Detecting Transaction Fraud

3 Major Challenges and a Proactive Way to Resolve Them

Watch this webinar to learn how to: 

  • Three major challenges of transaction fraud
  • How combining supervised and unsupervised machine learning increases detection
  • Real-world examples and insights from fraud experts

Learn How to Boost Fraud Detection

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.


Fang Yu
CTO & Co-Founder
Haibo Zhang
Managing Director
Crowe's Global Financial Crimes Data Analytics Practice
Tom Shell
Head of Alliances

Trusted by Leading Brands

About DataVisor

DataVisor is the leading fraud and risk management platform powered by transformational AI technology. Using proprietary machine learning algorithms, DataVisor restores trust in digital commerce by enabling organizations to proactively detect and act on fast-evolving fraud patterns, and prevent future attacks before they happen. Combining advanced analytics and an intelligence network of more than 4B global user accounts, DataVisor protects against financial losses and reputational damage across a variety of industries, including financial services, insurance, marketplaces, ecommerce, and internet platforms.