Using R to detect fraud at 1 million transactions per second
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In Joseph Sirosh's keynote presentation at the Data Science Summit on Monday, Wee
Hyong Took demonstrated
using R in SQL Server 2016 to detect fraud in real-time credit card transactions at a rate of 1
million transactions
per second.
The demo (which starts at the 17:00 minute mark) used a gradient-boosted
tree model to predict the
probability of a credit card transaction being fraudulent, based on attributes like the charge
amount and the
country of origin.
Then, a stored procedure in SQL Server 2016 was used to score
transactions streaming into the
database at a rate of 3.6 billion per hour.
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