A review of recent weather history paints a picture that is painfully familiar to insurers. According to Glenn McGillivray, managing director for the Institute for Catastrophic Loss Reduction (ICLR), the incidence of catastrophic events has nearly quadrupled over the past five decades, with meteorological and hydrological events increasing from fewer than 50 in the 1960s to more than 160 in the most recent decade.
The cost of catastrophic events to Canadian insurers topped $1 billion each year from 2009-2013, and is expected to be well over $900 million when all 2014 calculations are completed. During the period from 2009 to 2014, the Canadian insurance industry paid out more than $8.52 billion in severe weather-related claims arising from events with total claims value of more than $25 million.
This accelerating exposure to catastrophe risk isn’t causing insurers to exit the market, but it is prompting changes in how they conduct business, according to McGillivray. “We’re seeing changes in product – for example, we’re seeing some companies take a look at things like sewer back up coverage… we’re seeing increases in deductibles and premiums, of course…and some companies may be looking at where they choose to write business,” he notes.
To support this business transformation, many insurance providers are looking to invest in technologies that can help improve financial performance through better management of risks, such as flooding.
One way to connect information technology (IT) to the catastrophe management needs of the insurance industry is through location-based intelligence. These are systems that Steve Sigal, vice president of product management for DMTI Spatial, defines as “business intelligence plus geography.”
In the case of insurance, information generated by this technology enables insurers to make real-time business decisions based on “the location of the property in context of all of the things around that property,” Sigal notes. This could affect decisions on whether a specific application should be approved, including proximity to flood zones, earthquake zones, underground perils or other important contextual factors.
Location-based intelligence systems can support better decision processes within an insurance firm in a number of ways, while accelerating and enhancing both communications with clients and information exchanges involving insurers, third-party adjusters and reinsurers. The first entails making a complete set of important data available to insurers, and presenting it in a way that enhances decision and communications processes.
To deliver comprehensive information, location-based systems are built through the layering of hundreds of different data sets. This data provides intelligence that is critical to insurers: it provides accurate mapping of policyholder or policy applicants’ real estate, identifying issues that may affect risk assessment associated with a property.
For example, is it within a 1/20, 1/100, 1/200 or 1/1500 flood zone? What is the property’s elevation relative to potential flooding in the area? Is it high enough to escape the water in the event of a flood? How close is it to potential problem sources, ranging from those that are easily seen in an aerial view (such as railroad tracks) to those that require a deeper understanding of the landscape, such as the locations of buried fuel tanks?
The data is delivered to insurers through a visual interface that plots each important item on a map display, enabling system users to quickly grasp the relationship between a particular property and critical location factors.
This combination of very rich data and intuitive presentation supports multiple levels of analysis, and can be used across an insurer’s business and throughout the customer relationship. When an application is received, the data can be used for scoring. Applications requiring review can be assessed on screen with a multi-layered understanding of all relevant risk factors. Insurers can also obtain aggregate insights from the data to inform underwriting.
This same information can be used to help manage claims. As McGillivray explains, these kinds of systems “could be very helpful in managing the claim process,” especially when insurers are responding to large scale events. As an example, he described the Calgary flood of 2013, when firms had to respond to large numbers of claims. “Location-based data would help [insurers] come up with a plan and work through the logistics of dealing with large numbers of people in short amounts of time,” he says..
Location-based intelligence systems offer other logistics benefits, too. In addition to highlighting high-priority accounts and claims, location-based intelligence systems can help insurers understand the effect of a catastrophic event on staff, business branches and other resources. It can tell a manager which employees will be able to come to work and which branches can be opened, while helping the company direct remediation resources to the areas of greatest need.
Location-based understanding can also help support business-to-business communications within the insurance industry supply chain, providing all parties with the detailed information they need to make rapid, accurate decisions on claims. Using location intelligence capabilities, an insurer can understand which claims its own adjusters can handle, and which they should assign to the third party adjusters.
At the same time, the system contains information that can be helpful to reinsurers, who are (according to McGillivray) increasingly likely to demand detailed data from primary insurers. A ‘single version of the truth’ that is accurate and rooted in the relevant geographic data helps to improve response times and reduce costs throughout the system.
If location-based intelligence provides answers to so many insurance questions, why aren’t location-based intelligence solutions deployed by all insurers? McGillivray remarks that there are always “leaders, followers and those somewhere in between” in every industry – insurance is no different. Large companies have substantial budgets for technology, as well as in-house weather, earthquake and GIS experts who can deliver some of the insights available via location-based intelligence solutions. Smaller firms likely lack these specialized staff, and have a greater need for third-party services.
From this perspective, McGillivray believes that cloud-based solutions, which offer access to a wide range of resources and have low up-front investment requirements, may help to facilitate adoption. Cloud-based systems can be accessed in the field, providing real time, mobile intelligence to adjusters who may be coping with the effects of catastrophic events.
In the end, this technology may be the key factor that drives adoption of location-based intelligence within a broad swath of the Canadian insurance industry. By connecting deep information with rapid and ubiquitous communications, these systems enable all parts of the insurance ecosystem to reduce costs, respond faster and provide better customer service whether an event affects a home, a neighbourhood or an entire region.
Mary Allen and Michael O’Neil are principals in InsightaaS, a Toronto-based consulting firm that analyzes trends in technology and the benefits of IT-based business strategies.