Generative AI – A Catalyst in Banking and Financial Industry

Authors

  • Vivek Dubey Capgemini, India
  • Azher Mokashi Barclays, India
  • Ranjan Pradhan Capgemini, India
  • Sireesh Kumar Kalli Capgemini, India
  • Rakesh R. Sonar Capgemini, India
  • Kalpesh Parab Capgemini, India
  • Tarun Nayak Capgemini, India
  • Sandeep Ranade Capgemini, India

DOI:

https://doi.org/10.47577/business.v10i.12038

Keywords:

Generative AI, Banking, Financial Institutes, Large Language Models, Quantum Computing, Regulation, Innovation, Ethical Deployment, Personalization, Efficiency

Abstract

Gen AI is making the banks and financial markets stand on the pinnacle of technological excellence, acquiring the power of data analysis, customer service, and risk management at an unprecedented level. This paper is going to examine several aspects of banking and financial organizations in which Gen AI can have an impact, namely, client onboarding, fraud detection, lending, and payment processing. Doing a wide-ranging literature review is the core of our work, where we look at how technologies of Gen AI, including LLMs and Quantum Computing, are shaping conventional banking models while calling for increased efficiency and personalization. In addition, the paper discusses the role of the officials and the policymakers who would be responsible for guiding the deployment of Gen AI ethically and responsibly through the use of directives and innovative ideas that are intended to resolve new challenges that may arise such as algorithmic bias and data privacy among others. This paper highlights how GenAI can help bring innovation into the banking and finance industry, besides being efficient and inclusive, it may require collaboration between all stakeholders to achieve a positive societal impact.

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Published

2024-11-27

How to Cite

Dubey, V., Mokashi, A., Pradhan, R., Kalli, S. K., Sonar, R. R., Parab, K., Nayak, T., & Ranade, S. (2024). Generative AI – A Catalyst in Banking and Financial Industry. Technium Business and Management, 10, 68–83. https://doi.org/10.47577/business.v10i.12038