KR102139938B1 - System for selection of companies subject to credit guarantees based on credit guarantees propensity analysis - Google Patents

Abstract

The present invention provides a system for selecting a company subject to credit guarantee based on credit guarantee propensity analysis, comprising: a data input unit receiving a specification of a credit guarantee loan performed for a set time and company information; a credit rating calculation unit classifying the company information according to a business category sector, a technology sector and a finance sector of a company and performing analysis according to each sector to computationally calculate credit rating data of the company; a guarantee propensity detection unit sorting the specification of the credit guarantee loan based on the credit rating data to computationally detect guarantee propensity data according to the business category sector, the technology sector and the finance sector of the company; and a guarantee simulation unit selecting a company with high possibility to be subject to credit guarantee and sequentially leveling the company based on the guarantee propensity data provided by the guarantee propensity detection unit. The present invention can calculate the credit rating of a company.

Description

System for selection of companies subject to credit guarantees based on credit guarantees propensity analysis}

The present invention relates to a system for selecting a business subject to a credit guarantee based on an analysis of the credit guarantee propensity, and more specifically, to detect a guarantee propensity of the credit guarantee fund by using credit guarantee loan details and company information of the credit guarantee fund and to detect a credit guarantee target. This is a technical field for the system to be selected.

The credit guarantee system is a system that allows companies with insufficient collateral to receive loans from financial companies by providing credit guarantees by examining the creditworthiness of companies in the credit guarantee fund. The Korea Credit Guarantee Fund provides guarantee support to companies with certain qualifications to contribute to balanced national economic development and strengthen the competitiveness of the national economy. Companies that can receive credit guarantees include private companies that do business for profit, corporate companies that do business for profit, and SME cooperatives under the Small and Medium Business Association Act. Large corporations are limited to companies subject to guarantee, and listed companies are limited to certain funds.

Credit guarantee can be handled without restrictions by industry. However, some types of guarantee support may be limited for industries that may promote gambling, meandering games, luxury, entertainment, and real estate speculation. In addition, the guarantee handling may be restricted for companies that are deemed to be difficult to maintain continuously due to deteriorating credit status, and for companies that have suffered losses on new information and their debtors, the handling of guarantees may be prohibited.

The credit guarantee process goes through the process of applying for warranty consultation, consulting and receiving a guarantee, credit investigation, guarantee review and approval, and issuance of a warranty. The application for guarantee consultation is the first procedure to use the guarantee, and it is a process in which the company transfers the intention to use the credit guarantee to the credit guarantee fund. The guarantee consultation and the reception of the guarantee will grasp the contents of the credit management information of the company requesting the credit guarantee, and review the validity and basic credit status of the guarantee consultation application in advance. The credit survey conducts preliminary and on-site surveys, collects the credit survey data, and comprehensively reviews the company's management status, funding status, and management capabilities to determine whether or not to execute the guarantee. Assurance audit is the process of investigating, reviewing and approving the necessary matters to determine whether or not to execute the guarantee, and the screening criteria are different depending on the amount of the deposit. Finally, a credit guarantee agreement is signed with a company that has passed the screening, and a certificate is issued.

However, it is difficult to obtain a credit guarantee loan because the Credit Guarantee Fund does not provide guarantee support to all applicants, but only to companies that have been approved through a strict examination. Therefore, it is necessary to increase the probability of receiving the guarantee support by analyzing the credit status of the companies receiving the guarantee support, based on the guarantee loan data made in the credit guarantee fund.

As an example of a prior patent document related to this, there is “a roughly intermediary platform system and a credit evaluation apparatus and a method thereof” (Registration No. 10-1955546, hereinafter referred to as Patent Document 1).

In the case of Patent Document 1, the present invention provides a loan intermediary platform system and a credit rating evaluation apparatus and method for allowing a financial institution to grasp credit information of a borrower based on an interpersonal loan service. The loan intermediary platform system transmits and receives data to and from the lender terminal and the investor terminal, a communication unit that receives loan application information from the lender terminal, generates investment product information based on the loan application information, and transmits the investment product information to the communication unit Matching unit that matches the lender and the investor by providing to the investor terminal through the transaction history database storing user information and transaction history of the lender based on the matching result, and the transaction history stored in the transaction history database When the credit condition is satisfied, it may include a user information providing unit that provides the user information and transaction history to the affiliated financial institution server through the communication unit.

As an example of another patent document, there is an “evaluation and certification system for corporate value” (Registration No. 10-1279781, hereinafter referred to as Patent Document 2).

In the case of Patent Document 2, the present invention relates to a system for evaluating and authenticating corporate values, and more specifically, by providing certification-related information of a certified company to a financial institution server by performing certification of the corporate value at the credit guarantee institution server. , Financial institutions can receive credit investigation information from the credit guarantee institution as data from the financial institution server, which increases the efficiency of work and recommends financial institutions that have signed a business agreement with the credit guarantee institution in advance. It can be used as a means of supporting SMEs by government agencies, as well as being used as a means for supporting SMEs by government agencies, and it can be reflected in the credit screening of financial institutions. In addition to bringing about efficiency, it is possible to make a soft landing for the withdrawal of marginal companies. From a credit guarantee institution's perspective, it is possible to improve the external credibility of the company by switching the screening system according to the center of the company's future value. As a certification agency, it is possible to establish its status and expand its business scope, and from a company's point of view, it can create an environment where companies with good future growth and corporate value are favored, and also deal with financial institutions through transactions with credit guarantee institutions. You can proceed simultaneously, simplifying tasks such as burden on data submission and visiting financial institutions, and providing preferential benefits for interest rates and loan limits depending on the certified company of corporate value. In addition, it is possible to reduce costs by simplifying the examination process of the company, and it is possible to secure a high-quality company with high corporate value as a business partner.

However, in the case of patent document 1, in order to effectively intermediary loans in the loan service, information is provided to the lenders so that they can receive loans at a low interest rate quickly. Only technical ideas exist.

In the case of Patent Document 2, the financial institution provides the calculated corporate value through the corporate value solution developed by the Credit Guarantee Fund based on the corporate information and provides the calculated corporate value information to the financial institution server. Analysis of the guarantee propensity of the Korea Credit Guarantee Fund as a technical idea to provide a system for evaluating and evaluating corporate values that can provide financial institutions that have signed a pre-business agreement to companies that have applied for information and have the credit guarantee agency applied for guarantee. There is no technical idea for.

Registration No. 10-1955546 Registration No. 10-1279781

The credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention has been devised to solve the conventional problems as described above, and presents the following problems to be solved.

First, the credit guarantee fund's guarantee loan data and corporate information are extracted to classify the business into sectors, technical and financial sectors, and each sector is calculated to accurately analyze the company's creditworthiness.

Second, it is intended to detect guarantee propensity data by salting the credit guarantee data of the credit guarantee fund and the credit data of the company calculated from the credit calculation unit.

Third, we intend to select a company with a high probability of selecting credit guarantee support from the Korea Credit Guarantee Fund based on the guarantee propensity data.

The problem of the present invention is not limited to those mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.

The credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention has the following problem solving means for the above-mentioned problems.

The credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention includes a data input unit that receives credit guarantee loan details and company information performed for a certain period of time; A credit calculation unit that classifies the company information into sectors, technical sectors, and financial sectors of the companies, and analyzes each sector for computerized credit data; A guarantee propensity detection unit for computing the propensity propensity data according to the industry sector, technical sector, and financial sector of the enterprise by sorting the credit guarantee loan history based on the credit data; Based on the guarantee propensity data provided from the guarantee propensity detection unit, a guarantee simulation unit for sequentially selecting and leveling companies that are likely to be subject to the credit guarantee, the credit calculation unit comprising: An industry sector unit that classifies the industry type of the company based on the classification criteria and analyzes the market size, export size, government-funded amount, number of companies, and growth rate during the predetermined period to calculate future growth indicators of the industry type; A technical sector unit for calculating the technical index of the company by analyzing the research and development cost of the company, the ratio of R&D investment to sales, facility facility size, facility investment cost, production capacity index, and the number of intellectual property applications; And a financial sector unit for calculating the financial index of the company by automatically calculating a financial ratio indicating the liquidity, stability, profitability, and activity of the company by analyzing the financial activity status of the company performed for a certain period of time. It can be characterized as.

The financial sector portion of the credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention includes sales, sales performance, operating profit, interest, net income, capital, current assets, inventory assets, It may be characterized by calculating at least one of total assets, debt, current liabilities, debt ratio, return on investment (ROI) or growth rate, and calculating the financial ratio of the company by automatically calculating the financial ratio. have.

The credit calculation unit of the credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention scores the company information as the future growth index of the industry, the technology index of the company, and the financial index of the company, and ranks N It can be characterized by calculating by dividing by.

The guarantee propensity detection unit of the credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention, in order to reflect the credit data, iii) the weight of the technical sector and the financial sector according to the sector of the enterprise. Is applied differently, and ii) the weight of the industry sector and the financial sector of the company is applied differently according to the technical sector, and iv) the weight of the industry sector and the technical weight of the company is applied according to the financial sector. It may be characterized by detecting the guarantee propensity data by applying differently.

The guarantee simulation unit of the credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention selects and ranks the credit guarantee target companies and randomizes them randomly in the list data of the selected credit guarantee target companies It may be characterized in that it comprises an interrupting signal for adding a noise signal.

The credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention having the above configuration provides the following effects.

First, by extracting the guarantee loan data and company information of the Korea Credit Guarantee Fund, the company can be classified into industry, technology, and financial sectors, scored by each sector, and classified into grades to calculate the company's credit.

Second, the credit guarantee data of the credit guarantee fund and the credit data of the company calculated from the credit calculation unit can be detected by applying different weights to each sector.

Third, it is possible to sequentially level companies with a high probability of selecting credit guarantee support from the credit guarantee fund based on the guarantee propensity data.

The effects of the present invention are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

1 is a conceptual diagram of a credit guarantee target company selection system based on a credit guarantee propensity analysis according to an embodiment of the present invention.
2 is a block diagram of a credit calculation unit of a credit guarantee target company selection system based on a credit guarantee propensity analysis according to an embodiment of the present invention.
3 is a conceptual diagram of a sector sector of a credit selection target company selection system based on a credit guarantee propensity analysis according to an embodiment of the present invention.
4 is a conceptual diagram of a technical sector portion of a system for selecting a business subject to credit guarantee based on an analysis of credit guarantee propensity according to an embodiment of the present invention.
5 is a conceptual diagram of a financial sector portion of a system for selecting a business subject to credit guarantee based on an analysis of credit guarantee propensity according to an embodiment of the present invention.
6 is a conceptual diagram of a guarantee simulation unit of a credit guarantee target company selection system based on a credit guarantee propensity analysis according to an embodiment of the present invention.

The system for selecting a business subject to a credit guarantee based on the analysis of the credit guarantee propensity according to the present invention may apply various changes and may have various embodiments, and specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to specific embodiments, and should be understood to include all modifications, equivalents, and substitutes included in the technical spirit and technical scope of the present invention.

1 is a conceptual diagram of a credit guarantee target company selection system based on a credit guarantee propensity analysis according to an embodiment of the present invention. 2 is a block diagram of a credit calculation unit of a credit guarantee target company selection system based on a credit guarantee propensity analysis according to an embodiment of the present invention. 3 is a conceptual diagram of a sector sector of a credit selection target company selection system based on a credit guarantee propensity analysis according to an embodiment of the present invention. 4 is a conceptual diagram of a technical sector portion of a system for selecting a business subject to credit guarantee based on an analysis of credit guarantee propensity according to an embodiment of the present invention. 5 is a conceptual diagram of a financial sector portion of a system for selecting a business subject to credit guarantee based on an analysis of credit guarantee propensity according to an embodiment of the present invention. 6 is a conceptual diagram of a guarantee simulation unit of a credit guarantee target company selection system based on a credit guarantee propensity analysis according to an embodiment of the present invention.

In the case of a system for selecting a credit guarantee target based on a credit guarantee propensity analysis according to the present invention, as shown in FIG. 1, in order to select a credit guarantee target, a data input unit 100, a credit calculation unit 200, and a guarantee propensity It will include the detection unit 300 and the warranty simulation unit 400.

First, the data input unit 100 receives credit guarantee loan details and company information 10. Credit guarantee loan details are credit guarantee loan data made from the credit guarantee fund for 10 years, and corporate information is data on information of companies that have received credit guarantee for 10 years, extracted through the company's business reports, financial statements, and audit reports. It is desirable that the data is embedded.

In the case of the credit calculation unit 200 of the credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention, the company information is classified into the industry sector, technical sector, and financial sector of the company, and analyzed by each sector Will compute the creditworthiness data of.

As shown in FIG. 2, the credit calculation unit 200 includes an industry sector unit 210, a technical sector unit 220, and a financial sector unit 230.

As shown in Fig. 3, the sector sector 210 classifies the business sector of the enterprise based on standard industry classification criteria and analyzes the market size, export size, government support amount, number of enterprises, and growth rate over a period of time to start the business. The industry's future growth index will be calculated. Here, the standard industry classification refers to the standard that is applied uniformly to prepare various statistics related to industrial activities by classifying and encoding all industrial activities according to their nature, and government policies such as financial tax support or credit management. It is used as a criterion for classifying the scope and targets of industries that can be applied consistently in the process of establishing and implementing, and if necessary, it can be classified in more detail by standard industry classification standards. In addition, it is desirable to analyze the market size, export size, government-funded amount, number of companies, and growth rate in order to understand the future growth potential according to the classified industries and calculate future growth indicators.

In addition, the market size can be estimated by measuring the market size by using Total Addressable Market (TAM)-Service Available Market (SAM)-Service Obtainable Market (SOM). TAM refers to the size of the business domain that includes the category areas of products/services in the overall market, SAM is called the effective market, and the size of the business market pursued by startups in TAM, and the business pursued by the company among all markets It can be said to be a market where models can be applied. SOM is called a profit market and refers to the market size that can be secured at an early stage within the effective market. When TAM-SAM-SOM is combined, it is a process of logically deriving the size of the market to enter, and the ability to find a surviving market that can generate revenue is proved numerically. In the case of export size and growth rate, it is desirable to analyze the annual average export growth rate and growth rate by region, country, and type over the past five years.

As shown in FIG. 4, the technical sector unit 220 analyzes a company's R&D cost, ratio of R&D investment to sales, facility facility size, facility investment cost, production capacity index, and number of intellectual property applications to analyze the company's technical index. Will calculate. The reason for analyzing R&D cost, R&D investment ratio to sales, facility facility size, facility investment cost, and the number of intellectual property applications is a key factor in determining a company's future growth and profit, through which This is because the company can continue to grow by improving productivity and accumulating knowledge and technical capital. In addition, production capacity generally means the expected maximum production when the company's equipment is fully operated under normal conditions, that is, the maximum potential production, and the production capacity index is the index of the change in production capacity. You will be able to analyze how skill levels and trends change.

As shown in FIG. 5, the financial sector unit 230 analyzes the financial activity status of the company performed for a certain period of time, and automatically calculates the financial ratio 20 representing the liquidity, stability, profitability, and activity of the company. The company's financial indicators are calculated.

In more detail, the financial sector unit 230 includes a company's sales, sales performance, operating profit, interest, net income, capital, current assets, inventory assets, total assets, liabilities, current liabilities, debt ratio, The financial ratio 20 is automatically calculated with at least one indicator of Return On Investment (ROI) or growth rate.

이며, 당좌 비율은 기업의 단기 채무 지급 능력을 판단할 때 유동 비율보다 더 정확하며, 일반적으로 100% 이상이면 기업의 유동성이 양호한 것으로 보며, 당좌 비율 계산식은

이다.The financial ratio (20) calculated here includes a current ratio and a current ratio that measure the liquidity of an entity's ability to fulfill debts due in the short term. The flow rate is a rate that measures a company's ability to pay short-term debts, and varies depending on the characteristics of the industry.However, if it is more than 200%, the liquidity of the company is good.

The current rate is more accurate than the current rate when judging the company's ability to pay short-term debts. Generally, if it is 100% or higher, the company's liquidity is considered good.

to be.

이고, 이자 보상 비율은 기업의 부채에 따른 이자 비용 지급 능력을 측정하는 데 사용하며, 이 비율이 1보다 커야 이자를 정상적으로 지급할 수 있으며 이자 보상 비율의 계산식은

이다.The ratio of measuring a company's long-term payment ability to the financial ratio (20), which measures the stability of the firm's dependence on others' capital, is the ratio of debt to interest. The debt ratio is used to measure the stability of a company's capital composition. When the debt ratio is low, the financial structure is stable.

, And the interest compensation ratio is used to measure the ability to pay interest expenses based on a company's debt.If this ratio is greater than 1, interest can be paid normally, and the calculation formula of the interest compensation ratio is

to be.

이고, 기업의 경영 활동에 따른 성과를 총괄적으로 파악하는 비율로 매출액 1원에 대한 순이익을 나타내는 매출액 순이익률의 계산식은

이다.The financial ratio (20), which measures the profitability of a company's overall efficiency as a result of its overall efficiency as a return on sales or return on investment, represents the total net net profit margin There is a net margin of sales. The gross net profit margin is the ratio that represents the earnings of a company.

The ratio of the company's management activities to grasp the overall performance,

to be.

이고, 재고 자산 회전율은 재고 자산이 일정 기간 동안 몇 번이나 회전하였는가를 보여 주며, 이 비율이 낮으면 매출액에 비해 많은 재고를 보유하고 있음을 의미하며 재고 자산 회전율은

이다.The financial ratio (20), which measures activity, expressed as the turnover ratio of each important asset to sales, as a percentage of how effectively an entity owns assets is used, includes total asset turnover and inventory turnover, and total asset turnover. Is the ratio of how many times a year a company's total assets have been rotated, which is a comprehensive indication of the effective utilization of the total assets used by the company, and the higher the ratio, the better the efficiency.

, And inventory turnover shows how many times the inventory has been rotated over a period of time.If this ratio is low, it means that you have more inventory than sales, and the inventory turnover is

to be.

In addition, in the credit calculation unit 200, it is preferable to calculate the company information by scoring the future growth index of the industry, the technical index of the company, and the financial index of the company and classifying them into N grades.

The guarantee propensity detection unit 300 of the credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention sorts the credit guarantee loan history based on the credit quality data, so that the industry sector, technical sector, financial The guarantee propensity data according to the sector is computed.

At this time, in order to reflect credit data, ⅰ) the weight of the technical sector and financial sector are applied differently according to the sector of the company, and ii) the weight of the business sector and financial sector of the company is applied differently according to the technology sector. And iii) It is desirable to apply different weights to the sectors and technical characteristics of companies depending on the financial sector.

As illustrated in FIG. 6, the guarantee simulation unit 400 selects a company that is likely to be a credit guarantee based on the guarantee propensity data provided from the guarantee propensity detection unit 300 and levels it sequentially. It is preferred.

The guarantee simulation unit 400 of the credit guarantee target company selection system based on the credit guarantee propensity analysis according to the present invention may include an interrupting signal unit 410.

The interrupting signal unit 410 selects companies that are likely to be subject to credit guarantees and randomly adds noise signals to the leveled company list data.

In the case of the guarantee simulation unit 400 of the present invention, an interrupting signal unit 410 may be included.

In the case of the interrupting signal unit 410, a credit guarantee target company is selected and graded and leveled, and a random noise signal is randomly added to the list data information of the selected credit guarantee target company.

Since security is important for list data information of companies subject to credit guarantees, random noise signals are randomly generated when transmitting and receiving such information, and in addition to the list data information of companies subject to credit guarantees, the transmitting end and the receiving end exchange information. , The transmitting end and the receiving end share the ID of a function generating a random noise signal and the rules of a random variable generated by the ID.

The receiving end sharing the rule of the random variable is able to restore original data of the credit guarantee target company, which is the original information, after filtering and removing only the random variable from the information transmitted by the transmitting end.

The scope of rights of the present invention is determined by the matters described in the claims, and the parentheses used in the claims are not described for selective limitation, but are used for clear components, and the descriptions in parentheses are also interpreted as essential components. Should be.

10: Credit Guarantee Loan History and Company Information
20: Financial ratio
100: data input unit
200: credit rating calculation unit
210: sector sector
220: technical sector sector
230: Financial Sector Division
300: guarantee propensity detection unit
400: warranty simulation unit
410: interrupting signal unit

Claims (5)

A data input unit that receives credit guarantee loan history and company information performed for a period of time;
A credit calculation unit that classifies the company information into sectors, technical sectors, and financial sectors of the companies, and analyzes each sector for computerized credit data;
A guarantee propensity detection unit for computing the propensity propensity data according to the industry sector, technical sector, and financial sector of the enterprise by sorting the credit guarantee loan history based on the credit data;
Based on the guarantee propensity data provided from the guarantee propensity detection unit, it includes a guarantee simulation unit that selects a company that is likely to be subject to the credit guarantee and sequentially levels it,
The credit calculation unit,
Sector sector division that classifies the industry type of the company based on standard industry classification criteria and analyzes the market size, export size, government-funded amount, number of companies, and growth rate during the period to calculate the future growth index of the industry. ;
A technical sector unit for calculating the technical index of the company by analyzing the research and development cost of the company, the ratio of R&D investment to sales, facility facility size, facility investment cost, production capacity index, and the number of intellectual property applications; And
Includes a financial sector unit that calculates the financial indicators of the company by automatically calculating the financial ratios representing the liquidity, stability, profitability, and activity of the company by analyzing the current status of the financial activities of the company performed for a certain period of time,
The guarantee simulation unit,
Selecting and rating the company subject to the credit guarantee, and leveling, and includes an interrupting signal unit that randomly adds a random noise signal to the selected list of credit guarantee companies,
The interrupting signal unit,
In the information exchange between the transmitting end and the receiving end of the list data to which the random noise signal is added, let the transmitting end and the receiving end share rules of the ID of the function generating the random noise signal and the random variable generated by the ID. Credit guarantee target company selection system based on credit guarantee propensity analysis, characterized in that.
According to claim 1, wherein the financial sector unit,
At least one of the company's sales, sales performance, operating profit, interest, net income, capital, current assets, inventories, total assets, liabilities, current liabilities, debt ratio, return on investment (ROI) or growth rate over a period of time A system for selecting a business subject to credit guarantee based on a credit guarantee propensity analysis, comprising the above indicators and calculating the financial ratio of the company by automatically calculating the financial ratio.

The credit unit of claim 1,
A credit guarantee target company selection system based on a credit guarantee propensity analysis, characterized in that the company information is scored and classified into an N grade to calculate the future growth index of the industry, the technology index of the company, and the financial index of the company.
According to claim 1, The guarantee propensity detection unit,
In order to reflect the credit data, iv) the weight of the technical sector and the financial sector are differently applied according to the sector of the company, and ii) the sector of the enterprise and the financial sector according to the technical sector. Credit guarantee based on a credit guarantee propensity analysis, characterized by applying the weights of differently, and iii) applying the weights of the industry sectors and the technology differently according to the financial sector to detect the guarantee propensity data. Target company selection system.
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