Indian women are increasingly demonstrating their ability to borrow and repay loans, with delinquency rates lower than the overall average. Yet, access to credit remains a significant hurdle for women entrepreneurs, particularly when it comes to securing larger loans and working capital to expand their businesses.
According to the NITI Aayog-TransUnion CIBIL report of April 2026, women account for 26% of India’s total system credit. Their business loan portfolio has grown 7.5 times since 2017. Women who borrowed in 2024 had a delinquency rate on loans overdue by 90 days or more that was just 0.7 times the overall rate. Despite this stronger repayment record, only about a quarter of women entrepreneurs borrow in their businesses‘ names. Most continue to depend on personal loans, microfinance and Mudra schemes rather than the larger and more flexible credit facilities needed to scale their enterprises.
The disparity is particularly evident in access to overdraft facilities. As of April 2026, only around 4% of women-owned business entities had an overdraft facility, compared with 40% of businesses overall. This points to a deeper problem: the way lenders assess borrowers and determine their creditworthiness.
Traditional underwriting models rely heavily on collateral, formal documentation and established financial records. Women are often disadvantaged on all three counts. Properties offered as collateral are frequently registered in men’s names, leaving women with few assets to pledge. Many women-led enterprises also operate informally, without audited accounts or comprehensive financial documentation. In several cases, business transactions flow through a male family member’s phone or a shared bank account, making it difficult for lenders to establish the actual turnover and financial health of the enterprise.
Digital footprints are beginning to offer an alternative to conventional collateral. In March 2025, India introduced a digital credit assessment framework to facilitate lending to MSMEs using GST filings, income tax returns and bank statements accessed through account aggregators. Public sector banks and private sector initiatives such as Kinara Capital’s HerVikas programme are using data-driven approaches to widen credit access for women entrepreneurs.
However, newer lending channels have not fully addressed the gender gap. Women received just 19.8% of loans by volume, below their 26% share of overall system credit. This suggests that digital lending, despite its potential to make credit assessment more inclusive, is also reproducing inequalities embedded in traditional lending practices.
A key part of the problem is the digital divide. GSMA data for 2024 shows that 75% of Indian women own mobile phones, compared with 85% of men. More significantly, only 37% use mobile internet. Limited access to smartphones, digital payments and financial services restricts the digital trail lenders increasingly depend on to assess creditworthiness. As lending platforms incorporate artificial intelligence into credit decisions, this divide could widen further. The lack of accessible financial tools and interfaces in vernacular languages could leave many women entrepreneurs at a further disadvantage.
Addressing this requires concerted efforts by policymakers, banks and technology providers. Recognising jointly held property titles as valid collateral could help more women qualify for loans. Entrepreneurship and livelihood programmes run through banks and self-help groups should encourage women to open business bank accounts and build identifiable financial records through individual UPI IDs. Lenders, in turn, need to make greater use of digital footprints, including GST filings and UPI transactions, as alternatives to property-based collateral.
Equally important is making digital lending accessible. Loan applications, financial management tools and banking interfaces must work on basic smartphones and be available in vernacular languages. As lenders increasingly deploy AI-based credit scoring systems, they must guard against algorithmic bias. Models trained on historical lending data could inadvertently perpetuate gender disparities, penalising women for gaps in documentation and financial histories that the traditional system itself has helped create.
Another concern is that loans may be sanctioned in women’s names but the money is often controlled or used by male family members. This leaves women carrying the repayment liability without necessarily having control over the enterprise or the funds. Expanding access to credit, therefore, cannot be the sole measure of financial inclusion. Women must also have the agency to decide how borrowed money is deployed and how their businesses are run.
Awareness of financial rights, data ownership and privacy safeguards is equally important. The principles underpinning the Digital Personal Data Protection Act should be communicated to women borrowers so they understand how their personal and financial information is collected, shared and used.
Ultimately, the objective must go beyond increasing the number of loans sanctioned to women. It should be to build a lending ecosystem that recognises their creditworthiness, removes structural barriers and gives them meaningful control over the businesses they establish and seek to grow.
Source: The Financial Express
