On Higher Ground: Predicting Flood Costs in the UK

By Alun Jones, Ph.D.

Water views can be attractive so long as the viewer’s feet remain dry. But for homeowners living in flood zones, seasons of higher waters are always a pressing concern. And for insurers performing the underwriting on homes and other structures, concerns about flooding only seem to multiply. Damage costs incurred due to flooding vary significantly depending on the age and type of property involved. Such detailed information isn’t commonly available in the United Kingdom—and that can hamper efforts by insurers to accurately predict the potential costs of flooding at the property level.

Availability of a new property-level database of age and type may now offer insurers the ability to correctly identify the potential cost of damage for individual properties and therefore more accurately estimate total potential costs for their entire portfolio. In fact, access to detailed property information—not just about location—can help improve underwriting, claims management, and risk modeling across the insurance industry.

Many insurers, intermediaries, and reinsurers are aware of the potential costs of flooding and price a policy accordingly. That price is likely based on property location or proximity to a flood risk zone, whether coastal, fluvial, or surface water. Thanks largely to years of work by the Ordnance Survey in the United Kingdom, flood modelers and insurers can more precisely know the location of properties and whether they reside in a flood zone. Many insurers have modeled the risk at the postcode level; now they’re moving toward modeling this risk at the individual property level. That may mean the problem of flood risk location has been solved.

Depending on address, different costs

But what’s next? Do insurers treat possible damage as equal across all properties in the same flood risk zone? If location and the risk are the same, is insurer response the same? Are repair costs the same? Probably not, unless all properties are identical. But it’s safe to say that not all properties are equal. A report from the Flood Hazard Research Centre (FHRC), an interdisciplinary group based at Middlesex University in London, clearly shows variations in flood damage costs between different types of properties and different ages (see the following graph).

Flood Depth graph table

Note: Graph created from tables presented in MCM-Online.co.uk. Flood Hazard Research Centre, Middlesex University, London.

FHRC has determined the 2013 repair costs (shown here for a flood depth of 0.1 meter) for a short-duration flood period with different types of properties and ages, along with the residential sector average damage cost (dotted line). The research shows that even within one age group, there’s variation in damage costs between property types and across different property ages.

Detached properties dating from before 1919 exhibit the highest damage costs, at about £29,591 ($37,550 in U.S. dollars*). The average for each age group varies; and that means using a single figure or a simple trend to predict damage, such as older properties with higher damage costs, tends to produce inaccurate results.

A terrace house from the period between 1945 and 1964, for example, has one of the lowest damage costs, at £5,921 ($7,514*), well below the age and sector average. The residential sector average damage cost is around £10,500 ($13,327*) as shown by the dotted line, but using such an average will again likely lead to incorrect individual property damage costs because many ages and types vary about this figure.

Insurers understand that age and type of property are significant factors in flood damage costs—in addition to the time that their policyholders are out of their homes. But do insurers realize that accurate age and type data is available to model correctly and help predict potential loss costs?

Bridging the data void

Insurers have found that relying on property age and type information from policyholders tends to be risky. Property age and type is available in the UK census, although the information is grouped to show house types as a percentage of an area that commonly contains more than 1,000 properties. That can be very misleading when trying to work at the property level or even postcode level. The UK government releases data on property age or type only at a very coarse level, so accurate and detailed property age and type data at the address level for the UK isn’t readily available.

Verisk Analytics has worked on a UK-wide buildings database that provides information at the address level—for both residential and nonresidential buildings. The database includes the following information:

  • age
  • type
  • construction type
  • roof type
  • number of floors
  • number of bathrooms/bedrooms (residential)
  • floor area
  • basements (due for release in 2017)

Such work has shown the variability of property types across the UK at the individual property level, revealing significant variations even within one street. Looking at the sample map below, it’s easy to see that even within this small area—just a few streets and postcodes—all properties are within the flood zone and may previously have been treated as equal in terms of damage. And yet the property age and type differences show that conclusion likely isn’t realistic.

UK Buildings

UKMap and UKBuildings ©The GeoInformation Group 2015. Contains public sector information licensed under the Open Government Licence v3.0. Contains OS data. ©Crown copyright [and database right] (2015). Contains Royal Mail data. ©Royal Mail copyright and Database right (2017), Contains National Statistics data. ©Crown copyright and database right (2015)

The flood zone, provided by the UK Environment Agency in this example, shows late Victorian terrace houses (light blue) right next to post–World War II terraces and semis (purple). Those properties sit next to interwar-period terraced and detached houses (pink), and every property is within one street (and postcode) of each other. Even so, we now know there can be a damage cost variation of some £5,000 ($6,346*) between the various types of properties. Getting this analysis wrong for one property might be manageable, but mishandling it for hundreds or thousands of properties is a costly mistake and one that insurers can now avoid.

The availability of age and type data at the property level offers insurers the potential to correctly identify the cost of damage for each individual property and therefore the total costs for their entire UK portfolio. Having detailed property-level information—and not just about location—can only help improve and refine underwriting and claims management across the industry.

As insurers implement the UK Flood Reinsurance scheme, they have additional information beyond the council tax band. That data should help them identify new build properties, better determine potential damage costs, and decide whether they wish to transfer those properties into the program. Location does matter, but deeper-level property information matters just as much. Now, insurers can have a trove of data at their fingertips to more accurately determine potential losses due to flooding.

*U.S. dollars on January 1, 2017

 

Dr. Alun Jones

Dr. Alun Jones is director of underwriting solutions at the Cambridge UK office of Verisk Analytics.