Interview: Kueski’s CTO Jaime Romero on how AI is rebuilding credit infrastructu

Founded in 2012 in Mexico, Kueski can claim to be the leading local online lending platform designed to offer unsecured loans through direct deposits to clients' bank accounts or purchases through their tool. The company's platform leverages several data points to build credit risk and fraud risk machine learning models that will approve or reject loan applications quickly, enabling clients to cover their short-term cash or purchase needs anywhere, including in-store, in the case of BNPL transactions.

At its core, Kueski features a real-time credit system operating at scale, making millisecond decisions at checkout using behavioural and proprietary signals across tens of millions of loans. Jaime Romero, CTO at Kueski, tells RBI how real-time credit decisioning systems are built under latency constraints, why traditional scoring breaks down in emerging markets, discusses the convergence of fraud and credit risk in digital environments and what actually changes when these systems operate at scale.

Jaime Romero, CTO, Kueski: Mexico is one of the world's largest consumer markets, yet more than half of its adult population remains outside the formal financial system. That's not a nich

Fuente original: Yahoo Finance (https://finance.yahoo.com/technology/ai/articles/interview-kueski-cto-jaime-romero-200056745.html)