Credit Risk Modeling: Reject Inferencing with AI and Synthetic Data

When applicants are declined, their true performance remains unknown—creating blind spots that weaken credit risk models. This is where reject inference becomes critical.

Join us for an insightful session where we:

Compare traditional reject inference techniques with AI-driven synthetic data approaches

Share results from real-world experiments using both methods

Provide actionable insights to strengthen your risk modeling strategies

This webinar is designed for credit risk professionals, data scientists, analytics leaders, and anyone involved in building or validating risk models in banking, fintech, or lending.

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