Reinsurance may not make daily headlines, but it is the hidden engine behind financial stability for insurers, governments, and even disaster-prone communities.
Actuarial Scientist, Ernest Forson Aboagye, a former student of the University of Cape Coast and now a researcher at Georgia State University, has challenged the long-standing global assumptions about how insurers share risk.
His work proposes a smarter, data-driven approach to reinsurance that has already caught the attention of international scholars and could reshape how African insurers prepare for catastrophe, regulate solvency, and price protection.
In this interview, Mr Aboagye discusses the roots of his research, its real-world applications, and why it matters deeply for Ghana and the continent at large.
Can you briefly introduce yourself to our readers?
Sure. I am Ernest Forson Aboagye, a Ghanaian actuarial scientist and quantitative finance researcher. I graduated from the University of Cape Coast in 2014 with a BSc in Actuarial Science. After that, I worked there briefly as a teaching assistant, where my research interest was sparked while mentoring students and engaging with local insurance challenges. I later pursued a master’s in Mathematics in the U.S. and worked for a few years as a practising actuary across insurance and consulting firms, gaining practical exposure to pricing, pensions, and reinsurance. Currently, I’m completing my PhD in Risk Management and Insurance at Georgia State University. My work focuses on reinsurance design, financial risk modelling, and applying advanced analytics to strengthen the insurance ecosystem.
What inspired your career path in actuarial science and research?
Growing up in Ghana, I saw firsthand how financial shocks, whether from health crises, floods, or business failures, could destabilise families and communities. So, when I got the chance to study actuarial science at UCC and engage in early research, I quickly realised its potential to help people and institutions manage uncertainty using data, mathematics, and structured modelling. Research became a natural extension of that curiosity
Let’s talk about your latest study. In simple terms, what is it about?
At its core, the study challenges how insurers decide how much risk to keep and how much to pass on to a reinsurer. The current academic model utilises stop-loss reinsurance, which looks clean on paper but does not hold up in real-world insurance markets. We propose a more flexible, data-driven method based on excess-of-loss reinsurance. It helps insurers set optimal retention levels (“deductible to an insurer”) using real data and can adapt to different pricing rules and risk preferences. So, it’s not just a theory. It is practical and actionable.
How does this new model improve what Ghanaian insurers are doing today?
It gives insurers a clearer, statistically sound way to decide how much risk they can safely retain. Instead of relying on fixed rules or outdated pricing, they can now calculate retention based on their actual claims data and solvency targets. This helps prevent underinsurance or overpaying for reinsurance. It also allows for more transparency when engaging with regulators or global reinsurers, especially under Ghana’s evolving risk-based supervision regime.
Are there specific sectors in Ghana that could benefit more immediately?
Absolutely. Agricultural insurance, microinsurance and health insurance stand to gain. These sectors serve vulnerable populations and operate on thin margins. They face high volatility, whether from weather events or public health crises. A data-driven reinsurance strategy can improve capital management, reduce solvency risk, and allow these insurers to grow sustainably. For example, a crop insurer in the Northern regions could model losses over time and negotiate better reinsurance terms based on this framework, rather than using assumptions from foreign markets. It levels the playing field.
What about natural disaster coverage, like floods in Accra or droughts in the North?
That’s where this model becomes even more relevant. Natural disasters are unpredictable, but we can still model their impact using statistical tools. With my method, insurers can assess the financial consequences of extreme events like floods or droughts and design reinsurance layers that respond more accurately. For example, instead of covering aggregate annual losses, they can trigger reinsurance per event or per region. This helps insurers avoid long settlement delays and ensures timely payouts. It also builds confidence for international reinsurers to underwrite Ghanaian risks at better terms.
How does this study relate to regulatory reforms in Africa?
Many African regulators, including Ghana’s NIC, are moving toward risk-based capital frameworks similar to Solvency II. My model fits directly into that direction – it is aligned with risk measures like Value-at-Risk and Expected Shortfall. This allows insurers to demonstrate solvency in a quantifiable way, which satisfies both local and international standards. Moreover, it promotes more dynamic supervision, where regulators can assess how resilient a company is under different risk scenarios. So, it’s a tool that supports smarter regulation, not just better pricing.
Are there plans to collaborate with insurers or regulators in Ghana or across Africa?
Yes. I am in early conversations with academic peers in Ghana and professional bodies in West Africa, and I am very open to working with insurers, reinsurers, or regulators who want to test or adopt the model. Whether it’s through workshops, pilot studies, or training actuarial teams, I’d be happy to support knowledge transfer and adaptation. My goal is to make the tools accessible and locally relevant.
Are reinsurance companies in Ghana or Africa currently using the traditional stop-loss or excess-of-loss models?
What advice would you give them on adopting your new approach? Many prominent reinsurers like Ghana Re, WAICA Re, Africa Re, and Continental Re use stop-loss or excess-of-loss contracts in practice. These are valuable tools, but often they rely on rigid assumptions or simplified retention rules.
My advice is to invest in actuarial capacity, hire or upskill local actuaries who can work with data, and start adopting more flexible, evidence-based retention models. The framework we propose can be integrated gradually, using real claims data and aligned with local regulatory requirements. It’s not about abandoning old models, but improving them with better design, estimation, and transparency.
What advice would you give to young Ghanaian students aspiring to careers in actuarial science or research?
Focus on strong math skills, yes, but also understand the human side of risk. Actuarial science is not just about passing exams; it’s about helping families, businesses, and countries prepare for uncertainty. Seek internships, build coding skills, and engage with real problems. And if you’re drawn to research, stay curious. Ghana and Africa as a whole need more thinkers and doers in this space.
Any final thoughts? What’s your hope for how this work is used?
I hope that this study becomes more than theory. It helps African insurers and policymakers rethink how we price, share, and prepare for risk. And that it becomes a small step toward a more resilient financial future for the continent.
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