Last month, our team was in Mumbai for the ETBFSI CIO Digital Conclave 2026 — a room full of CTOs and CIOs from India's leading financial institutions, asking exactly the right questions.

The Galytix team at the ETBFSI CIO Digital Conclave 2026, Mumbai.

The Galytix team at the ETBFSI CIO Digital Conclave 2026, Mumbai. India is not just catching up. It is becoming one of the most consequential proving grounds for AI in financial services — and spending a day alongside the people who run credit and technology at institutions like SBI, ICICI, HDFC, Standard Chartered, IndusInd Bank and many others made that clear in a way that data alone cannot. The conversation in the room had matured. These leaders are not debating whether to adopt AI. They are asking harder, more important questions why isn't it scaling, why do pilots stall before production, and what does it take to build something a regulator can actually examine.

AI is not a chatbot. It is a digital worker. Raj Abrol, Co-Founder & CEO, Galytix Our CEO Raj Abrol spoke in the keynote session, making the case that the industry needs to move past experimentation. Generic AI cannot fix credit — credit is a domain problem, not a language problem. Every ratio, every covenant, every early warning signal must be grounded in structured financial data and traceable to source. POCs do not move balance sheets. Production does. Watch a summary here

Raj Abrol, Co-Founder & CEO, Galytix

Dalibor Hlava, panel session

Dalibor Hlava, panel session Our Chief AI Officer Dalibor Hlava addressed why so many pilots fail before they begin: data complexity, privacy constraints, and a trust deficit that forms when analysts cannot verify where numbers come from. The biggest production challenge in AI is not the model. It is building intelligence that genuinely understands credit, respects the complexity of real portfolios, and works with teams rather than around them.

Together, the sessions formed a single, grounded message: the industry does not need more AI experiments. It needs intelligence built specifically for lending — intelligence that earns trust, reaches production, and strengthens judgment rather than replacing it.

Galytix has spent the past decade building exactly that: risk-specialised AI agents trained on structured banking data, producing transparent and verifiable outputs that relationship managers, credit officers, and portfolio managers can rely on in the flow of daily work.

The $5.2 trillion SME financing gap is not just a development challenge. It is a commercial opportunity — and the institutions that close it will be the ones who get the foundations right.

Further Reading

Supercharging SME Credit Using Risk-Specialised AI

What risk-specialised AI actually looks like in credit — not the demo, but the production reality. The economics of the SME financing gap, and why it is a commercial opportunity.

Read the article - Supercharging SME Credit Using Risk Specialised AI