Grupo Casas Bahia: A major Brazilian retail group with a proprietary consumer-credit operation

Problem

Scale consumer-credit origination across physical and digital channels while maintaining consistent risk policies, approval speed, and portfolio quality.

Role

Data Science Coordinator contributing to retail-credit decisioning, customer analytics, and collections.

Approach

Contributed to the credit decision engine through application scoring, capacity-to-pay assessment, pre-approval and limit strategies, automated decision rules, behavioural monitoring, vintage analysis, and collections prioritization.

Impact

Contributed to scaling a retail-credit decision engine that automated 96% of credit decisions and supported a base of more than 11 million pre-approved customers. During the same period, the managed credit portfolio reached approximately R$6.4 billion, with record origination, while 90-day delinquency declined from 7.8% in September to 4.9% in December 2020.

Lessons

A credit decision engine only creates sustainable scale when models, policy rules, commercial operations, and collections share the same risk appetite and performance metrics.

Employers are named and consulting clients stay anonymized. Company-level figures such as portfolio size, GMV or delinquency show the context of the period in which the work took place.