Tuesday, June 25 | 3:35-4:50 PM
CPE: 1.5
Level: Basic
Recommended Prerequisite: None
Field of Study: Behavioral Ethics
In this session, industry experts will discuss the evolution of financial crime and how financial institutions can embrace innovative approaches to proactively prevent fraud and combat crime-ring activity. Learn how financial institutions can
leverage big data, machine-learning technology and 314(b) information sharing for effective fraud prevention. This includes proactive trend identification, reduction in false positive results and collaborative investigations of multi-institutional
crime-ring activity.
You Will Learn How To:
- Identify the limitations and challenges of conventional fraud prevention approaches that rely on limited data sets and approaches in today’s increasingly complex financial crime landscape
- Assess how financial institutions can leverage big data, machine-learning technology, and 314(b) information sharing to mitigate losses and prevent fraud
- Review a real-life crime-ring case, discovering how data and technology played a critical role to enhance detection, strengthen investigations and improve reporting to law enforcement
Scott Peddle
Product Manager - Payments Fraud, Verafin
Over several years at Verafin, Scott Peddle has excelled in a wide range of roles. This includes time as the leader of Verafin’s emerging threats research team and payments (wire & ACH) analytics team. These experiences have helped him develop an intimate knowledge of the challenges, and unique needs, faced by financial crime detection and BSA/AML compliance professionals at financial institutions across the country. He has been focused on the use on both AI and machine learning related technologies to help improve a financial institution’s effectiveness and efficiency in fighting financial crime.