By In my years in the Nigerian financial sector, compliance felt like constant firefighting. There was always something urgent. A disclosure that did not add up. A customer whose paperwork told one story while their transactions told another. A process that had worked last quarter but had somehow stopped working this quarter. The job demanded speed, instinct, and an almost exhausting vigilance.
In the UK, the system does much of that vigilance for you.
That contrast stopped me in my tracks. And it started a question I have not stopped asking since: why do two systems built to achieve the same goal, tax compliance, feel so fundamentally different to work inside?
The answer, I have come to believe, is not policy. It is not political will. It is not even resources, though resources matter. The biggest difference between the UK tax system and most African tax systems is the quality, consistency, and accessibility of the data that underpins them.
Two systems, one goal
The purpose of a tax compliance system is straightforward: to ensure that individuals and organisations contribute what they owe to public revenue. Every jurisdiction frames this differently, through legislation, through cultural expectation, and through enforcement culture, but the underlying objective is the same.
What differs is how each system knows what is owed.
In a data-rich environment like the UK, data such as employer payroll, self-assessment returns, property records, and banking disclosures can be cross-referenced in ways that create a relatively complete picture of an individual or business’s financial activity. The system is not perfect; no system is, but it is built on the assumption that data should flow between institutions and that compliance is most effectively enforced when the authority can see clearly.
In Nigeria, and across much of Africa, the infrastructure for that kind of data visibility simply does not yet exist at scale. Large portions of economic activity happen outside formal reporting systems. Small and medium enterprises, which account for the majority of employment and significant portions of GDP across the continent, often operate with limited digital financial records. The result is that compliance enforcement is built on a fundamentally incomplete picture.
Enforcing rules on invisible data is like trying to referee a match in a blackout.
What the financial sector taught me
Before relocating, I spent five years at the pension management arm of a prestigious financial institution. Across those years, I developed an instinct that I did not yet have a language for: the patterns in financial behaviour that the system was not designed to capture.
I watched accounts that passed every formal check but carried unmistakable risk. I watched processes that generated reports without generating insight.
I was, without knowing it, doing the foundational work of a data analyst: identifying anomalies, questioning assumptions, and asking what the numbers underneath the numbers were saying. The gap was in infrastructure. We did not have the tools to make the data speak.
What the UK showed me
The UK’s Making Tax Digital (MTD) initiative, which mandates digital record-keeping and return submission, is not primarily about convenience. It is about data. It creates a standardised, machine-readable trail of financial activity that the authority can analyse at scale. It removes the ambiguity that makes enforcement expensive and unreliable.
That kind of infrastructure does not arrive overnight. This has been building for decades, through investment in regulatory technology, legislative mandates, and a gradual cultural shift toward digital financial record-keeping. There have been failures and delays; the rollout of MTD has been slower and more contested than the government intended. But the direction of travel has been consistent.
Africa is beginning to move in the same direction. Nigeria’s FIRS has been advancing e-invoicing and digital filing systems. Rwanda’s Revenue Authority is widely cited as a continental model for data-driven tax administration. Ghana, Kenya, and South Africa have each made significant investments in fiscal technology infrastructure. The momentum is real.
But the gap remains wide. And the question I keep returning to is, what would it take to close it faster?
The dual-market lens
I occupy an unusual position. I grew up in Nigeria, built my professional foundation in the Nigerian financial sector, and now work in the UK. I carry both contexts not as abstract knowledge but as lived experience; I have been inside both systems, felt their textures, and understood their logics from the inside.
That position gives me something I think is genuinely rare: the ability to see each system through the eyes of the other.
From inside the UK system, I can see what data infrastructure makes possible: the speed, the precision, and the capacity for proactive rather than reactive enforcement. And I can see that Africa’s systems, for all their resource constraints, sometimes understand better the importance of meeting people where they are, of designing for the informal, and of building trust in a context where institutions have not always earned it.
Neither system has the full answer. But together, they suggest what a genuinely effective data-driven compliance framework might look like: one that combines the analytical sophistication of the UK model with the contextual intelligence that Africa’s realities demand.
That synthesis is what I am working toward.
Why this matters beyond compliance
Tax is not a technical subject. It is a social contract.
When tax systems work, when they are seen as fair, when the data they rely on is accurate, when enforcement is consistent, they generate the revenue that funds schools, hospitals, roads, and every other public good that societies depend on. When they fail, the consequences are not abstract. They are felt in under-resourced public services, in infrastructure that does not get built, and in inequality that compounds.
Africa’s tax gap, the difference between what is owed and what is collected, is estimated at hundreds of billions of dollars annually. That is not just a compliance failure. It is a development failure.
Closing that gap requires more than stricter enforcement. It requires the kind of data infrastructure that makes the gap visible in the first place and that can show, in real time, where the leakage is, who is missing from the system, and what interventions are most likely to work.
Building that infrastructure is the work I have come here to talk about. Not from the outside as a critic or a theorist, but from the inside as a practitioner who has worked in both systems and believes the bridge between them is worth building.
BY Bosola Odunuga
