In emerging markets, digital banks like TymeBank have shown what’s possible with scalable onboarding. In just under six years, TymeBank reached 10.7 million customers by December 2024, growing from 8.5 million in December 2023 at an average rate of 150,000 new customers per month, and became the first digital bank in Africa to achieve profitability—cementing its position as South Africa’s fastest-growing bank in 2024. However, as these institutions grow, they face new challenges. The focus must shift from merely acquiring customers to managing the complex risks that accompany rapid expansion. 

Success in these markets hinges not only on growth but also on maintaining a careful balance between expansion and risk management. Achieving this balance demands more than just cutting-edge technology; it requires a deep understanding of the local environment and the ability to apply sophisticated analytics that respect the nuances of each market. 

In more mature markets such as the EU, digital banks benefit from established infrastructures, abundant public data and reliable credit histories, making onboarding relatively straightforward. However, in developing nations, the transition from traditional to digital banking introduces a host of challenges, particularly in onboarding customers who might not have formal financial histories. With approximately 1.4 billion people globally remaining unbanked, predominantly in developing markets, the need for inclusive digital banking solutions is urgent. 

While scalable and adaptable onboarding frameworks are essential, the real challenge lies in managing the available data —or in many cases, the lack thereof. Leveraging alternative data sources, such as mobile phone usage or utility payments, can provide insights into a customer’s financial behaviour. But that’s just the beginning. The real challenge is ensuring this data is properly contextualised to fit the unique socio-economic environments of these markets. 

Leveraging alternative data holds great potential, but it comes with its own set of challenges. Raw data from these sources needs to be carefully cleaned, verified and contextualised for each specific market. This is no easy task—it requires both technical expertise and a deep understanding of local economic behaviours. If not handled properly, the risk models can be significantly off—either rejecting good customers by overestimating their risk or increasing exposure to defaults by underestimating it. 

What’s clear is that a one-size-fits-all approach to risk management simply won’t suffice in such diverse and dynamic markets. Instead, digital banks should adopt a tiered risk assessment model that adjusts based on real-time indicators. For instance, an initial, basic risk assessment beyond the standard KYC/AML checks might be sufficient to grant access to essential banking services. Then, as more data is gathered and the relationship with customers deepens, more detailed risk assessments can be applied. This approach ensures that people aren’t excluded just because the data is limited upfront, while still managing risk effectively as more insights are gained over time. 

One of the most pressing challenges in developing markets is the rapid and often unpredictable shifts in customer behaviour, frequently triggered by economic fluctuations or external shocks. To effectively manage this, banks must move beyond traditional, static models and adopt real-time adaptability. This is where continuous monitoring systems, powered by AI, become essential. These systems can analyse transaction patterns, spending habits and other real-time data, allowing banks to adjust risk models dynamically and update customer profiles or KYC procedures as circumstances evolve. 

In environments where economic conditions can shift overnight, relying on static risk models can result in misguided decisions. By leveraging a real-time, AI-driven approach, banks can stay ahead of these changes, ensuring that their risk assessments remain accurate and timely. This level of adaptability is vital for successfully navigating the complexities and uncertainties inherent in these markets. 

Security is a critical concern during the onboarding process, particularly in developing markets where identity fraud poses a significant risk. Traditional verification methods may fall short in these environments. Incorporating biometric authentication—such as facial recognition or voiceprints—can significantly enhance security and reduce the risk of fraud. This not only strengthens security measures but also ensures compliance with local regulatory requirements by making everything transparent and easily auditable. 

The future of digital banking in developing markets will heavily depend on the ability to build and maintain strong collaborative ecosystems. Financial institutions must work closely with fintech companies, telecom operators and local governments to create a comprehensive financial infrastructure. Each partner contributes unique strengths: fintechs bring advanced analytics and risk management tools, telecoms offer essential mobile data and governments can align these efforts with broader economic and social policies. 

By working together, these stakeholders can develop a financial system that is both scalable and sustainable. There is also significant potential to create new financial products tailored to the specific needs of underserved populations—such as microloans, savings plans, and insurance policies designed for low-income individuals. This collaborative approach not only drives financial inclusion but also supports sustainable economic growth by empowering individuals and communities. 

For digital banks in developing markets, financial inclusion is not just an opportunity—it’s essential for growth. Scaling customer acquisition is critical, but it’s only part of the solution. The real challenge is striking the right balance between expansion and effective risk management. 

At Elixirr, we recognise that addressing today’s challenges is only the beginning. Notably, TymeBank’s achievement of profitability in December 2023, in under five years, places it among the less than 5% of neobanks worldwide to reach this milestone, outpacing global peers like Nubank (8 years) and Monzo (7 years). For long-term success, digital banks must strategically leverage emerging technologies—not just to keep pace, but to lead the way. AI-driven decision engines and adaptive machine learning models can now automate onboarding flows, flag anomalous behaviour in real time, and evolve with changing risk patterns—making them indispensable in dynamic markets. At Elixirr, we partner with financial institutions to implement AI-driven solutions, advanced analytics, and adaptive risk management frameworks, enabling digital banks to scale inclusively while navigating complex market dynamics. 

Expanding access to financial services is critical, but it’s the ability to do so sustainably, securely and equitably that will truly set successful banks apart. Those that can navigate this balance effectively will not only achieve growth but also play a significant role in shaping the future of the financial landscape.