How to Maximize Data Used to Fight FraudSplunk's Jim Apger on Streamlining Omni-Channel Defenses
The data being used to drive effective anti-fraud efforts can be rich in context and useful for other activities. Jim Apger of Splunk describes emerging fraud schemes and solutions, highlighting the role of machine learning.
In a video interview at Information Security Media Group's recent Breach Prevention Summit: Washington, Apger discusses:
- How to maximize data from anti-fraud efforts;
- Machine learning's emerging role;
- Advice for streamlining anti-fraud efforts across channels.
Apger, a senior security architect at Splunk, is a member of the firm's global security specialists team. His digital hardware and software background paved a path for him to spend nearly 10 years in the network intrusion prevention space. Previously, Apger worked in the fields of web fraud detection, anti-money laundering, security information/event management, security operations and cyber threat intelligence.