Shane Latchman

The term “secondary perils” has become a thing lately, but what does it mean, if it means anything at all?

To help assess the resilience of the UK financial system, the Bank of England runs annual solvency stress tests and biennial exploratory scenarios for banks and periodic stress tests for select insurance firms.

The writer Will Storr states, “The unexpected signifies a change, and a change is where a story begins.”

Most coastal flooding in the UK is caused by extra-tropical cyclones (ETCs). The updated ETC model now incorporates storm surge and demonstrates more accurate event losses and a more certain view of risk.

When I hear the word "intuition," I think of something innate and untaught yet often improved by experience. Where we can get into trouble with our intuition is when we rely on it for things outside our experience.

Imagine two very different locations subject to every type of natural catastrophe. Which types of disaster do you think would cause the biggest difference in the loss at those two locations?

From my experience of explaining the concepts of catastrophe modeling, I've found that the ones associated with mathematics—and particularly with probability—are more difficult for audiences to grasp compared with, say, the scientific concepts associated with hurricanes and earthquakes.

In the winter of 2015/2016, three consecutive storms—Desmond, Eva, and Frank—brought severe flooding to the UK.

When it comes to the future, we can be certain about very little. We are all familiar with the success rate—or lack thereof—of weather forecasts.

After years of anticipation, preparations for the implementation of Solvency II in 2016 are now well underway in London.

Imagine you insure a set of locations spread out over an area. If you take a circle (radius of your choosing) and float it over a map of the region, at which point does it encompass the highest total accumulated exposure value? 

When I had to choose what I wanted to do when I grew up, my options were architecture and a math-based career like actuarial science.

They say you can't know where you're going if you don't know where you've come from. So as things are changing in the cat modeling world with new platforms that are faster, have more features, and are more intuitive than their predecessors, let's look back at how it all started.

Insuring high risk properties is a thorny issue in many regions and different countries have their own ways of dealing with it.

I got a real buzz out of attending "Understanding Risk," a week-long biennial conference hosted by the World Bank. London was this year’s venue, and the program offered a myriad of sessions and workshops. As the title suggests, the conference was focused on the understanding of risk across a wide range of hazards (including natural hazards).

To blend or not to blend, that is the question. Let’s say you have two sets of model results for the same exposure—should you combine them?

Gone are the days when analysts simply fed data into their catastrophe models and accepted the results at face value. Increasingly, model users expect to understand what goes on under the hood, and want to adjust the model machinery to modify results.

You can’t ignore it. Whatever your thoughts on causes and effects, the world’s climate is changing—and this has far-reaching implications for the insurance industry both now and in the future. That’s because changes in the climate and weather patterns have the potential to affect extreme weather events.

The term ‘non-modeled risks’ entered the insurance industry’s lexicon in a big way after a series of major natural catastrophe events in 2010 and 2011 led to significant losses from perils that had not been explicitly modeled. Catastrophe models were well established for Japanese earthquake scenarios in March 2011 when the Tohoku earthquake struck, for example, but none of the widely-available vendor models represented the potential for concurrent tsunami damage and losses at that time. Furthermore, commercial models for floods in Thailand were not available at the time of the 2011 flooding.

The insurance industry has seen a marked increase in the availability of tools to quantify the risk from natural catastrophes. Interest in them is considerable, as evidenced by the crowd that came to Lloyd’s of London in February for the launch of OASIS, an open access cat modeling platform.