A loan model can be 95% accurate and still be unfair in Nigeria.
AI loan systems make decisions using patterns from historical data.
They look at things like:
➖ transaction history
➖ location
➖ phone activity
➖ financial behaviour
On paper, this works pretty well.
But the problem is Many Nigerians are invisible in that data.
👉 The informal workers.
👉 The unbanked individuals.
👉 People operating in cash-based systems.
Take a skilled carpenter who gets paid mostly in cash for example
He has no strong transaction history. No formal credit trail.
To the model?
That looks like risk.
But in reality, it’s just missing data.
It gets more subtle.
Location also can quietly influence outcomes.
Someone from a high-activity area like Lagos Island may be favored over someone from the mainland, not because they’re more creditworthy, but because of patterns in the data.
This is how bias hides.
The model can be highly accurate overall…
While consistently failing certain groups.
Accuracy isn’t the problem.
Representation is.
If the data is incomplete, the decisions will be too.
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The biggest problem with AI in Nigeria isn’t accuracy.
It’s representation.