Can AI help make lending fairer in Egypt and the Gulf?

AI is transforming the way MENA financial institutions decide who’s a good loan prospect, stoking excitement about a more inclusive market, but also anxiety about who might get left out.

On the plus side: AI models are making it easier to assess the creditworthiness of small businesses and individual borrowers, especially newcomers to the financial system and lower-income people without bank accounts. These people often have little or no conventional credit history, but an AI model can use non-conventional data to make a decision. For people wanting personal finance, that can mean combing through their phones to look at how they pay their phone and utility bills, Ahmed Abaza (LinkedIn), co-founder and CEO of Synapse Analytics, tells EnterpriseAM.

It’s largely about cost. Making a decision on every personal or small business loan by hand takes so much staff time that it can eat up much of what the lender earns on it, the World Bank has noted. Letting software make those decisions can cut that cost significantly, McKinsey says, making those segments — as well as microfinance — more attractive to banks and non-bank lenders alike.

But there’s also a less rosy version of the story: AI is trained on existing data — and existing biases. If women, informal workers, and young people barely show up among a lender’s past borrowers, a model can end up shutting them out.

The developments highlight how the shift to AI can dramatically increase efficiency while simultaneously removing the human elements of any business transaction — a tradeoff that’s especially troubling when it comes to personal, home and business loans, which can be life changing for many borrowers.

The balancing act: “I use [AI] to increase human efficiency, not to replace people, because a human must guide it and assess the output, as AI can often be inaccurate,” Hossam Heiba, managing director of Orbis Capital and former head of Egypt’s state investment agency, GAFI, tells EnterpriseAM.

Big corporate loans are a whole other ballgame. Some banks are already using AI to help judge whether a company can handle a loan, Bassem Fayek (LinkedIn), managing director and partner at BCG, tells EnterpriseAM. But handing the final call to a machine is a much harder sell when a bank’s reputation is on the line. “I answer to the depositors and the shareholders. But the buck stops with me and my team,” Todd Wilcox, CEO and Deputy Chair of HSBC Egypt (LinkedIn), said at the EnterpriseAM Egypt Forum earlier this month. “It’d be difficult to defend to depositors that the bank failed because of our AI model and [its] judgment.”

Regulators in Egypt are starting to ease the path for more machine decisionmaking in lending. From April 2027, consumer-finance companies deciding whether to approve financing will have to consult a gauge from the country’s only licensed private credit bureau based on behavioural analysis of alternative data, per a new rule from the country’s non-bank financial regulator. The score is the type of information that feeds directly into AI-backed risk prediction and automated lending decisions.

Why it matters: Fewer than half of Egyptian adults have a bank or mobile money account, according to the World Bank, which makes it extremely difficult to assess their creditworthiness using traditional data and approaches.

Credit scoring is even more advanced in the UAE. Since July, credit scorers have begun incorporating how people repay micro-loans from buy-now-pay-later firms such as Tabby and Tamara in their credit reports.

And they’re increasingly interested in assessing those reports using AI agents rather than humans alone. Emirates NBD is set to become the first MENA bank to run ChatGPT on infrastructure inside the UAE. The bank recently ranked first among 25 banks in the Middle East and Africa edition of the Evident AI Index, which ranks banks on how far along they are in adopting AI. Emirates NBD declined to comment for this story.

Why that matters: UAE banks aren’t allowed to send customers’ private data out of the country without the central bank’s approval, and ChatGPT normally runs in data centers abroad. With ChatGPT running inside the UAE, the data never leaves the country, so the bank can use it on its own data.

Advocates say there’s an open-and-shut case for turning lending decisions over to AI agents — they’re smarter, faster and more capable than humans. Think of it as hiring “the best risk agent you can ever hire, that never sleeps, never eats, never takes time off,” who’s always “exploring how to have you accept more customers with less risk,” Synapse’s Abaza tells EnterpriseAM.

The numbers: Synapse, whose software is used by more than 50 financial institutions, says its clients are approving up to five times more customers with 40% fewer bad loans compared to before they signed up with Synapse. Abaza says his clients are not lowering the bar — they’re just getting through far more applications. Ultimately, banks that once approved around 10k people a month may end up approving 10k a day, Abaza says.

MNT-Halan, another Egyptian fintech, is using its in-house tool, Apollo, to tell staff which overdue loans to chase each month, as we previously reported. It’s set to roll the tool out across “many departments” within three months, CEO Mounir Nakhla said at our Egypt Forum, just weeks before the company’s Egyptian unit debuted on the EGX.

Flying solo: The Egyptian fintech Klivvr even expects to soon let AI agents make decisions about underwriting loans without any human approval, as we reported last week.

But there’s also anxiety about moving too fast to AI, especially at more traditional banks. Executives there worry about giving powers to AI without ensuring that its decisions are properly vetted and that there’s a human taking responsibility. “If you have poor governance and no accountability, it simply leads to making bad decisions faster,” HSBC Egypt CEO Todd Wilcox said at our Egypt Forum.

People, not algorithms: Even Emirates NBD, which styles itself a regional leader in the adoption of AI, insists in its published AI policy that “people, not algorithms, remain in charge.”

Important caveats: AI is only as good as the data it’s fed, and most companies’ data is a mess. That’s true for big firms and small ones, in every industry and almost everywhere, Hazem Gebili, chief AI and digital officer at Orange Egypt, tells us. Records tend to sit in old systems scattered across a company, much of it inaccessible to AI. And just plugging AI into the way things already work would be “the biggest failure,” he says: “You need to reimagine the journey.”

Most banks are keeping AI away from their core infrastructure, for now. They’re using it with customers, “but not in core banking operations yet due to high confidentiality and data protection rules,” Heiba says.

SOUND SMART- Non-bank lenders in Egypt like Klivvr and MNT are supervised by the Financial Regulatory Authority, which has in recent years been more willing to loosen rules and experiment with technology than the Central Bank of Egypt, which regulates the nation’s banks. The CBE didn’t reply to a request for comment for this story.

Egyptian banks aren’t spending much on AI, either. Only “a couple” of Egypt’s 30-plus banks are well ahead of the curve, BCG’s Fayek says. The nation’s two biggest state banks trail the region, too: on the Evident AI Index of 25 banks across the Middle East and Africa, Banque Misr ranked 19th and the National Bank of Egypt came last.

Computing power is another barrier: Central bank rules effectively prevent Egyptian lenders from sending customer data to cloud-based AI services like ChatGPT, Claude or Gemini, two bank CEOs confirmed to EnterpriseAM. Non-bank lenders have told us they feel similarly constrained. The result: Those experimenting with AI today are running smaller, open source models on their own servers instead, Abaza notes. That means buying GPUs, the super-expensive advanced computer chips that run most AI. “In Egypt, sometimes it’s very hard to get GPUs,” he says.