A Financial Risk Network Assessment Model Based on Artificial Intelligence and Machine Learning

Abstract

Innovative companies based on the combination of Internet technology and the financial industry have also started to specialise in the financial industry, with the entry of Fun Store, Yixin, and Pai Pai Loan into the financial industry. With this growth, the risks associated with it have also become the focus of much debate in society. The objective of this paper is to study financial risk network assessment models based on artificial intelligence and machine learning. Machine learning modelling techniques and the construction of an assessment system are analysed for the predictive classification of financial risk assessment of stocks in the internet finance industry. In the data processing process, support vector machine models are used and the experimental results show that classical support vector machines are used for discrete classification of data through regression classification hyperplanes, which show a strong overall dependence of key features between financial risk network assessment and data dimensions, and the existence of less dimensional key composite indicators has a better metric for financial risk.