Guest Post: Lock It Down and Smarten Up – Best Practices for Online Security

By | October 17th, 2016|Quick Takes, Technical Posts|

This is a guest post from Zack Pumerantz, fraud prevention manager at FanDuel. At FanDuel, Zack is responsible for proactive investigation, chargebacks, reporting and training his quickly growing team of cyber crime specialists.  Zack's team brings to the table a ruthless drive to catch criminals, a focused approach and team chemistry reminiscent of the '96 Bulls. [...]

Fake Accounts and Real Big Trouble

By | September 15th, 2016|Quick Takes, Technical Posts|

Wells, wells, wells, what do we have here? Last week the news broke that Wells Fargo had “been hit with $185 million in civil penalties for secretly opening millions of unauthorized deposit and credit card accounts that harmed customers,” and the backlash has been harsh. While the ethical issues with the Wells Fargo scandal are [...]

A Guide To Hiring Your Fraud Team Part 2: Automate, Motivate and Innovate

By | September 7th, 2016|Meetups, Technical Posts|

Matching wits with a nefarious user. Solving a puzzle where you have to find missing clues. Determining what steps they’ll take next. Getting an adrenaline rush when hot on the trail of a bad guy. Protecting good customers and keeping them safe. These all describe a typical day in the life of a fraud analyst. [...]

Where to Begin – A Guide to Hiring Fraud Analysts and Building Your Team

By | August 17th, 2016|Meetups, Quick Takes, Technical Posts|

In my last post, I talked about technology and, in particular, components in a fraud-detection architecture. But when it comes to building a fraud strategy, it’s not just about technology. Perhaps equally, if not more, important are the people who analyze and review cases to catch fraudsters. This post is part one of a two [...]

Unsupervised Analytics: Moving Beyond Rules Engines and Learning Models

By | August 1st, 2016|Technical Posts|

Rules engines, machine learning models, ID verification, or reputation lookups (e.g. email, IP blacklists and whitelists) and unsupervised analytics? I've often been asked which one to use and should you only go with one over the others. There is a place for each to provide value and you should anticipate incorporating some combination of these [...]