
Credit in Focus
Credit in Focus unpacks the global complexities of credit risk across the customer lifecycle, from marketing and origination to account management, collections and recovery. Industry experts across the globe join the conversation to discuss actionable insights and emerging trends in credit risk management. Credit in Focus is brought to you by LexisNexis Risk Solutions, which helps organizations improve outcomes across the customer lifecycle by expanding existing assessment strategies with alternative data insights to gain a better understanding of consumer and small business credit risk.
Credit in Focus
Untangling Early-Stage Defaults and First-Party Fraud
In this episode, Kevin King, VP of US Credit Risk & Marketing Strategy, and Kim White, Senior Director of North America Fraud & Identity, dive deeper into the complex world of first-party fraud, building on insights from Season 1. They explore how early payment defaults (EPDs) can mask first-party fraud and why distinguishing between identity and intent-based behaviors is critical for lenders and risk managers.
The episode features a case study using clustering analysis to profile EPD drivers and offers actionable strategies for isolating fraud entry points and applying friction intentionally. You’ll also learn:
- Why early-stage defaults are a key signal of first-party fraud
- How to differentiate between identity theft, synthetic identity and identity manipulation
- How to design smarter, targeted defenses that balance loss prevention, customer friction and operational efficiency
Visit risk.lexisnexis.com for more information on credit risk and fraud and identity solutions from LexisNexis Risk Solutions.
DISCLAIMER: The information provided in this podcast is for informational purposes only and is not intended to and shall not be used as legal advice. The views and opinions expressed in this podcast are solely those of the speakers and do not necessarily reflect the views or positions of LexisNexis Risk Solutions. LexisNexis Risk Solutions does not warrant that the information provided in this podcast is accurate or error-free.
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