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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2016/09/fraud-detection.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>In <a target="_blank" href="https://channel9.msdn.com/Events/Machine-Learning-and-Data-Sciences-Conference/Data-Science-Summit-2016#fbid=ltiG0C0MZyl">Joseph Sirosh's keynote presentation at the Data Science Summit</a> 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. </p>
<p><a target="_blank" href="https://channel9.msdn.com/Events/Machine-Learning-and-Data-Sciences-Conference/Data-Science-Summit-2016#fbid=ltiG0C0MZyl"><img title="Ignite" alt="Ignite" src="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b8d22235a1970c-800wi" border="0"></a></p>
<p>Later in the keynote (starting at 25:00), John Salch, VP of Technology and Platforms at <a target="_blank" href="http://www.pros.com/">PROS</a> describes using R to determine prices for airline tickets, hotel rooms, and laptops. PROS has been using R for a while in development, but found running R within SQL Server 2016 to be 100 <strong>times</strong> (not 100%, 100x!) faster for price optimization. &quot;This really woke us up that we can use R in a production setting … it's truly amazing,&quot; he says.</p>
<p>It's great to see these global-scale applications of R, driving the intelligence of businesses behind the scenes. As Joseph said in the opening, &quot;If there's one language you should learn today … it's R.&quot; </p>
<p>Channel 9: <a target="_blank" href="https://channel9.msdn.com/Events/Machine-Learning-and-Data-Sciences-Conference/Data-Science-Summit-2016#fbid=ltiG0C0MZyl">Microsoft Machine Learning &amp; Data Science Summit 2016</a></p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://blog.revolutionanalytics.com/2016/09/fraud-detection.html"> Revolutions</a></strong>.</div>
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