Data and Intelligent Risk Models Can Expand Financial Access in Emerging Markets’- Anthony Okolo
In many emerging markets, the story of financial inclusion is often told through the rise of mobile money and payment apps. Transactions are easier than ever, yet millions of people still cannot access credit, savings, or insurance in any meaningful way. The core challenge is simple: traditional financial systems were built for customers with payslips and formal histories, not for traders, drivers, artisans, or farmers whose economic lives sit outside standard templates.
Anthony Okolo, a Nigerian-born product and technology strategist, the problem is not the absence of activity, it is the absence of structured insight. “A payment trail only tells you one part of a person’s financial reality,” he notes. “To lend confidently, you need context, how people earn, spend, trade, and manage shocks over time.”
Working across fintech and digital services, Okolo focuses on building intelligent risk models for underserved segments. His work combines mobile money records, agent and merchant transactions, informal credit patterns, and basic behavioral signals into scoring engines that are transparent enough for both lenders and regulators to understand. The goal is not to overcomplicate risk, but to turn scattered data into decision-ready information.
What distinguishes Anthony Okolo’s approach is the use of segmented risk frameworks. Rather than relying on one-size-fits-all scorecards, he works with institutions to design models around distinct customer groups, farmers, ride-hailing drivers, small retailers, based on how each actually earns and absorbs risk. This level of segmentation helps reduce default rates, improve underwriting precision, and open up profitable but previously overlooked customer segments.
“Risk intelligence is not about excluding people,” Okolo says. “It’s about understanding them clearly enough to serve them responsibly and sustainably.”
Banks, insurers, and fintech operators are beginning to recognize the value of this shift. By converting fragmented data into clear risk layers, Okolo’s frameworks support the rollout of products such as micro-credit for merchants, asset finance for drivers, seasonal loans for farmers, and simple safety nets for low-income households. Instead of guessing who is “risky,” institutions can price and structure products with far greater confidence.
As investors and policymakers search for growth beyond saturated markets, one lesson is becoming obvious: payments alone will not deliver inclusion. Intelligent risk and data systems must sit underneath. In that quiet but critical layer, the work of practitioners like Anthony Okolo points toward a more honest and evidence-based way to extend finance to the people who have long been active in the economy, but invisible to its formal systems.
