TWI770426B - Cross-enterprise credit rating and risk assessment system - Google Patents

Abstract

A cross-enterprise credit rating and risk assessment system, comprising a first block chain and database unit for collecting credit rating-related information of the rated enterprise, the credit rating data at least including goodwill performance, financial performance, transaction performance, competition Performance and credit performance; a second blockchain and database unit that establishes business relationships between upstream and downstream and competing enterprises; a computing unit that analyzes the first blockchain and database unit and the second blockchain and database unit The collected information is used to evaluate the credit rating of the rated enterprise, and the risk trend of the previous credit rating data and the current credit rating data in different time series is compared using statistical methods, and the rated enterprise can be rated according to the time series. Changes in the company's current credit rating risk.

Description

Cross-enterprise credit rating and risk assessment system

The invention relates to a financial credit reporting system, especially a cross-enterprise credit rating and risk assessment system.

According to statistics, SMEs need funds to promote their business activities, but when their own funds are insufficient, they can obtain financing from financial institutions such as banks to make up for the funding gap. Generally, when small and medium-sized enterprises borrow money from banks, they are often limited by relevant information such as the company's financial and business performance. Compared with large companies, they are less transparent, resulting in difficulties in bank credit and higher financing costs. Banks target a single company. Credit ratings often fail to grasp the business crisis caused by industrial environmental factors such as upstream and downstream companies in the supply chain or competitive enterprises, and cannot fully and continuously grasp the hidden systemic risks.

In order to solve the above problems, Dun & Bradstreet of the United States proposed the invention patent No. I634508 in my country, "The System and Method for Determining the Future Commercial Viability of an Entity Using a Multi-Dimensional Rating System", which proposes to use corporate identity, activity signals, payment transactions and financial statements. And other multi-dimensional data, according to the data field scoring rules to calculate the enterprise viability score and rating. However, this credit evaluation method is limited to a single enterprise.

In addition, China's CN108960678 patent "Multi-dimensional control and processing method for risk control" proposed by China Kunshan Rongjie Information Technology Co., Ltd. includes multi-dimensional information such as parent-subsidiary associations, upstream and downstream enterprise associations, and regional/country associations to conduct enterprise risk management. control. However, this method is limited to the control of the total amount of financing of the enterprise cooperation system, rather than the assessment of the enterprise's operating risks.

Other prior technologies such as CN105930981 "Risk quantification and real-time automatic processing supply chain financing platform" patent, CN109191279 "Small and medium-sized enterprise credit risk assessment platform based on online supply chain finance" patent and CN109214703 "An evaluation method and "Device" patents, etc., respectively propose credit investigation or risk assessment methods for financing and credit-granting enterprises in supply chain finance business. However, these methods are limited to the evaluation of a single enterprise object, and are not intended to assess the overall risks of the enterprise itself, its supply chain, and the industry's prosperity.

The main purpose of the present invention is to provide a cross-enterprise credit rating and risk assessment method and system, which can be used to strengthen the financial credit investigation of small and medium-sized enterprises, fully grasp the systemic risks, reduce the occurrence of loan reversals, and protect the rights and interests of creditors.

In order to achieve the aforementioned purpose, the present invention provides a cross-enterprise credit rating and risk assessment method, which includes: associating the credit rating data of a rated enterprise and its upstream and downstream enterprises with competing enterprises, and the business relationship between upstream and downstream and competition. Established in the blockchain and database respectively, the credit evaluation data include at least goodwill performance, financial performance, business transaction performance, competition performance and credit performance (but not limited to); use statistical methods to analyze and compare different Time-series previous data and current data, and the credit rating and risk changes of the rated enterprise can be assessed in time series; according to the data including the blockchain and database of the upstream and downstream enterprises and other positive Influence index data, establish a pair of positive correlation credit rating change factors of the rated enterprise; establish a pair of the rated enterprise according to the data including the blockchain and database of the competitive enterprise and other negative impact index data The negative related credit rating change factor of the enterprise; Calculate a risk value of the rated enterprise according to the above-mentioned positive and negative related credit rating change factors; establish a risk trend curve according to the risk value of the rated enterprise in different periods; evaluate the risk trend curve according to the change in the slope of the risk trend curve. Evaluate the company's risk rating.

The risk assessment matrix is established according to the positive correlation credit rating change factor and the negative correlation credit rating variation factor. The strength and weakness are given different positive and negative weight values for comprehensive calculation of the comprehensive risk value, and the risk trend curve is established according to the comprehensive risk value calculated respectively in the time series.

The matrix evaluation system can give different weight values to each index value according to the strength of the positive correlation credit rating change factor and the negative correlation credit rating change factor, and then calculate the risk value by weighting.

Build a system according to the aforementioned method, including: a block chain and database unit for collecting information related to enterprise credit rating; a block chain and database unit for establishing business relationship between upstream and downstream and competing enterprises; A calculation unit for artificial intelligence credit evaluation for upstream and downstream enterprises and competitive enterprises; a calculation unit for credit and risk analysis of a pair of rated enterprises.

The above-mentioned objects and advantages of the present invention can be easily understood from the detailed description and accompanying drawings of the following selected embodiments.

Figure 1 is a flow chart of the present invention; Figures 2-6 are schematic diagrams of the credit rating evaluation process of the rated enterprise in the present invention; Figures 7-8 are schematic diagrams of the risk trend analysis process of the rated enterprise in the present invention .

Please refer to Figures 1 to 7, which show the cross-enterprise credit rating and risk assessment method provided by the present invention, which includes: correlating the credit rating data of a rated enterprise and its upstream and downstream enterprises with competing enterprises and the upstream and downstream The business relationship between the downstream and the competition is established on the blockchain and the database respectively; the above information is analyzed and used to evaluate the credit rating of the rated enterprise; according to the information including the blockchain of the upstream and downstream enterprises and other positive Influence index data, establish a pair of positive correlation credit rating change factors for the rated enterprise; establish a negative impact index data for the rated enterprise based on the data including the blockchain of the competing enterprise and other negative impact index data. Calculate the risk value of the rated enterprise according to the above-mentioned positive and negative related credit rating change factors; establish a risk trend curve according to the risk value of the rated enterprise in different periods; use statistical methods Analyze the slope change of the risk trend curve to evaluate the risk rating of the rated enterprise.

In the above method, the credit evaluation data of the rated enterprise and its upstream and downstream enterprises and competing enterprises include goodwill performance, financial performance, transaction performance, competition performance and credit performance, etc., wherein the goodwill performance includes the company's award or dismissal. Financial performance includes revenue growth rate, after-tax net profit growth rate, days of accounts payable payment, cash quick ratio, financing leverage and other financial indicators. Transaction performance includes financial indicators including core enterprises Upstream and downstream transaction records, transaction volume statistics, average transaction frequency, etc. Competitive performance includes revenue, number of customers, business scale, etc. Credit performance includes credit evaluation of third-party units, loan and repayment records, etc. The above-mentioned various information can be obtained through various channels, such as the self-provided information of the enterprise, the open information of the government, the public information of the Internet, the public information of the third party, or others.

As shown in Figure 4, it is a schematic illustration of the blockchain establishment model between the evaluated company, upstream and downstream companies and competing companies. For example, companies A and B have a product transaction data, and companies B and C also have a product transaction data. , The transaction data of companies A and B and companies B and C can be connected to each other to establish the relationship between the upstream and downstream of the enterprise. For example, the procurement catalog public information provides the company's product information, and through the data comparison, the enterprise competition relationship between the companies can be established.

The present invention conducts multi-dimensional data source credit evaluation model learning, training and prediction for the above-mentioned various credit evaluation data (data forms established in the block chain and database), so as to evaluate the credit evaluation of the evaluated enterprise. The method of the present invention not only uses the credit rating data of the rated enterprise to evaluate the credit rating, but also uses the credit rating data of the upstream and downstream enterprises related to the rated enterprise and the competitive enterprises to perform collaborative analysis, so as to evaluate the rated enterprise. Carry out a comprehensive and systematic objective evaluation; moreover, the previous credit evaluation data of different time series and the current credit evaluation data can be compared with the data statistics method, for example, several pre-credit evaluation data can be established to know the credit evaluation data of the evaluated enterprises in each period. Credit rating status, through trend analysis (monthly/quarterly credit rating change history) through data statistics, the risk changes of the current rated enterprise can be further evaluated; therefore, the present invention can analyze the rated enterprise, upstream and downstream enterprises by analyzing the credit rating status. 、Competitors' credit rating data will not be limited to the rated enterprise's own credit rating data for evaluation, but also conduct trend analysis based on the multi-period historical data accumulated in time series, so as to accurately judge the risk changes of the rated enterprise's credit rating in the current period. .

In addition, the present invention can further evaluate the risk change of the evaluated enterprise. Firstly, according to the upstream and downstream enterprises' credit rating and industrial prosperity and other index data, establish a pair of positively related credit rating change factors for the rated enterprise, and then based on the competitive enterprise's credit rating and the rated enterprise itself and bad debts, debts, and debts. Set up a pair of negatively related credit rating change factors of the rated enterprise based on the index data such as the concentration of accounts receivable and financing leverage ratio. The two establish a risk assessment matrix respectively, and then calculate the risk of the rated enterprise according to the above matrix. value. After accumulating the risk value of multiple calculation cycles, a risk trend curve as shown in Figure 8 (each The long end points can be connected to form a curve or a broken line), whereby the change of the slope of the curve (that is, taking the second derivative of the curve) can be used to evaluate the risk change of the rated enterprise as increasing, remaining the same or decreasing.

Specifically, a matrix evaluation system is established according to the positive correlation credit rating change factor and the negative correlation credit rating change factor. The strength of the evaluation change factor is given different positive and negative values for the comprehensive calculation of the risk value (the matrix evaluation system must be based on the strength of the positive correlation credit evaluation change factor and the negative correlation credit evaluation change factor. Different weight values are given, and the risk value is calculated by weighting), and the risk trend curve is established according to the respective calculated risk values of the time series.

Therefore, based on the above analysis of the credit rating of the rated enterprise and the establishment of the risk trend curve, the current credit rating and risk trend of the rated enterprise can be judged accordingly, such as the positive factor released by the rated enterprise due to favorable policies, although when In the future, the credit rating is not good, but the risk trend tends to decrease. Therefore, it may be considered to provide, for example, more favorable financing/loan conditions, or for example, because the credit rating of the rated enterprise is normal, but it is faced with the negative exchange rate fluctuation of its main trading country. As a result, the risk trend tends to increase. At this time, its financing/loan conditions should be carefully evaluated. Therefore, the present invention can accurately observe the business trend of the rated enterprise from the above-mentioned credit rating and risk trend curve.

Build a system according to the aforementioned method, including: a block chain and database unit for collecting information related to enterprise credit rating; a block chain and database unit for establishing business relationship between upstream and downstream and competing enterprises; A calculation unit for artificial intelligence credit evaluation for upstream and downstream enterprises and competitive enterprises; a calculation unit for credit and risk analysis of a pair of rated enterprises.

However, the disclosure of the above embodiments is only used to illustrate the present invention, but not to limit the present invention, so the replacement of equivalent elements should still belong to the scope of the present invention.

To sum up, those skilled in the art can understand that the present invention can achieve the above-mentioned purpose, and it complies with the provisions of the Patent Law.

Claims (4)

A cross-enterprise credit rating and risk assessment system, comprising: a first block chain and database unit for collecting credit rating-related information of the rated enterprise, wherein the credit rating data at least includes goodwill performance, financial performance, Transaction performance, competition performance and credit performance; a second blockchain and database unit for establishing business relationships between upstream and downstream and competing enterprises; a computing unit that analyzes the first blockchain and database unit and the second area The data collected by the blockchain and the database unit is used to evaluate the credit rating of the rated enterprise, and the risk trend of the previous credit evaluation data and the current credit evaluation data in different time series is compared using statistical methods, and can be determined according to the risk trend. Time series to assess the current credit rating risk changes of the rated enterprise. The cross-enterprise credit rating and risk assessment system according to claim 1, wherein the calculation unit establishes a The positive correlation credit rating change factor of the rated enterprise; the calculation unit establishes a pair of information about the rated enterprise according to the data on the competitive enterprise and other negative impact index data in the second blockchain and the database unit. Negative related credit rating change factor; the calculation unit calculates a risk value of the rated enterprise according to the above-mentioned positive and negative related credit rating change factors; the calculation unit establishes a risk value according to the risk value of the rated enterprise in different periods The trend curve, and the risk change of the rated enterprise is assessed according to the change in the slope of the risk trend curve. The cross-enterprise credit rating and risk assessment system according to claim 2, wherein the calculation unit establishes a risk assessment matrix according to the positive associated credit rating change factor and the negative associated credit rating variation factor, and the risk assessment matrix defines a number of Each index value is given different positive and negative values according to the strength of the positive correlation credit rating change factor and the negative correlation credit rating variation factor, so as to comprehensively calculate the risk value, and calculate the risk separately according to the time series. The value establishes the risk trend curve. The cross-enterprise credit rating and risk assessment system according to claim 3, wherein the calculation unit assigns different weights to each index value according to the strengths of the positive correlated credit rating change factor and the negative correlated credit rating change factor, The risk value is calculated by weighting.

Images