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Connecting the Dots of Insurance Fraud Using Graph Analytics
In The State of Insurance Fraud Technology (2019), the most recent report published by the Coalition Against Insurance Fraud (CAIF) and the SAS Institute, nearly 75% of survey participants experienced a rise in fraudulent claims in the past three years. This represents a disturbing 11% increase since 2014. The survey was based on 84 primarily property and casualty insurers. None of the participating insurers indicated that fraud had decreased significantly during the same time frame. As a consequence of the rise in fraudulent claims, insurers are moving away from traditional formulaic business rules and red flags for identifying fraud. Instead, insurers are enriching their data analytics arsenals to include more sophisticated tools, methods and means to investigate fraud.  
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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.
Work in SAS? Two SAS hacks I use every day (and you can too)!
Hannah Kaufmann October 09, 2019 Posted in: Blog Posts, Predictive Analytics
This past May I was able to attend the SAS Global Forum in Dallas, Texas. Like many in our industry, I work in SAS software every day. SAS is considered by some an industry standard data and analytics application. I was grateful to be able to attend the sessions in Dallas alongside thousands of other users, and learn so much more about SAS software tools and approaches.
AI and the Insurance Industry: A new white paper
At Pinnacle Actuarial Resources, we focus on innovation and thought leadership with a goal to make sure our clients remain ahead of the technological, economic and related forces shaping our profession and the insurance industry. Artificial intelligence (AI) and machine learning are two of those forces.
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.
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