Is AI Biased? The Hidden Risks of Automated Lending Decisions in Nigeria

Is AI Biased? The Hidden Risks of Automated Lending Decisions in Nigeria

The Rise of the Machine: From Paper Files to AI Algorithms

Deciding who gets a loan has always involved some form of scoring. The journey started long before the internet, with the first credit scoring systems appearing as far back as 1958. The popular FICO score, which many systems are based on, was introduced in 1989.

Today, AI has taken this a step further. Instead of just looking at your banking history, AI algorithms on loan apps can analyse hundreds of data points in seconds—your phone usage, online activity, and even your social connections—to make a decision. This promises to give more people access to credit, but it’s not that simple.

Can a Robot Be Unfair? Understanding AI Bias

It sounds strange, right? An AI is just a computer program; it doesn’t have feelings or prejudices. But that’s exactly where the problem lies. An AI can be biased if the data it learns from is biased.

Think of it like this: if you teach an AI to cook using only recipes for Jollof rice, it will never learn how to make a proper pot of Efo Riro. It doesn’t know any better. Similarly, if an AI is trained on historical loan data that contains human biases, it will learn and even amplify those biases.

The Problem of “Data-In, Bias-Out”

If, in the past, human loan officers were less likely to lend to people from certain areas or those with non-traditional jobs (like freelancers or small business owners), the AI will learn this pattern. It will see a correlation between these factors and loan defaults, and it will start automatically penalising new applicants who fit that profile, creating a cycle of automated lending risks.

When Having “No Bias” is a Risk

Here’s the tricky part: sometimes, a bit of human “bias” or empathy is a good thing. The provided notes for this article highlight that AI does not possess inherent human qualities. A human loan officer can listen to your story, understand that you had a one-off family emergency that affected your account balance, and make an exception.

An AI cannot. It strictly considers the facts and data presented. It can’t understand context or show compassion, which can be a major disadvantage for people who are financially literate but have complex financial lives.

Loan Officer ; Can consider context & show empathy, Slower, manual process, Prone to personal, conscious bias, Can provide a reason for rejection

AI Algorithm Strictly follows data and rules, Instantaneous decisions, Prone to systemic, coded bias, Decision can be a “black box”

The Real-World Risks for Everyday Nigerians

This isn’t just a theoretical problem; it has real consequences for people like Funke trying to get fair credit in Nigeria.

The Black Box: Rejection Without Reason

The biggest frustration with AI loan apps in Nigeria is the lack of transparency. As legal scholar Andrew Tutt points out, “Our inability to understand, explain, or predict algorithmic errors is not only unsurprising, but destined to become commonplace.”

This means you can be rejected for a loan and have absolutely no idea why. Was it because you had too many airtime top-ups last week? Or because you live in a certain neighbourhood? Without feedback, you can’t fix the problem or improve your chances for next time.

Why Financial Literacy is Now More Important Than Ever

Because AI judges you purely on your digital and financial data, managing that data is no longer optional—it’s critical. As experts have noted, “in essence, there has never been a better time to be financially literate than now.” Your financial habits are constantly being watched and scored by these automated systems.

How to Protect Yourself in the Age of AI Lending

You are not powerless. You can take steps to navigate this new world and present the best possible version of yourself to the algorithms.

• Build a Strong Digital Footprint: AI looks at everything. Pay your utility bills (like electricity and waste) on time. Have a consistent flow of money, no matter how small, into your bank account. Manage your mobile money accounts responsibly.
• Understand Your Credit Report: Knowing what’s in your credit report is crucial. You can get your report from a registered credit bureau and check for errors. If you find any, dispute them immediately. For more on this, learn about understanding your credit report in Nigeria.
• Start Small and Build History: If you’re new to credit, don’t apply for a huge amount. Take out small, manageable loans and focus on repaying them on time, every time. This is a powerful way of how to build credit in Nigeria.
• Choose Reputable Lenders: Stick to licensed and regulated lenders. They are more likely to have fairer, more transparent processes. When looking for quick loans, always do your research first.

Frequently Asked Questions (FAQs)

Q1: Can I ask a loan app why they rejected me?

A: You can try, but many fully automated systems don’t provide specific reasons. This is why building a strong financial history before you apply is your best strategy.

Q2: Are all loan apps in Nigeria using biased AI?

A: It’s impossible to know for sure, as their algorithms are private business secrets. However, the risk of bias exists in any automated system. You should always focus on what you can control: your own financial data and habits.

Q3: Is AI lending bad for Nigeria?

A: Not at all. It has given millions of people access to credit who were previously ignored by traditional banks. The goal isn’t to stop AI lending but to be aware of the risks and demand more transparency and fairness from providers.