Enterprise credit rating method

Abstract

The invention discloses an enterprise credit rating method. The enterprise credit rating method comprises steps that 1, capability index weight is quantized, and comprises an industry development index, a core team quality index, standard performance and risk, a competence scale, a debt paying capability, a profitability, an operation capability, a growth capability, a technology and innovation capability, and a market and channel index; 2, detail index weight is quantized; 3, every capability and every detail index of an enterprise are scored; 4, products of all of the capability index weights and the corresponding index scores are accumulated to acquire a capability index total score, the products of all of the detail index weights and the corresponding index scores are accumulated to acquire a detail index total score, and the enterprise credit score = the capability index total score + the detail index total score. Non-financial index descriptive languages are converted into the scores, and by adopting a quantitative researching method, all of the indexes are brought into a unified evaluation standard. A final middle and small-sized enterprise credit rating model is used to provide a rating method capable of minimizing subjective judgement, and the objective and fair credit evaluation of the enterprises is carried out by adopting the above mentioned thought.

Description

technical field [0001] The invention relates to an enterprise credit rating method, in particular to a method for small and medium-sized enterprises credit rating. Background technique [0002] Enterprise credit rating models are mainly divided into the following categories: [0003] 1. Quantitative analysis of credit risk [0004] This method starts from the financial data of the enterprise, and conducts modeling analysis on the financial data according to the statistical model and the law of large numbers, and finally evaluates the credit status of an enterprise. Representatives include Altman's Z-Score model, which takes 33 bankrupt companies as research samples, and forms a linear model by selecting 22 financial ratios that can best reflect the company's operating conditions. This model was later improved by Altman and established an improved Zeta Discriminant analysis model. Ohlson proposed for the first time that Logit analysis can be applied to credit risk assessme...

AI Technical Summary

Problems solved by technology

The main reason is that the financial indicators disclosed by small and medium-sized enterprises cannot objectively reflect the financial status of the enterprise, and if the financial indicators are the only data source for quantitative analysis, if the authenticity cannot be guaranteed, the objectivity and fairness of the rating results will be greatly compromised.

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