AI engineered for the most regulated industry on earth
Banks, insurers, and capital-markets firms do not get to apologise for a hallucinating chatbot or a fine-tuned model that learned to launder money. We deploy AI for BFSI with the engineering discipline, evaluation rigour, and sovereign-deployment options the regulator actually requires — KYC at four hours not five days, conversational banking that resolves rather than deflects, document automation auditable to the field, and a sovereign LLM stack that runs inside the bank's perimeter with zero outbound network. BFSI is our deepest vertical, with reference customers including tier-one banks across Africa, the Gulf, the UK, and South Asia.
Where BFSI organisations need AI most
KYC and onboarding friction
Manual KYC produces forty-percent dropout rates and multi-day cycle times. Regulators demand the rigour but customers — especially in mobile-first markets — abandon at the first speed bump. The technology to close this gap exists; the engineering discipline to deploy it inside a bank does not, in most places.
Regulatory reporting burden
Basel III/IV, IFRS 9 and 17, AML / SAR, FATCA, CRS, climate-risk disclosures — the volume and granularity of regulatory filings expands every reporting cycle. Eighty percent of the generation work is automatable with AI applied to source ledger and policy data; almost none of it is automated in most banks.
Behavioural fraud and AML evolution
Rules-based fraud and AML systems are years behind the typology evolution. The cost of false positives is operational; the cost of false negatives is regulatory. Behavioural ML closes the gap, but only with the data engineering and model governance to make it operable inside a financial-services risk function.
Core banking systems built before AI existed
Temenos, Finacle, Flexcube, FIS, FIS Profile — the cores were architected before AI was a category. Integrating AI at scale without disrupting the rails requires specialist patterns: API gateways, event-streaming overlays, and read-replica analytical stacks. Most generalist integrators get this wrong.
Sovereign deployment mandates
Increasingly, regulators across BRICS economies and the Gulf require AI workloads on regulated data to remain inside national borders and outside hyperscaler control planes. This rules out most of the popular cloud-AI architectures and demands a sovereign stack that very few vendors can actually deliver.
Proven accelerators for BFSI
Results we've delivered
AI for BFSI — let's talk
Speak to our team. No sales pitch — just a technical conversation about your challenges.
Start a conversation →