2025/12/01 by Arya Suneesh, Hazarika, Bharatdeep, Suneesh, Arya +8
Computer Science · #ICT in Developing Communities #AI in Service Interactions #Mobile Crowdsensing and Crowdsourcing
paper · pdf · doi:10.48550/arxiv.2512.01439
India's linguistic diversity presents both opportunities and challenges for fintech platforms. While the country has 31 major languages and over 100 minor ones, only 10% of the population understands English, creating barriers to financial inclusion. We present a multilingual conversational AI system for a financial assistance use case that supports code-mixed languages like Hinglish, enabling natural interactions for India's diverse user base. Our system employs a multi-agent architecture with language classification, function management, and multilingual response generation. Through comparative analysis of multiple language models and real-world deployment, we demonstrate significant improvements in user engagement while maintaining low latency overhead (4-8%). This work contributes to bridging the language gap in digital financial services for emerging markets.