Energy Performance Contracting Project Credit Risk Identification Model Research Based On Rough Set Theory

With the energy resource shortage in the world and the serious environment pollution, how to improve the energy-saving and environmental protection efficiency has become an urgent problem in Chinese sustainable development road. As a new energy management mechanism based on market, energy performance contract effectively promotes the energy-saving and environmental protection career. After being introduced into China, the new mechanism has encountered many barriers, in which credit barrier is quite serious.Through analyzing the energy saving service contract types, project funds, actual cases and project process, this paper considers that the credit deficiency of energy saving enterprise is the main cause of the energy performance contract credit risk. In order to ensure the healthy development of the new mechanism, it is very important to strengthen the credit risk management of energy saving enterprise. In credit risk management, risk identification is the first and foremost step.Credit economics considers information asymmetry is the main cause of credit risk identification; therefore, the main target of this paper is how to improve information asymmetry in energy performance contract mechanism. There are some questions in improving information asymmetry, such as reliance on the database, too much redundant data and vague decision-making rules. As an emerging mathematics method aiming at uncertain information, rough set theory has high correspondence with the solution for above questions.On the condition of unchanging its classification ability, this paper has selected energy saving enterprise credit risk index through rough set theory, attributed reduction of credit, eliminated redundant information and enrolled key attributes, in order to improve the situation of too much private information and information asymmetry. This paper has established the related model for financial data of 120 listed companies, and built decision table, pretreated the date, attributed reduction and finally selected six main influencing factors--- the current ratio, the asset-liability ratio, accounts receivable turnover, inventory turnover and comprehensive lever and net profit growth. At the same time, this paper has gotten recognition rules, which has passed the verification showing that the index and rules are high accuracy, which is applicable to credit risk identification about other energy saving enterprises.This paper has used rough set theory to discovery knowledge and mined the key index which is applicable to recognize credit risk. Through reducing the asymmetric to change the credit loss situation, this paper can help the development of energy services and the continuous improvement of the energy performance contract mechanism.