Anika
Birla Institute of Management Technology
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http://doi.org/10.37648/ijrst.v10i01.012
The rapid integration of technology in fintech companies has significantly increased the risks in this sector. Data analytics, particularly in fraud detection, prevention, and risk management, has emerged as a crucial tool for addressing these risks, offering more accurate predictions of potential outcomes. The growing volume of data has led to a heightened awareness of the importance of risk management through d ata analytics. Research in this field is essential for helping companies understand the emergence of risk factors more effectively. However, applying data analytics to risk management in fintech companies presents several challenges, including data quality and availability, lack of expertise, cybersecurity and data privacy issues, bias, and ethical concerns. Fintech companies must navigate these challenges while balancing the benefits of effective data analytics models. The necessity of collaboration with other companies, industry associations, and regulators becomes evident in the face of these challenges, as it can help fintech firms stay informed about the latest risks and best practices and identify potential threats early. This research paper provides a comprehensive overview of the role of data analytics in managing risks in fintech companies. It highlights the need for robust policies to ensure data management, transparency, and reliability.
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