构建支持印地语混英文的多语言对话系统，提升印度金融普惠性
Multilingual Conversational AI for Financial Assistance: Bridging Language Barriers in Indian FinTech
- 采用多智能体架构，支持语种识别、功能调度与多语言回复生成
- 真实场景部署显示用户参与度显著提升，延迟仅增加4-8%
- 特别适配印度多元语言环境，助力新兴市场金融包容
印度的语言多样性为金融科技平台带来机遇与挑战。该国拥有31种主要语言和超过100种次要语言，仅有10%的人口能理解英语，导致金融服务难以普及。本文提出一种面向金融协助场景的多语言对话AI系统，支持如Hinglish（印地语混英文）等代码混用语言，实现对印度多样化用户群体的自然交互。系统采用多智能体架构，包含语言分类、功能管理与多语言响应生成模块。通过对比多种语言模型并进行真实世界部署，验证了用户参与度显著提升，同时保持4-8%的低延迟开销。本工作有助于缩小新兴市场数字金融服务中的语言鸿沟。
原文摘要 · Abstract (English)
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.
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