The rules of traditional credit have never truly favored the informal worker, and in a system still dominated by payroll structure and employment contracts, millions of people earning income through digital gig work remain invisible. They’re not on payroll, they don’t have fixed monthly salaries, and their job titles may change every week. But their work is real, their earnings are steady in many cases, and their need for credit is just as legitimate.
The structure of the global economy is shifting. More people are working short-term contracts, freelancing, and relying on digital platforms to earn a living. In places like India, Brazil, and across much of Africa, this shift is even more pronounced. In 2023, the World Bank estimated that over 36 percent of U.S. workers engaged in some form of gig work. This trend is even more dominant in emerging markets, where informal work is often the default.
Yet, despite the growing importance of this segment, the credit system has barely changed. The gap between how people earn and how they are evaluated for credit has widened, leaving many behind.
A growing gig economy that remains financially invisible
The gig economy has experienced rapid global growth over the last decade, becoming a core part of how people work and earn across borders. In 2018, it was estimated to contribute over $200 billion in gross sales. Mastercard’s projections suggested that figure could rise to $300 billion by 2023, with developing regions driving a significant portion of that momentum. This is especially evident in Africa, where the proliferation of smartphones, affordable internet, and widespread use of digital platforms has transformed the way people access work.
Platforms like Uber and Bolt now provide flexible transport jobs across urban centers. Services like SweepSouth are linking domestic workers with homes in need of their support. Gig-based delivery jobs on platforms like Glovo are now commonplace in major cities. On the digital side, freelancers are finding work on international platforms like Upwork and Fiverr, handling everything from graphic design to customer service. For many, gig work is not just a temporary hustle but a main source of income. It’s offering an escape from unemployment and the chance to build a livelihood on their own terms.
But while participation in the gig economy has grown, financial visibility has not kept pace. Many gig workers across Africa are still excluded from the financial system. Applying for credit remains a difficult process, and rejection is common. It’s not because they earn too little or are unwilling to pay back loans. In most cases, the problem is that their incomes and work patterns do not fit into the rigid boxes used by traditional credit systems. Gig work often lacks pay slips, formal contracts, or predictable earnings, criteria that banks and even some digital lenders still prioritize.
This mismatch between how gig workers earn and how lenders assess creditworthiness is at the heart of the problem. As a result, thousands of hardworking individuals remain financially invisible, despite participating in an economy that’s very much alive and growing.
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Why gig workers get rejected for loans
For decades, the foundation of most lending models has rested on predictability. Lenders look for a stable salary, a confirmed employer, and a formal credit history. These markers are seen as proof that someone will repay a loan. But gig workers operate in a completely different rhythm. Their lives are filled with short-term contracts, flexible hours, and income that changes weekly, sometimes daily. This fluidity often gets mistaken for financial risk.
Consider the day-to-day of a typical gig worker. They may spend mornings driving for Bolt, afternoons running errands on Gokada, and weekends completing freelance projects on Upwork. Each task pays something different. Some pay through mobile money platforms, others through international payment gateways, and sometimes even in cash. At the end of the month, their earnings might equal or exceed that of a full-time employee. But because the income is spread across different channels and lacks formal documentation, it doesn’t register cleanly on the systems that banks and lenders use.
The issue goes deeper than job type. It comes down to how financial institutions collect and interpret data. In many African countries, credit bureaus are still building out their coverage. Their data sources are often limited to traditional financial behavior like loan repayments, utility bills, salary credits, and bank statements. Gig workers don’t always participate in this version of the economy. Many don’t have long-standing bank accounts. They rely on mobile wallets and digital tools to receive payments, make purchases, and send money. Yet, most of that activity never makes it into a credit profile.
There’s evidence to back this up. In 2022, FSD Africa conducted a study that found over 65% of Kenya’s boda-boda riders and digital freelancers were rejected for loans. This was despite the fact that many of them had active mobile money accounts with regular transactions. The problem wasn’t a lack of income. It was a lack of visibility. The systems used by lenders couldn’t see the full financial picture.
This lack of visibility has serious consequences. When traditional lenders turn them away, many gig workers are left with two choices: go to informal lenders who charge high-interest rates, or use digital loan apps that often come with short tenures and strict repayment penalties. Some get trapped in cycles of borrowing just to survive, while others miss opportunities to invest in tools, licenses, or training that could improve their earning potential. The system’s narrow definition of creditworthiness keeps locking them out.
Volatility, patchy data, and misconceptions
A major hesitation lenders have when it comes to gig workers is income volatility. Earnings in the gig economy are tied to how many tasks are completed, customer demand patterns, and the internal dynamics of the platforms themselves everything from app visibility to customer ratings can affect a worker’s income in any given week. This unpredictability tends to raise red flags. But the issue isn’t that gig workers earn too little or too inconsistently to qualify for loans. The real problem is that lenders lack the tools to understand and interpret the patterns behind the numbers.
Most lending models are built around formal employment, where salaries are fixed and income flows in like clockwork. In contrast, a gig worker’s income may ebb and flow depending on how much time they work, what platform they’re on, or whether they’re dealing with a strike or policy change. These fluctuations can be misread as personal instability or irresponsibility, when in fact they’re often reflections of how the platforms operate or how demand shifts seasonally. Without context, lenders are left to guess what’s happening in a borrower’s financial life, and that guess often leans toward rejection.
What makes this worse is how poorly data is collected and shared across the gig ecosystem. Platforms like ride-hailing apps, delivery services, and freelancing marketplaces sit on a wealth of behavioral and financial data. They know how many jobs a worker completes each day, how many hours they log, how quickly they respond to requests, what customers think of their work, and how much they earn over time. All of this could help build a clearer, more accurate picture of a worker’s financial habits. But much of that data isn’t collected in a structured way, and when it is, it’s rarely made available to lenders in a usable format.
There’s also no industry-wide practice for sharing or standardizing this data. One platform might track job completion rates, another might focus on customer feedback, while a third may do very little beyond processing payments. With no clear baseline, even lenders who want to experiment with alternative data struggle to compare gig worker performance across platforms. Add to that the issue of data privacy, commercial competitiveness, and regulatory ambiguity, and the result is a fragmented system where everyone loses, especially the worker.
Even when income data is available, it only tells part of the story. A worker might earn well during a particular month, but that snapshot doesn’t reveal their financial obligations, debt burden, or access to emergency funds. On the flip side, a worker with modest earnings might be disciplined with savings, debt-free, and financially responsible in ways that aren’t visible through raw numbers. Financial health is made up of patterns: how people save, spend, repay, and adapt. But current assessments continue to focus on narrow indicators, and in doing so, they miss out on the fuller picture.
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Financial inclusion doesn’t always translate into credit inclusion
Over the last decade, many developing countries have made significant progress in expanding financial inclusion. Mobile money, digital wallets, and simplified account opening procedures have opened up financial access to millions. The pandemic pushed this even further. In Latin America alone, more than 40 million people became financially included between 2020 and 2022, many through digital accounts created to receive government assistance. Similar trends emerged in parts of Africa and South Asia, where mobile-based platforms became the primary way to receive income, make payments, and store funds. Governments, regulators, and fintechs all played a role in making this happen.
However, the reality for many gig workers is that having access to a bank account doesn’t open up the full spectrum of financial services, especially credit. In most cases, the presence of an account only serves as proof that someone exists in the formal financial system. It doesn’t offer much insight into their financial habits, income regularity, or ability to repay a loan. For lenders, this lack of insight becomes a risk they’re not willing to take. So while millions may now have accounts, many still find themselves excluded when it comes to accessing meaningful, affordable credit.
This disconnect is especially sharp for gig workers, who often operate at the edge of formal systems. They may receive payments into digital wallets, but they rarely have any formal payslips, employer letters, or salary histories. Most of their income flows remain invisible or incomprehensible to traditional lending systems. Even when those systems are digitized, the backend risk models still lean on credit history, stable employment, and verifiable income sources, which are criteria that gig workers consistently fall outside of.
And while fintech lenders have been more experimental in using alternative data, they still face challenges in collecting high-quality, standardized inputs. Many rely on basic digital traces such as SMS alerts, wallet transaction records, or phone metadata to infer creditworthiness, but these signals alone don’t always reflect repayment behavior or long-term reliability. The result is a kind of shallow inclusion, where people are technically inside the financial system but still denied the financial tools they need to build stability or take risks.
Ultimately, financial inclusion should mean more than just having an account. It should create a pathway to participate in the full economy, including the ability to access loans when needed. Until credit products are designed to fit the realities of irregular earners like gig workers, the gap between access and inclusion will persist widening over time, even as more people appear to be “included” on paper.
Karmalife and Moove: Two experiments worth watching
Despite these barriers, a few companies are pioneering models that rethink credit for gig workers.
In India, Karmalife is providing credit using alternative data from ride-hailing and delivery platforms. The startup assesses hours worked, ratings, professional conduct, and income levels to offer salary advances and microloans. Loans are tailored to the worker’s earnings and repaid directly from their platform income.
The results are promising. Workers who took loans showed higher availability for work compared to those who didn’t. Repayment rates were above 90 percent, even among borrowers with limited or no formal credit history. The data used includes not only earnings but also behavioral patterns, creating a more nuanced risk model.
Karmalife has also found that these financial services improve worker retention on platforms. Workers who feel financially supported are more likely to stay active, take more jobs, and maintain high ratings. The startup’s partnership with LenDenClub, a peer-to-peer lending platform, helped solve liquidity constraints by connecting lenders directly to these workers.
In Africa, Moove is doing something similar but with vehicle financing. Starting in Nigeria, Moove provides gig workers with cars and motorbikes based on performance data from platforms like Uber and Glovo. Once approved, workers receive the asset and repay over time through deductions from their earnings. Moove also collects driving data through sensors to track behavior, helping reduce risk and maintain asset quality.
By combining platform metrics with usage patterns, Moove builds a comprehensive risk profile. This approach allows them to offer better rates and longer repayment terms than most digital lenders. They also include maintenance, insurance, and support services to reduce disruptions and keep workers on the road.
Also read: All you need to know about alternative credit scoring
What needs to change if gig workers are going to be seen as creditworthy
Across Sub-Saharan Africa, Southeast Asia, and Latin America, formal employment is no longer the norm. Instead, work is increasingly informal, flexible, and mediated by digital platforms. The traditional indications of creditworthiness are becoming less relevant for the millions who earn through gig work. Yet, much of the credit infrastructure is still built around those outdated signs.
Fortunately, change is starting to take root. Researchers, fintech leaders, and a handful of lenders are pushing for newer credit scoring models that reflect the economic realities of informal and platform-based work. These models go beyond job titles or salaries and instead assess consistency, digital engagement, and financial behavior. Early pilots and studies suggest that when given fair access, many gig workers repay their loans just as reliably as those in formal jobs. The issue isn’t willingness, it’s recognition.
But reimagining credit scoring isn’t as simple as pulling new data sources. It requires deep care. New models must be transparent, explainable, and free of hidden bias. They must protect user privacy while remaining accurate and auditable. A scoring system that no one understands or reinforces old inequalities through new algorithms, won’t improve outcomes for anyone.
That’s why collaboration is critical. Credit inclusion for gig workers isn’t just a fintech problem to solve. It’s a systems issue, and it calls for coordinated action across several fronts:
Policymakers need to make room for the responsible use of alternative credit data, with clear safeguards around how it’s collected, used, and shared. Regulatory clarity will give lenders the confidence to experiment, without compromising consumer protection.
Fintech lenders must design scoring models that reflect the non-linear, often volatile income patterns of gig workers. These models should blend transaction histories, platform behavior, and digital interactions to paint a fuller picture of creditworthiness.
Gig platforms have an essential role too. They hold rich data on worker performance, ratings, hours worked, and task completion. If workers are given the option to port that data into credit applications, it could become a powerful tool to unlock fairer access.
The shift in how people work is already well underway. The real question is whether credit systems will progress fast enough to keep up. Millions now rely on gig work to survive, grow their income, and support their families. If the financial system continues to treat that work as invisible or unworthy, it will not only exclude an entire generation from accessing credit, it will actively undermine their financial progress. The moment to build something better is now.
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