AI Powered Voice Assistant for Banking System

Saranya S, Jency J, Aparna V, Priya Dharshini E and Lavanya S

International Journal of Scientific Research in Science and Technology, 2025, vol. 12, issue 2, 111-119

Abstract: The rapid advancements in Artificial Intelligence (AI) and Natural Language Processing (NLP) have revolutionized customer interactions in the banking sector. Traditional banking interfaces, including text-based chatbots and manual document processing, pose accessibility challenges and inefficiencies. This research proposes the Intelligent Voice Banking Assistant (IVBA), an AI-powered voice assistant designed to enhance banking operations through secure and intuitive voice interactions. The system leverages Secure Adaptive Speech Processing (SASP) Algorithm, integrating speech recognition, deep learning-based NLP, document automation, and multi-factor authentication to enable seamless banking transactions. The IVBA model facilitates key banking operations such as account inquiries, fund transfers, bill payments, and loan applications through voice commands, ensuring an inclusive and accessible experience for all users, including visually impaired individuals. The Hybrid Transformer-BERT-based NLP engine ensures accurate intent recognition, while Blockchain-Enabled Transaction Logs (BETL) and Hybrid Homomorphic Encryption (HHE) enhance security and regulatory compliance. Furthermore, the integration of OCR-driven document automation minimizes manual processing efforts, reducing errors and improving operational efficiency. The IVBA model also ensures scalability and cost-effectiveness by leveraging open-source AI frameworks, enabling seamless integration into existing banking infrastructures with minimal modifications.

Keywords: AI-powered banking; Voice Assistant; Secure Adaptive Speech Processing (SASP); Conversational AI; NLP; Blockchain; Speech Recognition; Document Automation (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v12:y2025:i2:id:636

DOI: 10.32628/IJSRST25122203

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