DEVELOPMENT OF FINTECH AND BIG DATA IN THE FINANCIAL SPHERE: FEATURES, PROBLEMS, OPPORTUNITIES
Author(s): Niyazbekova Shakizada Uteulievna, Ivanova Olga Sergeevna
Release: 2020-1 (32)
Keywords: Financial technology, big data, digital transformation, financial industry
Annotation: This article discusses the development of FinTech and Big Data in the financial sector. It is revealed that the financial industry is rapidly moving towards data-based optimization, and organizations must respond to these changes in a timely manner. Financial and banking services are becoming more accessible, and the impact of technological innovations is very diverse. Big data problems in Finance are identified. The incentive to invest and implement data analysis tools and methods is huge, and businesses will need to adapt, innovate, and develop strategies for the emerging digital market. Big data is characterized by the following: the main volume of data, the speed with which it is processed, and a wide range of data. Data Analytics has expanded to the technological fields of machine learning and artificial intelligence. Along with the development of computer methods of data analysis, analysis relies on traditional statistical methods. Ultimately, data analysis methods are applied in two ways in an organization: big data analysis is processed by streaming data as it becomes available, and then batch data analysis is performed as it is created to search for behavioral patterns and trends. As data generation increases, various methods that manage this will evolve. As data becomes more insightful in its speed, scale, and depth, the more it spurs innovation. According to statistics, the revenues of the global big data market for software and services will increase from 42 to 103 billion USD by 2027.
Bibliography: Niyazbekova SH.UT., Ivanova OL.SE. DEVELOPMENT OF FINTECH AND BIG DATA IN THE FINANCIAL SPHERE: FEATURES, PROBLEMS, OPPORTUNITIES // Economics and Management. – 2020. – № 1 (32). – С. 30-36. doi: 10.21777/2587-554X-2020-1-30-36