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Model Monitoring--Can You Afford Not To? Part 2
Greg Frankowiak August 06, 2020 Posted in: Blog Posts, Predictive Analytics
Depending on the number and complexity of models that exist for an insurer, model monitoring runs the risk of becoming overwhelming very quickly. A first step to building a solid model monitoring program is to catalog models in use, including any state-specific versions and assessing the relative importance of each. That could be assessed in a variety of ways including by the number of policies that a model potentially impacts, or the premium volume that a model has influence on. An insurer may also want to assess the complexity of the model and its potential stability. Combining all of the different characteristics helps lead to determining which models are most important to monitor first (relative priority).
Model Monitoring--Can You Afford Not To?
Greg Frankowiak July 16, 2020 Posted in: Blog Posts, Predictive Analytics
Continuing our previous deeper dive into certain aspects of the Modeling Lifecycle concept, this installment is the last entry in the lifecycle—model monitoring. While monitoring is the last step in the process, it is arguably one of the more important steps since it can send a modeler back to nearly every other earlier step in the lifecycle. However, model monitoring often receives the least attention.
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.

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.
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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