Business Overview
Banks are under pressure to lend smarter — faster decisions, tighter compliance, zero room for error. But today’s ML models either perform well or explain well — rarely both. This trade-off slows down operations and frustrates regulators. With Snake, lenders can assess risk with state-of-the-art accuracy and total auditability — unlocking growth without compromising on trust or compliance.
Input Data
Supervised tabular data from credit applicant history: financial behavior, income, repayment history, and macroeconomic indicators.
Output
Predict: Default probability with a granular confidence score for every applicant. (AUC 0,70) Explain: RAG-based justifications detailing key variables that drove the risk assessment. (Avec image de l’exemple de R.A.G).
Deploy: Plug-and-play into risk scoring pipelines with full replicability and compliance-readiness.
