Premium leakage – whereby missing or misstated underwriting information leads to inaccurate rates, higher loss ratios or unexpected costs from claims – remains a big problem among UK property insurers.
Quantifying the risks of any given property at a profitable price point is challenging when the data used to support underwriting decisions is unreliable or difficult to obtain.
To avoid premium leakage, it’s becoming increasingly important that underwriters take advantage of the most accurate data and prefill solutions that provide them with all the information they need to ensure they’re assigning the correct premium to the insurance policies they issue.
In today’s marketplace there’s little room for error, and insurers can’t afford to carry the value of a residential or commercial property at a lower rate than its actual value. To help illustrate these challenges and how insurers might overcome them, here are five ways insurers are likely to suffer from premium leakage:
1. Omitting key building characteristics
Ensuring a property is insured to value requires underwriters to have access to data that’s not always immediately available or is difficult to quantify accurately.
Building characteristics are key rating variables and can have a material impact on the premium. As properties come in all shapes and sizes, it’s essential that insurers can verify this information quickly and efficiently.
Floor area is perhaps the most important variable when calculating the replacement cost of a building. The square footage of a building has a effect on all other aspects of the property and can give underwriters a better idea of how much they would have to spend on replacement building components.
Then there are other variables to factor in, such as building age, building height, and number of storeys, roof type, wall type, and the presence of basements. Building extensions are also common among UK households but can unintentionally be left out when calculating the value of a property and its associated risk.
Having missing or misstated information on any of these can mean that the premiums set for the policy weren’t appropriate at the time, and it’s the insurer’s bottom line that takes the hit.
2. Underestimating the cost to rebuild
The amount of insurance appropriate for a property should always be based on the cost to rebuild rather than its market value.
For example, non-standard materials or unique property characteristics may result in the rebuild cost of a property being higher than its market value, which means that a policy based on this could potentially lead to premium leakage at the point of claim.
The cost of rebuilding a property may be higher or lower than when an insurance policy was initially taken out and is dependent on numerous factors that can change over time.
The costs of materials used for reconstruction are also subject to change, for example, those imported to the UK and how this might potentially be affected by Brexit.
Insurers can’t afford to get building replacement costs wrong, as any deficiency will mean the property isn’t insured to value.
Replacement costs ideally should quantify both a property’s attributes and the building components needed for rebuild, factoring in the pricing for labour, materials, contractor overhead, and profit. Labour rates are another factor subject to change, and it’s important insurers keep abreast of these changes so there are no surprises at the claims stage.
Calculating replacement costs can be a laborious process for insurers, which is why external data sources that can help provide this information rapidly can give them that much-needed competitive advantage.
3. Not accurately assessing a property’s exposure to hazards
Underwriters need to be more mindful of the vulnerabilities to different perils within their property portfolios – which can each significantly impact loss ratios.
Many traditional policies consider perils on a combined, all-perils basis. However, this approach can often be to the detriment of both the insurer and the customer.
Whether its flood, storm, wind, escape of water, freeze, or subsidence, the perils that affect a property all behave very differently depending on the type of property and its location. Certain properties in one postcode may be more prone to burst pipe claims than another, or another group of properties may be more exposed to subsidence damage due to being situated on a soft band of clay.
The advantage of rating by peril, or cause of loss, is that it allows insurers to rate accurately, with a better evaluation of their true loss exposures. It provides insurers flexibility to rate policies adequately, increase market share, reduce loss ratios, and lower combined ratios.
With advanced analytics and risk models, insurers can look at a geographic area and see what types of claims typically occur there and how these change over time.
Using high-resolution spatial, natural hazard, and demographic data, insurers can easily grade postcodes and addresses into relative risk bands to help them increase the accuracy of their rating and drive underwriting results.
4. Using unreliable or unverified data
Analysing a commercial or residential property through on-site inspections or manually analysing imagery are both effective methods of ensuring that the data used to support underwriting decisions is reliable.
However, many insurers may not have the time or resources to carry out these procedures and must look elsewhere to verify their data. Often, they can obtain the information from third-party sources or directly from customers.
In many cases, a lot of homeowners simply don’t know all the information there is to know about their property, or they will take a guess, for example, for the building’s age or its roof type.
Insurers often operate under the assumption the information presented to them is factual. However, this can result in the premiums set being inappropriate. Or in the customer’s case, a claim might be denied on the basis the information provided is incorrect, whether the intention is accidental or potentially fraudulent.
Having access to prefill data from a third-party source can help not only to alleviate the guesswork but also largely reduce the time and effort required to obtain this information. Reliable property characteristics are an essential part of risk decision making, leaving substantially less room for error and reducing the vulnerability to premium leakage.
5. Not understanding the implications of occupancy type
For commercial structures, knowing what the building is used for is an essential part of understanding its associated risks and calculating the replacement costs.
Office buildings, warehouses, petrol stations, and recreational buildings are all built differently. For the replacement costs, having an idea of what the intended use of a property is can help underwriters understand how the building has been constructed and what materials were used.
Industrial classifications can give insurers an idea of the typical features within the building, for example, if it has a lot of walls, more kitchens, or more utility rooms.
While an office building will have many interior walls, a large warehouse will likely have very few. This helps provide an indication of the building characteristics and also the quality of construction. A storage warehouse is likely to have lower-quality materials used and less sophisticated methods of construction than an office block, for example.
Occupancy information is critical for underwriting commercial structures and affects a number of variables used for rating. It can be indicative of the types of activity taking place in the building, the number of people in the building, and the type of contents stored within, for example, machinery or chemicals.
To help classify business establishments by the type of economic activity they engage in, insurers can utilise external data sources to learn about a property’s occupancy details quickly and efficiently, for example, its Standard Industrial Classification (SIC) code, building use, and type of business.
Reducing the risk of premium leakage
To avoid premium leakage, insurers need to make sure the data they use to support underwriting decisions is complete and accurate. For more information on how Verisk’s UK underwriting tools might help you, please visit our UK General Insurance Market web page.