NPCI Launches FiMi Banking: India's First Sovereign AI Model for Retail Banking
At Global Fintech Fest 2026 in Mumbai, the National Payments Corporation of India (NPCI) unveiled FiMi Banking (Finance Model for India) โ described as India's first "sovereign compact model" purpose-built for retail banking tasks. Built on Google's open Gemma foundation and fine-tuned with Indian banking data, the model is designed not just to answer questions, but to let AI agents reason, use tools, and carry out actions within a bank's existing rules and systems.
โก Quick facts
- What it is: A sovereign compact AI model built on Google Gemma, trained with Indian retail banking data by NPCI.
- Purpose: Task-execution AI agents that can reason and act within bank rules, not just respond to queries.
- Partner: HDFC Bank is collaborating with NPCI on further development and testing.
- Benchmarks released: IndicBank Bench (799 test cases) and Tau Agentic Banking Benchmark (1,000 tasks) โ both using synthetic data only, publicly available.
What is FiMi Banking?
FiMi stands for Finance Model for India. NPCI describes it as a "sovereign compact model" โ meaning the model and its training data stay under Indian institutional control, rather than depending entirely on foreign AI labs for critical banking infrastructure.
The model is built on Google Gemma, Google's family of open-weight AI models, with NPCI conducting additional training using Indian retail banking data and scenarios. Unlike standard chatbots, FiMi Banking is designed for task execution: AI agents built on top of it can reason through multi-step banking workflows, invoke tools, and carry out actions โ all while operating within a bank's existing rules, compliance frameworks, and regulatory boundaries.
NPCI chairman Ajay Kumar Choudhary emphasized a critical guardrail at the launch: "AI agents may recommend UPI payments, but authentication and final settlement must remain deterministic." In other words, the model can assist with banking decisions, but the human and system-level safeguards for actual payments stay firmly in place.
The HDFC Bank partnership
NPCI is building FiMi Banking in collaboration with HDFC Bank, India's largest private bank by assets. The partnership merges NPCI's technology and payments infrastructure expertise with HDFC Bank's deep domain knowledge in retail banking operations, customer workflows, and regulatory compliance.
HDFC Bank's involvement is significant: as one of the largest deployers of UPI infrastructure in India, the bank brings real-world production banking context that purely academic or lab-trained models lack. The collaboration suggests FiMi Banking is intended for eventual production deployment across NPCI's ecosystem of partner banks and fintechs.
Two open benchmarks for banking AI
Alongside the model, NPCI released two open evaluation benchmarks designed to let banks, fintechs, and researchers test their own AI agents against standardized Indian retail banking scenarios:
| Benchmark | Scale | What It Tests |
|---|---|---|
| IndicBank Bench | 799 scripted multi-turn test cases across 6 banking domains | Agent safety, correct actions, and response appropriateness in Indian retail banking scenarios |
| Tau Agentic Banking Benchmark | 1,000 tasks across 50 scenario groups | Dynamic multi-turn testing via dual-control simulation (second model role-plays as the customer), built on the open-source ฯยฒ-bench framework |
Crucially, NPCI confirmed that both benchmarks use synthetic data only โ no actual customer, account, or institutional information is included. The technical report, evaluation framework, scoring methodology, and full results are all being made publicly available so developers, banks, fintech companies, and researchers can test their own banking AI agents against these standardized benchmarks.
NPCI and NVIDIA's open RL environment for banking agents
Also at GFF 2026, NPCI and NVIDIA jointly launched an open reinforcement learning (RL) training environment for banking AI agents. The framework lets institutions train and benchmark AI models on Indian banking tasks using synthetic data, described as "a stable, reusable and cost-effective platform for institutions to develop and evaluate" AI solutions.
Together, the FiMi Banking model and the NVIDIA RL environment signal that NPCI is building out a complete Indian banking AI ecosystem โ not just a single model, but the training infrastructure, evaluation benchmarks, and partner integrations needed to make banking AI agents production-ready.
Why this matters for India's banking future
India processes more real-time digital payments than any other country, with UPI handling billions of transactions every month. The prospect of AI agents handling banking tasks โ from account inquiries to transaction initiation โ raises both enormous efficiency potential and serious regulatory questions.
FiMi Banking addresses this by keeping the AI model under Indian institutional control (NPCI is the body that operates UPI, IMPS, and other core payment systems), using only synthetic data for training and evaluation, and insisting that payment authentication remains deterministic rather than delegated to probabilistic AI.
The approach also positions India's banking AI stack as distinct from the consumer-facing AI models from OpenAI, Google, or Anthropic. Rather than adapting a general-purpose chatbot for banking, NPCI is building a domain-specific model from the ground up with Indian banking regulation and infrastructure at its core โ an approach that could become a template for other countries building sovereign AI capabilities in sensitive sectors.
Frequently asked questions
What is NPCI FiMi Banking?
FiMi Banking (Finance Model for India) is a sovereign compact AI model purpose-built for Indian retail banking tasks, unveiled by NPCI at Global Fintech Fest 2026. It is built on Google's Gemma foundation and trained with Indian banking data.
What makes FiMi Banking different from a regular chatbot?
Unlike standard chatbots that only respond to queries, FiMi Banking is built for task execution โ meaning AI agents can reason, use tools, and carry out actions within a bank's existing rules and systems, with long-context processing.
Who is building FiMi Banking and with which partner?
NPCI (National Payments Corporation of India) is building FiMi Banking in collaboration with HDFC Bank, which will contribute its banking domain expertise to further develop and test the model.
What benchmarks did NPCI release alongside FiMi Banking?
NPCI released two open benchmarks: IndicBank Bench (799 scripted test cases across six banking domains) and Tau Agentic Banking Benchmark (1,000 tasks across 50 scenario groups using a dual-control simulation) to let developers and researchers evaluate their own banking AI agents.
Does FiMi Banking use real customer data?
No. NPCI confirmed that the benchmarks and training use synthetic data only โ no actual customer, account, or institutional information is included. The technical report, evaluation framework, and results are all publicly available.