Optimizing Risk Classification in Nth Party Relationships

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Presented by

Conner Reznicek, HackNotice; Sean McGovern, LogicGate; Steve Tobias, RiskRecon; and John Bree, Supply Wisdom.

About this talk

Understanding the intricacies of nth party relationships is paramount for effective risk management. Optimizing risk classification in nth party relationships entails a multifaceted approach geared towards enhancing visibility, comprehending dependencies, and implementing proactive risk management strategies. In this webinar we will delve into the concept of nth party relationships, the inherent risks involved, and strategies for optimizing risk classification in these relationships. Attendees will gain insights on: - Advanced machine learning methodologies and how they can enhance risk scoring and classification systems. - Strategies to integrate risk scoring and classification systems with diverse data sources, including fraud detection systems, ICT systems, and transactional systems, to foster a comprehensive view of data. - The benefits of implementing ongoing monitoring processes and increasing automation in forensic analytics processes, as well as integrating with blockchain technology for heightened security and data integrity. - How social media and text analytics can help augment risk scoring and classification systems by providing valuable insights into individual behaviors, entity interactions, and emerging events.
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