PNB Housing Finance is looking beyond its recent loan-book expansion to smaller cities, micro housing and digitally supported customer management as it seeks to sustain growth in a housing market that is becoming more geographically dispersed. The company’s strategy, outlined by managing director and chief executive Ajai Kumar Shukla, shows how housing finance companies are attempting to reach borrowers outside conventional metropolitan markets while retaining manual checks in a property system that remains only partly digitised.
The company’s loan book rose 19 per cent to ₹95,709 crore in the second quarter of FY27, according to the interview published by The Hindu BusinessLine. Profit after tax increased by about 6 per cent to ₹617 crore. The slower profit growth was attributed to higher write-offs and the changing contribution of recoveries from the company’s write-off pool.
PNB Housing Finance has maintained its guidance for about 20 per cent book growth for the financial year. Retail growth was nearly 19 per cent, within the company’s stated range of 18-20 per cent. Assets under management increased 17 per cent. These figures place the company’s next challenge beyond simply expanding its book: it must grow while managing credit costs, interest-rate changes and the operational complexity of serving a wider customer base.
The geographical shift is central to that plan. Shukla said the company would continue expanding into new geographies because reaching customers more closely supports business growth. He also pointed to the development of smaller cities and continuing urbanisation as sources of demand. The interview does not identify the specific cities or quantify the expected contribution from each geography, but it makes clear that the company sees housing demand outside the largest urban centres as a significant growth lever.
That approach reflects an important change in the housing-finance opportunity. Formal mortgage lending has traditionally been easier to organise where property records, incomes and employment patterns are more visible. Smaller cities can offer expanding housing demand, but they may also present more complicated documentation, less standardised property transactions and a larger share of self-employed borrowers. The lender’s comments suggest that geographic reach alone will not be enough; underwriting capability and local customer acquisition will determine whether expansion can be scaled.
Micro housing is one of the new products being used to pursue that opportunity. Shukla said the company had done almost ₹70 crore of business through micro housing. PNB Housing Finance is also encouraging its prime and emerging branches to source more affordable housing business. The company plans to enter construction finance in a limited way, with that segment expected to account for about 3 per cent of its book this year.
The combination of micro housing, affordable lending and smaller-city expansion places the company closer to the parts of the housing market where demand may be substantial but formal credit assessment is more difficult. However, the interview provides no details on borrower income bands, average loan sizes, geographic distribution, repayment performance or the pricing of these products. Those measures would be necessary to judge whether the expansion is broadening access to housing finance or mainly reallocating existing demand across products.
The company’s credit performance also explains why growth cannot be assessed through loan-book numbers alone. Shukla said the recovery from the write-off pool was much higher in the second quarter of FY26 than in the corresponding quarter of FY27 because the pool was larger earlier. As the pool shrinks, recoveries are expected to normalise. He said the negative rate-cost regime could continue until the end of the year, after which credit cost would move towards a normalised range of 10-15 basis points.
This distinction matters for housing finance companies because a growing loan book can produce different earnings outcomes depending on the age and quality of the portfolio, recoveries from stressed accounts and the cost of acquiring and servicing customers. PNB Housing Finance’s reported numbers show that a 19 per cent increase in the book did not translate into a similar increase in profit. The company’s explanation links that gap to write-offs and recoveries rather than to a deterioration in the broader growth target.
Interest rates are another variable, although the company does not currently see a major disruption from the latest increase. Shukla said a 25-basis-point hike had not slowed the market and that companies remained comfortable with the numbers they had committed to in October. He also rejected expectations of a 75-100-basis-point increase in FY27, while allowing for some further increase depending on the macroeconomic situation and rate movements across the industry.
For borrowers, the effect of higher rates depends on the structure of their loans, repayment capacity and whether lenders pass on increased funding costs. The interview does not provide details on PNB Housing Finance’s loan repricing, borrower mix or the share of fixed and floating-rate loans. It therefore establishes the company’s current assessment of market conditions, but not the full effect of rate changes on household affordability.
The lender’s comments on credit scores offer another view of how formal housing finance is being extended. Shukla said most of the portfolio was above a credit score of 700. Customers with scores between 675 and 690 could still be considered where there was a satisfactory explanation for the lower score and approval was granted at a senior level.
That approach indicates that credit scores are being used as an important screening tool rather than as the only basis for a lending decision. It also highlights the limits of automated lending in housing, where the quality of the property, the legality of ownership, the borrower’s business and the reliability of income records all influence the final decision. The interview does not establish how many applications fall into the lower score band or how those loans perform after approval.
PNB Housing Finance also faces a competitive difference between banks and non-banking finance companies. Shukla said nationalised banks can reach customers directly, while NBFCs have to find and acquire customers. The company intends to compete through reach, service and expertise in underwriting self-employed borrowers. That model can help an NBFC access customers who are less easily assessed through standard salaried-income documentation, but it also makes distribution and field operations more important to the economics of the business.
The company is using artificial intelligence in customer service, pre-delinquency management, post-onboarding and pre-onboarding processes. It is also using predictive models to identify customers who may transfer their loans elsewhere and to manage repayment follow-ups. Shukla said these tools could reduce the need for field effort, which he described as a costly model.
Yet the company is not relying heavily on AI for final underwriting. Shukla said PNB Housing Finance was using a data-science approach but not much AI in underwriting because housing loans require legal verification, technical verification and direct customer interaction. Lenders may need to inspect a borrower’s business and assess the physical setup before deciding whether to approve a proposal.
The most significant constraint, according to the interview, is the incomplete digitisation of historic property documents. Shukla said AI cannot search sub-registrar offices unless the government digitises those records, adding that the process had begun but remained under way. This is more than a technology limitation. It is an institutional constraint: automated lending can only be as reliable as the public records and verification systems on which it depends.
That point connects PNB Housing Finance’s expansion strategy to a wider urban question. Smaller-city housing markets may have demand, but the ability to provide safe and affordable formal credit depends on land records, property registration, income documentation, local legal capacity and reliable verification. Branch expansion and predictive software can improve reach, but they cannot by themselves resolve gaps in the administrative systems that establish ownership and legality.
For now, the evidence supplied by the company shows a lender with a growing loan book, a stated 20 per cent annual growth target and several expansion levers: new geographies, micro housing, affordable housing and a limited construction-finance business. It also shows the limits of that growth story. Profit growth remains slower than loan-book growth, rate conditions remain relevant, and AI is being applied more readily to servicing and collections than to the core decision on whether a property and borrower can safely support a loan. The next indicators to watch are the company’s progress against its growth guidance, the normalisation of credit costs and whether its smaller-city expansion can scale without weakening underwriting standards.
