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Model Implementation—Begin With the End in Mind
Greg Frankowiak June 17, 2020 Posted in: Blog Posts, Predictive Analytics
Last year I wrote about a concept called the Modeling Lifecycle (Modeling Lifecycle). In that blog, I spent time addressing the many steps that are necessary for a predictive modeling project to be a success. Obviously, one of those critical steps is actual implementation of the model itself. Without that, you only have a fancy formula that doesn’t do much of anything for you. While insurers continue to devote more and more time and resources to predictive analytics, it would also benefit them to make sure they are devoting sufficient attention to model implementation.
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Commentary on NAIC’s Casualty Actuarial and Statistical Task Force White Paper – “Regulatory Review of Predictive Models”
Greg Frankowiak March 24, 2020 Posted in: Blog Posts, News, Predictive Analytics

While predictive analytics can provide significant benefits to insurance companies and customers, the rapid pace at which analytics is evolving and the relative complexity of some of the models used poses a significant challenge to state regulators who are charged with reviewing and approving such models. The National Association of Insurance Commissioners (NAIC) recognized this emerging issue and created the Casualty Actuarial and Statistical Task Force (CASTF), which has been charged with identifying best practices to guide state insurance departments in their review of predictive models for underlying rating plans. Over the course of the last year, the CASTF has released multiple drafts of the white paper “Regulatory Review of Predictive Models” for public comment. And comment the public has! Numerous letters have been submitted from trade associations, actuarial organizations, credit agencies, consumer groups and even insurance departments to provide their input on the lengthy white paper.

Commentary on Actuarial Standard of Practice No. 56 – “Modeling”
The Actuarial Standards Board (ASB) of the American Academy of Actuaries (AAA) recently announced the release of the new Actuarial Standard of Practice (ASOP) 56, entitled “Modeling.” This new standard will be applicable to actuaries governed by the AAA for modeling work performed on or after October 1, 2020.
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.
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