CN106339940A - A method for detecting financial acquisition values and calculating a credit line - Google Patents
A method for detecting financial acquisition values and calculating a credit line Download PDFInfo
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Abstract
The invention discloses a method for detecting financial acquisition values and calculating a credit line. The method comprises the following steps: obtaining credit basic information and a plurality of financial acquisition values of a loaning subject; obtaining N financial data values; calculating credit scoring adjustment coefficient alpha, which influences the credit line; obtaining dispersion degrees delta1, delta2,......,[delta]n of the financial data values respectively; carrying out weighted calculating to obtain a comprehensive dispersion degree of the financial data values; and utilizing (1-Delta) as a credibility adjustment coefficient to calculate a suggested credit line, wherein the suggested credit line= annual net profit* (1-Delta)*alpha. The invention provides the method for ingeniously and reasonably detecting the financial acquisition values and calculating the credit line; and data deviation degree is introduced to modify the credit line, so that the final credit amount is allowed to be more accurate and reliable, and financial safety and risk assessment operation efficiency of the loaning subject are improved greatly.
Description
Technical field
The present invention relates to a kind of data processing method, more particularly, to a kind of financial data processing method.
Background technology
With China market expanding economy, the development of financial circles is particularly swift and violent, and in increasingly huge finance activities
The more and more important role of the positive performer of credit operation, it sets foot in social every field, and audience includes all kinds of enterprises
And individual, then increasingly frequently how to be come according to the daily economic data (financial collection value) of client in credit financing business
Assess, analyze the relative credit worthiness of this client, thus obtaining the rational line of credit that becomes most just become modern credit gold
Melt a urgent need to solve the problem of industry.
If the problem during this cannot get a rationally effective solution, bull loan, chain debts, cheat loan, dislike
Meaning is in arrears with and will constantly be grown with malignant events such as the evasion of repayment of bank loans, the economic order of heavy damage social stability.
The scheme of prior art is as shown in figure 1, by the communication of customer manager and loaning bill main body, obtain the letter of loaning bill main body
Borrow essential information and some finance collection values, described credit essential information include age of enterprise operator, marital status,
Working experience, reference report, house property information and guarantor's income etc.；Described some finance collection values include loaning bill main body
Sales price, sales volume, unit price of procurement, purchase quantity, volumn of purchase, buying expenses, production efficiency, the electricity charge, energy consumption, pay taxes
Data, selling charges, performance pay, accounts receivable detailed data, same period last year stock, asset-liability ratio, assets net profit margin, should
Receipt on account money turnover rate；Then statistics obtains the n financial data value that can weigh a loaning bill principal sector of the economy situation, then passes through
The computer of preset computation model calculates the information scoring regulation coefficient α of impact line of credit, as loan risk evaluation system
Number, then calculates suggestion line of credit it is proposed that line of credit=annual net profit × α.
The defect that the scheme of prior art exists is to provide mistake or in order to obtain when serious information in loaning bill main body
Higher loan limit and can fake offer wrong financial information when, the customer manager as execution business is many times difficult to
Differentiate error message therein, be both to identify some mistakes, many times do not understand how scientifically and rationally by these
Error message is embodied in the influence degree to line of credit.
Content of the invention
The technical problem to be solved is that offer one kind is ingenious reasonably tests to financial collection value and counts
The method calculating line of credit, the correction introducing data irrelevance to credit line is so that final credit number is more accurate
Credible, substantially increase the financial security of credit main body and the operating efficiency of risk assessment.
The present invention the technical scheme is that for solving above-mentioned technical problem
A kind of method financial collection value tested and calculates line of credit, its step includes:
S101 obtains the credit essential information of loaning bill main body and several financial collection values, described financial collection value by
Loaning bill main body is directly provided and/or is obtained by affiliated partner；
S102 obtains n financial data value, and described financial data value is to weigh a described loaning bill principal sector of the economy situation
Every financial index；
At least two kinds acquisition modes of described financial data value, including directly being provided by described loaning bill main body and/or logical
Cross association object acquisition and/or obtained through calculating according to described financial collection value；
S103 obtains the respective weighted mean of n financial data value as the final value of n financial data value, according to
The final value of the credit essential information of described loaning bill main body and n financial data value uses computation model, carries out risk and comments
Estimate, calculate the information scoring regulation coefficient α of impact line of credit；
S104 obtains each financial data value dispersion δ, calculates each described financial data obtaining by least two modes
Value dispersion: δ 1, δ 2 ..., δ n, wherein n≤n；
S105 according to dispersion δ 1 of each described financial data value, δ 2 ..., that δ n weighted calculation obtains financial data value is comprehensive
Close dispersion, the dispersion of each of which financial data value gives default weight；
S106, using described financial data value synthesis dispersion as comprehensive irrelevance δ, is come instead by comprehensive irrelevance δ
Reflect the really degree of the related described finance collection value of loaning bill main body or financial data value, the less explanation of its comprehensive irrelevance is described
The genuine and believable degree of loaning bill main body related data is higher；
It is used (1- δ) to calculate suggestion line of credit as credibility regulation coefficient:
Suggestion line of credit=annual net profit × (1- δ) × α.
Further, the process being artificial collection input except s101 in described step, remaining step is all by intelligently counting
Calculation equipment calculates and completes.
Described intellectual computing device is computer, smart mobile phone, panel computer.
Described being obtained by affiliated partner is included being obtained by original certificate, is obtained by trading object and pass through network
Platform obtains.
It is known that being frequently encountered a very stubborn problem in credit scoring it is simply that loaning bill main body is providing
During information data, a kind of is probably for its bigger loan interests purpose, and a kind of interpretation of records of possibly financial data has
Error, the data that it directly provides is likely to be can be devious, in this case, will significantly hinder the accurate of credit evaluation
Property, greatly increase the later risk of credit.In the prior art, we often rely on risk assessment staff's root of credit
To judge the verity of the various data messages that loaning bill main body provides according to experience, just to bring many uncertain factors like that,
Because artificial judge there is the objective defect such as randomness, experience subjectivity, and is assessed personnel's personal knowledge structure, cognition
The restriction of ability, but also may because the problems such as inside and outside personnel gang up, take bribes so that during Credit Risk Assessment and can occur
Uncontrollable deviation is it is clear that provide, for debt-credit main body, the power artificially passed judgment in the judge of the credibility of data in credit evaluation
Prestige is poor and is difficult to control.
It is based on these puzzlements, the method for the present invention then provides effectively objective solution.
Financial collection value or finance that the method for the present invention directly can provide to loaning bill main body during credit evaluation
Data value carries out effective data verification data analysis, and the present invention passes through at least two acquisition modes and obtains same financial data
Value, including directly being provided and/or according to described financial collection value through calculating acquisition by stating loaning bill main body.So first
First it is simply that verifying to of loaning bill main body unsolicited relevant financial collection value, if obtain in several ways is same
As soon as the dispersion of financial data value is very big, illustrate that the credibility of relevant financial collection value is relatively low, its reason is possibly borrowed money master
Body provides deceptive information it is also possible to make mistakes in the Financial information processing of loaning bill main body.
The present invention have chosen n financial data value as the index weighing a loaning bill principal sector of the economy situation；To same wealth
Business data value is provided with multiple acquisition modes, can be that loaning bill main body directly provides, at least one kind is by some finance
Collection value calculates acquisition；If wherein have multiple by way of calculating and obtaining, it uses incomplete same financial collection value
As sample data, thus more it is able to verify that the really degree of each finance collection value, because much financial collection value is as list
Solely it is difficult to find out its verity during data, but financial data has a feature it is simply that having very strong between a lot of data
Relatedness, financial data itself is quite complicated again, although we know the certain relatedness between them, but
If by manually go with various calculations go collection, arrange, classification, calculate, be again relatively the huge thing of a workload
Feelings, and its checking computations itself because arrange, calculate the complicated possibility that also can there is very big error, that also just loses checking computations
Meaning, thus artificial just relatively I haven't seen you for ages when process verified using multiple analytical calculations by the way of, the present invention exactly make use of meter
The powerful arrangement of calculation machine, computing capability, set multiple acquisition modes, every kind of acquisition modes are not using to same financial data value
Identical one group financial collection value, presets different computing formula, then analyzes the multiple of multiple acquisition modes acquisitions
The dispersion of same financial data value, thus judge the really degree of initial data (financial collection value or financial data value), can
Letter degree.
And the comprehensive dispersion financial data value, comprehensive irrelevance δ bring the computation model of suggestion line of credit into
In, in the form of (1- δ) is as regulation coefficient, suggestion line of credit is carried out with the adjustment of credibility.
Obviously this adjustment is more scientificization, by financial data between multiple relatedness, financial data is carried out many
The calculating of dimension, analysis, checking, had both made the acquisition more science of financial data value, had also implied to loaning bill main body credit simultaneously
The evaluation of degree, this point is never to take into account appraisement system in the prior art, this dispersion, irrelevance no matter
The subjective false offer of loaning bill main body or non-subjective work mistake are provided, all objectively reflect its financial credit,
Certainly a factor of credit safety evaluation should be become, its line of credit can be affected, undoubtedly comprehensive dispersion, irrelevance factor
The significantly perfect credit risk appraisement system of introducing, this objective credit risk evaluation taking into account loaning bill main body financial credit
System is unprecedented, is also breakthrough, its science, objectively reflect debt-credit main body provide data verity,
Do not affected by factors such as personal subjective factors, knowledge structure and bad economic behaviours, be truly realized credit evaluation
Objective, science, quick, effectively.
Brief description
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
Have technology description in required use accompanying drawing be briefly described it should be apparent that, drawings in the following description be only this
Some embodiments of invention, for those of ordinary skill in the art, without having to pay creative labor, also may be used
So that other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is suggestion line of credit calculation process of the prior art；
Fig. 2 is the method financial collection value tested and calculates line of credit of the present invention.
Specific embodiment
The invention will be further described with reference to the accompanying drawings and examples.
Described below loaning bill main body includes self-employed businessman, company and other operational main body.
A kind of method financial collection value tested and calculates line of credit, its step includes:
S101 obtains the credit essential information of loaning bill main body and several financial collection values, described credit essential information
Including the age of enterprise operator, marital status, working experience, reference report, house property information and guarantor's income etc.；Described
Financial collection value directly provided and/or obtained by affiliated partner by main body of borrowing money, include loaning bill main body sales price,
Sales volume, unit price of procurement, purchase quantity, volumn of purchase, buying expenses, production efficiency, the electricity charge, energy consumption, data of paying taxes, selling charges
With, performance pay, accounts receivable detailed data, same period last year stock, asset-liability ratio, assets net profit margin, accounts receivable turnover
Rate；
Described being obtained by affiliated partner is included being obtained by original certificate, is obtained by trading object, passes through network
Platform acquisition etc.；
S102 obtains n financial data value, and described financial data value is to weigh a described loaning bill principal sector of the economy situation
Every financial index；
At least two kinds acquisition modes of described financial data value, including directly being provided by described loaning bill main body and/or logical
Cross association object acquisition and/or obtained through calculating according to described financial collection value；
Described financial data value includes income from sales, selling cost, gross profit, rate of gross profit, net profit, net profit margin, goods
Coin fund, accounts receivable, stock, fixed assets, accounts payable, asset-liability ratio, assets net profit margin, accounts receivable turnover
Rate etc..
S103 obtains the respective weighted mean of n financial data value as the final value of n financial data value, according to
The final value of the credit essential information of described loaning bill main body and n financial data value uses computation model, carries out risk and comments
Estimate, calculate the information scoring regulation coefficient α of impact line of credit；
In view of including the loaning bill main body weaker by credibility in multiple acquisition modes of same financial data value
Directly the finance such as oral account, network platform information collection value obtains, and also the higher financial collection value of with good grounds credibility obtains (such as
Financial audit data, bill evidence etc.), so can basis in the weighted average of multiple acquired value of same financial data value
Source credibility gives different weights.
S104 obtains each financial data value dispersion δ, calculates each described financial data obtaining by least two modes
The dispersion of value: δ1、δ2、……、δn, wherein n≤n；
S105 is according to dispersion δ of each described financial data value1、δ2、……、δnIt is comprehensive that weighted calculation obtains financial data value
Close dispersion, the dispersion of each of which financial data value gives default weight；
S106, using described financial data value synthesis dispersion as comprehensive irrelevance δ, is come instead by comprehensive irrelevance δ
Reflect the really degree of the related described finance collection value of loaning bill main body or financial data value, the less explanation of its comprehensive irrelevance is described
The genuine and believable degree of loaning bill main body related data is higher；
It is used (1- δ) to calculate suggestion line of credit as credibility regulation coefficient:
Suggestion line of credit=annual net profit × (1- δ) × α.
In above-mentioned steps, s101 is the process that artificial collection is input to a panel computer, and remaining step is all by panel computer
Calculating completes.
Certainly described panel computer can also be other intellectual computing devices, such as: computer, smart mobile phone etc.
Deng.
Illustrated with the income from sales of certain enterprise below:
1. loaning bill main body word picture directly provides 10,000,000 yuan of an annual sales revenue；(this 10,000,000 yuan is finance collection
Value m1)
2. provide invoice for sales to calculate 9,940,000 yuan of an annual sales revenue (m2) by client；
3. at the beginning of, stock (m3)+period stock increases (m4)-year end stock (m5)=period stock and reduces volume (m6), period
Stock's minimizing/cost rate=period sales volume=9,030,000 yuan；
4. this enterprise specifies that the performance pay of salesman is, often sells ten thousand yuan of performance pay that can obtain 1% (m7), warp
Counting this year performance pay total value is 120,000 yuan (m8), then can calculate annual sales amount and be 12,000,000 yuan；
5. in this example, employ 8 financial collection values (m1-m8), through calculating or having directly obtained 4 finance
Data value (10,000,000 yuan, 9,940,000 yuan, 9,030,000 yuan, 12,000,000 yuan)；
6. this 4 financial data value are done and averagely obtain 10,240,000 yuan, that is, this financial data value (income from sales) is
Whole value；
7. pair this 4 financial data value carry out dispersion calculating, obtain dispersion δ1；
8. successively dispersion calculating is carried out to financial data value such as rate of gross profit, accounts receivable, stocks, obtain dispersion
δ2、δ3、δ4、δ5……；
9. the dispersion of pair each financial data value gives default weight, calculates financial data value comprehensively discrete
Degree；Using financial data value synthesis dispersion as comprehensive irrelevance δ
10. it is used (1- δ) to calculate suggestion line of credit as credibility regulation coefficient:
11. suggestion line of credit=annual net profit × (1- δ) × α
The above, the only specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, and any
Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, all should contain
Cover within protection scope of the present invention.Therefore, protection scope of the present invention should described be defined by scope of the claims.
Claims (4)
1. a kind of financial collection value tested and calculates the method for line of credit it is characterised in that step includes:
S101 obtains the credit essential information of loaning bill main body and several financial collection values, and described financial collection value is by borrowing money
Main body is directly provided and/or is obtained by affiliated partner；
S102 obtains n financial data value, and described financial data value is each of one described loaning bill principal sector of the economy situation of measurement
Item financial index；
At least two kinds acquisition modes of described financial data value, including directly provided by described loaning bill main body and/or by close
Join object acquisition and/or obtained through calculating according to described financial collection value；
S103 obtains the respective weighted mean of n financial data value as the final value of n financial data value, according to described
The credit essential information of loaning bill main body and the final value of n financial data value use computation model, carry out risk assessment, meter
Calculate the information scoring regulation coefficient α of impact line of credit；
S104 obtains each financial data value dispersion δ, calculates each described financial data value obtaining by least two modes
Dispersion: δ1、δ2、……、δn, wherein n≤n；
S105 is according to dispersion δ of each described financial data value1、δ2、……、δnWeighted calculation obtain financial data value comprehensive from
Divergence, the dispersion of each of which financial data value gives default weight；
S106, using described financial data value synthesis dispersion as comprehensive irrelevance δ, is reflected by comprehensive irrelevance δ and borrows
The related described finance collection value of money main body or the really degree of financial data value, its comprehensive irrelevance is less to illustrate described loaning bill
The genuine and believable degree of main body related data is higher；
It is used (1- δ) to calculate suggestion line of credit as credibility regulation coefficient:
Suggestion line of credit=annual net profit × (1- δ) × α.
2. method according to claim 1 it is characterised in that: the mistake being artificial collection input except s101 in described step
Journey, remaining step is all to be calculated by intellectual computing device to complete.
3. method according to claim 2 it is characterised in that: described intellectual computing device be computer, smart mobile phone,
Panel computer.
4. the method according to claim 1,2 or 3 it is characterised in that: described acquisition by affiliated partner includes passing through
Original certificate is obtained, is obtained by trading object and obtained by the network platform.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107563589A (en) * | 2017-07-26 | 2018-01-09 | 广东电力交易中心有限责任公司 | A kind of electricity market main body credit management system and management method |
| CN109308660A (en) * | 2017-07-27 | 2019-02-05 | 财付通支付科技有限公司 | A kind of reference Rating Model appraisal procedure, device, equipment and storage medium |
| CN109427009A (en) * | 2017-08-23 | 2019-03-05 | 北京嘀嘀无限科技发展有限公司 | A kind of calculation method, system and computer installation for netting Yue Che driver's line of credit |
| CN110246023A (en) * | 2018-03-09 | 2019-09-17 | 上海秦苍信息科技有限公司 | User information appraisal procedure, system and equipment based on internet finance |
| CN110532131A (en) * | 2018-05-24 | 2019-12-03 | 上海方付通商务服务有限公司 | A kind of processing method of cross check, intelligent questionnaire data processing method |
| CN114648400A (en) * | 2022-04-08 | 2022-06-21 | 武汉初旦软件技术有限公司 | Financial data intelligent acquisition analysis management system based on mobile internet |
-
2016
- 2016-08-26 CN CN201610742866.9A patent/CN106339940A/en active Pending
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107563589A (en) * | 2017-07-26 | 2018-01-09 | 广东电力交易中心有限责任公司 | A kind of electricity market main body credit management system and management method |
| CN109308660A (en) * | 2017-07-27 | 2019-02-05 | 财付通支付科技有限公司 | A kind of reference Rating Model appraisal procedure, device, equipment and storage medium |
| CN109308660B (en) * | 2017-07-27 | 2023-03-10 | 财付通支付科技有限公司 | Credit assessment scoring model evaluation method, apparatus, device and storage medium |
| CN109427009A (en) * | 2017-08-23 | 2019-03-05 | 北京嘀嘀无限科技发展有限公司 | A kind of calculation method, system and computer installation for netting Yue Che driver's line of credit |
| CN110246023A (en) * | 2018-03-09 | 2019-09-17 | 上海秦苍信息科技有限公司 | User information appraisal procedure, system and equipment based on internet finance |
| CN110532131A (en) * | 2018-05-24 | 2019-12-03 | 上海方付通商务服务有限公司 | A kind of processing method of cross check, intelligent questionnaire data processing method |
| CN114648400A (en) * | 2022-04-08 | 2022-06-21 | 武汉初旦软件技术有限公司 | Financial data intelligent acquisition analysis management system based on mobile internet |
| CN114648400B (en) * | 2022-04-08 | 2023-01-17 | 深圳肆专科技有限公司 | Financial data intelligent acquisition analysis management system based on mobile internet |
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Application publication date: 20170118 |