Prospects of the Application of Data Science in the Financial Field

Abstract

The application of data science in the financial field has become an important trend in the financial industry. This article reviews the current application status of data science in the financial field, including application scenarios in risk management, credit assessment, market forecasting, etc. Through the analysis of existing research, this article summarizes the benefits brought by data science in the financial field, such as improving decision-making efficiency, reducing risks, optimizing customer experience, etc. In addition, this article also looks forward to the future development trends of data science in the financial field, including the application prospects of new technologies such as machine learning and deep neural networks in the financial field. Finally, this article calls on financial institutions to strengthen the training and technical investment in data science talents to adapt to the new trends in the development of financial technology and achieve digital transformation and innovative development in the financial industry. This article provides a relatively comprehensive introduction to the application of data science in multiple financial fields, reflecting the integration of mathematics, finance, computer science, and other disciplines. Most of the literature on academic websites starts from a specific aspect and introduces a certain field in depth. Although it is quite specific, it lacks an overall perspective.