Fraud Detection using ML – Deep Dives with IIQF Experts

Session Focus:

“With commerce comes fraud” – Airbnb cofounder Nathan Blecharczyk

US Federal Trade Commission data show that consumers reported losing more than $10 billion to fraud in 2023 – an all-time high and a 14% increase over losses reported in 2022.

Fraud is not new. However, social media, internet-based commerce and digital banking have significantly changed the way fraudsters target victims along with exponential increase in the pool of potential victims.

In response to the increasing menace of online fraud, fraud prevention has increased in sophistication as well. Traditional rules – based engines have been supplemented by machine learning for spotting patterns.

This webinar addresses the key aspects of using machine learning / artificial intelligence for fraud detection / prevention.

Session Coverage:
Classical approach for fraud prevention
Advantages of data-driven fraud prevention
ML techniques for fraud prevention
Challenges of ML in fraud prevention
Required skills for fraud-prevention data scientists

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