Navigating the Intersection of Credit, Fraud, and Compliance

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

Innovations in post-login fraud have exposed gaps in login defenses. How are leading businesses responding? Experts from TD Bank and Experian take a look at modern ATO attacks and scams — and how to stop them.

What you’ll learn:

• How fraudsters exploit vulnerabilities in login defenses
• The operating structure of a real-world ATO fraud ring
• Keys to stopping coordinated attacks in real time

This tip sheet explores where fraud can enter the customer lifecycle and how predictive fraud risk scores help distinguish fraud from true credit risk and help you:

• Reduce first-payment default and bust-out fraud
• Detect synthetic identities earlier
• Improve prescreen and campaign ROI
• Strengthen account management decisions

Learn how a multilayered fraud strategy can help organizations protect every digital entry point and stop fraud earlier in the journey.

Key insights:

• Learn how behavioral analytics, identity verification and risk signals can stop fraud early.
• Explore how device, network, phone and email intelligence can strengthen defenses.
•  See how step-up verification can help block high-risk actions and prevent fraud losses.