Assessing the Impact of Building Type on Flood Risk

Flooding poses a major risk to communities in the UK and around the world. To better understand and manage this risk, it is vital that multiple datasets are incorporated within the flood tools used across all industries concerned with flood risk. This includes datasets that allow us to understand how vulnerability, such as building type, can impact the risk to a property.

What difference does building type make?

Not all flood is created equal. In fact, flooding can have different impacts on different properties due to a range of factors, a key one being building type. The vulnerability of a property to flood is significantly influenced by the property type and can play a major part in the risk of damage and loss.

For example, a residential stone-built terraced house will be impacted very differently at different flood intensities (depths) compared to a single-storey metal-clad commercial warehouse. This is not only due to the building materials reacting differently to the level of protection in the event of a flood, but also because of the contents likely to be found inside these buildings. A warehouse could contain high-value machinery, meaning this should be taken into account when considering flood risk.

The importance of vulnerability factors – such as the number of floors, whether a property has a basement, and building material – should not be underestimated when assessing risk, and it’s important to understand these when looking at the minimum hazard intensity (e.g., depth) above which damage is likely to occur.

JBA’s Built Environment (BE) Dataset helps ensure these factors are always taken into account and is a key part of our flood risk modelling.

So what is the Built Environment Dataset?

The JBA UK Built Environment Dataset contains information on the proportion of property types within a postcode, enabling users to compare residential terraced houses with second-floor flats, for example, or ground-floor office buildings with warehouses. It's derived from a range of data sources, mainly from property search and government data, and can be split into residential, commercial and industrial properties.

The postcode boundaries in the Built Environment Dataset are updated annually alongside our UK and Republic of Ireland Flood Map and Pricing Data updates.

How does JBA use BE data?

This dataset is used in multiple products, including our UK Pricing Data and UK Flood Model.

Pricing Data

Pricing Data™ enables technical risk pricing at a property and postcode level expressed as an Annual Damage Ratio (ADR) – essentially, it quantifies the annual cost of flooding to a property or postcode as a proportion of the total sum insured (an estimation of the property or postcode value).

When creating Pricing Data, the BE data is used to understand the proportion of property types within each postcode. As discussed previously, different property types have different vulnerabilities to flood - leading to different risk levels - which therefore generate different ADR values.

These different ADR values create a unique risk profile for each property and postcode, allowing users to compare these profiles to identify an accurate price for each risk. To create this dataset, vulnerability data is combined with our hazard datasets, which describe flood perils (river, surface water, coastal) in terms of location and depth, and exposure data, to produce a risk dataset, providing a view of the risk of flooding to specific properties or locations.

This enables insurers and reinsurers to further understand how the proportion of different building types in a postcode will impact the level of risk. For example, Figure 1 shows a seaside town, where we would expect a high proportion of shops and retail, which is what we can see in the commercial BE data.

Figure 1. Typical British seaside town with a high number of hotels, B&Bs and tourist focused retail outlets. This is reflected in the built environment data, with hotel and retail as the dominant commercial property types for this postcode

The BE data is also useful if an individual property type is not known to insurers during pricing, as it enables a proxy for this information and a more informed pricing estimate than using an unknown value.

UK Flood Model

JBA's UK Flood Model is used to understand correlation and accumulation of risk of loss across a whole portfolio of exposed locations.

The UK Flood Model uses the same Built Environment data; where a location within a portfolio is of an unknown structure type, the model’s logic creates, dynamically at runtime, postcode-level vulnerability functions derived from the proportions of risk types described in the BE for that postcode.

Again, this enables a more effective assessment of risk based on informed vulnerability data, often when structures are unknown to re/insurers when assessing risk.

Due to JBA’s modelling technology, which builds a model at runtime rather than from pre-built parameters, updates to source data such as the BE can be incorporated easily without requiring a full model rebuild.

For more information on our Built Environment Data, Pricing Data, and JBA’s market-leading UK Flood Model, get in touch today or check out our analytics to find out more about our work.