Application of Data Analytics in Risk Management of Fintech Companies

Abstract

Technology is rooting the fintech companies at an unprecedented rate raising the rate of risk prevailing in this domain. The application of Data Analytics in the fintech industry, characterized by fraud detection, prevention, and risk management, has offered better solutions to the risks. It provides a more accurate prediction of their potential outcomes. There is a considerable increase in recognition of risk management in Data Analytics due to the increasing volume of data. There is a need for research in Data Analytics as it helps companies better understand the onset of risk factors. The application of data analytics in risk management for fintech companies presents several challenges, like data quality and availability, lack of expertise, cybersecurity and data privacy, bias, ethical concerns, etc. Fintech companies must balance the potential benefits of data analytics in risk management with the challenges and risks of implementing and maintaining effective data analytics models. Fintech companies can mitigate risks by collaborating with other companies, industry associations, and regulators. This can help them stay updated with the latest risks and best practices and identify potential risks early on. This research paper comprehensively presents a picture of the application of Data Analytics in managing the risks involved in Fintech companies and notes the shortcomings regarding appropriate policies for data management, transparency, and reliability.