Analysis of the Impact of Digital Currency on Traditional Banking and Financial Stability

Abstract

Digital currency, as a representative product of blockchain technology, such as Bitcoin and Ethereum, has begun to have a far-reaching impact on traditional banking business, but also brought new challenges to financial stability. This article studies the financial risk assessment and pre-alarm model based on support vector machine (SVM) algorithm, aiming at accurately assessing the risks in digital currency market and providing timely pre-alarm. Through comparative experiments, it is found that the algorithm has obvious advantages in dealing with high-dimensional and nonlinear problems, and can accurately classify and warn financial risks. The accuracy of the model is as high as 96.88%, and the average absolute error is reduced by 40.22%, which proves the effectiveness and superiority of the model. Generally speaking, the financial risk assessment and pre-alarm model studied in this article provides a scientific and effective method for digital currency market risk management, which has important application value. Regulators need to invest more resources and energy to monitor and analyze the dynamic changes in the digital currency market and reduce financial risks.