Elevating credit risk analysis: advanced reject inferencing techniques

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

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

The credit marketing landscape is evolving. As competition intensifies and consumer expectations rise, financial institutions that can predict, personalize and perform at scale will define the next generation of success.

In this webinar, our experts explore how financial institutions can use connected intelligence to find, know and grow the right customers, leading to:

• Smarter acquisition
• Stronger customer retention
• More proactive growth

Join Ashley Knight, Experian’s SVP of Product Management, and Haiyan Huang, Prosper’s Chief Credit Officer, to discover how:

• Alternative finance data is redefining how to verify and connect identities.
• Email and phone intelligence is unlocking new levels of precision in credit marketing.
• Open banking insights are becoming increasingly critical for financial inclusion and mitigating risk.