Predictive Analytics Times
Predictive Analytics Times
EXCLUSIVE HIGHLIGHTS
Exploring the Increased Significance of Third Party Data Within Big Data
 For today’s leading deep learning methods...
Dr. Data Show Video: Five Reasons Computers Predict When You’ll Die
  Watch the latest episode of...
How to Perfect Your Data Science Resume in 3 Easy Steps
 Breaking into the world of Data...
Robotic Modeler for Marketing Campaigns
 SUMMARY: Automated modeling is already in...
SHARE THIS:

2 years ago
Wise Practitioner – Predictive Analytics Interview Series: Darryl Humphrey at Alberta Blue Cross

 

In anticipation of his upcoming conference presentation, Claim Pattern Anomalies – Making a Mole Hill Out of a Mountain at Predictive Analytics World San Francisco, May 14-18, 2017, we asked Darryl Humphrey, Senior darryl-humphrey-imageData Scientists at Alberta Blue Cross, a few questions about his work in predictive analytics.

Q: In your work with predictive analytics, what behavior or outcome do your models predict?

A: Our scope is health, dental, and pharmacy benefit claims submitted by plan members and providers.  Our objective is to reliably gauge the probability that a claim, or series of claims, is / are fraudulent or represent abuse of the benefit plan.

Q: How does predictive analytics deliver value at your organization – what is one specific way in which it actively drives decisions or operations?

A: Obtaining strong evidence of fraud or plan abuse most often requires an on-site investigation and other labor intensive activities.  The result of our analytics materially increases the probability that these efforts will have a positive ROI.

Q: Can you describe a quantitative result, such as the predictive lift of your model or the ROI of an analytics initiative?

A: We have increased the financial recovery per investigation as the analytics indicates which of the behavioral measures are anomalous which facilitates more specific lines of investigation.

Q: What surprising discovery or insight have you unearthed in your data?

A: Random forest analyses indicates that some behavioral measures long-held to be important actually don’t contribute much to the differentiating provider claiming patterns.

Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World.

A:
Developing an in-house capability (analytics skills, business experience, and tools) has been more cost-effective than using a third-party and is providing a greater analytics depth, breadth, and agility.

———————

Don’t miss Darryl’s conference presentation, Claim Pattern Anomalies – Making a Mole Hill Out of a Mountain on Wednesday, May 17, 2017 at 3:30 to 4:15 pm at Predictive Analytics World San Francisco. Click here to register to attend. Use Code PATIMES for 15% off current prices (excludes workshops).

By: Eric Siegel, Founder, Predictive Analytics World

Eric Siegel is the founder of Predictive Analytics World (www.pawcon.com) — the leading cross-vendor conference series consisting of 10 annual events in New York, Chicago, San Francisco, Washington DC, London, and Berlin — and the author of the award-winning book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die – Revised and Updated Edition, (Wiley, 2016).

Leave a Reply