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Computer technology has revolutionized the collection and use of massive amounts of data, and yet, somewhat ironically, it’s frequently harder to find what one actually needs. Aphorisms abound – “big data; the devil’s in the details; garbage in garbage out.” These are shorthand references to the problem, however, and they contribute very little to the efforts of those who are tasked with understanding the increasingly complex world that ever more sophisticated computers and programs create.

Brokers, insurers and reinsurers aren’t alone in trying to make sense of all of the technical data that they can obtain, but it’s become clear that determining what’s important, perhaps vital, from what’s not; i.e. “separating the wheat from the chaff,” to use another aphorism, has become increasingly important.

Pricing risks requires estimating potential losses, and the P&C re/insurance industry has come to rely on catastrophe models in order to do so. The problem is: “the devil’s in the data.” There’s either too much of it to be adequately analyzed, or there isn’t enough of it to assess the loss potential of any given risk with certainty.

Help, however, may be at hand. The announcement on May 6 in Lloyd’s Old Library by, a UK based company that it has the ability to examine, collate and refine massive amounts of data relevant to insured, or potentially insured properties, promises a breakthrough in how the P&C industry can use its cat models more effectively.

“Big data is the issue,” said Gavin Lewis, inhance’s commercial director in a telephone interview. “You need to look at the exposure data and the broker’s data, and there’s no real way of understanding [all of] that data; to determine how complete it is and how accurate it is.”

Lewis echoed the conclusion reached by Matt Foote, head of exposure and catastrophe management for Mitsui Sumitomo Å˽ðÁ«´«Ã½Ó³»­ Underwriting at Lloyd’s, cited in the press bulletin. He said: “Data quality is one of the industry’s most intractable problems, and we welcome initiatives like inhance which help us to isolate unidentified high risk properties and manage our exposures.”

Inhance is a product from ImageCat, which was developed with close support from the London Market. ImageCat is an international risk management innovation company, providing support services for the global risk and catastrophe management needs of the insurance industry, governments and NGOs.

It was formed in the U.S. in 2000 and opened its London facility several years later. The company specializes in post disaster loss evaluations, and has worked on assessments for catastrophes: Superstorm Sandy, the Japanese earthquake and tsunami, a number of hurricanes, including Katrina and Ike, as well as the Haitian earthquake.

Inhance uses the technology developed by ImageCat to asses pre-loss rather than post loss information. It isn’t involved in creating cat models, but in providing as much additional information as may be required by insurers, reinsurers, coverholders and, implicitly the insureds, to more accurately ascertain what the actual risk exposures are for any given region and the individual properties within it.

As an example Lewis, who has a background in spatial data and technology for the global insurance market, including leading the commercial markets and partner business for the UK’s Ordnance Survey, cited a 10-story building. In addition to its location and primary use – commercial, residential or mixed – “you need to know the construction type,” as well as the type of ground it’s built on; how near is it to the coast, or to a river; when was it constructed, as older buildings may not meet current code standards, and as many other details about the property as are ascertainable. If they aren’t then these “unknown unknowns” should be noted.

The more uncertainties exist for any given property, the higher the price for insuring the risk. In the aggregate this affects a re/insurer’s capital requirements, as more reserves must be maintained to meet potential losses, even if it can’t be determined what they might be. As a result, “better data lowers the cost of insurance and reinsurance coverage,” Lewis said. It also frees up additional capital, enabling the re/insurer to write more coverage.

The more information an underwriter has about any given risk, the more they narrow the parameters affecting that risk. This not only correlates more closely with the price charged for coverage, but also simplifies the application of the relevant terms and conditions to the contract.

More and better information can also affect regulatory and rating agency capital requirements, as it reduces uncertainty. This is of particular concern in Europe where Pillar 2 of the Solvency II regulations mandates ongoing risk assessments of potential losses and may require additional capital to cover them.

The system inhance presents appears highly complex, as one would expect in trying to assess individual risks throughout 168 countries for fires, floods, windstorms, earthquakes, volcanic eruptions, rising sea levels and a number of other perils. But, if the person using it knows what they’re doing, it can be accessed relatively easily.

Lewis explained that by opening and closing “modifiers” for any given property the information relative to that property can be determined. Each modifier relates to a specific risk relative to an identified property. Going back to the 10 story building, inhance’s modifiers provide as much information as may be available on the property, thereby giving a potential re/insurer as complete a picture as possible of the risks relevant to writing coverage on it.

Much of this information has been amassed by ImageCat from its post event analysis of more than 40 major disasters. “These post event datasets are exclusively available within inhance to help users understand the potential impacts of similar events on users’ property portfolios,” the press release announcing the launch of inhance explained. “Data for new catastrophic events will be made available within inhance for users to rapidly assess the impact of each new event on their risk portfolios.”

We “find risks,” Lewis said. “We gather the data from brokers and their clients, and identify the gaps in their information. We then go back to third party datasets.” These are primarily those provided by cat modelers, such as AIR Worldwide, EQECAT and RMS. “By doing that we fill in the gaps and verify what the [actual] exposures are. We improve data certainty.”

He also noted that this type of data examination is useful for MGA’s, multinational companies, who may be contemplating an acquisition, and ILS transactions, mainly cat bonds, as well as for brokers and re/insurers.

Beyond that inhance sources data from brokers such as Aon, from United Nations datasets as well as its own work using “remote data sensing.” Lewis explained that “we can achieve closer resolution to provide more detail to create datasets.”

The launch announcement also explained that “inhance has a unique pricing model in the world of catastrophe risk management. It offers three levels of subscription, including a simple, pay-per-use for corporates and small companies that offers access to global flood, earthquake, windstorm and many other perils, and non-catastrophe datasets from partners such as JBA Risk Management, Kat Risk and Kinetic Analysis Corporation, with more signing up.”

Inhance also said the new service will be compatible with the new non-profit loss modelling framework, Oasis, launched in January this year.”

Topics Catastrophe Agencies Data Driven Reinsurance Market Property Earthquake