[R-sig-ins] General Insurance Data

[Brian Fannin]

Edward,

It may not be exactly what you're looking for, but MRMR could have some things you might like. My primary aim was to develop a package which made data manipulation for loss reserving a bit more efficient. However, it has application in a more general context as well. It begins with a clear, robust yet flexible notion of an origin period (accident/underwriting/report year). For each origin year, one may store measured observations, which have an arbitrarily complex set of dimensions. For example, written premium is allocated to territory, line of business, currency, etc. For loss reserving, we go a step further and allow those measures to change at regular evaluation points.

That's that for the data structure. I've tried to build in reasonable support for simple multidimensional/multivariate visualizations. I've got a lot more work to do here, but it's a good start. There's also a new generic method "write.excel" which stores information to a spreadsheet in a reasonable way. This is a pragmatic feature to facilitate data exchange with folk who aren't yet using R. The loss reserving methods presume a linear model framework with chain ladder as a special case. We use mixed effects regression for "loss reserving with credibility".

Attached is a very short vignette which may help you to understand how the package is meant to be used. I'm happy to talk more about it, if you're interested.

Note that I'm describing features on the development version of MRMR. The CRAN version is more limited. I hope to get the new version submitted and approved before the end of the year.

Regards,
Brian Fannin

-----Original Message-----
From: Markus Gesmann [mailto:markus.gesmann at googlemail.com] 
Sent: Sunday, September 28, 2014 6:36 AM
To: Christophe Dutang
Cc: Edward Roche; R-Sig-Insurance at R-Project. Org; Brian Fannin
Subject: Re: [R-sig-ins] General Insurance Data

Hi Edward,

Have you looked at Brian Fanin's MRMR package, http://cran.r-project.org/web/packages/MRMR/index.html or https://github.com/PirateGrunt/MRMR? 
The package provides quite a bit on infrastructure for dealing with triangle like data.

Regards

Markus

On 27 Sep 2014, at 14:08, Christophe Dutang <dutangc at gmail.com> wrote:

> Dear Edward,
> 
> To my knowledge, there is no single package doing data manipulation in the insurance context.
> 
> There are package for manipulating from database manager and other 
> proprietary softwares : see 
> http://cran.r-project.org/doc/manuals/r-release/R-data.html
> 
> Maintaining the CASdatasets package, I face to some of your problem to read SAS or excel files. Typically the case, where there is a separator for thousand. I did write some R functions :
> - readfunc(filelist, yearlist, sheetname, pattern, nrow, ncol, 
> colname, col2conv, echo=FALSE, row2rm=NULL) : read a list of excel 
> file to extract the same sheet and concatenate the whole
> - str2num(x) : convert a character string to a numeric dealing with 
> thousand separator
> - concatmultcol(df, nbinfo, nbblock, col2foot, col2conv, col2rmpre, 
> cm2rmpost, cname2trunc=NULL, echo=FALSE) : concatenate blockwise data into a rowwise dataframe etc...
> In such function, I read excel files with gdata package.
> 
> As you say, for manipulating triangles, there are functions in ChainLadder. By the way, I propose cum2incr and incr2cum to M. Gesmann. Another function shrinkTriangle was not kept in this package: this function computes an annual triangle from a monthly or quarterly basis.
> 
> For manipulating string, there is a good book by Gaston Sanchez, see 
> http://gastonsanchez.com/work/
> 
> At the last R in insurance conf, there was a good presentation of data manipulation (see http://www.cass.city.ac.uk/news-and-events/conferences/r-in-insurance-2014/r-in-insurance,-conference-programme and ask for presentation file).
> 
> Do you have a detailed list of what type of data you want to 
> manipulate? for which purpose? (is it only for reserving purpose?) If you are willing to create a package, I will be happy to contribute.
> 
> Regards, Christophe
> -
> Christophe Dutang
> LMM, UdM, Le Mans, France
> web: http://dutangc.free.fr
> 
> Le 27 sept. 2014 à 01:16, Edward Roche <ed.roche at yahoo.co.uk> a écrit :
> 
>> Hi all,
>> I am interested in a package for working with General Insurance data, i.e. something that deals with the initial stage of getting GI data into R, reshaping it and subsetting it before performing projections using packages such as ChainLadder or claim development visualisations using googlevis.
>> 
>> When working with GI data before you can do any meaningful analysis or projections you need to get your data in the right format. Typically you might start with incremental long format data showing claim transactions and this needs to be reshaped and summarised into triangle matrices (e.g.  paid and incurreds). You can then perform projections with packages such as ChainLadder or other simple development methods. This initial manipulation stage is not always easy to do especially for novice users of R. There are helper functions in the ChainLadder package such as incr2cum, as.triangle etc that let you perform conversions on the fly but I cant find anything for the wholesale restructuring or manipulation of GI data such as converting it from Annual Quarterly to Annual Annual etc. This type of manipulation is very easy to do in some proprietary software (not R based) that I use on a daily basis.
>> I am considering working on a package that would generally provide helper functions to load untidy GI data into R and let a novice R user perform restructuring and manipulation on the fly.  I envisage a GUI such as is available in Rattle to load the data and specify the key variables and formats. Once the data is loaded intuitive helper functions would let you manipulate it on the fly. For example you might wish to pick out paid and incurred triangles, subset the data in some way or convert it to Annual Annual or from cumulative to incremental.
>> 
>> My question for this mailing list is are there any such packages out there? or is anyone working on something like this? I would love to get involved if so. Any other thoughts?
>> 
>> Thanks
>> Ed
>> 
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