PNB Housing Finance is betting that India’s next housing-credit expansion will come less from saturated major markets and more from smaller cities, affordable housing and closer engagement with self-employed borrowers. The strategy, outlined by managing director and chief executive Ajai Kumar Shukla, links the company’s growth plans to a broader urban shift: smaller urban centres are expanding, formal housing demand is widening and lenders are trying to reach customers whose income and property records are harder to assess through conventional banking systems.
The company’s loan book grew 19 per cent to ₹95,709 crore in the second quarter of FY27, while profit after tax rose about 6 per cent to ₹617 crore. The contrast between strong loan growth and slower profit growth is important. It shows that expansion in housing finance is not determined only by demand for loans. It also depends on recoveries, write-offs, credit costs, underwriting capacity and the cost of reaching borrowers.
Shukla attributed the slower profit growth largely to the changing recovery profile of the company’s write-off pool. Recoveries in the second quarter of FY26 had been higher because the pool was larger, while the pool has since shrunk. He said the company’s credit cost could remain in a negative-rate regime until the end of the year before normalising at 10-15 basis points.
That explanation places the company’s performance in the context of a balance-sheet transition. A lender can report improving credit quality and still show modest profit growth if exceptional recoveries from earlier stressed assets decline. The distinction matters for housing finance companies because loan-book expansion and earnings quality do not always move at the same pace.
PNB Housing Finance’s smaller-city strategy is built around reach. Shukla said new geographies would remain part of the company’s expansion plan because proximity to consumers supports business growth. He also pointed to increased urbanisation and the development of smaller cities as sources of future demand. The company is maintaining guidance for around 20 per cent book growth for the year, while retail growth is expected to remain in the 18-20 per cent range.
The numbers indicate that retail housing remains the centre of the strategy. Assets under management rose 17 per cent, and the overall loan book grew 19 per cent. The company is therefore presenting its expansion not as a shift away from housing finance, but as a widening of the customer and geographic base within that business.
## PNB Housing Finance and the smaller-city opportunity
The phrase “smaller cities” covers a wide range of urban conditions, but the interview identifies the central lending challenge: formal credit has to follow urbanisation beyond the largest metropolitan markets. As more economic activity develops outside major cities, housing demand may increasingly involve self-employed households, informal or mixed income streams and properties whose documentation is not yet fully digitised.
These customers are not necessarily outside the formal economy, but they may be more difficult to evaluate using standard salaried-borrower models. Shukla said PNB Housing Finance competes with banks through its reach and its capability in serving self-employed customers. He contrasted the direct reach of nationalised banks with the customer-acquisition model of non-bank finance companies, which often depends on intermediaries and local relationships.
This makes distribution an institutional issue, not merely a sales decision. A lender expanding into smaller cities needs local knowledge, staff who can assess borrowers and properties, and processes capable of handling documentation that may not fit a standard digital workflow. The company’s stated focus on prime and emerging branches sourcing more affordable business reflects that operational requirement.
The company also plans to develop micro-housing as a growth area. Shukla said it had already done almost ₹70 crore of business in the segment. The interview does not define the product’s borrower profile, ticket size or geographic distribution, so the available evidence does not establish how large the segment can become. It does, however, show that affordable housing is being treated as a distinct growth lever rather than simply as a by-product of overall loan expansion.
PNB Housing Finance also expects construction finance to account for a very small share of its book, around 3 per cent this year. That limited allocation is significant because it suggests the company’s immediate growth strategy remains weighted towards retail and affordable housing rather than a major increase in developer or project lending.
## The limits of rate-led housing demand
The interview also provides a view of how the company sees interest-rate risks. Shukla said a 25-basis-point hike had not slowed the market and that companies remained comfortable achieving numbers committed in October. He did not expect rates to rise by 75-100 basis points in FY27, although he anticipated some increase depending on macroeconomic conditions and broader industry pricing.
This is a company-level assessment rather than a forecast that can be applied to all borrowers. It indicates that, at the time of the interview, the lender had not observed a material slowdown in its market. The statement also highlights the difference between a policy-rate change and its eventual effect on housing demand. Borrowers may experience the impact through lending rates, repayment burdens and underwriting decisions, while lenders may see it through disbursement volumes, spreads and credit quality.
The supplied material does not provide borrower-level data on repayment stress, regional demand or changes in affordability following the rate increase. It therefore cannot establish whether the absence of a slowdown is broad-based or concentrated in particular customer segments. What it does show is that PNB Housing Finance is continuing to maintain its growth guidance despite the rate environment.
Credit selection remains another constraint on expansion. Shukla said most of the company’s portfolio is made up of borrowers with credit scores above 700. In cases where a customer’s score falls between 675 and 690 because of a small or older adverse history, a loan may still be permitted at a senior level if there is proper justification.
That approach illustrates the continuing role of human judgement in housing finance. A credit score provides a standardised signal, but it does not capture every feature of a borrower’s income, business, property or repayment history. For self-employed borrowers in particular, underwriting may require a combination of financial assessment, customer interaction, legal checks and technical verification.
## Why AI cannot yet replace property verification
PNB Housing Finance is using AI in customer service, pre-delinquency management, post-onboarding and pre-onboarding processes. The company is also using predictive models to identify customers who may transfer their loans to another lender and to manage follow-ups with borrowers who provide a payment date.
The stated benefit is operational efficiency. Field-based collection and follow-up can be costly, and predictive tools may help a lender decide where human intervention is most necessary. Used in this way, AI supports the servicing and monitoring functions around a loan rather than determining the entire lending decision.
Shukla drew a clear boundary around the use of AI in underwriting. He said the company was using a data-science approach but not extensive AI for final underwriting because housing loans require legal verification, technical verification and direct customer interaction. Staff may need to inspect a business setup and assess the circumstances behind a proposal.
The most important limitation identified in the interview concerns property records. AI cannot search historical sub-registrar records effectively unless property documents are digitised. Digitisation has begun, Shukla said, but remains in progress. This is a governance and infrastructure constraint as much as a technology constraint. The quality of digital lending depends not only on algorithms and lender data, but also on the public records that establish ownership, transactions and property status.
That limitation is especially relevant to smaller-city housing finance. As lenders move closer to self-employed borrowers and less standardised properties, the availability, accuracy and accessibility of land and property records become central to credit decisions. Until those records are consistently digitised, technology can reduce some costs but cannot eliminate the need for field verification and institutional checks.
The company’s strategy therefore combines expansion with selective automation. New geographies, micro-housing and affordable business are expected to grow the loan book, while data science and AI are being used to improve customer engagement, collections and retention. Human underwriting remains necessary where property documentation and borrower circumstances cannot be reliably captured in structured data.
The evidence supports a measured conclusion. PNB Housing Finance is maintaining an ambitious growth plan, with a 19 per cent increase in its loan book and guidance for about 20 per cent growth for the year. Its stated growth levers are smaller-city expansion, affordable housing, micro-housing and stronger reach to self-employed customers. At the same time, profit growth has been moderated by the changing recovery profile of written-off assets, and the company expects credit costs to normalise.
The larger urban question is whether housing finance can expand at the same pace as India’s smaller cities without improvements in the systems that make properties and borrowers legible to formal lenders. The interview suggests that demand is available, but reaching it requires distribution, specialised underwriting and better public records. The developments to monitor are whether the company meets its growth guidance, how its micro-housing business develops, whether construction finance remains limited to 3 per cent of the book, and how quickly property-document digitisation progresses.
