Managing Risks In Fintech: Applications And Challenges Of Artificial Intelligence-Based Risk Management
DOI:
10.47353/ecbis.v2i3.127Published:
2024-05-23Downloads
Abstract
Artificial Intelligence has become a transformative technology in the field of financial technology, leveraging advanced algorithms and machine learning to identify risks and make informed decisions. However, its widespread adoption presents new challenges related to ethical use, data privacy, security concerns, potential bias, and discrimination. This study aims to explore the benefits of AI-based risk management in Fintech while highlighting associated challenges and providing recommendations. This research utilises the systematic review methodology to analyse existing literature and identify important patterns, gaps, and areas for further investigation. The study utilised data gathered from the Scopus database to obtain credible scholarly materials. Research data was collected from a variety of countries including the United States, China, European nations, and other Asian countries in order to develop a comprehensive understanding of AI-based risk management on a global scale. The findings highlight the crucial role of ethical considerations in implementing AI-based risk management systems to ensure fairness, transparency, and accountability. Moreover, the fintech industry needs to establish strong data protection measures and address issues related to bias and discrimination in order to instil trust and uphold public confidence in AI-based risk management. Future research should emphasise assessing the effectiveness of different algorithms and approaches while also examining potential regulatory frameworks and legal implications associated with AI-based risk management strategies.
Keywords:
Financial Technology Artificial Intelligence Risk Management AI-Based Risk Management Fintech Risk ManagementReferences
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