Construction and Optimization of a Financial Early Warning System Based on Big Data and Deep Learning Technology

Abstract

New technologies such as big data, artificial intelligence, mobile internet, cloud computing, Internet of Things, and blockchain have brought about significant changes and development in the financial industry. Predicting the financial situation of enterprises, reducing the probability of uncertainty risks, and reducing the likelihood of financial crises have become important issues in enterprise financial crisis warning. In view of the issues in enterprise financial early warning systems such as lag, low accuracy, and high warning costs in data analysis, a financial early warning system based on big data and deep learning technology has been established, taking into account the different situations of listed and non-listed companies. This carries significance in improving the accuracy of enterprise financial early warning and promoting timely and effective decision-making.