Banks and financial institutions in emerging markets could be turning away significant commercial opportunities. This is usually due to an oversight in how most of them assess or judge credit, as well as the traditional mindset that has evolved and been adopted over time.

The credit frameworks that most institutions use were built for mature and developed economies decades ago. These frameworks depend on bank statements, payslips and credit bureau files. They use formal policies, traditional datasets and processes that are built for a different business environment, and they exclude by consequence, not by intention.

In mature markets, these tools work well. But businesses in emerging markets depend on different norms: small merchants can remain stable without audited accounts, informally employed delivery riders can be paid in physical cash, and even profitable firms can sustain themselves without bank loans.

Despite making up a large part of the market, they all share one thing: they cannot be scored using traditional datasets or a decision outcome derived using developed market credit tools, policies or processes.

Fortunately, the right data models, policies aligned with the conditions of an emerging economy, and digitally enabled processes can resolve that. A previously unreadable credit picture can turn into a chance for banks and financial institutions to serve a large, growing market.

Who traditional credit tools are leaving out

1.3 billion adults worldwide remain unbanked. More than half are concentrated in just eight economies, many of them in the developing world, including Nigeria and Indonesia.

To institutions using traditional credit frameworks, these individuals appear as outliers. In reality, these are far from fringe cases. They are simply how emerging markets work.

Informal workers, market traders and small merchants are key players in these economies. They earn consistently, reinvest in local economies and generate visible transaction patterns, none of which appear on a payslip or a balance sheet. Even with variable incomes, their financial behaviour is stable. Traditional credit frameworks were never designed to read it.

Why traditional credit tools produce the wrong answer

Conventional credit decisioning assumes a stable salary, formal employment, and a documented identity for consumers, as well as audited financials or management accounts for SMMEs or merchants.

In emerging markets, those assumptions describe a minority of borrowers, while excluding most potential, financially stable clients. Bureau data, payslips and tax records, where these inputs exist, provide a credit risk assessor something to work with. Where they don’t, the model has nothing, and the process fails.

Without those inputs, models don’t return a negative score. They return no score or a cautious estimate that leads to a high probability of default risk or even inadequate affordability.

A lack of credit bureau records does not mean a borrower has poor credit. Most traditional models do not distinguish between the two cases.

This is a gap in data misread as a risk. The absence of traditional indicators is treated as exposure, and the cost of that mistake falls on both borrowers and banks.

The hidden costs of misreading the signal

For borrowers, exclusion from credit means more than a declined application. It limits economic mobility and the ability to create wealth. Across the mass market, this exclusion of consumers, informal merchants, micro-enterprises constrains the growth these participants would otherwise produce.

Take a micro-enterprise hit by a supply shock. Access to small, short-term credit can mean the difference between absorbing the shock and closing the doors. Multiply that one moment by the size of the mass market, and the stakes become clear.

For banks and financial institutions, the cost is missing out on some of the fastest-growing consumer markets in the world. McKinsey projects that 250 million Africans will join the consuming class by 2030, unlocking US$3 trillion in consumer spending. Institutions without a mass market strategy are positioned to miss a material share of it.

The institutions that solve the decisioning problem first will have a structural advantage in markets their competitors cannot yet read.

Adopting a more accurate model

Most borrowers in emerging markets don’t have a credit file. They have a phone. In these markets, mobile penetration far exceeds formal banking penetration. This gap is an opportunity. Mobile-derived data is one of the richest inputs available for assessing risk, and it is already in active use by nearly every potential borrower.

Regular airtime top-ups, on-time utility payments, steady mobile money activity: none of this shows up on a payslip or a bureau file, but all of it reflects financial discipline in a way that can be measured and assessed accurately.

Merchants and SMMEs leave a different trail: supplier payment patterns, mobile point-of-sale transaction history, inventory cycle behaviour. The data exists. It has simply never been used this way before.

Modelled correctly, these signals turn a segment that looked opaque into one that is legible. The risk profile looks materially different from what traditional tools suggested.

Gain a deeper, complete picture with Ezra

Ezra’s credit modelling capability and exposure management framework are built for emerging markets where traditional data is sparse and conventional frameworks fall short.

Using non-traditional data inputs, it produces a clear picture of a borrower’s actual credit risk and affordability across multiple products through one integration. Each additional product improves the accuracy of the overall credit picture over time.

For banks and financial institutions, working with Ezra means accurate visibility into a segment they were previously assessing with limited insight. That visibility translates directly into new lending opportunities, stronger customer relationships and a foothold in markets that are only going to grow.

The opportunity already exists. The question is whether you have the tools to see it.

To discover emerging market opportunities with Ezra, reach out to our team.