Under the Microscope: AI Credit Decisioning | Automotive Finance Canada 2026 скачать в хорошем качестве

Under the Microscope: AI Credit Decisioning | Automotive Finance Canada 2026

The era of the "static scorecard" is fading. Auto and leasing credit teams are now rapidly deploying Machine Learning (ML) to handle decisioning, pricing, and limit management in real-time. But how do you balance high-speed automation with regulatory scrutiny? In this technical and strategic session from the 2026 Automotive Finance Canada Summit, experts from RBC, Trust Science, and Northlake Financial pull back the curtain on AI in production. Moderated by Deloitte, the panel explores the "Performance vs. Explainability" trade-off and the governance frameworks required to satisfy both boards and regulators. Key Discussion Points: From Rules to Models: The practical steps of migrating from traditional rules-based engines to ML-driven decisioning. The "Black Box" Problem: How lenders are managing model risk, fairness, and "Explainable AI" (XAI) to meet Canadian regulatory standards. Measurable Lift: Real-world examples of how AI is improving approval rates without increasing delinquency. Human-in-the-Loop: Identifying the specific scenarios where human judgment must still overrule the algorithm. Governance Frameworks: Building a robust AI policy that stands up to internal audit and external oversight. The Panel: Moderator: Jose Guido | Sr. Advisor, Credit Risk, Deloitte Sarah Sun | Sr. Director Risk Modelling, RBC Matt Browning | President, Trust Science Dinesh Mistry | SVP, Risk & Strategy, Northlake Financial #AICreditScoring #AutoFinance #MachineLearning #RiskManagement #RBC #TrustScience #FintechCanada #CreditDecisioning #Underwriting #CanadianLenders #2026AutoFinanceCanada #AutoFinanceCanada