Every Fraudster Has a Tell

In this session, participants explore techniques used to detect fraudulent activities by analyzing behavioral data. The session will cover common fraud tactics, such as identity theft, phishing, and account takeovers, and will demonstrate how irregularities in user behavior can be indicators of fraud. By examining case studies and utilizing data-driven approaches, participants will learn to recognize the red flags of potential threats early on. Attendees come away with an understanding of how to apply real-time monitoring and machine learning algorithms to detect anomalies that deviate from expected behavior. Participants will be introduced to techniques for identifying outliers in data, developing behavioral profiles for typical users, and implementing automated systems that flag suspicious activities. The session will also focus on how to assess risk levels and prioritize responses based on the severity of the threat. Speakers also review mitigation methods, such as implementing multi-factor authentication, limiting access to sensitive data, and enhancing fraud prevention policies.