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A woman’s name on the property title is only the beginning

Posted on by harshita

When a woman’s name appears on a property title, what does it really signify? Does it reflect genuine ownership, control over assets, and financial agency, or does it simply indicate formal inclusion? India has made significant progress in expanding women’s participation in the workforce, property ownership, and formal housing finance through legal reforms, public policy, and lender initiatives. Yet, formal inclusion does not automatically translate into economic agency. The challenge now is to ensure that inclusion translates into meaningful participation as earners, borrowers, asset owners, and financial decision-makers. Housing lies at the heart of this challenge because, for most households, a home is their largest asset and an important source of long-term financial security. 

A secure home offers far more than shelter. It provides privacy, stability, dignity, and safety, while also supporting work, generating income, and offering protection during periods of financial distress. For decades, women have played a central role in building and sustaining households, yet their contribution has rarely translated into property ownership or access to formal housing finance. Women’s growing contribution to household income, together with supportive policies and lender initiatives, is creating stronger pathways to home ownership and housing finance. 

In 2023-24, the labor force participation rate among women aged 15 and above rose to 41.7%, up from 23.3% in 2017-18, while the share of women in employment increased from 22% to 40.3%. The redesigned Periodic Labor Force Survey (PLFS) for 2025, the first survey under the new format also points to continued momentum, with rural women’s participation rising further up to 45.9%. Yet, higher workforce participation does not necessarily mean women have stable or well-paying jobs, as much of their employment remains informal, self-employed, or linked to family enterprises. These trends suggest that, despite rising labor force participation, important gaps in the quality of employment and meaningful economic participation remain. At the same time, they show that women’s contribution to household income is becoming increasingly visible and harder for financial institutions to overlook. This growing economic visibility has also coincided with an increase in women’s recorded ownership of housing, although much of this ownership remains joint rather than independent. 

UNFPA’s analysis of the National Family Health Survey (NFHS)-4 and NFHS-5 data shows that the share of women aged 15-49 who owned a house, independently or jointly, increased to 42.3% in 2020-21 from about 37.1% in 2015-16.  

This progress has been supported by legal reforms, government housing programs, state-level incentives, and initiatives by financial institutions. Together, these measures have created stronger pathways for women to own property and access housing finance. At the national level, the Hindu Succession (Amendment) Act, 2005, gave daughters in Hindu joint families the same coparcenary rights as sons. Government housing programs then created direct pathways to ownership. Under the Pradhan Mantri Awas Yojana–Urban 2.0, houses receiving central assistance are generally required to be registered in the name of the female head of the household or jointly in the names of both spouses, subject to specified exceptions. About 8.9 million PMAY-U houses stood in women’s sole or joint names by August 2024. By January 2026, the government reported that it had sanctioned 9.0 million houses to women. Under Pradhan Mantri Awas Yojana Gramin (PMAY-G), around 19.5 million of the 26.8 million houses completed by December 2024 were registered solely in a woman’s name or jointly in the names of both spouses. This represents about 73% of completed houses under the program. The program now aspires to achieve 100% women’s ownership. 

State governments have reinforced these measures by reducing the upfront cost of property registration for women. In Delhi, stamp and transfer duty stands at 4% for women purchasers, compared with 6% for men. Financial institutions also introduced incentives, such as lower interest rates for women owners or co-owners and higher loan eligibility when they included a woman’s income in household assessments. In 2023, the International Finance Corporation (IFC) committed up to USD 100 million to IIFL Home Finance, with half the funding earmarked for women’s housing finance. Women-focused portfolios have become more than an inclusion objective. They are also emerging as an important funding and business strategy for financial institutions. These policies and market interventions are increasingly reflected in women’s participation in housing finance and their performance as borrowers. 

Over the five years through December 2025, the number of women borrowers registered a compound annual growth rate (CAGR) of 14.2%, compared with 8.2% for men. Women represented 32.2% of outstanding housing-loan portfolios, and their repayment performance was also marginally stronger, with 2.2% of women’s home-loan balances being overdue by 31 to 180 days, compared with 2.5% for men. Even after accounting for the smaller base, the data indicate that women are emerging as a comparatively resilient borrower segment, with repayment performance that is marginally better than that of men. 

MSC’s (MicroSave Consulting) recent research on affordable housing across selected geographies revealed strong demand for self-construction, renovation, reconstruction, and incremental expansion. Women accounted for more than two-fifths of the study participants. They expressed a desire to build on existing plots, add rooms or floors, repair aging structures, and move out of rented or inadequate homes. Although women did not always interact directly with lenders, their preferences shaped key household decisions. Affordability, privacy, sanitation, ventilation, children’s space, and household safety consistently influenced those decisions. Women often served as co-decision-makers during housing decisions. They also shaped what households considered affordable equated monthly installments (EMIs) and acceptable financial risk. Lenders should therefore assess women’s housing demand beyond the number of primary female applicants. Women often influence the purpose, affordability, and repayment of housing loans even when a man submits the application. 

As India has made strong progress in recording women as owners and borrowers. The next challenge is to give that formal visibility economic meaning. Affordable housing finance can translate women’s growing presence in property and credit records into meaningful economic empowerment. Property ownership can strengthen women’s financial security, resilience, and influence over household decisions. Lenders must now move beyond traditional products for women and adopt women-centric approaches that offer a broader range of services. A woman’s presence on a loan document should reflect her role in the decision rather than satisfy a procedural requirement. Lenders must recognize informal and home-based income more systematically, involve women directly in loan counseling, and ensure they understand repayment obligations, fees, insurance, and the risks associated with mortgaging property. The first phase of inclusion brought women onto property titles and loan documents. The next phase must recognize them as income earners, informed borrowers, and decision-makers. It must also give them a meaningful voice in how their assets are financed, used, and managed. 

Everyone sees financial fraud. It is time for institutions to stop it.

Posted on by harshita

A schoolteacher in Madhya Pradesh received a call from someone who sounded exactly like her cousin. The caller claimed to be in trouble and needed money transferred at once. The voice sounded authentic, and the teacher transferred the funds immediately.

The call was a fraud. The relative’s voice had been cloned using AI. No suspicious links, stolen passwords, or warning signs were involved. The teacher did nothing wrong. Yet, the transaction need not have proceeded unexamined. Her bank could see that it sharply deviated from her usual pattern. It was an unusually large, urgent payment to a new payee.

Meanwhile, the receiving bank held information about the recipient’s account history, including whether it resembled the rapid-in, rapid-out behaviour typical of a mule account. No single institution had the complete picture, yet together, they held sufficient signals to justify a warning, additional verification, or temporary review. Instead, the transfer went through without intervention.

Every stage of the fraud was visible to a different institution. A telecom network carried the call, and the bank processed the payment. The receiving account existed within the financial system. Each institution could see part of the risk, but no one was tasked to connect those signals or act on them.

Fraud networks have industrialized deception using AI impersonation, spoofed identities, mule accounts, and sophisticated social engineering. They exploit the gaps between institutions far more effectively than institutions cooperate with one another.

Banks remain the closest line of defence because they sit at the point of transaction. Yet the scale of exposure is significant. RBI data shows that digital payment fraud cases involving cards and internet banking run into the tens of thousands each year. MSC’s research across India, Bangladesh, and Kenya shows that 55% of low- and moderate-income respondents receive fake calls or messages that impersonate legitimate institutions. A growing share of these losses stems from authorized push payment (APP) fraud, where victims themselves authorize transfers under coercion or deception. These cases often bypass conventional fraud controls designed to detect unauthorized activity.

The warning signs, however, are often visible before victims lose their savings. Earlier this year, in Visakhapatnam, a retired nurse arrived at her bank to transfer INR 50 lakh after fraudsters who posed as cybercrime officials threatened her with arrest. She arrived at her bank to initiate the payment. There, the bank manager recognized the warning signs, alerted authorities, and stopped the payment. This intervention required neither breakthrough technology nor perfect fraud detection. It required trained people who could recognize suspicious patterns and act.

The contrast with the Madhya Pradesh teacher is striking. In both cases, victims were manipulated into authorizing a payment. In one case, the transaction proceeded without intervention. In the other, human intervention prevented a loss.

In the teacher’s case, the fraud began long before the payment was made. The cloned voice reached her through a telecom network. Caller ID spoofing and SIM-swap fraud increasingly allow criminals to impersonate banks, regulators, and law enforcement agencies. Telecom providers can often detect suspicious patterns before payments occur. India has already shown that such intervention is possible. Bharti Airtel, for example, uses AI systems to flag suspected spam calls and malicious links in real time.

Digital platforms have become another major channel for fraud distribution. Fake investment schemes, impersonation accounts, and fraudulent advertisements can reach thousands of potential victims before removal. Fraud today moves seamlessly across telecom networks, banking systems, and digital platforms, but accountability remains siloed. India, therefore, faces less of a detection problem than an accountability problem. The response requires action on three fronts.

The first step is a mandatory reimbursement framework for APP fraud backed by enforceable fraud-risk controls. In October 2024, the UK’s Payment Systems Regulator introduced rules requiring sending and receiving banks to share liability for qualifying APP fraud losses, capped at GBP 85,000 (approximately INR 90 lakh) per claim. When institutions bear part of the financial consequences, prevention becomes a business priority rather than a compliance exercise.

Second, accountability must extend beyond banks. Australia’s Scams Prevention Framework requires banks, telecommunications providers, and digital platforms to implement anti-scam controls or face financial penalties of up to AUD 50 million (INR 344 crore). Fraud prevention cannot stop at institutional boundaries because fraud crosses them.

Third, fraud detection must become collaborative. India’s MuleHunter.AI initiative demonstrates that mule account detection at the network level is technically feasible. Patterns visible to one institution can become actionable across the system before funds disappear.

No fraud-detection system can fully distinguish coercion from legitimate urgency in real time, especially in a country processing billions of low-friction digital transactions. However, that cannot justify a system where institutions face little consequence for failing to act on visible warning signs.

The Madhya Pradesh teacher could not have known the voice on the call was fake. The institutions around her knew more than she did. The question is why none of them were required to act on it.

This was first published in “Mid Day” on 3rd August 2026.

Affordable housing finance: Addressing the last-mile challenge

Posted on by harshita

India’s affordable housing challenge is often measured by the number of homes built or sanctioned. While these metrics matter, they reveal only part of the story. The more fundamental question is whether households can access formal finance to build, purchase, or improve their homes. For millions of low- and moderate-income (LMI) families, the challenge extends beyond housing availability. They also need affordable, adequate, and timely housing finance. 

Financial institutions generally consider housing loans among the safest lending products because tangible collateral backs them, and delinquency rates have remained relatively low. Affordable housing finance (AHF), however, presents a far more complex picture than conventional housing loans. Lenders must adopt a different approach for economically weaker sections (EWS) and lower-income group (LIG) households. Success depends not only on the underlying asset but also on a clear understanding of the borrower. Lenders must assess household income, seasonal income fluctuations, employment patterns, housing aspirations, social and economic constraints, financial behavior, and repayment capacity. These factors carry as much weight as product pricing and collateral when lenders design sustainable and affordable housing finance solutions. 

The need to expand access to AHF is especially important because India’s housing challenge remains significant. India’s Supreme Court recognizes access to safe and adequate housing as part of the fundamental right to life under Article 21 of the Constitution. The country continues to face a substantial urban housing deficit. Current projections estimate a shortage of 31.2 million units by 2030. Other methodologies estimate a deficit of 50 to 70 million units, as nearly 95% of this shortage affects EWS and LIG households.  

These families face housing constraints due to affordability issues and structural barriers that limit access to the formal financial system. Many earn irregular incomes through self-employment, casual labor, or informal occupations. Their incomes fluctuate across seasons, which makes conventional income assessment difficult. Many also lack clear property records, land titles, or income documentation. Limited or non-existent credit histories further reduce access to formal housing finance, even when households are both willing and able to repay. As a result, many households with genuine housing needs remain outside the reach of institutional finance. 

The evolution of India’s housing finance ecosystem partly explains this financing gap. Historically, India’s housing approach remained supply-driven and state-centric. After Independence, public agencies led housing construction, while housing finance and private sector participation received limited attention. During the liberalization era of the 1990s, housing finance companies emerged as specialized lenders and expanded housing credit. However, they primarily served middle- and upper-income households, namely prime and near-prime borrowers. These borrowers could easily provide formal income documentation, posed lower credit risk, and offered stronger commercial returns. As a result, many lower-income households continued to rely on informal borrowing, incremental self-construction, or delayed housing investments. 

Over the past decade, public policy has sought to address this imbalance. A major shift occurred in 2015 with the launch of the Pradhan Mantri Awas Yojana (PMAY). The program shifted government strategy from housing construction to a broader housing ecosystem. PMAY introduced demand-side support through the Credit-Linked Subsidy Scheme (CLSS), which enabled beneficiaries to access institutional finance with interest subsidies. The program also repositioned the government from a housing provider to an enabler of housing finance through subsidies and institutional support. 

The results have been significant. As per data from 2026, under PMAY-U and PMAY-U 2.0, 12.7 million houses have been sanctioned, while 12.0 million houses have been grounded for construction, and 9.86 million have been completed and delivered to beneficiaries. Under PMAY-Gramin Phase I and II, states have received allocations for 41.5 million houses, sanctioned 39.0 million, and completed 29.9 million. Regulatory reforms, including revisions to priority sector lending (PSL) norms, have also expanded eligibility for affordable housing loans. Yet, policy support alone cannot address the structural barriers that continue to exclude lower-income households from formal credit. 

Affordable housing has received greater policy attention, while revisions to PSL norms have expanded eligibility to reflect changing property prices across geographies. Together, these measures recognize that better housing outcomes require better access to housing finance. Yet, policy support alone cannot close the financing gap. Greater access to affordable housing finance requires solutions that address structural, behavioral, and documentation barriers, which continue to exclude many lower-income households from formal credit. 

The AHF ecosystem relies on a diverse mix of institutions. Public-sector banks account for nearly 46% of the market, followed by housing finance companies at 29% and private-sector banks at 22%. At the same time, specialized affordable housing finance companies (AHFCs) have emerged as an important segment. This shift reflects the growing demand for lenders that serve customers excluded from mainstream housing finance. 

However, greater market access requires more than conventional lending approaches. Affordable housing finance cannot rely solely on household income or collateral value. Lenders must also understand housing aspirations, affordability thresholds, financial behavior, property ownership patterns, documentation readiness, and the broader housing supply ecosystem. Traditional underwriting models often fail to assess borrowers with irregular, seasonal, or self-employment income. Street vendors, transport operators, artisans, contractors, shopkeepers, and other informal workers often demonstrate stable earning capacity over time. Yet, their cash flows rarely fit salary-based assessment models. Effective, affordable housing finance, therefore, requires lenders to complement collateral-based underwriting with cash flow assessments and a deeper understanding of household financial resilience. This approach supports prudent risk management and expands access for underserved segments. 

Documentation also presents a major challenge. Unclear property ownership records, incomplete 13-year title chain documents, procedural complexity, and lengthy verification processes prevent many creditworthy households from accessing formal housing finance. Greater credit access, therefore, requires better loan products, simpler customer journeys, streamlined documentation where feasible, and operational processes that reduce friction throughout the lending cycle. 

Affordable housing markets are also highly local. Housing demand, construction activity, income levels, employment patterns, housing loan penetration, and repayment capacity vary across districts and states. A market with a large housing shortage may not offer the strongest lending opportunity if household incomes remain unstable or local credit ecosystems lack maturity. In contrast, economically stronger regions may show lower unmet housing demand. Lenders must therefore balance housing need with credit opportunity and economic stability instead of relying on a single indicator. 

The decision to buy, construct, or extend a house is shaped by a complex interplay of household needs, aspirations, family dynamics, and financial capacity. Once this decision is made, households must determine how to finance, as housing finance is usually their largest lifetime investment. At this stage, understanding borrowers becomes equally important. Trust in financial institutions, awareness of formal financial products, confidence in their ability to repay, previous borrowing experiences, and intra-household decision-making all influence whether households seek formal finance, the type of financing they choose, and the terms they are willing to accept. Gender roles, social networks, interactions with intermediaries, and perceptions of lenders also influence borrowing behavior. Treating LMI households as a single customer segment overlooks these vital differences. Evidence-based product design should therefore combine quantitative market analysis with a qualitative understanding of customer behavior. Market size estimates, affordability analysis, demographic profiles, and housing demand projections provide a strong foundation for eligibility assessments. These insights become more valuable when lenders also understand borrower motivations, financial decision-making, documentation challenges, and local market conditions. Together, these perspectives support stronger product design, underwriting frameworks, operational processes, and customer engagement strategies. 

These complexities have reshaped credit assessment across the sector. AHFCs now use AI-powered analytics and alternative data sources to evaluate informal sector borrowers. Lenders assess utility payment records, mobile usage patterns, and social data to evaluate customers without traditional credit histories. This approach expands market reach while improving risk management in underserved segments. Market leaders also adopt hybrid “phygital” distribution models that combine digital capabilities with physical presence. They establish micro-branches in Tier-II and Tier-III cities to deepen market penetration while maintaining personal interactions. Physical presence remains essential for accurate credit assessment and relationship-building, where digital literacy and formal documentation are limited. This model allows lenders to scale without compromising underwriting quality. 

The implications of the affordable housing finance ecosystem extend beyond individual lenders. As India continues to urbanize and housing demand grows, financial institutions must adopt business models that balance commercial sustainability with a deeper understanding of customer realities. Products designed only around institutional processes may fail to serve households whose financial lives fall outside conventional lending models. In contrast, institutions that understand informal income patterns, housing journeys, local markets, and customer behavior are more likely to develop scalable and inclusive products. India’s affordable housing challenge also presents one of the country’s largest opportunities for financial inclusion.India’s affordable housing challenge extends beyond building more homes. It also requires households to access the finance needed to purchase, construct, or improve them. However, affordable housing finance requires more than sanctioning additional loans. It will succeed when formal finance reaches families historically excluded from the financial system and reflects the realities of their lives.  

Lenders must move beyond collateral and compliance and adopt evidence-based product design, customer-centric underwriting, and operational models that reflect the realities of LMI households. Such an approach enables affordable housing finance to bridge the gap between housing need and home ownership while ensuring commercial viability and social meaningfulness. 

Design principles for effective digital financial capability

Posted on by Srijan Paul

MSC’s (MicroSave Consulting) digital financial capability (DFC) framework offers a practical approach to designing financial capability policies, programs, and digital solutions. Its five design principles seek to understand target segments, create innovative content, balance delivery channels, coordinate stakeholders, and embed impact-oriented monitoring and evaluation. This framework shows how governments, regulators, and financial service providers can move beyond awareness campaigns to achieve measurable behavior change, safer digital financial use, and stronger consumer protection.  

Roadmap to the HPFD gender budget statement 2027–28 based on field diagnostics

Posted on by harshita

Gender-responsive budgeting (GRB) is a key public financial management tool that helps governments integrate gender considerations into planning, budgeting, and resource allocation. India has institutionalized GRB through gender budget statements and supporting policy frameworks. However, many line departments still face challenges that limit implementation due to gaps in institutional systems, administrative data, and reporting mechanisms.

Under the GIZ-supported Strengthening Gender Responsive Forest Ecosystems Management and Agroforestry in India (G-VAN) project, MSC worked with the Himachal Pradesh Forest Department (HPFD) to strengthen its institutional readiness for GRB. The engagement included reviews of departmental schemes and budgets, field diagnostics, assessments of institutional mechanisms and administrative data systems, and consultations with key government stakeholders.

This report presents a practical roadmap to prepare HPFD’s gender budget statement and institutionalize GRB within the department. It identifies implementation gaps, recommends measures to strengthen gender-disaggregated data and institutional processes, and shows how the department can embed GRB across the budget cycle, from planning and resource allocation to implementation, monitoring, and reporting.

As Digitalization Grows, Will Indonesia’s Agent Networks Survive?

Posted on by harshita

Indonesia is Southeast Asia’s largest digital economy, poised to reach $180 to $340 billion by 2030—by all measures a success story of rapid digital growth. Yet, even as digital transactions surge, Indonesia’s vast informal sector holds on to cash as a central aspect of daily life. Despite the expansion of digital payments, cash in circulation has more than doubled over the past decade to reach approximately $65 billion as of July 2025.

Agents move between the digital and cash economies

At the heart of this coexistence are millions of local agents who make the digital economy work for everyone. Many of them are small business owners who operate from kiosks and local shops called warungs, serving as trusted financial intermediaries that connect communities to banks, payments and other digital products that would otherwise remain out of reach.

As the number of bank branches and ATMs in the country has declined by 25% over the past five years, the number of agents has grown by about 40% annually over the past decade, according to MSC estimates. By 2025, there were more than 2 million registered agents nationwide. While only about one-third of agents remain consistently active, they form a cornerstone of Indonesia’s financial inclusion efforts, serving as the primary channel for FSPs to reach last-mile communities.

Global Findex 2025 data shows that only 30% of Indonesian adults conduct payments independently through self-service channels, such as mobile applications, cards or online platforms, indicating that most people still depend on assisted channels for financial transactions. This continued reliance is reflected in agents’ growing activity, as transaction values continue to increase. Between 2017 and 2023, cash-out transactions rose by 43% and the average transaction volume through agents grew five-fold.

However, as Indonesia’s digital economy grows, individual access to digital channels continues to deepen. Cellphones now reach 68% of the population, and 72% have internet access. Cashless transactions, particularly through Indonesia’s interoperable QR code payment system (QRIS), have been growing at a rate of more than 150% year-on-year. As more people begin to transact independently through mobile and internet banking, a critical question emerges: will agents remain relevant?

How are agents faring in other digital economies?

Globally, digital growth has yet to replace cash, and agents keep the two worlds connected. We see this even in the world’s largest and fastest-growing digital payment ecosystems, such as India and Kenya.

In Kenya, one of the global pioneers of mobile money, cash in circulation continued to climb by $2.6 billion in 2024, a 5.6% increase from the previous year. Meanwhile, agents facilitated mobile money transactions worth $67.3 billion in 2024, nearly double the level recorded in 2019.

In India, the Unified Payments Interface (UPI) – a real-time platform that enables instant fund transfers between bank accounts – has driven a surge in digital payments. UPI transaction volumes increased tenfold in just four years, from 12.5 billion in 2020 to 131 billion in 2024, to account for nearly 80% of all digital payments. At the same time, cash in circulation has more than doubled from $200 billion in November 2016 to reach $418 billion by September 2024, with SBI, India’s largest bank, channeling approximately 3.2 million transactions per day through its agent network.

These examples reveal that even in highly digitalized markets, assisted channels remain essential, suggesting that digital and agent ecosystems will coexist for years to come.

Agents in Indonesia adapt to a dual cash-digital system

Indonesia mirrors this global reality. The strength of its agent model lies in its adaptability to a dual cash-digital system. What began as a simple cash-in, cash-out function has gradually expanded in scope. While not all agents can offer advanced services, many have started to diversify and now sell digital products, offer loans and microinsurance, facilitate QRIS payments, and even serve as delivery or return points for e-commerce.

Traditionally, agents have been vital to enable government-to-person (G2P) transfers and ensure cash reaches low-income households efficiently. Building on this foundation, many agents are now becoming the frontline for financial service providers (FSPs) to deliver more specialized financial products, such as microloans, savings, and climate-risk insurance, helping strengthen rural economies and household resilience.

Agents’ adaptability has built both structural and economic resilience. Agents are not competing with Indonesia’s rapid digitalization; they are powering it. Rather than being displaced by fintechs and mobile banking apps, they form the human infrastructure that makes digital services accessible and trustworthy, especially in areas where cash use is prevalent and digital literacy is low.

Agents remain the bridge between digital systems and communities

The shift toward digital finance in Indonesia is well underway, but agents will remain the critical bridge that connects digital systems to communities. As the ecosystem matures, stakeholders in the ecosystem should now shift their focus from expanding agent coverage to strengthening their capabilities, which would enable them to manage more complex, higher-value transactions and provide greater value to customers.

Providers can support this evolution if they invest in advanced training, streamlined business processes, and data-driven, AI-enabled, tools for effective agent management. Even as technology transforms financial services, the human presence and local trust that agents bring will remain essential to ensuring that Indonesia’s digital finance is both inclusive and scalable. The future of finance is digital, anchored by the agents and their customers who make it work.

This was first published on 28th January 2026 by FinDev Gateway.