Fraud Management & Cybercrime

Using Machine Data Analysis to Detect Fraud

Jade Catalano of Splunk Discusses Early Detection Methods
Jade Catalano, senior product manager, Splunk

Connecting the dots between disparate forms of machine data can prove to be valuable in discovering fraud patterns, says Jade Catalano of Splunk, who explains how.

In a video interview at Information Security Media Group's recent Fraud & Breach Prevention Summit: Toronto, Catalano discusses:

  • How to recognize fraudulent activities in your environment;
  • Getting started in monitoring for fraudulent patterns in machine data;
  • Data capture recommendations for financial institutions.

Catalano is senior product manager at Splunk. With more than 10 years of cybersecurity experience, she has most recently been focusing on anti-fraud efforts.


About the Author

Nick Holland

Nick Holland

Director, Banking and Payments

Holland, an experienced security analyst, has spent the last decade focusing on the intersection of digital banking, payments and security technologies. He has spoken at a variety of conferences and events, including Mobile World Congress, Money2020, Next Bank and SXSW, and has been quoted by The Wall Street Journal, CNN Money, MSNBC, NPR, Forbes, Fortune, BusinessWeek, Time Magazine, The Economist and the Financial Times. He holds an MSc degree in information systems management from the University of Stirling, Scotland.




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