Smart Banking Chatbot: AI-Powered Virtual Banking Assistant

Authors

  • Shaik Khasim Author
  • M Nithin Author
  • Danapelli Ramganesh Author
  • B Prasad Naik Author
  • Maddela Badrinath Author
  • Mrs. P. Devaki Author

DOI:

https://doi.org/10.64751/ijdim.2026.v5.n2(1).1178

Abstract

The Smart Banking Chatbot is an AIdriven virtual assistant designed to enhance customer experience and streamline banking operations. Traditional banking systems often require customers to visit branches or navigate complex online platforms, which can be timeconsuming and inefficient. The chatbot addresses these challenges by providing an intuitive, conversational interface that allows users to perform various banking tasks, including checking account balances, viewing transaction history, transferring funds, paying bills, and managing other financial services, all in realtime. Leveraging natural language processing and machine learning algorithms, the system understands user queries accurately and delivers personalized responses. It also continuously learns from interactions to improve its performance and provide smarter, contextaware assistance. Security is a core component, with measures like multi-factor authentication and end-to-end encryption ensuring that sensitive financial data remains protected. By automating routine banking processes, the Smart Banking Chatbot reduces dependency on human staff, minimizes errors, and enhances operational efficiency. Its scalability allows integration across multiple banking platforms, making it a versatile solution for modern financial institutions. Overall, this chatbot represents a significant step toward intelligent, customer-centric banking, offering convenience, efficiency, and secure financial management at users’ fingertips.

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Published

2026-04-27

How to Cite

Shaik Khasim, M Nithin, Danapelli Ramganesh, B Prasad Naik, Maddela Badrinath, & Mrs. P. Devaki. (2026). Smart Banking Chatbot: AI-Powered Virtual Banking Assistant. International Journal of Data Science and IoT Management System, 5(2(1), 642-647. https://doi.org/10.64751/ijdim.2026.v5.n2(1).1178