Detecting Transaction Fraud

Detecting transaction fraud today requires real-time capabilities that legacy solutions don’t provide. Models can’t adapt to new and emerging patterns and limited access to data complicates decision-making, putting organizations at risk. 

During this webinar, data scientist and fraud expert Haibo Zhang from Crowe LLP and DataVisor’s CTO and Co-Founder Fang Yu explore key challenges in fighting transaction fraud and how DataVisor’s proactive approach changes the game.

Watch this webinar to learn how to: 


Three major challenges of transaction fraud

How combining supervised and unsupervised machine learning increases detection

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Learn How to Boost Fraud Detection

3 Major Challenges and a Proactive Way to Resolve Them

Real-world examples and insights from fraud experts

"DataVisor’s machine learning solution is the most critical component of our fraud defense as we grow in digital space, helping us minimize customer friction while defeating fraud risk."

Richard Cooney

Head of Fraud


Tom Shell

Head of Alliances, DataVisor

Fang Yu

CTO, Co-Founder, DataVisor

Haibo Zhang

Managing Director 

Crowe's Global Financial Crimes Data Analytics Practice