[R-sig-ins] General Insurance Data

Thu Oct 2 21:38:21 CEST 2014

Indeed.
http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=2&f=G&l=50&co1=AND&d=PTXT&s1=metarisk&OS=metarisk&RS=metarisk
Thanks, Mark.

On Wed, Oct 1, 2014 at 10:14 PM, Mark Shapland <mark.shapland at milliman.com>
wrote:

> Dan,
>
> I haven't been following this thread, but your comment on patents caught
> my eye.
>
> I am not an attorney either, but I think the patent law changed within the
> past 10 years to allow ideas to be patented. In fact, Guy Carpenter
> recently (within the past few years) filed for and received something like
> 22 patents on their reserving software. Reading the patent application it
> looks to me like only one of the patent items is an original idea from Guy
> Carpenter. It also seemed like everything they received patents for would
> have already been covered by copyright laws. If you are interested, you
> should be able to do an internet search for their patent application or if
> you can't find it I'm sure I have a copy someplace.
>
> Mark
>
>
> Mark Shapland, FCAS, FSA, MAAA  |  Senior Consulting Actuary   |
> mark.shapland at milliman.com
> Milliman   |  Liberty House, Unit 809, Level 8  |  Dubai International
> Financial Centre  |  Dubai P.O. Box 506784   |  United Arab Emirates
> Main +971 4 386 6990   |  Fax +971 4 386 6950   |  Mobile +971 56 179 1532
>  |  milliman.com
>
>
>
>
> -----Original Message-----
> From: r-sig-insurance-bounces at r-project.org [mailto:
> r-sig-insurance-bounces at r-project.org] On Behalf Of Dan Murphy
> Sent: Thursday, October 02, 2014 12:35 AM
> To: Brian Fannin
> Cc: R-Sig-Insurance at R-Project. Org; Edward Roche
> Subject: Re: [R-sig-ins] General Insurance Data
>
> I don't agree, Brian, that that's the question I'm begging.
>
> I don't have all the details, but the story goes that a while back (pre21st
> century?) an actuary tried to patent an actuarial method/calculation that
> he/she invented. I can't even remember if that attempt was successful. But
> the actuarial community was against such endeavors. I'm in that camp,
> having learned on my daddy's knee that you can't patent an idea. (He was
> not a patent attorney!)
>
> OTOH, Apple Computer (and others) made a business out of patenting the
> look and feel of their products, including their software. (E.g., I cannot
> zoom in on an Instagram photo on my android phone, but last night was
> demonstrated the three-finger-tap to do it on an iphone!) I don't believe
> the tool that creates the look and feel is germane to the patent, but I'm
> not a patent attorney either.
>
>
> On Wed, Oct 1, 2014 at 10:42 AM, Brian Fannin <BFannin at redwoodsgroup.com>
> wrote:
>
> >  That begs the question of which tool you prefer for a GUI? I’ll
> > confess that it’s fairly easy to knock something together in Excel.
> > However, I’d like to move to something that has more natural support for
> forms.
> >
> >
> >
> > *From:* Dan Murphy [mailto:chiefmurphy at gmail.com]
> > *Sent:* Wednesday, October 01, 2014 1:22 PM
> > *To:* Brian Fannin
> > *Cc:* Christophe Dutang; Edward Roche; Markus Gesmann;
> > R-Sig-Insurance at R-Project. Org
> >
> > *Subject:* Re: [R-sig-ins] General Insurance Data
> >
> >
> >
> > Thank you for that reference. Looks nice. More than the original
> > poster was looking for?
> >
> >
> >
> > IMO, open-source is a great vehicle for distributing the guts
> > engineering that accommodates data exchange and munging. OTOH, I'm not
> > convinced that open-source is the right vehicle for distributing the
> > "look and feel" of a GUI. But I'm "open" for persuasion. :)
> >
> >
> >
> > Dan
> >
> >
> >
> > On Tue, Sep 30, 2014 at 10:37 AM, Brian Fannin
> > <BFannin at redwoodsgroup.com>
> > wrote:
> >
> >  Can’t believe I forgot to mention that! I remember the presentation
> > and it looks to be a very powerful tool. The integration with LaTeX is
> > particularly nice.
> >
> >
> >
> > *From:* Christophe Dutang [mailto:dutangc at gmail.com]
> > *Sent:* Tuesday, September 30, 2014 11:30 AM
> > *To:* Brian Fannin
> > *Cc:* Edward Roche; Markus Gesmann; chiefmurphy at gmail.com;
> > R-Sig-Insurance at R-Project. Org
> >
> >
> > *Subject:* Re: [R-sig-ins] General Insurance Data
> >
> >
> >
> > On the GUI part, there is a private software RPGM (
> > http://www.pgm-solutions.com/) offering what Edward is looking for.
> >
> >
> >
> > This tool was presented at the r in insurance conference this year also!
> >
> >
> >
> > It is partially developed by an actuary.
> >
> > Christophe
> >
> >
> > Le 30 sept. 2014 à 15:25, Brian Fannin <BFannin at redwoodsgroup.com> a
> > écrit :
> >
> >  Edward,
> >
> >
> >
> > If I’m reading your message right, the problem seems to break down
> > into two parts: 1) reshape claims data, either by aggregating
> > individual claim amounts or reshaping data from wide to long. 2)
> > Provide a GUI to guide the user through the process of munging the data
> so that it may be analyzed.
> >
> >
> >
> > On the first point, it would be helpful to identify a typical
> > structure which must be modified. MRMR doesn’t have a function to go
> > from wide to long as that’s a very simple melt command. The data I use
> > in my work lives in a RDBMS in long format, so I’m sorted. I’ve toyed
> > with the idea of a “collapse” function that would aggregate data along
> > temporal dimensions, or summarize across a hierarchical axis (i.e. sum
> > all of the territories into a single country). Such a function would
> > be general enough that it could summarize individual claim
> > transactions, though that’s likely better done by a database server.
> >
> >
> >
> > One the second point, note that an absence of a GUI is a universal
> > issue with R. However, it’s worth emphasizing that this issue also
> > exists with Excel. A comfortable user interface which permits users to
> > flag columns as development, or origin period or whatever, must be
> > constructed by hand. Dom Yarnell’s EBDEx tool was a great example of
> > this. Shiny is a powerful option for a user interface to support the
> > kinds of transformation you describe. It’s possible to upload and
> > download files and there are a number of user widgets for
> > identification of the structural elements of data. One may also
> > display some basic ggplot type graphics for basic exploratory
> > analysis. I’ve started a project called “shout” which will eventually
> > be a GUI for MRMR. It’s been dormant for about three months, but have
> > a look- or have a look at Shiny apps in general- and see if that’s a
> direction that makes sense.
> >
> >
> >
> > Do you have a GitHub repository list where others can contribute? Mine
> > may be found here: https://github.com/PirateGrunt/.
> >
> >
> >
> > Also, have a look at XLConnect. RExcel actually requires a commercial
> > license, whereas XLConnect is GPL 3. XLConnect allows one to read and
> > write to/from Excel files. This is what I use for the “write.excel”
> > method in MRMR.
> >
> >
> >
> > Regards,
> >
> > Brian
> >
> >
> >
> > *From:* Edward Roche [mailto:ed.roche at yahoo.co.uk
> > <ed.roche at yahoo.co.uk>]
> > *Sent:* Monday, September 29, 2014 7:19 PM
> > *To:* Brian Fannin; 'Markus Gesmann'; Christophe Dutang;
> > chiefmurphy at gmail.com
> > *Cc:* R-Sig-Insurance at R-Project. Org
> > *Subject:* Re: [R-sig-ins] General Insurance Data
> >
> >
> >
> > Hi All,
> >
> > Thank you all for your responses. What I have in mind is a package to
> > help with the initial stage of getting claims data into R and ready to
> > use (formatting etc) before any modeling is done. Effectively to
> > provide a workflow for working with actuarial claims data.
> > My past experiences, using GI reserving projection programs, have
> > usually involved a stage to summarise the data in some format then
> > later feed this data into a program, be it a proprietary program or one
> of the R packages.
> > The key stage I wish to contribute to here is where the data has to be
> > fed in to R. MRMR and ChainLadder do allow for reshaping of the data
> > (and loading data) but I would like to build on the functionality in
> > these packages while not reinventing the wheel. I will take some time
> > to digest the MRMR package as this does seem to have a lot of
> > functionality that I could use for manipulating the data.
> >
> > A package providing a workflow to get data into a basic tabular
> > structure would act as a stepping stone for getting claims data
> > available and cleaned for use in packages such as ChainLadder or MRMR.
> > It would even be easier to perform other more basic analysis. As I see
> > it at the moment when someone gets to the stage that the data is
> > loaded and formatted in R they are basically ready to go and use MRMR
> > or ChainLadder *but* this is a very big hurdle for novice R users who
> > typically have data stored elsewhere (SAS, SQL Excel or other flat
> > files). Even moving from Excel to R, where data can be stored in
> > objects as opposed to tables is a giant leap in its own right and I
> > fear this is the stage where a lot of novice R Actuarial users are
> > lost or lose confidence in R. I am not a professional programmer and I
> > am not very knowledgeable about different types of connections or
> > porting files from one format to another so I was hoping to leave that
> > up to packages such as RODBC or xlsx. My idea is to provide a workflow
> > structure to load claims data into a data.table using a simple GUI
> > interface. Its worth mentioning, I have come across RExcel which
> > allows you to call R from Excel but what I am talking about is
> > somewhat different in that your using R as the backbone, rather than
> > Excel, for storing and manipulating the data. This would at the same
> > time leave the data in familiar tabular format but helper functions
> > could pivot the data and allow novice R users to create triangles
> intuitively or extract useful representations such as latest diagonals
> cumulative data, in year data etc.
> > It would still be easy to manipulate the basic underlying data
> > structure if desired as it is just a data.table but helper functions
> > would give it intuitive Actuarial functionality. The goal would be to
> > reduce the time to close to zero for a novice R Actuarial user to go
> > from using existing data (e.g. Excel or SAS) to a data object that
> > could then be passed to ChainLadder, MRMR or ggplot2.
> > The package Rattle,, has a lovely GUI interface for loading data. I
> > have something like this in mind to get people started. A GUI
> > interface could be used to specify key fields and formats such as
> > origin period etc. The data stored in R as a data.table would still be
> > in a very familiar tabular format and look similar to what novice R
> > users are used to when they have worked with data stored elsewhere in
> > SQL, SAS or Excel files.  This would provide a bit of reassurance  to
> > get working in R. It would also facilitate novice R users to plot the
> > data using ggplot or googlevis, reshape it, summarise it in tables for
> > printing and you also get the benefit that the data.table structure is
> quite efficient for working with big in memory data.
> >
> > My recent background is claims reserving in a GI company and claims
> > data is what I have initially in mind to tackle. Other data such as
> > pricing data, time series etc would also certainly lend themselves to
> > more specialised Actuarial data structures and I think I could work on
> > these down the road.
> >
> > From my description above the package might just sound like its to
> > load and format the data. This is a non trivial exercise for novice R
> > users and such a package would reduce the barrier for people adopting
> > R especially at work. At the optimistic end of the scale I also think
> > it could make development data analysis accessible to non Actuaries
> > and could even be useful in other fields. I would love the help from
> > anyone that is interested in contributing as I am working on this solo
> > at the moment. I wish to work a bit on a basic proof of concept first
> > and when I get it working I will load it to git hub and post some links
> to this mailing list.
> > I wanted first to check that such a package does not exist but it will
> > take a bit of time to get something useful and working. I also
> > appreciate any comments, contributions or feedback.
> >
> > Thanks again for the help
> >
> > Regards
> > Edward Roche
> >
> > On 29/09/14 02:03, Brian Fannin wrote:
> >
> > 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
> > <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> <
> 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> <
> 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
> >
> >
> >
> > _______________________________________________
> >
> > R-SIG-insurance mailing list
> >
> > R-SIG-insurance at r-project.org
> >
> > https://stat.ethz.ch/mailman/listinfo/r-sig-insurance
> >
> >  _______________________________________________
> >
> > R-SIG-insurance mailing list
> >
> > R-SIG-insurance at r-project.org
> >
> > https://stat.ethz.ch/mailman/listinfo/r-sig-insurance
> >
> >
> >
> >
> >
>
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