Success case — Credit Scoring As a Service
AI-driven scores designed to maximize approval rates for non-traditional borrowers
Improve risk assessment to promote financial inclusion.
+ 65% of consumers and 45% of SME’s with no access to traditional credit in Latam.
+ Collateralized lending dominating markets excluding many potential borrowers.
+ Limited use of alternative data or methodologies in the financial sector.
A flexible credit decision engine to automate underwriting and increase precision.
+ AI credit scoring models implemented for non traditional risk assessment.
+ Technological solution with real-time decisioning and process consistency.
+ Models with flexible credit risk parameters designed to maximize eligibility.
Credit applications reviewed
A.I. credit scoring models implemented
Approval rate improvement for low credit scores versus traditional approaches
Approval rate improvement for users under age 35 versus credit-bureau-based models