A Review on: Generative AI and its Impact on Banking & Financial Sector

Abstract

This review delves into the revolutionary effects of Generative AI on the banking industry, tracking its potential to disrupt several banking processes and relationships with customers. Personalized financial advice, risk management, client service, fraud detection, and generative AI\'s capacity to produce fresh data and answers that resemble human behavior are just a few of the many uses for generative AI in the banking industry. Generative AI can boost productivity, precision, and happiness among consumers by automating tedious tasks and improving judgment. But there are obstacles to integrating new technology as well, including worries about data privacy, ethical implications, and the need to invest much in infrastructure and training. To give a thorough picture of how Generative AI is changing the banking industry, this study compiles recent studies and case studies, summing up the pros and cons that banks are encountering as a result of embracing this cutting-edge technology

Introduction

The banking sector, a historic leader in technological innovation, is now poised for transformation through Generative AI, which can create human-like text, images, and code. Generative AI offers significant potential to enhance banking operations by improving efficiency, accuracy, personalization, fraud detection, risk management, and customer service through AI-powered chatbots and tailored financial advice.

However, challenges such as ethical concerns, data privacy, regulatory compliance, and the high costs of implementation remain. Policymakers must balance innovation with regulation to avoid stifling progress or creating risks. Studies highlight the growing impact of AI on banking performance, customer experience, and operational processes globally, with Indian banks being notable examples of AI adoption.

Generative AI is also influencing education and ethical discussions around AI use, emphasizing the need for transparency, accountability, and human-centered design. Overall, adopting Generative AI responsibly is critical for banking’s future, offering opportunities to optimize services, enhance security, and deepen customer relationships while navigating significant moral and practical challenges.

Conclusion

By streamlining operations, improving decision-making skills, and creating tailored experiences for customers, generative AI has the potential to radically alter the banking industry. Generative AI has the ability to revolutionize the banking industry by enhancing efficiency, accuracy, and customer happiness through its application in areas like fraud detection, customer care, personalized financial advising, and risk management. The incorporation of this technology, however, is not a picnic. Responsible and effective implementation requires thorough attention to ethical considerations, data protection problems, and the necessity of major investment in infrastructure and training. In this analysis, we look at the pros and cons of using Generative AI in financial institutions. Better risk management, more efficient operations, and more satisfying encounters with customers are just a few of the many advantages. However, we must not ignore the difficulties associated with ethical use, data security, and compliance with regulations. To responsibly deploy Generative AI, financial institutions need to develop transparent guidelines, conduct regular assessments, and set explicit policies and principles. To be competitive and fulfill the needs of a digital-first society, the banking sector must strategically incorporate Generative AI as it continues to evolve. A future that is more efficient, safe, and customer-centric can be achieved if banks take advantage of Generative AI\'s advantages while also tackling its inherent problems. This shift, propelled by unwavering dedication to ethical principles and ever-improving AI technology, will redefine the banking environment in the end, encouraging innovation and growth in the business.

References

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Copyright

Copyright © 2025 Ashish Dibouliya, Aditya Shelar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.