From 50% Automation to Unscoreable Users: MNT-Halan's AI Credit Scoring Engine and the FinTech Revolution in Emerging Markets
Key Takeaways Traditional credit models fail 64% of adults in the Arab world who lack a formal banking history, making them "unscoreable" and excluding them from loans. MNT-Halan built a super-app for daily life (payments, e-commerce) to collect alternative data like bill payment history and app engagement. A proprietary AI engine analyzes this behavioral data, achieving a 60% loan approval rate for previously unscoreable users with repayment rates on par with traditional banks. What if your daily grocery run, your mobile data top-up, and the time you spend scrolling an app could unlock your first-ever loan? What if these digital breadcrumbs could do what banks never could: see you? For a staggering 64% of adults in the Arab world , this isn't a hypothetical—it's a financial lifeline. They are the "unscoreable," and one company, MNT-Halan, is using a brilliant AI engine to bring them into the financial fold . This isn't just another fintech ap...
