Credit Risk Early Warning of Small and Medium-Sized Enterprises Based on Blockchain Trusted Data

Abstract

Small and medium-sized enterprises (SMEs) are now growing rapidly and playing an important role in the development of the national economy. As the economy grows, the contradiction between the credit risk of SMEs and the credit risk early warning mechanism of traditional supply chain financing has become increasingly important. In response to the issues of a single source of business information, the high investment cost of the existing early risk early warning mechanism, etc., from a commercial bank credit risk management perspective, this paper proposes to build an SMEs credit risk early warning system based on reliable blockchain data. The reliability of the data obtained is assessed utilising a hierarchical analysis and a vague overall judgement method. The results show that the use of blockchain technology can enhance the credibility and accuracy of the data, which provides a data guarantee for more rapid risk alert.

Research on Credit Risk Prediction Method of Blockchain Applied to Supply Chain Finance

“…Research on blockchain-based supply chain financial credit risk prediction and evaluation should not only study the construction of blockchain-based supply chain financial credit risk evaluation index system, but also study the algorithms and methods of constructing blockchain-based supply chain financial credit risk prediction model [7]. Currently, supply chain finance credit risk prediction and evaluation methods include grey prediction model [8], linear regression model [9], support vector regression [10], machine learning methods [10], deep learning methods [11], etc. Literature [12] applies blockchain technology to the supply chain smart contract aspect and proposes a credit risk prediction method for supply chain finance based on grey theory; Literature [13] researches the method of combining blockchain technology with the actual needs of enterprises based on the underlying technology of Bitcoin and using the transparency of the transaction information; Literature [14] researches the supply chain architecture based on the blockchain technology, and proposes the supply chain process optimization method; Literature [15] proposed a financial credit risk prediction method based on improved machine learning method through the perspective of global supply chain product security and challenges; Literature [16] proposed blockchain-based encryption technology and studied the evaluation and analysis method of the corresponding technology; Literature [17] predicted the supply chain financial credit risk by analyzing the supply chain financial credit risk influencing factors and adopting the artificial neural network method to predict the supply chain finance credit risk and responds to enterprise demand in real time.…”

Low voltage user demand response management platform based on blockchain technology

“…Demand response needs to adapt to China's energy layout and energy strategy, and demand response can be an important means of renewable energy consumption and regulation. Therefore, in order to effectively reduce peak power demand, achieve the goal of energy conservation and emission reduction and improve the consumption capacity of renewable energy, it is necessary to build a demand response management platform [3][4][5].…”