A great advantage of tech-based financial solutions lies in their inherent ability to collect usage data and glean valuable insights into user behaviour. Imagine the wealth of information gleaned from every tap, swipe, and transaction – a goldmine for understanding the financial needs and preferences of users. 

However, in Africa, where financial inclusion is a work in progress, relying solely on this native data presents a limited picture. Here, on the vibrant continent teeming with potential, researchers must delve deeper, adopting unconventional yet effective strategies to unlock the true potential of fintech research.

While established financial markets in the US and UK boast robust credit bureau data and meticulously maintained customer information, the African landscape presents a fragmented ecosystem. Mobile money providers (MMOs), informal financial networks, and fledgling fintech platforms each hold pieces of the puzzle. Integrating and anonymising this data presents a unique challenge – a far cry from the streamlined data warehouses of the developed markets. This “data scarcity,” as some might perceive it, is precisely where the ingenuity of African researchers comes into play.

While Silicon Valley boasts populations glued to their smartphones, a significant portion of Africa’s populace, not only in the rural areas, lacks the digital literacy required for online surveys or complex mobile applications. Traditional methods, often relegated to the periphery in developer markets, become essential tools here. CAPI,  Face-to-face interviews, conducted in local dialects and steeped in cultural sensitivity then become essential; allowing for deeper understanding and nuanced data collection.

However, these very limitations nurtured creativity in a way; that we’ve become adept at exploring alternative data sources and collection methods. Anonymized mobile network operator (MNO) data, obtained with user consent, offers a rich source of insights into user behaviour and financial needs. Imagine analyzing anonymized call patterns to understand geographic distribution of financial services usage, or studying mobile money transaction data to identify underserved regions or spending habits. These seemingly mundane data points, when carefully analyzed, paint a vivid picture of the financial landscape in our kind of terrain.

Also, collaboration is a major cornerstone of success. Partnering with local research institutions, NGOs, and even telecommunication companies allows us to leverage their expertise and navigate the complexities of the African context. We go to great lengths to be transparent about data collection practices, prioritizing user privacy through robust anonymization techniques and clear communication about how data will be used. The mobile phone, a ubiquitous presence in Africa, has become a powerful tool for data collection; SMS surveys and USSD menus (interactive mobile phone menus) – a user-friendly approach perfectly tailored to the African reality. 

Culturally sensitive research design is another non-negotiable. Questionnaires must be meticulously adapted to local languages and cultural nuances to ensure accurate and meaningful data collection. For instance, a seemingly straightforward question about “income” might require significant reframing in a context where a substantial portion of the population relies on informal income sources.

This “data-scarce” environment, as some might perceive it, is an opportunity in disguise. By embracing the unique challenges and adopting innovative approaches, we can unlock a goldmine of insights. We can move beyond simply mimicking foreign models and develop a robust, inclusive fintech ecosystem built specifically for Africa’s needs.

The journey to financial inclusion across Africa is paved with unique challenges, but the rewards – a continent empowered and connected – are worth the extra effort. We, the African researchers stand ready to chart this path, armed with our ingenuity, a deep understanding of the African context, and a toolbox overflowing with unconventional yet effective data collection techniques.