equal to Yz1, generating an intermediate risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than Yz1, generating a low risk repayment mark for the corresponding borrower;
substituting the borrower employment coefficient jyxi into gradient threshold values Yz3 and Yz4 for analysis, and if the borrower employment coefficient jyxi is larger than Yz4, generating a low risk employment mark for the corresponding borrower; if the career employment coefficient jyxi is smaller than or equal to Yz4 and larger than or equal to Yz3, generating an intermediate risk employment mark for the corresponding career; if the borrower employment coefficient jyxi is less than Yz3, a high risk employment indicia is generated for the respective borrower.
In a preferred embodiment, the quality rankings include a top-level borrower, a sub-top-level borrower, and a sub-level borrower, the generating step includes obtaining different risk repayment signatures and different risk employment signatures for the same borrower at the same time,
if the same borrower has both a low risk repayment signature and a low risk employment signature, generating a premium borrower for the corresponding borrower;
If the same borrower has both a low risk repayment signature and a medium risk employment signature, the low risk employment signature and the medium risk repayment signature, generating a suboptimal borrower for the corresponding borrower;
if the same borrower has both a medium-risk repayment sign and a medium-risk repayment sign, a medium-risk repayment sign and a high-risk repayment sign, a high-risk repayment sign and a high-risk repayment sign, a low-risk repayment sign and a high-risk repayment sign, and a low-risk repayment sign and a high-risk repayment sign, then generating a secondary borrower for the corresponding borrower.
The loan inspection processing method has the technical effects and advantages that:
the loan examination processing method of the invention corrects the relevant data of the borrower in the analysis process by comprehensively analyzing the corresponding repayment information and employment information of the borrower, reflects the probability of falsification of the income data of the corresponding borrower, furthest reduces the actual income condition and the actual repayment capability of the borrower, carries out quality grading on the corresponding borrower based on the data, makes examination standard for the default risk of the corresponding borrower and reduces the default risk.
Drawings
FIG. 1 is a schematic diagram of a loan inspection processing system of the present invention;
FIG. 2 is a schematic diagram of a loan inspection processing method 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.
Examples
Referring to fig. 1, in the loan inspection processing system of the present embodiment, a credit acquisition module 1, a credit comparison module 2, a data acquisition module 3, a data analysis module 4, and a risk rating module 5 are described.
And the credit investigation acquisition module 1 acquires credit investigation information of the borrower according to the identity information of the borrower.
The credit investigation comparison module 2 compares and analyzes the credit investigation information of the borrower with the preset credit investigation conditions, and refuses the borrower to apply if the credit investigation information of the borrower does not accord with the preset credit investigation conditions; and if the credit investigation information of the borrower accords with the preset credit investigation condition, generating a credit investigation information depth analysis signal.
The data acquisition module 3 acquires the borrower repayment information and the borrower employment information according to the borrower information depth analysis signal, and sends the borrower repayment information and the borrower employment information to the data marking module, wherein the borrower repayment information comprises a borrower repayment pressure value and a borrower mortgage change value, and the borrower employment information comprises a borrower employment unit prospect value and a borrower employment wish value.
The borrower repayment pressure value obtaining step includes marking the borrower repayment pressure value as hyz; and acquiring a total income value, a total expenditure value and a total surplus value of the borrower n months before the current moment, wherein the total surplus value is equal to a result value obtained by subtracting the total expenditure value from the total income value.
The total income value comprises income values of a payment transaction system such as a bank card income value, a WeChat income value, a payment treasury income value and the like, the income values can be obtained through a banking system, the income except the bank card is comprehensively considered, the actual income situation of a borrower can be better embodied, and more accurate judgment can be made for subsequent loan examination.
The total payout value comprises a total fixed payout value and a total floating payout, and the total fixed payout value obtaining process comprises the following steps: analyzing n months of total expenditure value data, marking the names of the payees with the occurrence times equal to n as fixed payees, marking the payees' payouts received by the fixed payees in n months as total fixed expenditure values, further explaining the fixed payees, such as the monthly fixed payouts of the fuel gas fee, the electric fee, the deduction of the existing bank loans and the like of the borrowers, wherein the payouts are all charged once a month; the total floating payout value is equal to a result value of subtracting the total fixed payout value from the total payout value; since the total fixed payout value is a monthly fixed payout, it is common that the total surplus value is the total floating payout value that has the greatest impact, and by removing the total fixed payout value from the total payout values, the borrower repayment pressure value of the borrower is better reflected in subsequent calculations, making a more accurate determination for subsequent loan reviews.
Dividing the total floating payment value by n to obtain a total floating payment average value, marking the total floating payment average value as y1, calculating to obtain a monthly payment value according to the loan amount, the payment period and the payment mode of the borrower, marking the monthly payment value as y2, and marking the sum of y1 and y2 as y3;
where y4 is the total surplus mean, which is the total surplus divided by n, where hyz represents a smaller value, a smaller borrower repayment pressure, a lower relative risk of contraband, and vice versa.
The above-mentioned loan mortgage present value is expressed by the formula if the loan is a loan mortgage value of 0, if the loan is a business
Where bxz is the borrower mortgage present value and the corporate mobile liabilities include the monthly repayment value for the present loan.
The smaller the borrower mortgage present value bxz, the better the rendering ability, and the greater the probability of withdrawing the loan and the less the lender loss when the corresponding borrower breaks.
The step of obtaining the prospect value of the career employment unit includes obtaining the latest month social insurance payment unit name of the career, aiming at determining the current employment unit of the career, obtaining the latest N unit time tax payment amounts corresponding to the current unit name according to the unit name, arranging the N time tax payment amounts according to time sequence, wherein the N units can be quarterly units or annual units, and are not particularly limited; and calculating the difference value of the two adjacent tax payings in sequence, marking the difference value as p1, marking the result value of dividing the p1 by the tax payings with the adjacent tax payings with the time sequence being the front as p2, and marking the sum of all p2 in N unit time as the prospect value of the career employment unit.
The greater the borrower employment prospect value representation, the faster the borrower employment development increases, the borrower current employment, directly related to the borrower's post-day income, the better the borrower's employment development, the less the borrower's probability of default.
The step of obtaining the employment wish value of the borrower includes obtaining the name of the social security payment unit in k unit time of the borrower, wherein the k unit time can be a year unit or a quarter unit, and the method is not particularly limited herein; if the social security payment unit names are consistent in the k unit time, marking the employment willingness value of the borrower as 1, and if the social security payment unit names are r inconsistent social security payment unit names in the k unit time, marking the practical value of the employment willingness value of the borrower as r.
The larger the career's intention value is, the lower the career's intention is, otherwise, the stronger is, the real income situation of the career's income can be reflected by analyzing the career's intention value, the running water false probability of the career's bank can be obtained, if the career's intention is low, the stable income is not available, the larger the corresponding running water false probability of the career's bank is, in order to meet the approval condition of the loan, the real repayment capability is judged by analyzing the career's intention, and the probability of the default of the loan is reduced.
The data analysis module 4 performs formulated analysis on the loan repayment pressure value and the loan mortgage change value to obtain a loan repayment coefficient, and generates different risk repayment marks for the corresponding loan according to the size of the loan repayment coefficient, wherein the different risk repayment marks comprise a low risk repayment mark, a medium risk repayment mark and a high risk repayment mark.
The process of generating the low-risk repayment mark, the medium-risk repayment mark and the high-risk repayment mark comprises the steps of respectively marking a borrower repayment pressure value and a borrower mortgage change value as hyzi and bxzi, and according to a formula, hkxi=1 x hyzi+alpha 2 x bxzi, wherein hkxi is a borrower repayment coefficient, alpha 1 and alpha 2 are preset proportionality coefficients, alpha 1 is larger than alpha 2 and larger than 0, i is the number of corresponding borrowers, and i is an integer larger than or equal to 1.
It should be noted that, the smaller the borrower repayment coefficient hkxi expression value, the stronger the borrower's ability to repay the loan in a later month, and the smaller the risk of default; the opposite is true.
The data analysis module 4 is further used for carrying out formulated analysis on the foreground value of the borrower employment unit and the employment wish value of the borrower to obtain a borrower employment coefficient, and generating different risk employment marks for the corresponding borrower according to the size of the borrower employment coefficient, wherein the different risk employment marks comprise a low risk employment mark, a medium risk employment mark and a high risk employment mark.
The low risk employment marking, the medium risk employment marking and the high risk employment marking generating steps include: the borrower employment prospect value and the borrower employment will value are respectively marked as jdzi and jyzi, and according to the formula,
wherein jyxi is a borrower employment coefficient, β1 and β2 are both preset scale coefficients, and β1 > β2 > 0.
It should be noted that, the larger the expression value of the employment coefficient jyxi of a borrower, the smaller the probability that the corresponding borrower's income data can be reflected to be false, for example, the bank's running data, the more stable the corresponding real income representing the borrower, and the smaller the risk of default.
The preset proportionality coefficient in the formula is used for balancing the proportion of each item of data in the formula, so that the accuracy of a calculation result is promoted.
Setting gradient thresholds Yz1 and Yz2 of a borrower repayment coefficient hkxi, wherein Yz2 is larger than Yz1, and setting gradient thresholds Yz3 and Yz4 of the borrower repayment coefficient hkxi, and Yz4 is larger than Yz3; the borrower repayment coefficient hkxi is substituted into the gradient threshold Yz1 and Yz2 for analysis.
If the borrower repayment coefficient hkxi is larger than Yz2, generating a high risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than or equal to Yz2 and the borrower repayment coefficient hkxi is larger than or equal to Yz1, generating an intermediate risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is less than Yz1, a low risk repayment signature is generated for the corresponding borrower.
Substituting the borrower employment coefficient jyxi into gradient threshold values Yz3 and Yz4 for analysis, and if the borrower employment coefficient jyxi is larger than Yz4, generating a low risk employment mark for the corresponding borrower; if the career employment coefficient jyxi is smaller than or equal to Yz4 and larger than or equal to Yz3, generating an intermediate risk employment mark for the corresponding career; if the borrower employment coefficient jyxi is less than Yz3, a high risk employment indicia is generated for the respective borrower.
Comprehensively analyzing the corresponding borrower repayment coefficient related data and the borrower employment coefficient related data to obtain the actual compensation ability of the borrower after the actual payment is made, and making a checking standard for the corresponding borrower default risk so as to reduce the default risk.
The risk rating module 5 ranks the quality of the corresponding borrowers according to the different risk repayment marks and the different risk employment marks.
The quality grade comprises a top grade borrower, a sub-top grade borrower and a sub-grade borrower, the specific generating step comprises the steps of obtaining different risk repayment marks and different risk employment marks of the same borrower at the same time,
if the same borrower has both a low risk repayment signature and a low risk employment signature, generating a premium borrower for the corresponding borrower;
If the same borrower has both a low risk repayment signature and a medium risk employment signature, the low risk employment signature and the medium risk repayment signature, generating a suboptimal borrower for the corresponding borrower;
if the same borrower has both a medium-risk repayment sign and a medium-risk repayment sign, a medium-risk repayment sign and a high-risk repayment sign, a high-risk repayment sign and a high-risk repayment sign, a low-risk repayment sign and a high-risk repayment sign, and a low-risk repayment sign and a high-risk repayment sign, then generating a secondary borrower for the corresponding borrower.
Sequentially sorting the first-class borrower, the second-class borrower and the second-class borrower according to the default risk probability from low to high; the lending unit can conveniently make corresponding adjustment on whether to lend or not and the amount of the quality grading borrowers with different grades according to market environment and policies.
The loan inspection processing system of the embodiment corrects the relevant data of the borrower in the analysis process through the comprehensive analysis of the corresponding repayment information and the employment information of the borrower, reflects the probability of falsification of the income data of the corresponding borrower, furthest reduces the actual income condition and the actual repayment capability of the borrower, carries out quality grading on the corresponding borrower based on the data, makes inspection standard for the default risk of the corresponding borrower, and reduces the default risk.
Example two
Referring to fig. 2, the detailed description of the present embodiment is not provided in the section of the description of the embodiment, and a loan inspection processing method is provided, which includes,
acquiring credit investigation information of a borrower according to the identity information of the borrower;
comparing the credit investigation information of the borrower with the preset credit investigation conditions for analysis, and rejecting the loan application of the borrower if the credit investigation information of the borrower does not accord with the preset credit investigation conditions; if the credit investigation information of the borrower accords with the preset credit investigation condition, generating a credit investigation information depth analysis signal;
collecting borrow repayment information and borrow employment information according to a borrow information depth analysis signal, wherein the borrow repayment information comprises a borrow repayment pressure value and a borrow mortgage change value, and the borrow employment information comprises a borrow employment unit prospect value and a borrow employment willingness value;
carrying out formulated analysis on the loan repayment pressure value and the mortgage change value of the loan to obtain a loan repayment coefficient, and generating different risk repayment marks for corresponding loans according to the size of the loan repayment coefficient; carrying out formulated analysis on the foreground value of the career employment unit and the career employment wish value according to the foreground value of the career employment unit to obtain a career employment coefficient, and generating different risk employment marks for corresponding careers according to the size of the career employment coefficient;
And grading the quality of the corresponding borrower according to the different risk repayment marks and the different risk employment marks.
The borrower repayment pressure value obtaining step comprises the steps of marking the borrower repayment pressure value as hyz, and obtaining a total income value, a total expenditure value and a total surplus value of the borrower n months before the current moment, wherein the total surplus value is equal to a result value obtained by subtracting the total expenditure value from the total income value; the total income value comprises a bank card income value, a WeChat income value and a Payment device income value;
the total payout value comprises a total fixed payout value and a total floating payout, and the total fixed payout value obtaining process comprises the following steps: analyzing the n-month total expenditure value data, marking the names of the payees with the occurrence times equal to n as fixed payees, and marking the payees of the fixed payees for n months as total fixed expenditure values; the total floating payout value is equal to a result value of the total payout value minus the total fixed payout value;
dividing the total floating payout value by n to obtain a total floating payout average value, marking the total floating payout average value as y1, calculating to obtain a monthly payout value according to the loan amount, the payout period and the payout mode of the borrower, marking the monthly payout value as y2, and marking the y1 and the y2 And is labeled y3;
wherein y4 is a total surplus mean value, and the total surplus mean value is a result value obtained by dividing the total surplus value by n;
the present value of the borrower mortgage is calculated according to the formula if the borrower mortgage value is marked as 0 and if the borrower is a business
Where bxz is the borrower mortgage present value and the corporate mobile liabilities include the monthly repayment value for the present loan.
Obtaining the latest month social security payment unit name of a borrower, obtaining the latest N tax payment amounts in unit time corresponding to the current unit name according to the unit name, arranging the N time tax payment amounts according to time sequence, sequentially calculating adjacent two tax payment amount difference values, marking the adjacent two tax payment amount difference values as p1, marking the result value of dividing the p1 by the tax payment amount of which the time sequence of the adjacent two tax payment amounts is forward as p2, and marking the sum of all p2 in the N unit time as the borrower employment unit prospect value;
the step of obtaining the employment willingness value of the borrower comprises the steps of obtaining the name of a social security payment unit in k unit time of the borrower, marking the employment willingness value of the borrower as 1 if the name of the social security payment unit is consistent in k unit time, and marking the actual value of the employment willingness value of the borrower as r if the name of the social security payment unit is inconsistent in k unit time.
The process of generating the low-risk repayment mark, the medium-risk repayment mark and the high-risk repayment mark comprises the steps of marking a borrower repayment pressure value and a borrower mortgage change value as hyzi and bxzi respectively, and carrying out formulated analysis on the two values to obtain a borrower repayment coefficient hkxi;
the low risk employment marking, the medium risk employment marking and the high risk employment marking generating steps include: marking the foreground value of the borrower employment unit and the value of the borrower employment willingness as jdzi and jyzi respectively, carrying out formulated analysis to obtain the borrower employment coefficient jyxi
Setting gradient thresholds Yz1 and Yz2 of a borrower repayment coefficient hkxi, wherein Yz2 is larger than Yz1, and setting gradient thresholds Yz3 and Yz4 of the borrower repayment coefficient hkxi, and Yz4 is larger than Yz3; substituting the borrower repayment coefficient hkxi into gradient thresholds Yz1 and Yz2 for analysis;
if the borrower repayment coefficient hkxi is larger than Yz2, generating a high risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than or equal to Yz2 and the borrower repayment coefficient hkxi is larger than or equal to Yz1, generating an intermediate risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than Yz1, generating a low risk repayment mark for the corresponding borrower;
substituting the borrower employment coefficient jyxi into gradient threshold values Yz3 and Yz4 for analysis, and if the borrower employment coefficient jyxi is larger than Yz4, generating a low risk employment mark for the corresponding borrower; if the career employment coefficient jyxi is smaller than or equal to Yz4 and larger than or equal to Yz3, generating an intermediate risk employment mark for the corresponding career; if the borrower employment coefficient jyxi is less than Yz3, a high risk employment indicia is generated for the respective borrower.
The quality grading comprises a top-grade borrower, a sub-top-grade borrower and a sub-grade borrower, the generating step comprises the steps of obtaining different risk repayment marks and different risk employment marks of the same borrower at the same time,
if the same borrower has both a low risk repayment signature and a low risk employment signature, generating a premium borrower for the corresponding borrower;
if the same borrower has both a low risk repayment signature and a medium risk employment signature, the low risk employment signature and the medium risk repayment signature, generating a suboptimal borrower for the corresponding borrower;
if the same borrower has both a medium-risk repayment sign and a medium-risk repayment sign, a medium-risk repayment sign and a high-risk repayment sign, a high-risk repayment sign and a high-risk repayment sign, a low-risk repayment sign and a high-risk repayment sign, and a low-risk repayment sign and a high-risk repayment sign, then generating a secondary borrower for the corresponding borrower.
The above formulas are all formulas with dimensionality removed and numerical calculation, the formulas are formulas with the latest real situation obtained by software simulation through collecting a large amount of data, and preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present application are all or partially produced. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely one, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. A loan inspection processing method, comprising:
acquiring credit investigation information of a borrower according to the identity information of the borrower;
comparing the credit investigation information of the borrower with the preset credit investigation conditions for analysis, and rejecting the loan application of the borrower if the credit investigation information of the borrower does not accord with the preset credit investigation conditions; if the credit investigation information of the borrower accords with the preset credit investigation condition, generating a credit investigation information depth analysis signal;
collecting borrow repayment information and borrow employment information according to a borrow information depth analysis signal, wherein the borrow repayment information comprises a borrow repayment pressure value and a borrow mortgage change value, and the borrow employment information comprises a borrow employment unit prospect value and a borrow employment willingness value;
Carrying out formulated analysis on the loan repayment pressure value and the mortgage change value of the loan to obtain a loan repayment coefficient, and generating different risk repayment marks for corresponding loans according to the size of the loan repayment coefficient; carrying out formulated analysis on the foreground value of the career employment unit and the career employment wish value according to the foreground value of the career employment unit to obtain a career employment coefficient, and generating different risk employment marks for corresponding careers according to the size of the career employment coefficient;
and grading the quality of the corresponding borrower according to the different risk repayment marks and the different risk employment marks.
2. The method of claim 1, wherein the borrower repayment pressure value obtaining step includes marking the borrower repayment pressure value as hyz, and obtaining a total income value, a total expense value and a total surplus value n months before the borrower at the current time, wherein the total surplus value is equal to a result value obtained by subtracting the total expense value from the total income value; the total income value comprises a bank card income value, a WeChat income value and a Payment device income value;
the total payout value comprises a total fixed payout value and a total floating payout, and the total fixed payout value obtaining process comprises the following steps: analyzing the n-month total expenditure value data, marking the names of the payees with the occurrence times equal to n as fixed payees, and marking the payees of the fixed payees for n months as total fixed expenditure values; the total floating payout value is equal to a result value of the total payout value minus the total fixed payout value;
Dividing the total floating payment value by n to obtain a total floating payment average value, marking the total floating payment average value as y1, calculating to obtain a monthly payment value according to the loan amount, the payment period and the payment mode of the borrower, marking the monthly payment value as y2, and marking the sum of y1 and y2 as y3;
wherein y4 is a total surplus mean value, and the total surplus mean value is a result value obtained by dividing the total surplus value by n;
the present value of the borrower mortgage is calculated according to the formula if the borrower mortgage value is marked as 0 and if the borrower is a business
Where bxz is the borrower mortgage present value and the corporate mobile liabilities include the monthly repayment value for the present loan.
3. The loan inspection processing method according to claim 2, wherein the step of obtaining the borrower employment unit prospect value comprises the steps of obtaining the latest month social insurance payment unit name of the borrower, obtaining the latest N unit time tax payment amounts corresponding to the current unit name according to the unit name, arranging the N time tax payment amounts according to time sequence, sequentially calculating the difference value of two adjacent tax payment amounts, marking the difference value as p1, marking the result value of dividing p1 by the tax payment amount of which the time sequence of the two adjacent tax payment amounts is forward as p2, and marking the sum of all p2 in the N unit time as the borrower employment unit prospect value;
The step of obtaining the employment willingness value of the borrower comprises the steps of obtaining the name of a social security payment unit in k unit time of the borrower, marking the employment willingness value of the borrower as 1 if the name of the social security payment unit is consistent in k unit time, and marking the actual value of the employment willingness value of the borrower as r if the name of the social security payment unit is inconsistent in k unit time.
4. A method of loan inspection processing according to claim 3 wherein the steps of generating a low risk repayment signature, a medium risk repayment signature, and a high risk repayment signature include marking a borrower repayment pressure value and a borrower mortgage change value as hyzi, bxzi, respectively, and performing a formulatory analysis to determine a borrower repayment coefficient hkxi;
the low risk employment marking, the medium risk employment marking and the high risk employment marking generating steps include: marking a borrower employment prospect value and a borrower employment willingness value as jdzi and jyzi respectively, and carrying out formulated analysis to obtain a borrower employment coefficient jyxi;
setting gradient thresholds Yz1 and Yz2 of a borrower repayment coefficient hkxi, wherein Yz2 is larger than Yz1, and setting gradient thresholds Yz3 and Yz4 of the borrower repayment coefficient hkxi, and Yz4 is larger than Yz3;
Substituting the borrower repayment coefficient hkxi into gradient thresholds Yz1 and Yz2 for analysis; if the borrower repayment coefficient hkxi is larger than Yz2, generating a high risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than or equal to Yz2 and the borrower repayment coefficient hkxi is larger than or equal to Yz1, generating an intermediate risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than Yz1, generating a low risk repayment mark for the corresponding borrower;
substituting the borrower employment coefficient jyxi into gradient threshold values Yz3 and Yz4 for analysis, and if the borrower employment coefficient jyxi is larger than Yz4, generating a low risk employment mark for the corresponding borrower; if the career employment coefficient jyxi is smaller than or equal to Yz4 and larger than or equal to Yz3, generating an intermediate risk employment mark for the corresponding career; if the borrower employment coefficient jyxi is less than Yz3, a high risk employment indicia is generated for the respective borrower.
5. The method of claim 4, wherein the quality level includes a top level borrower, a sub-top level borrower, and a sub-level borrower, the generating step includes obtaining different risk repayment signatures and different risk employment signatures for the same borrower at the same time,
if the same borrower has both a low risk repayment signature and a low risk employment signature, generating a premium borrower for the corresponding borrower;
If the same borrower has both a low risk repayment signature and a medium risk employment signature, the low risk employment signature and the medium risk repayment signature, generating a suboptimal borrower for the corresponding borrower;
if the same borrower has both a medium-risk repayment sign and a medium-risk repayment sign, a medium-risk repayment sign and a high-risk repayment sign, a high-risk repayment sign and a high-risk repayment sign, a low-risk repayment sign and a high-risk repayment sign, and a low-risk repayment sign and a high-risk repayment sign, then generating a secondary borrower for the corresponding borrower.
6. A loan inspection processing system, comprising:
the credit investigation acquisition module (1) acquires credit investigation information of a borrower according to the identity information of the borrower;
the credit investigation comparison module (2) compares and analyzes the credit investigation information of the borrower with the preset credit investigation conditions, and refuses the loan application of the borrower if the credit investigation information of the borrower does not accord with the preset credit investigation conditions; if the credit investigation information of the borrower accords with the preset credit investigation condition, generating a credit investigation information depth analysis signal;
a data acquisition module (3) for acquiring, according to the depth analysis signal of the borrower information, borrower repayment information and borrower employment information, wherein the borrower repayment information comprises a borrower repayment pressure value and a borrower mortgage change value, and the borrower employment information comprises a borrower employment prospect value and a borrower employment wish value;
The data analysis module (4) is used for carrying out formulated analysis on the loan repayment pressure value and the loan mortgage change value according to the loan repayment pressure value and the loan mortgage change value to obtain a loan repayment coefficient, and generating different risk repayment marks for corresponding loans according to the magnitude of the loan repayment coefficient; carrying out formulated analysis on the foreground value of the career employment unit and the career employment wish value according to the foreground value of the career employment unit to obtain a career employment coefficient, and generating different risk employment marks for corresponding careers according to the size of the career employment coefficient;
and the risk rating module (5) is used for quality rating of corresponding borrowers according to different risk repayment marks and different risk employment marks.
7. The loan inspection processing system of claim 6, wherein the borrower repayment pressure value obtaining step comprises marking the borrower repayment pressure value as hyz, obtaining a total income value n months before the borrower at the current time, a total expense value, and a total surplus value, wherein the total surplus value is equal to a result value of subtracting the total expense value from the total income value; the total income value comprises a bank card income value, a WeChat income value and a Payment device income value;
the total payout value comprises a total fixed payout value and a total floating payout, and the total fixed payout value obtaining process comprises the following steps: analyzing the n-month total expenditure value data, marking the names of the payees with the occurrence times equal to n as fixed payees, and marking the payees of the fixed payees for n months as total fixed expenditure values; the total floating payout value is equal to a result value of the total payout value minus the total fixed payout value;
Dividing the total floating payment value by n to obtain a total floating payment average value, marking the total floating payment average value as y1, calculating to obtain a monthly payment value according to the loan amount, the payment period and the payment mode of the borrower, marking the monthly payment value as y2, and marking the sum of y1 and y2 as y3;
wherein y4 is a total surplus mean value, and the total surplus mean value is a result value obtained by dividing the total surplus value by n;
the present value of the borrower mortgage is calculated according to the formula if the borrower mortgage value is marked as 0 and if the borrower is a business
Where bxz is the borrower mortgage present value and the corporate mobile liabilities include the monthly repayment value for the present loan.
8. The loan inspection processing system of claim 7, wherein the borrower employment unit prospect value obtaining step includes obtaining a latest month social insurance payment unit name of the borrower, obtaining latest N unit time tax payment amounts corresponding to the current unit name according to the unit name, arranging the N time tax payment amounts according to time sequence, sequentially calculating adjacent two tax payment amount difference values, marking the adjacent two tax payment amount difference values as p1, marking a result value of dividing the p1 by the tax payment amount of which the adjacent two tax payment amounts are in time sequence as p2, and marking the sum of all p2 in the N unit time as the borrower employment unit prospect value;
The step of obtaining the employment willingness value of the borrower comprises the steps of obtaining the name of a social security payment unit in k unit time of the borrower, marking the employment willingness value of the borrower as 1 if the name of the social security payment unit is consistent in k unit time, and marking the actual value of the employment willingness value of the borrower as r if the name of the social security payment unit is inconsistent in k unit time.
9. The loan inspection processing system of claim 8, wherein the generating of the low risk repayment signature, the medium risk repayment signature, and the high risk repayment signature comprises marking a borrower repayment pressure value and a borrower mortgage change value as hyzi, bxzi, respectively, and performing a formulated analysis to obtain a borrower repayment coefficient hkxi;
the low risk employment marking, the medium risk employment marking and the high risk employment marking generating steps include: marking the foreground value of the borrower employment unit and the value of the borrower employment willingness as jdzi and jyzi respectively, carrying out formulated analysis to obtain the borrower employment coefficient jyxi
Setting gradient thresholds Yz1 and Yz2 of a borrower repayment coefficient hkxi, wherein Yz2 is larger than Yz1, and setting gradient thresholds Yz3 and Yz4 of the borrower repayment coefficient hkxi, and Yz4 is larger than Yz3; substituting the borrower repayment coefficient hkxi into gradient thresholds Yz1 and Yz2 for analysis;
If the borrower repayment coefficient hkxi is larger than Yz2, generating a high risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than or equal to Yz2 and the borrower repayment coefficient hkxi is larger than or equal to Yz1, generating an intermediate risk repayment mark for the corresponding borrower; if the borrower repayment coefficient hkxi is smaller than Yz1, generating a low risk repayment mark for the corresponding borrower;
substituting the borrower employment coefficient jyxi into gradient threshold values Yz3 and Yz4 for analysis, and if the borrower employment coefficient jyxi is larger than Yz4, generating a low risk employment mark for the corresponding borrower; if the career employment coefficient jyxi is smaller than or equal to Yz4 and larger than or equal to Yz3, generating an intermediate risk employment mark for the corresponding career; if the borrower employment coefficient jyxi is less than Yz3, a high risk employment indicia is generated for the respective borrower.
10. The loan inspection processing system of claim 9 wherein the quality level comprises a top level borrower, a sub-top level borrower, and a sub-level borrower, the generating step comprising obtaining different risk repayment indicia and different risk employment indicia for the same borrower at the same time,
if the same borrower has both a low risk repayment signature and a low risk employment signature, generating a premium borrower for the corresponding borrower;
If the same borrower has both a low risk repayment signature and a medium risk employment signature, the low risk employment signature and the medium risk repayment signature, generating a suboptimal borrower for the corresponding borrower;
if the same borrower has both a medium-risk repayment sign and a medium-risk repayment sign, a medium-risk repayment sign and a high-risk repayment sign, a high-risk repayment sign and a high-risk repayment sign, a low-risk repayment sign and a high-risk repayment sign, and a low-risk repayment sign and a high-risk repayment sign, then generating a secondary borrower for the corresponding borrower.
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| CN117670510A (en) * | 2023-11-30 | 2024-03-08 | 广东省中保小额贷款股份有限公司 | Small loan management system |
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| CN117670510A (en) * | 2023-11-30 | 2024-03-08 | 广东省中保小额贷款股份有限公司 | Small loan management system |
| CN117670510B (en) * | 2023-11-30 | 2024-05-28 | 广东省中保小额贷款股份有限公司 | Small loan management system |
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