5 model classification blind spots to watch out for in 2026

Discover where leading institutions are taking decisioning:

• Explores why intelligent decisioning is becoming a competitive advantage for financial institutions.
• Examines research on AI, data, governance and decision intelligence.
• Highlights common modernization challenges and practical strategies for improving decision outcomes.

Discover how lenders can strengthen prime portfolio performance by combining traditional credit risk strategies with first-party fraud analytics to identify hidden risk and improve early payment default detection.

Key insights:

• Traditional credit scores measure ability to repay but may not identify consumers with no intent to repay. 
• First-party fraud models can uncover hidden early payment default risk within prime portfolios and improve risk segmentation. 
• Research shows measurable lift in early delinquency detection and ROI when fraud analytics complement credit scoring.

Your most valuable customers don’t announce their departure. By the time balances decline or activity slows, competitors have already captured share of wallet.

Download our strategic snapshot to learn how your institution can identify behavioral shifts early, respond confidently and accelerate high-value customers forward.

Did you know?

• Customers typically hold less than 50% of their deposits or loans with a single institution.
• Selling to an existing customer can be up to 10x more successful than acquiring a new one.
• A 5% increase in customer retention can boost profits by 25% to 95%.

Bayesian Optimization offers a more efficient way to tune machine learning models at scale. This white paper presents a controlled comparison with Grid Search using production credit-risk data to measure runtime and model performance.

• Up to 80× faster hyperparameter tuning
• No loss in CV or holdout AUC
• Evidence from LightGBM credit-risk models
• Guidance for governed ML environments