Home loan crisis: Informal incomes keep Indians locked out of credit, expert shares solutions

Despite government initiatives such as the Pradhan Mantri Awas Yojana and the Credit Linked Subsidy Scheme (CLSS), low- and mid-income homebuyers in India with informal income sources continue to face major hurdles in securing traditional home loans. These barriers persist largely due to lenders' reliance on formal income documentation, which is often unavailable for individuals working in sectors such as agriculture or informal employment, where earnings can be irregular and difficult to document.

Sumit Sharma, Founder of Radian Finserv, told Business Today, "Mid-income buyers make up a large chunk of aspiring homeowners, but they struggle because lenders typically require formal income documents to evaluate loan eligibility." This situation is further complicated by the unpredictability of income in these sectors, as Sharma explained: "Many of these individuals work in agriculture or the informal sector, where earnings are seasonal, irregular, and hard to document. That creates uncertainty in the eyes of banks, who often see them as high-risk borrowers."

Property documentation also poses a significant challenge. "Unclear land titles or incomplete paperwork for properties in semi-urban and rural areas often derail loan applications before they even begin," noted Sharma. Such documentation issues can be a major stumbling block in loan processing, especially in areas where formal property records are either incomplete or non-existent.

However, the landscape is gradually changing with the introduction of fintech-driven innovations and alternative credit assessments. According to Sharma, "Instead of only relying on payslips or tax returns, lenders can look at cash flow-based assessments." This shift involves using documents such as business registrations and bank statements to establish financial credibility, providing a clearer financial picture in the absence of traditional income proofs.

Fintech companies and Non-Banking Financial Companies (NBFCs), often supported by the National Housing Bank, are increasingly adopting alternative credit scoring models. "These models leverage a variety of data—from digital footprints and behavioural patterns to geotagging and demographic data—to assess a borrower’s ability, stability, and willingness to repay," Sharma explained. This approach helps to mitigate the risks associated with lending to individuals with informal incomes.

Despite these advancements, risks remain a concern. "It’s difficult to accurately assess leverage and true repayment capacity," Sharma cautioned. Nonetheless, the use of co-applicants, flexible repayment options, and AI-driven behavioural models are strategies being employed to address these challenges, paving the way for improved accessibility to home loans for informal income segments.