By Irene Nafula, Ag. Managing Director at M-Tiba
There is one sentence you do not hear often enough in Kenya’s health insurance industry: growth is not the problem.
By almost every headline measure, the sector is expanding. According to the latest Insurance Regulatory Authority (IRA) report, medical insurance grew by 22.4 percent in 2025, becoming the largest class of general insurance and accounting for 41.1 percent of the segment. Premiums rose 13.4 percent in the first half of the year. More Kenyans are buying health cover, insurers are onboarding new members, and new products continue to enter the market.
Yet beneath these encouraging figures lies a worrying reality.
The general insurance industry’s combined ratio stood at 108.3 percent, meaning insurers paid out more in claims and expenses than they collected in premiums. The sector is growing, but it is not becoming more profitable.
That tells us something important: health insurance has a structural challenge, not simply a growth challenge.
As a technology platform operating between insurers, healthcare providers and members, we see what headline statistics often conceal. Claims still arrive weeks after treatment despite the availability of real-time digital submissions. Many providers continue to rely on manual processes instead of embracing electronic claims. Reconciliations drag on for weeks. Fraud is often detected only after payments have already been made. Pricing decisions continue to rely on historical information even though current utilisation data is increasingly available.
For years, the industry’s answer to these inefficiencies has been straightforward: grow.
Expand the portfolio. Enrol more members. Enter new market segments. The assumption has been that scale would eventually solve profitability.
It hasn’t.
In many cases, growth has simply magnified inefficiency.
Insurance is fundamentally a business of managing risk. Yet risk cannot be managed if it cannot be seen.
For decades, insurers had limited visibility across the healthcare journey—from consultations and laboratory tests to pharmacy claims, hospital admissions and provider billing. Data often became outdated before it was analysed. Claims arrived retrospectively. Fraud investigations started after losses had already occurred. Pricing models relied on last year’s trends instead of today’s realities.
That is administration, not active risk management.
At a time when medical inflation continues to rise and insurance fraud is becoming increasingly sophisticated, delayed information comes at a significant cost.
Fortunately, the industry is beginning to change.
The digitisation of healthcare administration has created something that scarcely existed before: a real-time view of healthcare utilisation.
Hospitals, clinics and pharmacies are increasingly operating on connected digital platforms. Mobile connectivity and modern insurance systems now allow claims, authorisations and billing information to move almost instantly across the healthcare ecosystem.
When this infrastructure is combined with artificial intelligence, the impact is measurable rather than theoretical.
Several insurers are already reporting that AI enables the majority of claims to be processed faster without compromising accuracy. Others have successfully prevented hundreds of millions of shillings in fraudulent claims through AI-driven detection systems.
These are not pilot projects. They are operational improvements already being realised in Kenya.
The broader market is also moving rapidly in this direction. Deloitte projects that AI adoption across African insurance operations could rise from just 1 percent today to as much as 80 percent within five years. Meanwhile, KPMG’s 2025 Africa CEO Outlook found that 41 percent of African CEOs now rank AI integration as their highest investment priority.
The direction of travel is unmistakable.
At M-TIBA, we are already seeing what this transformation looks like in practice. Our AI-powered decision engine processes pre-authorisations and claims in real time, automatically adjudicating requests against benefit rules while routing complex cases to human assessors where clinical judgement is required.
Fraud detection models identify suspicious claims several times faster than manual review, allowing insurers to intervene before payments are made. As a result, insurers using our platform have reported healthcare cost reductions of up to 15 percent, alongside portfolio margin improvements ranging between 10 and 20 percentage points.
These are not projections. They are outcomes already being delivered in the Kenyan market.
More importantly, they demonstrate that AI is not replacing people. It is enabling insurers to make faster, better-informed decisions while allowing specialists to focus on the cases that truly require human expertise.
Ultimately, this is about far more than technology.
It is about changing the economics of health insurance.
When claims are assessed instantly, unnecessary leakage declines. When provider billing patterns are monitored continuously, fraud can be prevented rather than investigated after the fact. When pricing reflects current utilisation instead of historical averages, premiums become more sustainable. When members receive instant pre-authorisation decisions and can track their claims digitally, confidence in health insurance grows.
Technology is not the objective.
Operational discipline is.
Kenya has demonstrated before that it can lead global innovation. Mobile money was not imported; it was developed here. M-Pesa fundamentally transformed financial services and became a global benchmark because technology solved a real market problem.
Health insurance is approaching a similar inflection point.
The foundations are already in place. Healthcare providers are digitising. Modern insurance platforms are replacing legacy systems. Richer data is becoming available. Artificial intelligence is maturing rapidly.
At the same time, insurance penetration remains just 2.4 percent of GDP, highlighting the enormous opportunity to expand access while improving sustainability.
The next chapter of Kenya’s health insurance sector will not belong to the insurers that grow the fastest.
It will belong to those that execute with the greatest discipline; those that use data in real time rather than in retrospect; those that detect fraud before it happens instead of after; and those that recognise profitability and wider coverage are not competing objectives, but complementary ones.
Growth has brought Kenya’s health insurance industry this far.
Artificial intelligence, combined with better data and stronger execution, can ensure the next phase of growth is not only bigger—but sustainable.
