Credit Decisioning

Q1 FY26 didn't slow credit--it got smarter. Housing upmarket, credit cards slowing, automobile loan lifted; lenders chose quality over quantity. See what's next.

Partnership lending has the rails--apps, UPI, marketplaces. Read how AI can act as the orchestrator in the partnership lending value chain.

RBI's new 'tolerant supervisory stance' for AI is a stark departure from its usual hawkish stance. Read now to discover what this could mean for India's financial future.

Indian finance should focus on AI automation over lending decisions. Learn why data quality issues make operational AI the smart choice for NBFCs and banks.

Affordable housing finance faces higher NPAs and credit costs in Q1 FY26. Learn why inclusion needs guardrails and how lenders can balance growth with risk.

With the bank credit growth plummeting from 16% a year ago to a cautious 9% in June 2025, along with export and diesel consumption declining, there are signs that a storm could be in the offing

Could the most crucial customer-faced financial process in India finally get the overhaul it deserves? ____________________________________________________________________________________________ So, you&

As personal loan growth slows and young borrowers pull back, housing finance is emerging as the next big opportunity in India's credit story backed by demand, policy, and smart lending.

RBI's new rule mandates NBFCs to exclude fintech DLGs from provisioning. How will this rule reshape digital lending, impact partnership lending, and redefine accountability for NBFCs?

RBI's new rule mandates NBFCs to exclude fintech DLGs from provisioning. How will this rule reshape digital lending, impact partnership lending, and redefine accountability for NBFCs?

Indian banks are shifting from unsecured to secured loans amid rising delinquencies and regulatory pressure.

The "black box" problem refers to AI systems that make decisions through processes that remain opaque even to their creators. The dilemma is straightforward: if we cannot explain how AI reaches its conclusions, how can we possibly trust it?