FiMI: A Domain-Specific Language Model for Indian Finance Ecosystem
This model addresses the need for a high-performing financial language model tailored to the Indian finance ecosystem, specifically for NPCI's digital payment systems.
This paper introduces FiMI, a domain-specialized financial language model for Indian digital payment systems. FiMI Base improves finance reasoning by 20% over Mistral Small 24B, and FiMI Instruct outperforms Mistral Small 24B Instruct by 87% on domain-specific tool-calling.
We present FiMI (Finance Model for India), a domain-specialized financial language model developed by National Payments Corporation of India (NPCI) for Indian digital payment systems. We develop two model variants: FiMI Base and FiMI Instruct. FiMI adapts the Mistral Small 24B architecture through a multi-stage training pipeline, beginning with continuous pre-training on 68 Billion tokens of curated financial, multilingual (English, Hindi, Hinglish), and synthetic data. This is followed by instruction fine-tuning and domain-specific supervised fine-tuning focused on multi-turn, tool-driven conversations that model real-world workflows, such as transaction disputes and mandate lifecycle management. Evaluations reveal that FiMI Base achieves a 20\% improvement over the Mistral Small 24B Base model on finance reasoning benchmark, while FiMI Instruct outperforms the Mistral Small 24B Instruct model by 87\% on domain-specific tool-calling. Moreover, FiMI achieves these significant domain gains while maintaining comparable performance to models of similar size on general benchmarks.