Assigning Risk to Targets of Terrorism - A Location Intelligent Approach

By Joe Francica

Editor-in-chief Joe Francica interviewed Simon Sole, CEO of London-based Exclusive Analysis, and Ben Hirsch, director of business development for Insurance at Pitney Bowes MapInfo about a collaboration between the two companies.

Joe Francica (JF): Please provide a brief overview of your criteria for assessing risk by country or region. What percentage of those criteria would you say are related to certain location-based risk factors (environmental impact, susceptibility to natural disaster, regional politics)?

Simon Sole (SS):
Exclusive Analysis' core activity is forecasting violent and political risk globally. Within this purview, it is violent risk that is primarily location-based. It is true to say that war, terrorism or civil unrest always occur somewhere. When a bomb detonates or a riot breaks out, it occurs at a known location, meaning the event can be captured by a global Current Intelligence network and used within our models. Likewise, when we advise clients on the risk of terrorism, it is always possible to precisely define the location of the risk. This is exactly shown by the TerrorRisk product that allows us to precisely differentiate terrorism risk, right down to building level. Conversely, it is far more difficult to relate political risk (such as trade credit risk, nationalization, regime instability or contract frustration) to location, as it clearly does not apply to a specific point.

JF: Explain briefly a typical model that you would develop that would incorporate location-based risk factors.

Ben Hirsch (BH):
TerrorRisk and Pitney Bowes MapInfo location intelligence capabilities can be used in a variety of ways to analyze terrorism risk exposure.

For instance, TerrorRisk's 3,700 global points of interest, with their accompanying numeric Risk Values, can be added to MapInfo Professional where they can be layered in with an insurance carrier's existing policy portfolio in order to assess aggregate exposure to terrorism loss. Policy accumulations can be calculated around the points (for instance using rings or grids) and thematically mapped in order to locate terrorism risk "hotspots,' identify potential areas to setup exclusionary zones, or to flag regions where additional reinsurance coverage will be necessary.

For any given location, multi-ring studies can be used to model various loss scenarios that might result from terrorist actions at a given location and quantify what the impact would be to the carrier across its lines of business.

Another scenario would be to automatically load the TerrorRisk intelligence into a Web-based underwriting application created using Envinsa, or leveraging the Envinsa Online Services. The underwriter could view any policy up for consideration in relation to the TerrorRisk points (as well as any other policy risk factors of interest - for example, historic weather perils) to better rate the policy.

If an insurance company has a better understanding of its potential for loss in a given area, it is much further ahead of managing its risk than it was without this insight. The carrier can also more clearly demonstrate its terrorism risk exposure to rating agencies such as A.M. Best, which evaluate the carrier's preparedness in their supplemental questionnaire.

JF: How does mapping/GIS technology support your model development?

Geospatial analysis puts this layer of data to work to develop insight for making sound business decisions, something that has become known as location intelligence. Realizing the proximity to such exposures is a consideration in the underwriting of an insurance policy or the site selection for an asset such as a store or cell tower. Understanding how much exposure already exists in close proximity to a scored Point of Interest (investments such as mortgages, insurance coverage, or inventory) allows better enterprise risk management decision making, including business interruption planning, portfolio risk management, as well as insurance/reinsurance decision making.

JF: Are you assigning risk to certain land-based features?

The current iteration of TerrorRisk allows the client to understand the terrorism risk at specific targets. The next iteration, currently in development, assigns risk to entire cities, regions and countries with a progressive granularity that allows street-level risk differentiation in major cities.

JF: Are you assigning risk to weather or other random, transient phenomena?

Pitney Bowes MapInfo has developed its Risk Data Suite, which contains historical weather and geological event data to help underwriters, actuaries and risk managers to better assess exposure to "natural" perils. Risk Data Suite comes with aggregate exposure grids that can be used to help assign risk scores to properties and assets. Subscribers can also use the historic data (alone or in conjunction with other data they may have) to develop their own custom risk exposure grids in MapInfo Professional or other spatial applications.

Using the grid scoring approach, analysts are able to easily return a combined weighted score for a geocoded point. For instance, policyholder location based on historical propensity and severity of wind, hurricane, hail, lightning, flood, tornado, earthquake and other layers of data can be used in underwriting a business decision. MapInfo can also provide location intelligence solutions that incorporate real-time weather data (converted into polygons with associated weather severity ratings) and forecasts that can be used by insurance companies, call centers and disaster response hubs to better prepare for and respond to impending natural disasters. In insurance, both claims departments and reinsurance, financial reporting activities hinge on timely and accurate estimates of the potential impact of weather-related events.

JF: Are you assigning risk to man-made features like transportation, buildings, etc.?

The TerrorRisk dataset includes those targets that we consider at greatest risk of terrorism. Naturally, many of these potential targets are buildings - for example, government offices, abortion clinics, major mass transit hubs and so on. Additionally, targets that are at risk of attack but are not discrete points, such as rail or pipeline networks, present greater challenges of how to assign risk.

JF: Can you explain the interaction between spatial and non-spatial phenomena and how you would visualize this type of interaction of risk factors?

Clearly there are area-applied risk metrics, for example Chavez in Venezuela, or financial risks that are not geographically located to a specific position. These types of risks cannot be directly attributed to a particular target, but area factors do contribute to a number of input indicators that affect target selection.

JF: Does the Country Risk Evaluation and Assessment Model (CREAM) include a map interface? After clients use CREAM, are they provided both a written and map-based report?

CREAM is the industry-leading online facility. It models violent and political risk globally across asset type and location to provide actionable, intelligence-led forecasting for the effective management of commercial risks worldwide. The combination of our propriety intelligence methodology with our forecasting expertise sets Exclusive Analysis apart and has enabled us to build an international reputation as being at the forefront of strategic intelligence. It includes both spatial and non-spatial features.

Written material is split into 'Assessments' that provide a topical and/or thematic forecast of a particular issue in a given country and 'Risk Briefs' that provide a snapshot of the risk profile in each of these risk classes for all countries. Both forms of analysis are divided into risk classes and sectors to ensure a tailored service.

Metrics are accessible in the form of Risk Ratings. War, Terrorism, Civil Unrest and Political Risks are given numerical ratings on 30-day, one-year and three-year horizons that are designed to enable the comparison of different risks within a country, the same risk over time within country and the same risk between different countries. Spatial tools are focused on high risk countries, where CREAM models risk at specific asset locations using our innovative Interactive Country Risk Maps. Individual country maps can be enlarged and show "risk clouds" and level of risk generated by events in specific areas. The maps can also be customized to show the scale of risk by asset type, or the risk to key road and rail cargo routes.

Although the current joint offering of Exclusive Analysis and MapInfo, TerrorRisk, is limited to scored Global Points of Interest with continued updates and supporting advice, we have additional products and services planned for introduction to the market, including the Web-based CREAM services that we plan to offer as a Web service. Frankly, we have been careful not to overwhelm the market, as it is just now maturing to the whole prospect of developing location intelligence around terrorism and political risk as a part of everyday business. So, yes, CREAM includes mapping and we will be expanding these offerings to meet market demand which we already see evolving.

JF: Are your clients finding mapping technology beneficial and what elements do they see as helping them to best assess risk?

In insurance, retail, telecommunication and banking we have seen business people recognizing location intelligence as a required competency. Exclusive Analysis' partnership with Pitney Bowes MapInfo is augmenting the breadth of analyses that clients can employ in their daily business decision making. Our clients have found value in being able to go to one trusted location intelligence advisor that can provide all the necessary ingredients for them to be able to deploy a solution that meets their business needs. Pitney Bowes MapInfo can provide not only the software and data they need and ensure that it integrates together seamlessly, but also provide industry-specific experience in solving similar problems for other clients.

Mapping and visualization business users understand relationships between data in new and powerful ways. We've always known this, but have not necessarily had easy means to incorporate consistent and reliable geospatial analyses into existing business workflows. Web services has been a major enabler of this change. Let's not overlook the value of being able to use Web services to "feed" answers like "Is this location proximate to a TerrorRisk point of interest?" back to a system that will only involve a human if the answer is unacceptable and requires intervention. This is something that is revolutionizing the efficiency of decision making in the insurance industry.

JF: Would an actionable assessment of risk tell your client "where" the risk factor is highest and how do you define the accuracy of "where"? For example, can you assess the risk factor for the detonation of an IED in downtown Baghdad within blocks? Square miles?

The specificity and accuracy of the forecast to an extent depends on the risk being assessed and the intelligence available. For example, our Middle East analysts have identified a small number of very specific military and energy installations as being at significant risk in Bahrain - a country with an otherwise low terrorism risk profile. Conversely, large areas of Baghdad share a similar risk profile so the ability to differentiate IED risk on a street-by-street level is limited. It is also true that modeling risk in high-threat environments, such as Baghdad, necessitates different approaches to those applied to London or Manhattan. In Iraq, for example, a high event density (multiple attacks occurring per day) allows risk differentiation to be based heavily on event data. In Manhattan, where attacks are a rarity, a different approach to modeling is required; one based more on forward-looking intelligence and indicators, such as analyses of terrorist group intentions and capabilities.

JF: What is your intended future use or deployment of location-based technology to help you model risk?

While client demand and maturity will drive the product life cycle, there are several ways in which we intend to integrate location-based technology and modeling risk. One is to develop into the emerging markets. We are also looking to make location the portal for analysis, enabling users to search for intelligence and analysis against specific locations, accessible via maps. Location-based technology will let us relatively risk rate books of business; we aim to provide differentiated treaty risks ratings. Finally, location intelligence allows us to carry out advanced, asset-specific, location-specific analysis to provide accurate Monte Carlo simulation driven risk forecasts.

Published Thursday, September 6th, 2007

Written by Joe Francica

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