Home Authors Posts by David Speights, Ph.D., Daniel Downs, Ph.D., and Adi Raz, DBA

David Speights, Ph.D., Daniel Downs, Ph.D., and Adi Raz, DBA

David B. Speights, Ph.D., is the chief data scientist for Appriss, which provides proprietary data and analytics solutions to address risk, fraud, security, safety, and compliance issues. He has 20 years of experience developing and deploying analytical solutions for some of the world’s largest companies and government agencies. Speights was formerly first vice president of Mortgage Credit Risk Modeling at Washington Mutual and chief statistician at HNC Software. He holds a Ph.D. in Biostatistics from the University of California, Los Angeles, and has several patents. Daniel M. Downs, Ph.D., is the senior statistical criminologist at Appriss and has spent the last six years focusing on predictive modeling. Dr. Downs is an author, presenter and researcher, and has a vast background in loss prevention and criminology. Downs was a research coordinator for the Loss Prevention Research Council, where he engaged in fact-based research to develop loss control solutions to positively affect the retail industry. Downs received his Ph.D. in Criminology from the University of Illinois, Chicago, and his M.A. in Experimental Psychology from California State University, San Bernardino. Adi Raz, DBA, is the Senior Director of Data Sciences and Modeling at Appriss and has over 15 years of experience developing analytics solutions and modeling for the retail, healthcare, and public safety industries. Adi has spent many years developing predictive models for over 30 national retailers. She also analyzed, designed, and implemented analytical solutions designed to target the opiate epidemic and reduce risk for government agencies. She manages a data sciences and modeling team and is also responsible for analytical research and development. She received her B.S. in Economics and Statistics from James Madison University, her MBA from Pepperdine University, and a Doctorate in Business from Walden University.

RESEARCH: Retail Theft and Loss Prevention Analytics

Who shoplifts? There is no typical profile of a shoplifter. Based on our experience of interviewing offenders, shoplifters can be male or female, of any race, as young as five or well into their seventies.

Criminological Theory and Loss Prevention

This post is designed to provide a theoretical context for understanding the psychological and social forces that drive people to become criminals, how criminogenic opportunities can be reduced, as well as where analytics fits into loss prevention.

Integrating Analytics in Loss Prevention

The ability to assess patterns in data, measure loss prevention programs, and make decisions in real time is fundamental in solving complex issues related to customers, sales, and loss.

Experimental Design and Loss Prevention Programs

“Why do the iPads in the display area of the store continue to get stolen?” LP pros can conduct experiments to find out.

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