Abstract
Affected by the COVID-19 epidemic, financial regulators urgently need to establish a sensitive and scientific financial risk pre-alarm system that is suitable for the economic environment under the COVID-19 epidemic. The perfect pre-alarm system is based on in-depth scientific theoretical research, so it is of great practical significance to study the financial security assessment and systemic financial risk pre-alarm. The accumulation of massive data puts forward higher requirements for the effective organization and management of financial information. How to quickly extract effective information and analyze and predict it effectively on the basis of data has become an important issue in academic and industrial research. Exploring the nature of financial markets, analyzing and mastering the potential development rules between data not only provide effective technical support for financial management and investment business, but also play a pivotal role in promoting the steady growth of financial markets. This article proposes a financial risk pre-alarm model based on deep learning (DL). This model can detect the financial risk behaviors brought by a few people, and provides a new theory and method for the financial risk management (FRM) system. This algorithm solves the difficulties that traditional models are difficult to deal with highly nonlinear models and lack of adaptive ability.
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