Enterprise debt paying credit risk assessment system

Abstract

The invention discloses an enterprise debt paying credit risk assessment system, which comprises a debt paying history tracing module, a debt paying credit trend assessment module, an enterprise reputation assessment module, an enterprise asset stability assessment module and a comprehensive assessment module, wherein the comprehensive assessment module is respectively connected with the debt paying history tracing module, the debt paying credit trend assessment module, the enterprise reputation assessment module and the enterprise asset stability assessment module. According to the enterprise debt paying credit risk assessment system provided by the invention, an enterprise debt paying credit threshold a, an enterprise reputation threshold b, an enterprise asset stability threshold c and a trend value lambda are combined to assess lending risks, the financial condition of the enterprise is considered to a certain degree, a condition of depending too much on the financial condition can be avoided, the problem of assessment risks caused by current low enterprise financial data credibility can be solved, the reputation and the credit of the enterprise are considered, and assessment rigor of enterprise subjective data can be ensured.

Description

technical field [0001] The invention relates to the technical field of enterprise evaluation, in particular to an enterprise debt repayment credit risk evaluation system. Background technique [0002] Many enterprises in China have difficulty in financing and must obtain financing through mortgages and pledges. It is very necessary to establish a series of enterprise-oriented risk warning software to assist financial institutions in making credit decisions and credit risk management for enterprises. At present, the widely used enterprise risk assessment software uses the enterprise's financial statements as the basic data for evaluation. Based on these credible financial basic data, the enterprise's operating conditions are calculated through the risk control model. However, due to the low quality of financial statement information of many enterprises, especially small and medium-sized enterprises, corporate credit risk is highly influenced by the person in charge of the en...

AI Technical Summary

Problems solved by technology

However, due to the low quality of financial statement information of many enterprises, especially small and medium-sized enterprises, corporate credit risk is highly influenced by the person in charge of the enterprise, the credibility of financial statement information is low, and there are often inconsistencies between internal and external accounts.

Therefore, when the traditional enterprise risk prediction model is applied to small and medium-sized enterprises, there will inevitably be structural errors, resulting in a reduction in the prediction ability, which will inevitably affect the bank's credit test and increase the credit risk of the bank.

[0003] All in all, the existing evaluation methods rely too much on the financial data provided by the enterprise and the current financial resources of the enterprise, while ignoring the creditworthiness of the enterprise's debt repayment. Therefore, the availability of evaluation results is low.

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