Alex Franco, Chief Risk Officer and Chief Technology Officer at Jeitto, artificial intelligence and alternative data can democratize access to credit at a faster pace.
Franco, a Supernova Award 2025 finalist, recently outlined Jeitto's mission and approach to technology. Jeitto primarily operates in Brazil and provides credit to more than 11 million customers. Many of those customers are underserved by banks.
Jeitto has automated decision workflows through its mobile app and AI-led processes. Since deploying Provenir’s AI Decisioning Platform, Jeitto has seen a 20% reduction in defaults on the Jeitto Loan, grown its customer base and recorded a 10% increase in its credit approval rate. Jeitto's credit assessment cycle time has moved from 1.5 minutes per application to 30 seconds.
We caught up with Franco to talk shop. Here's a look at the key themes.
Target market. Franco said Jeitto is focused on Brazil's underserved population "that earns low income, that has a lot of difficulty to get access to credit in Brazil."
Alternative data. Jeitto leverages AI and alternative data for credit decisions. Franco said: "Since 2014 Jeitto has been working on AI and alternative data to provide credit to the population in Brazil." Key data points include.
- Cell phone data, a key factor in credit decisions.
- Fiscal data retrieved through the customer's fiscal ID in Brazil
- Customer behavior data.
Strategic expansion. Franco said Jeitto has 13 million consumers in its database and is now looking to add new services and loans to become a broader financial platform.
Technology strategy. Franco said Jeitto's stack revolves around combining best-in-class platforms to leverage AI and intelligence. Core functions are those technologies that affect the customer experience and long-term value.
Jeitto's platform connects fraud scores, identity checks and device validation, integrating multiple layers of fraud detection into decisioning workflows to mitigate threats at application screening, including synthetic fraud, impersonation and mule indicators. This eliminates siloed environments between credit and fraud risk teams, to ensure holistic, end-to-end decisioning with a complete view of customers across the entire lifecycle.
