LAUSR

This study focuses on the financing difficulties of small and medium enterprises (SMEs) in China to study the application of blockchain technology in developing the real economy. Deep learning neural network is applied to the vulnerability analysis and detection of smart contracts in blockchain technology by analyzing the connotation of blockchain technology and deep learning. A multiparty joint financial service platform based on blockchain technology is established to help SMEs financing institutions reduce transaction costs, thereby helping them reduce loan interest rates. Finally, Jiangsu Province is studied as a pilot unit. The results show that the Recall and F-score of Bidirectional Neural Network for smart contract vulnerability detection are higher than those of the original neural network. The Recall rate and F-score value of the Wide and Deep model are up to 96.2% and 94.7%, which are higher than those of other vulnerability detection schemes. The Timestamp vulnerability has the highest Recall rate, 94.2%, which can rely on a large amount of valid data to improve detection efficiency. The distribution of financing needs of SMEs in Jiangsu Province from 2020 to 2021 shows that the loan number of SMEs is generally not high. Still, financial institutions and enterprises must spend the same transaction cost. After a technology company in Nanjing made a loan through a blockchain financial service platform, its financing cost decreased by 0.5331%. Blockchain technology has played a great role in the financing process of SMEs, reducing intermediate links and credit costs, and promoting the development of SMEs and the real economy.