Business Intelligence SIG: Five Ways Predictive Analytics Cuts Enterprise Risk
Five Ways Predictive Analytics Cuts Enterprise Risk
All business is an exercise in risk management. All organizations would benefit from measuring, tracking and computing risk as a core process, much like insurance companies do. Predictive analytics does the trick, one customer at a time. This technology is a data-driven means to compute the risk each customer will defect, not respond to an expensive mailer, consume a retention discount even if she were not going to leave in the first place, not be targeted for a telephone solicitation that would have landed a sale, commit fraud, or become a "loss customer" such as a bad debtor or an insurance policy-holder with high claims.
In this presentation, Dr. Eric Siegel will reveal:
-Five ways predictive analytics evolves your enterprise to reduce risk
-Hidden sources of risk across operational functions
-What every business should learn from insurance companies
-How advancements have reversed the very meaning of fraud
-Why "man + machine" teams are greater than the sum of their parts for enterprise decision support
Eric Siegel, Ph.D., is the founding conference chair of Predictive Analytics World – the leading cross-vendor commercial event – as well as Text Analytics World, and the President of Prediction Impact, Inc., providing analytics services to mid-tier through Fortune 100 companies. An expert in data mining and predictive analytics, Dr. Siegel served as a computer science professor at Columbia University, where he won the engineering school’s award for teaching undergraduate and graduate courses. At Columbia, he advanced data mining technology in the realms of machine learning performance optimization, text analytics and data visualization. Dr. Siegel also cofounded two New York City-based software companies for customer/user profiling and data mining.
Dr. Siegel is the instructor of the acclaimed training program, Predictive Analytics for Business, Marketing and Web, and the online version, Predictive Analytics Applied. He has published over 20 papers and articles in data mining research and computer science education and has served on 10 conference program committees.
6:30pm - 7:00pm - Registration & Networking
7:00pm - 8:30pm - Presentation