Tag Archives: Risk Intelligence

SiteIQ: More Power and Control for Your Underwriters

If on-the-ground underwriters can get risk insight instantly – and can make a quick check simply by entering a location rather than waiting for a risk analyst or trying to gather public data themselves, it has the potential to radically improve underwriting performance. We are seeing this change beginning to happen with SiteIQ, a recently launched application that utilizes the RMS open platform – Risk Intelligence™.

SiteIQ uses our trusted risk model data – the same data used across a client’s organization, to deliver hazard risk scores instantly for a location, to help underwriters make better decisions on whether to reject, accept or refer a risk for further analysis. Using the same risk data throughout means that new risks reflect a business’s acceptance criteria, bringing harmony to the book of business.

By making SiteIQ quick and simple to use, underwriters see it as a useful tool in their armory, knowing they can get valuable, modeled risk insight whenever they need it. The breadth of the instant insight adds to its usefulness, covering many available perils, with outputs including risk scores, loss costs – all presented in a highly visual, intuitive app.

We keep going back to users to find out how they are using SiteIQ and what they would like to see in terms of developments. And, in its first few months since launch, thanks to client feedback, RMS has now released the third iteration since launch – SiteIQ version 1.3.   

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ExposureIQ: Launch of the Next Generation RMS Exposure Management Application

RMS launches new exposure management application focused on the portfolio manager – ExposureIQ on the new cloud platform, Risk Intelligence™.

The role of a portfolio manager is a demanding one. It represents a high-wire balancing act between managing profitability and growth on one hand and keeping within exposed limits and minimizing risk accumulation and potential losses on the other. It is the portfolio manager who must uncover the “hot spots” if an individual line of business, geography, or risk type is looking under pressure as a loss driver – and highlight the “cold spots” where segments have growth potential.

They are always under the watchful eye of regulators and governance functions who need regular reports to show that the business is sticking to its stringent boundaries and limits. And if all this wasn’t enough, they are also on the frontline when a cat event strikes and on duty throughout to regularly update and reveal the impact of the event on the portfolio before, during, and post-event.

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New Era of U.S. Wildfire Modeling Begins with Risk Modeler

The last two North America wildfire seasons have seen total insured losses skyrocket to over US$23 billion – compared to 1991-2010 where average annual losses totaled US$600 million. Wildfire has staked its claim as a major U.S. peril, with events now consistently topping the multi-billion dollar mark. Four of the five all-time biggest wildfire events occurred in 2017 and 2018, and seven wildfires exceeded the US$1 billion threshold in this timeframe. 

When the WUI is Not Enough

Wildfire risk can no longer be managed through accumulation strategies, hazard zoning, or simple extrapolation of historical data because the fundamental drivers of wildfire risk are changing:  

All these factors mean that past losses cannot be easily extrapolated to predict future risk levels. Instead, the industry needs tools from a probabilistic catastrophe model to properly capture future wildfire risk. 

Wildfire risk is not limited to the Wildland Urban Interface (WUI) anymore. The figure below shows DINS (Damage Inspection) data from CAL FIRE overlaid on the burn perimeter for the 2017 Tubbs Fire in Northern California. Almost half of the destroyed structures in that fire came from areas considered to have no wildfire risk since they are in sub-urban areas classified as non-burnable by existing risk scoring methods. It is not sufficient to manage insurance portfolios with simple hazard zoning approaches. 

Figure One: DINS (Damage Inspection) data from CAL FIRE overlaid on the burn perimeter for the 2017 Tubbs Fire in Northern California
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Risk Intelligence 1.12 Release … and How to Democratize Your Data Using a JDBC/ODBC Connector

We are pleased to announce that RMS Risk Intelligence™ version 1.12 has now been released. This new release includes many improvements such as the introduction of new Structure Tags and Domain Data Tables related to items such as “Line of Business”, “Underwriting Group” and “Offer Type”. The release also includes an assortment of quality improvements.

With these Structure Tags, users can now sort and filter data in the Data Directory, delivering effective data organization capabilities on the platform. But while we realize getting your data into the platform is important – getting insights from your data off the platform is even more important. There are already plenty of options available to do this. You can get these insights from the user interface (UI), exporting your data via CSV files and our APIs. You can now use SQL or your own preferred tools to obtain deep insights into your data.

So, for the rest of this blog post, I want to give you a deep dive into a new, valuable tool available for Risk Modeler users on the Risk Intelligence platform that will help you generate reports – regardless of how you access your data or deliver your final report output.

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Exceedance: The Times They Are a Changin’

The opening keynote at Exceedance clearly set the agenda for this year’s conference – the future of risk. Karen White, chief executive officer for RMS, in her opening address, summarized the state of the risk management industry with one of her favorite songs – it just had to be David Bowie and “Changes”. But Karen asked what’s driving these changes, how do our clients see change, and how are they responding? Karen outlined how she had travelled the globe, (and clocked up hundreds of thousands of United MileagePlus points), talking to clients to get a clear-eyed view of what has changed and what to do about it.

Karen discovered that the catalysts for change had come from a wide range of sources, from how bad surprises are becoming, how new opportunities are motivating change, and how technology is changing approaches to risk. And it is a poignant time for RMS to look to the future of risk, as we celebrate and reflect on thirty years in business this year – and the birth of the nat cat modeling industry in 1989. Change has been constant in thirty years, but is now accelerating ahead, as Karen remarked that the next five years will define the future of risk.

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