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Publication Number

2501116

 

Page Numbers

1-11

 

Paper Details

The Next Frontier of AI and RPA in Financial Technology: Hyper-Automating FinTech Operations

Authors

Vidushi Sharma

Abstract

This research explores the transformative potential of Artificial Intelligence (AI) and Robotic Process Automation (RPA) in driving hyper-automation within financial technology (FinTech). Hyper-automation, which combines AI’s cognitive capabilities with RPA’s process automation, aims to create self-sustaining, adaptive systems that not only automate routine tasks but also enhance decision-making, scalability, and customer experiences. The research examines how these technologies can be integrated in FinTech operations, identifying both the benefits and challenges associated with their use. A mixed-methods approach is employed, combining a thorough literature review, case studies from leading FinTech firms, and a survey of 50 industry professionals. The findings indicate that hyper-automation leads to significant operational improvements, such as faster processing times, reduced error rates, and lower operational costs. Additionally, it enhances customer satisfaction through personalized services and faster response times. However, challenges such as data quality, integration complexities, and resistance to workforce adaptation remain barriers to widespread adoption. This paper contributes to the growing body of knowledge on AI and RPA in FinTech by providing empirical insights into the practical implementation of hyper-automation. It offers recommendations for FinTech firms on how to leverage these technologies effectively while addressing the associated challenges, ultimately enhancing both operational efficiency and customer value.

Keywords

Hyper-automation, Artificial Intelligence, Robotic Process Automation, FinTech, Operational Efficiency, Customer Experience, Regulatory Compliance

 

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Citation

The Next Frontier of AI and RPA in Financial Technology: Hyper-Automating FinTech Operations. Vidushi Sharma. 2025. IJIRCT, Volume 11, Issue 1. Pages 1-11. https://www.ijirct.org/viewPaper.php?paperId=2501116

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