Improving learning outcomes in Kenya through school-level financing incentives

Decision-maker’s challenge

Low-cost private schools in Kenya are growing fast, with more than 60% of school-age children in urban and informal settlements enrolled in these schools. But enrollment numbers tell only half the story.

The non-state sector and low-cost-private schools are led by inspiring education entrepreneurs, delivering education provision in low-and-middle-income countries to support the education for underserved children in low-resource settings. Yet, because these schools operate as small businesses, their owners’ core concern is financial survival — filling seats and repaying loans — not necessarily whether students can read or do basic math. Parents may not know to demand better learning outcomes, and government oversight of the private school sector remains limited. The result is a market gap: schools have the financial incentive to enrol more students, but no equivalent incentive to optimize learning outcomes.

Global Schools Forum and IDP Foundation support low-cost financing for school entrepreneurs through financial institution partners to start and run low-cost private schools in informal settlements in Kenya. They quickly realized that financing alone, though it increased access to schooling, was not enough to improve learning outcomes for students. The Incentives for Learning program is designed to change that by making learning outcomes a direct driver of a school’s financial bottom line.

Our approach

The central question driving this work is whether linking a school’s financial returns to its students’ learning outcomes can shift proprietor and teacher behaviour in ways that lead to real, measurable improvements in whether children learn. To answer this, IDinsight was brought in as the independent assessment and learning partner, working alongside Global Schools Forum, IDP Foundation, and two Kenyan financial institutions: Jackfruit Finance and Premier Credit. 

Global Schools Forum is a community convenor, knowledge accelerator, funding catalyst, and partnership builder supporting non-state education organisations across low- and middle-income countries. Its community spans 224 schools, networks, and funders across 71 countries, reaching 150 million children. Through programmes like Incentives for Learning, delivered in partnership with IDP Foundation, Jackfruit Finance, and Premier Credit, GSF increases the finance flowing into education by connecting members, funders, and the broader sector, providing practical support to help organisations access funding, catalyse new funding mechanisms, and connect directly to funders, accelerating the pace and scale of investment in education.

Our core task was to build the measurement system that makes the model work. Schools earn financial rewards based on how their students perform on independent reading and math assessments and how well teachers understand where their students stand.

For the incentives to be credible, the assessments have to be trustworthy. We tested three different student assessment tools across 97 schools before settling on a tablet-based approach (the self-administered EGRA/EGMA, delivered on Tangerine Central’s platform) where students complete reading and math tasks independently on a device. This method lets one assessor work with a group of up to ten students at once, making it practical to run at scale without sacrificing accuracy. 

Together with Global Schools Forum and IDP Foundation, we helped to design the reward structure that ties loan interest reductions to student performance. Schools are placed into one of five tiers and can earn between 35% and 100% off their loan interest depending on how their students do. The thresholds were worked out collaboratively with program partners and include a small bonus adjustment for the lowest-fee schools, recognizing that they often serve the most under-resourced communities. Every school, whether or not they qualify for a reward, gets a report card showing how their students performed and where there is room to improve.

To rigorously assess whether this financial incentive program can improve learning outcomes, we are running a randomised controlled trial, comparing schools that receive incentivised loans against those that receive standard loans. This will allow us to isolate the effect of the financial incentive itself, generating evidence that is both credible and actionable for funders, financial institutions, and policymakers considering whether this model is worth scaling.

The results

So far, we have collected baseline data (July 2025), randomized schools into treatment and control groups (September-December 2025), and conducted the first assessment of treatment schools to determine initial financial rewards (February-March 2026). Endline data will be collected in September 2026. Some findings from baseline data collected across 97 schools in Nairobi and peri-urban areas in July 2025 include:

• Reading outpaces math across all grades. 56.7% of students met grade-level reading expectations versus 48.8% in math.
• Math gaps are steepest in the early years. Only 29.1% of Grade 1 students met math expectations, rising sharply to 72.8% by Grade 3.
• Teachers consistently overestimate student performance. Most predicted scores were well above what students actually achieved, even in schools where students scored in the 20 to 40% range. This points to a significant gap in teachers’ understanding of grade-level standards and a key lever for improvement.
• School recruitment proved harder than anticipated. Three rounds of randomization were needed through December 2025 to reach the final study sample, underlining how important clear eligibility criteria and sustained financial institution engagement are for programs of this kind.

These baseline findings set the stage for the program’s core question: Can the incentive structure shift these numbers? The gap between reading and math performance, and the steep drop in math proficiency in Grade 1, point to specific areas where targeted school investment and teacher support could make the most difference.

When endline results are available in late 2026, we will be able to report not just whether the incentive model worked, but which types of schools benefited most and at what cost. That evidence will directly inform how the model is refined and whether it is ready to scale.