Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

I am a banking practitioner and a certified credit & risk specialist with over 18 years of experience in the Indian financial sector. Most of my career has been spent "on the desk," managing the complexities of Corporate Credit and Credit Risk Management during some of the most transformative years for the Indian banking Industry.

My core expertise lies in Credit & Credit Risk, a domain I have lived and breathed for nearly two decades. At State Bank of India (SBI), I served as Vice President (Corporate Credit), where I was responsible for the end-to-end credit life cycle of high-value corporate loans—from appraisal and loan structuring/rating to sanction and, subsequently, the ongoing monitoring of large corporate portfolios. This experience gave me a ground-level view of how industrial cycles and economic shifts impact creditworthiness in our country.

Later, as the Head of Credit Risk at Bandhan Bank since its inception as Universal Bank, I was tasked with building and overseeing the entire credit risk frameworks across all loan segments during the institution’s critical transition into a universal bank and thereafter. This role required a balance between maintaining high growth and ensuring the quality of the loan book, particularly across the microfinance, corporate, and retail segments. During my tenure as Head-Credit Risk for more than a decade here, I had the privilege of attending Board-level meetings, which provided me with deep strategic oversight and a high-level perspective on institutional governance, which was crucial for aligning risk appetite with long-term goals.

Beyond traditional credit risk, I have expanded my focus to include Sustainability and Climate Risk (SCR) as well. I am SCR-certified, which allows me to help institutions understand how climate risk is now synonymous with financial risk. I have also qualified for the IICA Independent Director exam, positioning me to provide strategic oversight at the board level of any institution.

Today, I operate as a Banking Consultant and Educator through my own venture, Banking Simplified Masterclass. My goal is to bridge the gap between academic theory and industry reality by providing specialized training and consulting that make complex banking and risk concepts accessible to professionals and students alike.

Q2. In a phase where retail credit growth remains strong but regulatory tightening is kicking in, how do you read the current stage of the credit cycle, and what signals suggest a potential turning point?

Yes, growth is strong, but we are probably in a late-expansion phase now, since growth is naturally moderating from the 16–20% highs of FY25 to approximately 14% as of March 2026, despite demand remaining high. This slowdown is, of course, a direct result of regulatory guardrails—specifically, increased risk weights and tightened LTV ratios—designed to cool over-leveraged retail segments. At the same time, stable asset quality remains at a multi-year low of 2.1%.

But the defining signal of a turning point is the abnormally high Credit-Deposit (CD) ratio, which reached a historic peak of 82.5% in February 2026. With the incremental CD ratio frequently exceeding 100%, the banking system is facing a structural liquidity squeeze. Unless deposit mobilization accelerates to close the gap with credit growth, banks may be forced to recalibrate credit supply to the market.

Combined with early stress signals in "new-to-credit" low-ticket-size (below 50k) personal loans, specifically extended to the younger generation, and lingering instability in parts of the Microfinance sector, these factors indicate the cycle may be pivoting toward a period of capital preservation and selective lending in the future.

Q3. As borrowers increasingly access credit across multiple platforms—banks, NBFCs, and fintechs—how is aggregate leverage evolving, and where do you see visibility gaps that could become problematic?

Aggregate leverage is shifting toward a highly fragmented and "high-velocity" model. Beyond the formal interplay of banks, NBFCs, and fintechs, a significant volume of credit still flows through informal sources, particularly in the small-ticket and consumption segments. The ease of access—where credit is now available with a single click on a mobile device—has made it increasingly difficult for lenders to track a borrower’s total indebtedness prudently. This "instant" availability often leads to debt stacking, where individuals facing personal emergencies resort to multiple sources simultaneously, pushing their leverage beyond sustainable levels before formal monitoring can catch up.

The most critical visibility gap lies in the disconnect between the speed of borrowing and the frequency of reporting. While the regulatory shift to a 15-day reporting interval (effective January 1, 2025) and the move toward a 7-day mandate (starting July 2026) are welcome steps, they still may not provide "real-time" oversight. A 48-hour window is often all it takes for a borrower’s leverage profile to change completely, specifically for small-ticket loans or consumption loans. Yet, this surge remains invisible to the next lender until the weekly incremental file hits the bureau.

Furthermore, technical challenges such as data mapping errors, overlapping platform entries, and a lack of cross-platform synchronization continue to plague the system. Industry estimates suggest that approximately 30–40% of small-ticket loans may suffer from bureau misses or fragmented data issues. When you combine these technical "blind spots" with the total absence of informal sector data in Credit Information Company (CIC) reports, the risk of systemic over-leveraging becomes a significant concern for the industry's long-term stability.

Q4. With rising digital adoption, how are fraud patterns and borrower behavior evolving, and how should credit risk frameworks adapt to these emerging risks?

With the rise of digital banking, fraud patterns have changed significantly. Think of these as the "new age" of digital bank robbery. Instead of walking into a branch with a mask, fraudsters use data and AI to trick the system from the inside. Plus, the ease of obtaining instant loans across multiple apps often leads to impulsive borrowing, which increases default risk. Because everything is digitized, a borrower’s financial footprint is scattered across multiple platforms, making it harder for traditional banks to see the full picture of their debt. Plus, the visibility gap discussed above persists. 

To remain resilient, the Risk Framework must be forward-looking. In a digital world, Operational Risk and Credit Risk are inseparable. Weak processes or "operational lapses" during onboarding are exactly what allow fraud to turn into bad loan portfolios.

So, the Risk frameworks must move away from looking at the past and start using real-time analytics and alternative data. By monitoring behavior as it happens, meaning shifting from Post-Mortem Risk Analysis to Real Time Monitoring, lenders can spot threats before they hit the balance sheet. This ensures that the speed of our risk oversight finally matches the speed of digital credit.

Q5. Beyond direct exposure, how do you see climate risk indirectly affecting credit quality through supply chains, income volatility, or regional disruptions?

We can no longer treat climate risk as a siloed event; it is a macro-financial driver, where a disruption today becomes a balance-sheet default tomorrow. Even if there is no direct exposure, it can still affect credit quality through the cascading or risk-multiplication effects via alternative channels.

A climate event in one region can halt production, delaying payments, hiking borrowing costs for firms reliant on them in other regions, and eroding profitability. This is Supply Chain Contagion. Income volatility can sometimes be created in retail portfolios, such as microfinance or similar. A physical risk event, such as a heatwave, drought, or unseasonal rain, spikes food inflation, reducing borrowers' disposable income and, in turn, affecting their repayment capabilities. Similarly, a regional disruption can add to this if a region is chronically hit by a localized event whose impact cascades through layers and geography via the contagion effect. 

Q6. How do purchasing criteria differ across segments like retail, MSME, and microfinance, and where do you see the greatest risk of misalignment between criteria and actual borrower behaviour?

Purchasing criteria means the "rules" banks use to decide who gets a loan. Retail loans are individual loans, and Lenders rely mainly on individual salary slips, Fixed Obligation to Income (FOIR) ratio, and Credit bureau scores. These are standardized processes. But MSMEs are basically business loans, where the business turnover and loan limit/repayment capacity are assessed using GST returns, bank statements, and audited financials. Microfinance prioritizes group lending, considering cash flow from informal incomes, JLG models, informal group guarantees, peer pressure, etc. 

Mis-alignment happens when the credit underwriting rules do not match the reality, especially when underwriting is totally formal, document-based, or quantitative data / rule-based without considering behavioral alternative data, because, in the unorganized sector like low-end MSME or bottom of the pyramid lending like Microfinance, the “paper trail” is often a dead end. Plus, in the Cash trap, where bank statements capture only a fraction of real activity, the risk of traditional data-based underwriting becoming ineffective is high, and a balanced, hybrid credit appraisal that gives due cognizance to physical inspection, alternative data such as utility bills, customer footfalls, location advantage, etc., merits consideration. 

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management?

If I were an investor, the most critical question I would pose to senior management is:

• Process or IT capabilities to assess and monitor over-leveraging at the aggregate level of the borrower, on a real-time basis or with a minimum visibility gap.
• Roadmap / Vision for integrating AI into risk management and data analytics, subject to constant output validation while ensuring transparency for regulators to trust their decisions.
• The organization's strategy for determining when to grow versus consolidate.