Micro, Small, and Medium Enterprises (MSMEs) are a critical part of Nepal's economy, contributing more than 90% of industrial GDP and approximately 70% of total national exports. Yet, despite their economic importance, access to formal finance remains a persistent structural challenge.
According to the World Bank, Nepal faces an estimated US$6 billion MSME financing gap, equivalent to approximately 14% of GDP.
The numbers reveal the scale of the challenge:
The challenge isn't simply a lack of capital. Traditional lending models can make it difficult for many small businesses to demonstrate their creditworthiness. Limited financial records, insufficient collateral, short operating histories, and gaps in formal credit information can all restrict access to loans.
But there is another source of information that lenders can increasingly use: the data businesses generate through their everyday financial activity. Digital payments, transaction histories, cash flows, and other business-related information can provide lenders with additional signals for assessing credit risk.
This raises an important question:
Can data-driven lending help Nepal move beyond the traditional loan application and build a more accessible MSME financing ecosystem?
For years, lending decisions have relied on financial statements, collateral, credit history, and information provided in loan applications. But businesses generate far more financial data through digital payments, bank transactions, supplier payments, customer receipts, and repayments.
When these signals can be accessed, verified, and analyzed responsibly, they can provide lenders with a more dynamic view of business performance.
Data-driven lending is therefore not about replacing traditional credit assessment. It is about moving from a static view of the borrower to a more data-informed view of the business.
And Nepal is beginning to create the regulatory and financial infrastructure that can make this approach increasingly possible.
Two developments are particularly relevant.
In June 2026, Nepal Rastra Bank amended its Digital Lending Guidelines, increasing digital lending limits for MSME working capital to:
The revised framework also permits lenders to incorporate electronic transaction histories, payment records, and other business-related data into digital credit assessment.
This represents an important shift.
Credit assessment does not necessarily have to rely exclusively on traditional documentation. The financial activity of a business can itself become part of the evidence used to understand its ability and willingness to repay.
Nepal is also investing in the infrastructure needed to make broader credit access possible.
The World Bank’s $95 million Sustainable and Inclusive Finance project is designed to strengthen risk-sharing and credit-information infrastructure, including broader data coverage and the use of alternative data sources.
Together, regulatory changes and infrastructure investment can create an environment in which digital credit assessment becomes increasingly practical.
Around the world, financial institutions and fintech companies are already demonstrating how digital data can change the way credit is assessed, delivered, and scaled. And Nepal can also learn from markets where these models are already being implemented at scale.
International examples show that alternative-data lending is not a single model. Different markets have used digital information in different ways, depending on their financial infrastructure, customer behavior, and regulatory environment.
Four examples illustrate four mechanisms that are particularly relevant to Nepal.
Indonesia’s Amartha uses machine learning and more than 800 variables, including behavioral, transaction, and demographic data, to broaden credit assessment. The key principle is that more relevant and reliable information can provide a more nuanced view of borrower risk. For Nepalese MSMEs, this could mean combining traditional financial information with verified transaction and behavioral data to assess how a business actually operates, beyond collateral and documentation alone.
Bangladesh’s bKash app and City Bank demonstrates the potential of embedded lending. By July 2026, digital nano-loans through bKash had surpassed Tk 10,000 crore in cumulative disbursements across 3.5 million customers. For Nepalese MSMEs, a similar model could integrate working-capital financing directly into banking, payment, or business platforms, moving from a document-heavy application process toward lending based on ongoing transaction activity.
India’s KreditBee illustrates how digital underwriting can make high-volume, smaller-value lending more efficient. By 2026, it had facilitated more than 60 million loans for over 18 million customers. For MSMEs, this is particularly relevant because financing needs are often modest but recurring. Digital onboarding, credit assessment, decision-making, and servicing can potentially make these smaller working-capital facilities more viable for lenders.
Brazil’s Nubank demonstrates a shift from individual credit decisions toward continuous financial relationships. Its Nu Empresas platform reached 6 million SME customers, alongside expanded working-capital and cash-flow products. The model recognizes that SME finances change continuously, allowing lenders to use updated revenue, expenses, transactions, and cash-flow data to better understand evolving financing needs rather than assessing creditworthiness only at a single point in time.
Nepal already has many of the building blocks required for this transition. Digital payment adoption is expanding. Businesses are generating transaction histories. BFIs already maintain relationships with millions of customers. Regulatory changes are creating greater room for digital credit assessment. And investments in credit-information infrastructure are improving the foundations for data-driven lending.
The opportunity for BFIs is therefore broader than simply digitizing the loan application. It is to turn the information already generated across the financial ecosystem into repeatable underwriting, embedded credit and scalable distribution.
The next generation of MSME lending may not be about digitizing the loan application. It may be about redefining how creditworthiness itself is understood. The future of MSME lending isn't simply digital. It is data-informed, continuously assessed, embedded in everyday financial activity, and distributed at scale.
Jun 23, 2026
May 25, 2026
