Posted: 20th March 2018
On the 1st March 2018, the Financial Conduct Authority (FCA) published its second set of data in relation to the general insurance value measures pilot.
This strand of work follows on from the FCA’s general insurance add-ons market study, which highlighted potential poor value in both add-on and stand-alone insurance products. The FCA introduced the value measures data as one of the remedies, as it noted consumers, firms and other organisations found it difficult to assess value within the market due to the lack of commonly available measures of value.
The FCA has committed to piloting the publication of value measure data to help address some of the issues. The data includes claims frequencies, claims acceptance rates and average claims pay outs by insurers, for four general insurance products:
- Home insurance (combined buildings and contents)
- Home emergency insurance
- Personal accident insurance sold as an add-on to motor or home insurance
- Key cover sold as an add-on to motor insurance
Christopher Woolard, Executive Director of Strategy and Competition at the FCA said:
“Publishing value measures data increases the range of information available about general insurance products. This will help increase market focus on suitability and value, as well as the headline price. We have already seen examples of where publishing the first set of data has incentivised insurers to make product improvements and focus more on overall product value.”
Key Findings from the data
The second set of data relates to 36 insurers and covers the year ending 31st August 2017.
The high-level data indicates that there have been positive measures taken by firms to ensure value for money is inherent in products. The increase in claims acceptance rate noted below, may suggest that firms are taking active measures to ensure customers who have a genuine claim on an insurance product receive the right outcome.
Home (combined buildings and contents) – Claims acceptance rate (CAR)
2016 – 89.06% to 91.88%
2017 – 92.05% to 94.47%
Home emergency (HE) – Claims acceptance rate (CAR)
2016 – 89.33% to 93.94%
2017 – 93.29% to 95.72%
Personal Accident (PA) – Claims acceptance rate (CAR)
2016 – 84.29% to 94.26%
2017 – 90.71% to 95.67%
Key Cover (KC) – Claims acceptance rate (CAR)
2016 – 80.0% to 84.9%
2017 – 85.0% to 89.9%
It is also worth noting that in relation to the other data points captured, claims frequency remains broadly static and the average claims pay out reduced for home insurance but increased for personal accident cover. Firms should be careful when reading into the data, as some spikes may be caused by seasonal fluctuations or other unrelated movements between time periods.
Overall however, it is clear that the regulator wishes firms to consider value for all products on an on-going basis and is using the combined pressure generated by publicity, potential changes in wider consumer behaviour and peer review to ensure firms actively review value.
Regulatory next steps
The data collected is part of a pilot exercise designed to allow the FCA to further develop measures and collect evidence of their impact on the market. This evidence will inform a decision on whether the FCA publish a consultation on new rules for firms in relation to reporting value measures data. Firms should also expect the regulator to take an active interest in understanding how firms have responded to the publication and participation in the value measures study.
Consideration for firms
Many firms are actively reviewing product value as part of product governance frameworks and processes. Considerations which should be asked as part of the product review process include:
- Do you have a methodology that uses a combination of different benchmarks to demonstrate how a product is performing? These could be financial or customer-based benchmarks, for example, within the life and pension’s space, performance against relevant indices and benchmarks, customer outcomes results, persistency and complaint volumes and within the general insurance market, the claims frequency ratio against policy volumes, the percentage of notified claims that are accepted, and the average sum paid out. Finally, and crucially, do you reconcile all of these metrics to form an objective view?
- In some scenarios, customers are paying more than others for the same service. Are the terms of this cross-subsidisation fair on the customer groups paying more? How does it impact on value for money and the final return on investment, and are customers who are investing in the same product experiencing different results?
- How do you examine whether the information needs of customers are being fulfilled? Customers should not only be engaged at the outset, but on a regular basis and at key trigger points during the life of the product. Do your outcomes test on the back of such interactions?