How Lloyd’s of London uses R for Insurance

September 15, 2011

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

Lloyd's is the world's leading specialist insurance market, and is often the first to insure new, unusual or complex risks. So it's no surprise that Lloyd's is one of the many companies that use R and its advanced capabilities for data analysis to help manage its insurance risks. At the useR! conference last month, Lloyd's analysts Markus Gesmann, Viren Patel and Gao Yu presented a poster "Using R in Insurance: Examples from Lloyds" showing how the insurance giant makes extensive use of R. After the jump you'll find examples from the poster of how Lloyd's uses R for performance management, exposure analysis, Monte-Carlo simulation, data visualization, reporting, and much more. 

Performance management

Lloyd's syndicates are compared to the market and against their individual business plans.

Performance management

Bespoke reporting

A combination of R and LaTeX is used to generate bespoke analytical reports for more than 80 syndicates. 


Exposure analysis and reinsurance

Lloyd's uses R to manage its exposure by analyzing reinsurance and catastrophic risk.

Exposure analysis

Lloyds also uses R to generate KML files, allowing analysts to visualize the exposure of geographic regions to disasters like hurricanes and earthquakes using Google Earth.


Interactive Data Visualization

Online analysis tools for the Statistics Relating to Lloyd's service were created using R and the googleVis package.

A general statistical toolset

Lloyd's also uses R as a general-purpose data analysis and visualization tool, as for example in this Monte Carlo simulation of loss distributions.


To leave a comment for the author, please follow the link and comment on their blog: Revolutions. offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: , ,

Comments are closed.


Mango solutions

RStudio homepage

Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training


CRC R books series

Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)