CREDIT ASSESSMENT

CONTEXT
A digital bank wanted to improve its credit assessment and authorization models to make them more efficient and faster.

SOLUTION
Credit granting data were collected, similar to existing processes, and supervised learning techniques were applied to learn default standards and limits.

RESULTS
The models based on machine learning obtained a superior performance to the existing models and without the need to consult the credit bureaus, saving the consultation fee.