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September APEX:  Digging Into the Modeling Lifecycle
Multiple October 21, 2019 Posted in: Blog Posts, Apex Webinar, Predictive Analytics
On Pinnacle’s September 2019 APEX webinar, “Digging Into the Modeling Lifecycle,” we discussed the importance of understanding all of the steps involved in the modeling lifecycle—far beyond simple model construction. That includes understanding the business question, anticipating the potential constraints of implementation, and staying ahead of model usage from a change management perspective. Management of those issues are among the most critical contributors to the model’s best chance for success.
Michael Chen

When Preparation Meets Opportunity

Being ready when opportunity knocks.

When Preparation Meets Opportunity
My colleague at Pinnacle Actuarial Resources, Inc., Gary Wang, often says that he’s lucky. As a consulting actuary in the field of predictive analytics, Gary lives the exact life he envisioned for himself when he was a kid. I understand how Gary feels. We are fortunate to work in an exciting and expanding industry absolutely filled with opportunity. We get to work with great clients and tackle interesting projects on a daily basis. It’s an exceptional time to be in predictive analytics and I agree with Gary: We are incredibly lucky.
The Modeling Lifecycle—Don’t Break the Chain!
Greg Frankowiak June 19, 2019 Posted in: Blog Posts, Predictive Analytics
When it comes to advanced analytics such as building predictive models, many people immediately think about the vast amounts of data, computing horsepower needed, and very sophisticated (often mysterious) techniques applied to the data to produce the results. Without question, all of these aspects are important steps in the process. However, there are several other critical steps both before and after these that can truly make or break an advanced analytics project. We can think of this as the Modeling Lifecycle.
Cybersecurity
Amanda Conklin June 17, 2019 Posted in: Blog Posts, Cyber
During the recent Pinnacle University event, I discussed the growing challenges of the cybersecurity industry in today’s evolving technological world. The importance of advanced measures and practices and how actuarial modeling techniques can be applied to the cybersecurity industry were also discussed. 
May I Have Some Neural Networks with My Insurance Data, Please?
Machine learning techniques, particularly Artificial Neural Networks (ANNs), have enjoyed an upsurge in popularity and practical applications in a myriad of disciplines.  The explosion in the variety and volume of available data, coupled with cheap data storage and fast computing power, have placed ANNs front and center in data scientists’ tool boxes. 
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