Behavioral analytics supports security, fraud detection, and AML models by detecting anomalies in user behavior on their devices, networks, applications, and data. Behavioral analytics empowers companies to establish a baseline for their user’s actions so they can detect a deviation from typical user behavior, which could be warning signs of a bad actor.4
Artificial intelligence (AI) and machine learning (ML), and data analytics often bolster behavioral analytics. For example, used together to analyze activity logs, companies could derive a trust score for each user based on the user’s normal behavior, compared to their past behavior, and how they compare to their peers.
If you’re interested in learning more about identity, fraud, AML, and behavioral analytics, listen to the Under the Hood podcast, season 2.
1. Association of Certified Fraud Examiners, Fraud 101
2. LexisNexus, Risk Solutions Fraud and Identity Trends Infographic 2022
3. LexisNexus, Risk Solutions Fraud and Identity Trends Infographic 2022
4. PYMNTS, PYMNTS Intelligence: Behavioral Analytics’ Role in Multilayered Fraud Defense Systems, February 11, 2022