Generative Artificial Intelligence: Prospects for Banking Industry


  • Bahadur Singh Chief Manager Research, State Bank of India, Hyderabad, India



Generative Artificial Intelligence, GenAI, ChatGPT, Banking, Open AI, Fraud Detection, Customer Service


Banking, as an indispensable service, operates around-the-clock, catering to diverse clientele ranging from common individuals to professionals. GenAI emerges as a potent tool reshaping the banking landscape, offering immense potential for innovation and efficiency. Its strategic adoption is imperative for banks to stay competitive and cater to the evolving preferences of tech-savvy customers. Reskilling initiatives are crucial to equip banking professionals with the requisite knowledge and skills to harness GenAI effectively. As GenAI continues to evolve, its integration into banking operations promises transformative outcomes, ensuring a customer-centric approach and sustainable growth in the digital era. The advent of Generative Artificial Intelligence (GenAI) marks a significant milestone in banking evolution. GenAI, a subset of AI, leverages neural networks to generate original content based on provided input, thereby transforming banking operations and customer experience. OpenAI, a prominent player in AI research and development, has pioneered GenAI through models like ChatGPT, enabling natural language interactions akin to human conversation. GenAI offers multifaceted benefits with challenges and limitations to the banking sector. It enhances customer experience by providing round-the-clock support through chatbots, offers personalized product recommendations, and assists in loan eligibility assessments. Moreover, it aids in risk management, fraud detection, and personalized marketing campaigns, thereby optimizing operational efficiency and bolstering customer engagement. Despite its capabilities, GenAI necessitates human oversight, especially in critical decision-making processes.


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How to Cite

B. Singh, “Generative Artificial Intelligence: Prospects for Banking Industry”, IJRESM, vol. 7, no. 3, pp. 83–86, Mar. 2024, doi: 10.5281/zenodo.10897014.