BFSI Decision Intelligence
Risk models and document systems that survive the regulator.
Banks, NBFCs, and insurers have budget, measurable P&L, and a reason not to move fast with ChatGPT. They need classical decisioning and generative systems that pass RBI, IRDAI, and model-risk review.
BFSI still leads India on AI budget discipline and governance maturity. DPDP Rules and sector guidance make ungoverned copilots a non-starter, which is exactly why specialist delivery is funded.
Pure-LLM shops fail model-risk. Pure-quant shops miss the servicing and document wave. We ship both stacks: scorecards, boosting, and graphs where they belong; retrieval and agents where they belong; one audit trail across both.
We enter through a production failure or a GCC mandate more often than through a cold RFP. The first engagement is a regulated use case with an owner in risk or operations, not a lab.
Engagement shapes
- 01Fraud, credit, or underwriting model rebuild: classical methods, graph features, and LLM-derived signals under one governance story.
- 02Claims and KYC document intelligence with explainability packs for operations and audit.
- 03Model risk, fairness, and audit artefacts for internal audit and the regulator.
- 04Servicing and collections agents on top of existing core systems, not a parallel stack.