Tan: Traditional rule-based fraud detection systems do not scale
Jason Tan · Jason Tan, Sift Science // Data Driven #26 // April 2014 (Hosted by FirstMark Capital) · May 27, 2014 · at 7:40
Jason Tan, CEO of Sift Science, discusses the limitations of legacy static rules in e-commerce fraud detection at Data Driven NYC.
0:00 / 0:06exact quote · 6.2s
▶ Watch the full episode on YouTube → 720p mp4 · rendered on demand · StarZero watermark
“So this is the way that things are done, is really building these rule-based systems that do not scale, okay?”
quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →
More from Jason Tan
Jason Tan: Email addresses containing digits have higher fraud rates
“If you have numbers in your email address, more likely to be a fraudster.”
Tan: Google generates $55B annually due to its search data lead
“They make fifty-five billion dollars a year, because they have so much data by being the number one search engine.”
Tan: Sift Science has 25 employees and 175 customers including Twitter and Uber
“We have 25 people out in San Francisco just closed our Series B recently, and we have about a 175 customers around the world, including Twitter, Square, Match.com, OpenTable, Uber, Airbnb, Kickstarter and others.”