Re: DM: Comparision of Different Data Mining Methods in Insurance

[Joe Evans]

There is a case study of such an application, using the Clementine 
Data Mining System, at http://www.isl.co.uk/wint.html. Whilst not 
very technical, it does contain some discussion of the relevant 
issues. If you want a longer version, let me know and I can give you 
something a
bit more in-depth.

I hope this of some use.

Joe Evans
ISL

Jakob Laursen wrote:

> Dear colleague
>
> I am trying to find out whether there in practice have been made 
>any comparison of different data mining methods with the purpose to 
>predict damages in an insurance company respectively to predict the 
>additional sale and drop-out behavior as to direct marketing 
>activities.
>
> I am thinking of a comparision of e.g.
>
> · Logistic regression
> · Linear regression
> · Non-linear regression
> · Neutral net
>
> Which methods give notoriously the best stability as to a temporal 
>point of view.
>
> What is the difference in the different methods ability to predict 
>the customer behavior.
>
> Which method is the easiest to survey the effect of?
>
> If you have any practical experiences in comparisons in either 
>insurance or in marketing activities, I would be pleased to hear 
>from you.
>
> Yours faithfully
>
> Jakob Laursen
>
> Head of dep. f Analysis and Support
>
> ALKA Insurance
> Engelholm alle 1
> Dk 2630 Taastrup
> Denmark
>
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