CN111626475A - Credit credit calculation method based on product diffusion model - Google Patents
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Abstract
The invention belongs to the technical field of financial risk prevention application, and particularly discloses a credit line measuring and calculating method based on a product diffusion model, which comprises the following steps of 1, obtaining product operation data and previous year financial data of a target enterprise; step 2, preprocessing and characteristic engineering are carried out on the original data; step 3, calculating the predicted sale amount of each product in the next period through an improved product diffusion model; step 4, calculating the predicted operation fund amount by using the product sales amount calculated in the previous step and an operation fund measuring and calculating formula; and 5, measuring and calculating the current credit line of the enterprise by using the calculated predicted operation fund amount and the calculated financial data of the enterprise. The invention has the beneficial effects that: the diffusion model has the advantages that the bank can obtain the later-period sales condition of the enterprise from the historical sales data of the enterprise, the risk caused by the asymmetry of the information between the bank and the enterprise is avoided, and a brand-new direction is provided for accurately measuring and calculating the credit line.
Description
Technical Field
The invention belongs to the technical field of financial risk prevention application, and particularly relates to a method for measuring and calculating credit line based on a product diffusion model, which is suitable for accurate and reliable measurement and calculation of credit loan and credit line of small and medium-sized micro enterprises.
Background
Credit limit, the highest value of credit granted to the client in the credit period approved by the bank, the purpose of the limit measurement
The method is used for accurately and efficiently predicting the risk and calculating the credit line based on the existing information. "three directions are one
Approaches, namely fixed-asset loan management provisional approach, floating-fund loan management provisional approach,
Personal loan management temporary solution and project financing service guide as the means for credit line measurement
And (4) guiding and referring.
Small and medium-sized micro-enterprises have thin own fund, single upstream and downstream channel, fierce competitive environment and higher enterprise risk
High, simultaneously, the finance and the file of the small and medium-sized micro-enterprises are not standardized, the availability and the accuracy of the information are poor, and the credit amount is awarded
The measurement and calculation are more difficult.
The product diffusion model is a product sales condition prediction method, can be used for predicting the first purchase of durable consumer products and the repeated purchase of non-durable consumer products, and can also be used for predicting the market promotion of updated products and predicting the number of users and sales of the products. The Bass model is the most classical product diffusion model and is widely applied in the popularization process of new products, new services and new technologies, and the rest product diffusion models are basically improved based on the Bass model.
Therefore, in view of the above problems, the present invention provides a credit calculation method based on a product diffusion model.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a credit line calculation method based on a product diffusion model, which is used for predicting the transaction amount of an enterprise in a future time period by constructing the product diffusion model, calculating the operation fund of the enterprise based on the prediction and further accurately estimating the credit line of the enterprise.
The technical scheme is as follows: the invention provides a credit line measuring and calculating method based on a product diffusion model, which comprises the following steps of 1, obtaining product operation data and previous year financial data of a target enterprise; step 2, preprocessing and characteristic engineering are carried out on the original data to obtain product sales data and enterprise financial data which can be used by the module; step 3, calculating each predicted product by using the product data calculated in the previous step and through an improved product diffusion model
Sales volume of the product at the next date; step 4, calculating the predicted operation fund amount by using the product sales amount calculated in the previous step and combining three data of product price, enterprise profit rate, operation fund turnover frequency and the like obtained after the original data are processed; and 5, measuring and calculating the current credit line of the enterprise according to the mobile fund loan management method by using the calculated predicted operation fund amount and the calculated financial data of the enterprise.
According to the technical scheme, the data acquired in the step 1 and the step 2 are sales data and financial data, wherein the sales data are product names sold by enterprises, product prices, sales volumes, sales time, buyer information and the like, the financial data are index information capable of reflecting assets, liabilities, damages, costs, profits, repayment capabilities and operation efficiency, and the data are required to be preprocessed according to input requirements of models and calculation algorithms after the data are acquired.
In the technical scheme, the predicted sale amount of each product in the next period is calculated through a formula in the step 3,
wherein in the formula, t is a period (month, season or year);
number of product picks (i.e., predicted sales) for period t;
innovation factor for first purchase;
innovation factor for repeat purchase;
a simulation coefficient for first purchase;
a simulation coefficient for repeat purchase;
market potential for the first purchased product;
market potential for repeatedly purchased products;
the accumulated number of the first purchased adopters in the period t-1 (the number of the first purchased adopters after the weight of all the purchasing parties is removed);
cumulative use count (i.e., sales) for repeated purchases for the t-1 period;
cumulative adoption (i.e., cumulative sales) for repeated purchases for period t; λ is the regression coefficient of the repeat purchase (i.e. the weight of the repeat purchase);
is the number of the purchase in the period t;
is composed of
In the technical scheme, the predicted operation fund amount is calculated by an operation fund measuring and calculating formula in the step 4, the mobile fund loan is mainly used for meeting the fund required by daily operation of an enterprise, the future sales income is estimated firstly during estimation and is converted into the operation fund amount during each turnover, and therefore after the next-period product sales amount is predicted, the operation fund amount is calculated according to the following formula by combining the current-period product sales price, the last-year sales profit rate, the (per-period) operation fund turnover times and the like: the current product sales price x the predicted next product sales volume x (1-last year sales profit margin)/(per term) operational capital turnover number.
In the technical scheme, in the step 5, the self-owned funds of the borrower, the existing liquidity loan and other financing are deducted from the calculated operating fund demand of the borrower, the newly added liquidity loan amount can be estimated, and the credit granting amount and the like of the enterprise are measured and calculated by combining the characteristics (reflected by the operating efficiency index) of seasonal production, order financing and the like of the borrower;
firstly, carrying out regression fitting on the sales data in the step 3 by adopting a formula, calculating parameters for predicting the sales of the product in the next period, wherein in the formula in the step 3, the parameters to be predicted comprise an innovation coefficient p, a simulation coefficient q, a market potential M and a regression coefficient/weight lambda for repeated purchase, after the parameters are estimated, predicting the sales of the product in the next period by utilizing the formula in the step 3,
wherein in the formula, t is a period (month, season or year);
the predicted next product utilization number (i.e., predicted sales);
innovation factor for first purchase;
innovation factor for repeat purchase;
a simulation coefficient for first purchase;
a simulation coefficient for repeat purchase;
market potential for the first purchased product;
market potential for repeatedly purchased products;
the cumulative number of adopters (the number of people who have been removed from the weight of all the purchasing parties) purchased for the first time in the period t;
cumulative adoption (i.e., sales) for repeated purchases for period t; λ is the regression coefficient of the repeat purchase (i.e. the weight of the repeat purchase);
secondly, estimating the operating fund amount of the enterprise in the next period according to the product sales volume of the predicted product in the next period, the current sales price, the annual sales profit rate and the like, and the consideration of the sales profit rate in the current period, the operating fund turnover times and the like;
and finally, according to the estimated operation fund amount of the next period of the enterprise, combining other financial data of the enterprise, such as own fund, mobile fund loan, other financing, operation efficiency indexes and the like, and performing credit line measurement and calculation for the commercial bank to provide credit line reference for clients of the enterprise.
Compared with the prior art, the credit line measuring and calculating method based on the product diffusion model has the beneficial effects that: the use of the diffusion model is advantageous in that the bank can obtain the next date of the enterprise from the historical sales data of the enterprise
The risk caused by the asymmetry of information between banks and enterprises is avoided under the condition of sales; the product diffusion model is combined with the credit loan credit line measurement and calculation of small and medium enterprises, a brand new direction is provided for accurately measuring and calculating the credit line, and the method is an innovation of applying the diffusion model to the field of intelligent wind control.
Drawings
FIG. 1 is a schematic view of the work flow structure of the credit rating calculation method based on the product diffusion model of the present invention.
Detailed Description
The invention is further elucidated with reference to the drawings and the embodiments.
Examples
The credit line calculation method based on the product diffusion model shown in fig. 1 comprises the following steps of 1, obtaining product operation data and past year financial data of a target enterprise; step 2, preprocessing and characteristic engineering are carried out on the original data to obtain product sales data and enterprise financial data which can be used by the module; step 3, calculating the predicted sale amount of each product in the next period by using the product data calculated in the previous step and through an improved product diffusion model; step 4, calculating the predicted operation fund amount by using the product sales amount calculated in the previous step and combining three data of product price, enterprise profit rate, operation fund turnover frequency and the like obtained after the original data are processed; and 5, measuring and calculating the current credit line of the enterprise according to the mobile fund loan management method by using the calculated predicted operation fund amount and the calculated financial data of the enterprise.
Further preferably, the data collected in step 1 and step 2 are sales data and money
The system comprises affair data, wherein the sale data comprises product names, product prices, sales volumes, sale time, information of purchasing parties and the like sold by enterprises, the financial data comprises index information capable of reflecting assets, liabilities and benefits, costs, profits, repayment capacity and operation efficiency, and the data needs to be preprocessed according to input requirements of a model and a measuring and calculating algorithm after being collected; the predicted sale amount of each product at the next period is calculated by a formula in the step 3,
wherein in the formula, t is a period (month, season or year);
number of product picks (i.e., predicted sales) for period t;
innovation factor for first purchase;
innovation factor for repeat purchase;
a simulation coefficient for first purchase;
a simulation coefficient for repeat purchase;
market potential for the first purchased product;
market potential for repeatedly purchased products;
the accumulated number of the first purchased adopters in the period t-1 (the number of the first purchased adopters after the weight of all the purchasing parties is removed);
cumulative use count (i.e., sales) for repeated purchases for the t-1 period;
cumulative adoption (i.e., cumulative sales) for repeated purchases for period t; λ is the regression coefficient of the repeat purchase (i.e. the weight of the repeat purchase);
is the number of the purchase in the period t;
is composed of
In the step 4, the predicted operation fund amount is calculated through an operation fund measuring and calculating formula, the mobile fund loan is mainly used for meeting the fund required by daily operation of an enterprise, the future sales income is estimated firstly during estimation and converted into the operation fund amount during each turnover, and therefore after the product sales amount of the next period is predicted, the operation fund amount is calculated according to the following formula by combining the current product sales price, the annual sales profit rate, the operation fund turnover frequency (in each period) and the like: the current product sale price is multiplied by the predicted next product sale quantity x (1-the last year sale profit rate)/(each period) operation fund turnover number; in the step 5, the operating fund demand of the borrower measured in the front is deducted from the own fund, the existing liquidity loan and other financing of the borrower, the newly added liquidity loan amount of the borrower can be estimated, and the credit granting amount of the enterprise and the like are measured and calculated by combining the characteristics (reflected by the operating efficiency index) of seasonal production, order financing and the like of the borrower;
firstly, carrying out regression fitting on the sales data in the step 3 by adopting a formula, calculating parameters for predicting the sales of the product in the next period, wherein in the formula in the step 3, the parameters to be predicted comprise an innovation coefficient p, a simulation coefficient q, a market potential M and a regression coefficient/weight lambda for repeated purchase, after the parameters are estimated, predicting the sales of the product in the next period by utilizing the formula in the step 3,
wherein in the formula, t is a period (month, season or year);
the predicted next product utilization number (i.e., predicted sales);
innovation factor for first purchase;
innovation factor for repeat purchase;
a simulation coefficient for first purchase;
a simulation coefficient for repeat purchase;
market potential for the first purchased product;
market potential for repeatedly purchased products;
the cumulative number of adopters (the number of people who have been removed from the weight of all the purchasing parties) purchased for the first time in the period t;
cumulative adoption (i.e., sales) for repeated purchases for period t; λ is the regression coefficient of the repeat purchase (i.e. the weight of the repeat purchase);
secondly, estimating the operating fund amount of the enterprise in the next period according to the product sales volume of the predicted product in the next period, the current sales price, the annual sales profit rate and the like, and the consideration of the sales profit rate in the current period, the operating fund turnover times and the like;
and finally, according to the estimated operation fund amount of the next period of the enterprise, combining other financial data of the enterprise, such as own fund, mobile fund loan, other financing, operation efficiency indexes and the like, and performing credit line measurement and calculation for the commercial bank to provide credit line reference for clients of the enterprise.
The foregoing is only a preferred embodiment of this invention and it should be noted that modifications can be made by those skilled in the art without departing from the principle of the invention and these modifications should also be considered as the protection scope of the invention.
Claims (5)
1. The credit line measuring and calculating method based on the product diffusion model is characterized in that: comprises the following steps of (a) carrying out,
step 1, acquiring product operation data and previous year financial data of a target enterprise;
step 2, preprocessing and characteristic engineering are carried out on the original data to obtain product sales data and enterprises which can be used by the module
Business financial data;
step 3, calculating each predicted product by using the product data calculated in the previous step and through an improved product diffusion model
Sales volume of the product at the next date;
step 4, using the product sales calculated in the previous step and combining the product price and the enterprise obtained after the original data processing
Calculating the predicted operation fund amount according to operation fund measuring and calculating formulas based on the three data of the operation profit rate, the operation fund turnover frequency and the like;
and 5, measuring and calculating the current credit line of the enterprise according to the mobile fund loan management method by using the calculated predicted operation fund amount and the calculated financial data of the enterprise.
2. The credit line calculation method based on the product diffusion model as claimed in claim 1, wherein: the data collected and obtained in the step 1 and the step 2 are sales data and financial data, wherein the sales data are product names sold by enterprises, product prices, sales volumes, sales time, purchaser information and the like, the financial data are index information capable of reflecting assets, liabilities and losses, costs, profits, debt paying capacity and operation efficiency, and the data need to be preprocessed according to model and calculation algorithm input after being collected.
3. The credit line calculation method based on the product diffusion model as claimed in claim 1, wherein:
the predicted sale amount of each product at the next period is calculated by a formula in the step 3,
wherein in the formula, t is a period (month, season or year);
number of product picks (i.e., predicted sales) for period t;
innovation factor for first purchase;
innovation factor for repeat purchase;
a simulation coefficient for first purchase;
a simulation coefficient for repeat purchase;
market potential for the first purchased product;
market potential for repeatedly purchased products;
the accumulated number of the first purchased adopters in the period t-1 (the number of the first purchased adopters after the weight of all the purchasing parties is removed);
cumulative use count (i.e., sales) for repeated purchases for the t-1 period;
cumulative number of purchases repeated for period t (alsoI.e., cumulative sales); λ is the regression coefficient of the repeat purchase (i.e. the weight of the repeat purchase);
is the number of the purchase in the period t;
is composed of
4. The credit line calculation method based on the product diffusion model as claimed in claim 1, wherein: in the step 4, the predicted operation fund amount is calculated through an operation fund measuring and calculating formula, the mobile fund loan is mainly used for meeting the fund required by daily operation of an enterprise, the future sales income is estimated firstly during estimation and converted into the operation fund amount during each turnover, and therefore after the product sales amount of the next period is predicted, the operation fund amount is calculated according to the following formula by combining the current product sales price, the annual sales profit rate, the operation fund turnover frequency (in each period) and the like: the current product sales price x the predicted next product sales volume x (1-last year sales profit margin)/(per term) operational capital turnover number.
5. The credit line calculation method based on the product diffusion model as claimed in claim 1, wherein: in the step 5, the operating fund demand of the borrower measured in the front is deducted from the own fund, the existing liquidity loan and other financing of the borrower, the newly added liquidity loan amount of the borrower can be estimated, and the credit granting amount of the enterprise and the like are measured and calculated by combining the characteristics (reflected by the operating efficiency index) of seasonal production, order financing and the like of the borrower;
firstly, carrying out regression fitting on the sales data in the step 3 by adopting a formula, calculating parameters for predicting the sales of the product in the next period, wherein in the formula in the step 3, the parameters to be predicted comprise an innovation coefficient p, a simulation coefficient q, a market potential M and a regression coefficient/weight lambda for repeated purchase, after the parameters are estimated, predicting the sales of the product in the next period by utilizing the formula in the step 3,
wherein in the formula, t is a period (month, season or year);
the predicted next product utilization number (i.e., predicted sales);
innovation factor for first purchase;
innovation factor for repeat purchase;
a simulation coefficient for first purchase;
a simulation coefficient for repeat purchase;
market potential for the first purchased product;
market potential for repeatedly purchased products;
the cumulative number of adopters (the number of people who have been removed from the weight of all the purchasing parties) purchased for the first time in the period t;
cumulative adoption (i.e., sales) for repeated purchases for period t; λ is the regression coefficient of the repeat purchase (i.e. the weight of the repeat purchase);
secondly, estimating the operating fund amount of the enterprise in the next period according to the product sales volume of the predicted product in the next period, the current sales price, the annual sales profit rate and the like, and the consideration of the sales profit rate in the current period, the operating fund turnover times and the like;
and finally, according to the estimated operation fund amount of the next period of the enterprise, combining other financial data (such as own fund, moving fund loan, other financing, operation efficiency indexes and the like) of the enterprise to carry out credit line measurement and calculation for the commercial bank to provide credit line reference for clients of the enterprise.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101901403A (en) * | 2009-05-27 | 2010-12-01 | 北京正辰科技发展有限责任公司 | Customer credit line information management platform system |
| CN106600415A (en) * | 2015-10-19 | 2017-04-26 | 阿里巴巴集团控股有限公司 | Method and apparatus for determining business credit |
| CN106886944A (en) * | 2017-03-23 | 2017-06-23 | 深圳微众税银信息服务有限公司 | A kind of enterprise's accrediting amount computational methods and enterprise's accrediting amount computing system |
| CN107492033A (en) * | 2017-08-30 | 2017-12-19 | 广东信基蜂巢科技有限责任公司 | A kind of credit estimation method and device based on air control model |
| CN107590734A (en) * | 2017-08-21 | 2018-01-16 | 中国建设银行股份有限公司 | Determine method and device, terminal device and the computer-readable storage medium of the accrediting amount |
-
2020
- 2020-04-23 CN CN202010325199.0A patent/CN111626475A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101901403A (en) * | 2009-05-27 | 2010-12-01 | 北京正辰科技发展有限责任公司 | Customer credit line information management platform system |
| CN106600415A (en) * | 2015-10-19 | 2017-04-26 | 阿里巴巴集团控股有限公司 | Method and apparatus for determining business credit |
| CN106886944A (en) * | 2017-03-23 | 2017-06-23 | 深圳微众税银信息服务有限公司 | A kind of enterprise's accrediting amount computational methods and enterprise's accrediting amount computing system |
| CN107590734A (en) * | 2017-08-21 | 2018-01-16 | 中国建设银行股份有限公司 | Determine method and device, terminal device and the computer-readable storage medium of the accrediting amount |
| CN107492033A (en) * | 2017-08-30 | 2017-12-19 | 广东信基蜂巢科技有限责任公司 | A kind of credit estimation method and device based on air control model |
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