The Financial Conduct Authority’s upcoming reforms to general insurance pricing are likely to have a substantial impact on the UK insurance industry, with many insurers re-evaluating their own approaches to pricing home and motor policies.
By refocusing their efforts on new data sources and analytic models insurers can help improve risk segmentation and repair any underwriting margins that are adversely affected by these changes.
Many home and motor insurers have invested a lot of time and effort in developing price optimisation models which measure a customer’s sensitivity to price changes and propensity to renew as well as the likely prices offered by competitors.
These models have been created to maximise underwriting margins over the lifetime of the policy. Some customers have benefitted from this because they shop around and take advantage of the discounts available in the first year with an insurer. However, other customers that are less likely to shop around could potentially be paying higher prices as a result.
After much consultation and debate, the FCA suggested that some insurance providers were increasing prices in the home and motor for loyal customers that renew with them year on year, and has ruled that customers renewing should not have to pay more than someone who is new to that provider.
The regulator also suggested that some consumers are not getting their general insurance products at a “fair value” and is introducing product governance rules and data reporting requirements to help tackle this. Pricing, auto-renewal and data reporting measures will come into effect on 1st January 2022.
Given the looming regulatory changes, climate related changes, along with COVID-19 and changing patterns of consumer behaviour, there is a strong incentive for insurers to review the underlying component of their pricing models. By refocusing their efforts on new data sources and analytic models insurers can help improve risk segmentation and repair any underwriting margins that are adversely affected by these changes.
Price optimisation through better data
Developing insurance products at profitable price points can still be achieved by incorporating more granular data and analytics to assess risk more accurately.
For property, address-level models are paving the way for more precise risk assessments. Individual property risk and their associated perils can vary drastically from one location to the next. Being able to capture that information can vastly improve risk selection and ultimately underwriting profitability.
Changing weather trends can help identify areas with increased vulnerability to flood, storm, and subsidence when previous claims history are not sufficient. Escape of Water is a persistently high source of claims, which is likely to get worse with remote working and an increased load on plumbing systems.
For motor insurance, there are many useful indicators of consumer behaviour and risk which could help identify gaps in coverage or improve pricing. Examples of this include mileage data, MOT warnings, change of ownership, imports, and write-offs. More granular data is also starting to emerge on technical vehicle data such as ADAS data and safety ratings, as well as location-based risk by postcode.
One method of ensuring insurance is provided at a fair value to consumers is by accurately assessing each of the risks that would be covered by a policy at a more granular level, using data and analytics to support the decisions behind them.
Verisk offers a whole suite of advanced analytics and data sets focused on property and motor underwriting, perils risk modelling, quote enrichment, and more. As regulatory pressure continues, having a reliable source of information about the nature of risk at an individual level will be critical to achieving consistency and fairness in risk evaluation.
Learn more about Verisk's home and motor solutions.