Digital financial inclusion risk prevention based on machine learning and neural network algorithms

Abstract

In recent years, China has increased its investment in science and technology, and digital technologies such as mobile Internet, big data, and cloud computing have continuously made breakthroughs. The integration with the modern financial industry has stimulated online lending, third-party payment, digital insurance, and New financial forms such as digital wealth management are booming. With the rapid development of digital financial inclusion, the development of traditional financial industry has broken through time and geographical constraints, allowing more groups excluded from the traditional financial system to participate in financial activities and enjoy more convenient and faster personalized financial products and services, meet their financial needs and improve the reach of financial services. While the development of digital financial inclusion has benefited more groups, it has not changed the original risks of the financial industry. It has also brought about some negative external effects of financial technology, which poses greater challenges to the protection of financial consumers’ rights and interests. Therefore, this research aims at the digital inclusive risk prediction of financial institutions and personal risk prediction respectively, and proposes a financial risk prediction method based on the adaptive fusion of multi-source heterogeneous data, which can improve the effect of financial risk prediction through the effective use of multi-source data. purpose.