USE OF BIG DATA IN FINANCIAL RISK MANAGEMENT

In the context of digitalization of the economy and growth of available information, the use of Big Data technologies in the financial risk management system is of particular importance. This article is devoted to the analysis of methods and practices of using Big Data to identify, assess and minimize financial risks in the corporate and banking sectors. Key data sources are considered, including transactional, behavioral and alternative data, as well as analysis algorithms – from classical statistics to machine learning methods. Particular attention is paid to the issues of integrating Big Data into credit scoring processes, assessing market and operational risks, and countering fraud. The article substantiates the effectiveness of using Big Data as a tool for improving the accuracy of forecasting and making management decisions. The conclusions are supported by cases and examples of successful implementation practices in organizations in the financial industry.