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Using Advanced Analytics in the Insurance Industry-EDT (TRA55)

Allen Engelhardt

Monday, September 23, 2013 at 8:00 AM - Friday, September 27, 2013 at 12:00 PM

Using Advanced Analytics in the Insurance Industry-EDT...

Registration Information

Registration Type Sales End Price Fee Quantity
General Admission Ended $1,500.00 $9.95
Academic Admission Ended $1,000.00 $9.95
Student Admission Ended $500.00 $9.95

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Event Details

This is a 5-day class that runs for 4 hours + exercises

to accommodate multiple time zones, check your local time

8AM - 12PM EST

(Click here for the time in your local time zone)

  

This course covers the use of the R platform for statistical computing and data visualization within the Insurance industry focusing on non-life insurance (Casualty and Property) pricing.


Prerequisites: The students are expected to be comfortable using R and understand basic insurance concepts.

Target audience: actuaries and their teams in Casualty and Property (non-Life Insurance) industry

 

Course contents

Non-life insurance pricing is a well-known and well-established process and yet still a critical business issue. The standard for tariff analysis is generalised linear models. We first work through how to develop such a model in R, including model selection and validation. We touch upon how to deploy the model (both scoring using the model and updating the model itself) while ensuring the results remain validated and reproducible.

 

Next we show how easy it is to extend the model to more complex techniques, and the advantages and challenges of doing so. We cover the usual extensions of GLM to GAM and GLMM, and also dive into modern techniques and ensemble models.

 

From a business perspective we are in no way advocating wholesale abandonment of classical approaches for modern techniques, “black-box” or otherwise. Rather, we propose that you make use of both: continuity and understanding tempered with the results from the latest up-to-date methods. In the final part we cover some of these business issues to show how other insurers resolved them and what commercial benefits resulted. Examples include using the advanced models to restrict the validity domain of the classical approach (“risk we do not understand and will not insure”) and using them to create derived variables, such as interaction variables, to extend the domain of the GLM (“understanding complex risk”).

Course Modules

1. Introduction to pricing: the business problem and the data sets we will be using.

2. GLM - Generalized Linear Models: Independent claims with categorical rating factors.

  1. The basics: assumptions and a brief introduction to generalized linear models.
  2. Model details: tests, confidence, and model selection.
  3. Multi-level factors and credibility theory.

3. GAM - Generalized Additive Models: continuous rating factors.

4. GLMM - Generalized Linear Mixed Models: longitudinal claims.

5. Ensemble models: maximum predictive power.

6. Summary and recommendations.


Note that part 1-3 of the course covers substantially all the practical material of
Non-Life Insurance Pricing with Generalized Linear Models by Ohlsson and Johansson, the standard textbook for the European Actuary Academey. The book is recommended (but not required) for its deeper theoretical coverage. 

 


 

Disclaimer:

 

We have the right to cancel the event for any reason at any time. Revolution Analytics will refund all monies paid for ticket sales in full in the event of a cancellation.  We are not responsible for any travel related expenses incurred by attendees for this event. This includes but not limited to transportation, hotel accommodations or any other travel related expenses secured by the attendee, due to a cancellation on our part.

 

Cancellation Policy:

 

  • 30 or more days from the event date: Full refund less 10%
  • 16-29 days from the event date: 50% refund
  • 15 or less days from the event date: No refund

 

Note:

 

  • all related transaction fees PayPal and Eventbrite are not refundable
  • discount offers cannot be combined
  • A student ID Number is not a proof of full time university enrollment to get the student’s discount.  Proof of enrollment in 9 units or more on a current academic registration document will be required to receive the student's discount.

 

Have questions about Using Advanced Analytics in the Insurance Industry-EDT (TRA55)? Contact Allen Engelhardt

When

Monday, September 23, 2013 at 8:00 AM - Friday, September 27, 2013 at 12:00 PM


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