Year: 2025
Type: article
Abstract: This article explores the application of Large Language Models (LLMs) for conversational payment initiation and management within financial services. It proposes an intelligent assistant capable of securely handling financial transactions through natural language interfaces. The article addresses architectural components, natural language understanding, integration with payment systems, security protocols, and user authentication methodologies. The article examines implementation considerations including fraud detection, regulatory compliance, multi-modal interfaces, contextual awareness, and error handling. Through article evaluation of operational metrics and user experience data, the article demonstrates significant advantages of conversational payment systems over traditional interfaces. Despite notable limitations in privacy, cross-lingual capabilities, and integration with legacy systems, the article concludes that LLM-powered payment assistants represent a fundamental advancement in financial interaction, with promising directions for future research to enhance their sophistication, trustworthiness, and integration within the broader financial ecosystem.
Author: Kamal Singh Bisht
Institution: Bangalore University
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410701935