Aerospace Insurance Market: Air Navigation Service Providers (ANSPs)

The insurance pricing trends for ANSPs in the first quarter of 2021 are based on:

Key rating factors

Underwriter considerations include the limit of liability required; frequency of takeoffs, landings, and overflights; air traffic density; flight paths being handled; training provided to staff; and loss history, including near miss data.

Insurance market notes

Historically, insurers viewed ANSPs as attractive risks based on low loss frequency compared to other sectors. Although major incidents have occurred, losses were infrequent and allowed insurers to project a “payback” period. An increased focus on the inherent catastrophe exposure, such as a midair collision, coupled with increasing liability settlements, has tempered insurer appetite. Insurers are less willing to delegate authority to facilities, and while loss performance remains stable, the consensus is that the overall premium base compared to capacity deployed is inadequate. Insurers are seeking to increase the base premium while reducing line sizes to mitigate their maximum exposure in the event of a catastrophe.

Premium trends

The data analysis is derived from the aggregation of hundreds of discrete insurance renewals for aerospace organisations. The de-identified sample set is global and encompasses results from organisations of all sizes, varying claims records, and a range of lead insurers. It should not be read as a guide in terms of what to expect at renewal, but rather an illustration of the general market trend.

Methodology

We use three types of calculations within the chart.

1. Weighted premium average: Total the premium spend per quarter, then map the percentage difference between corresponding quarters in different years.

2. Mean average: Take the percentage difference in premium between renewals for each account, sum the percentage differences, and divide by the number of percentage differences.

3. Rolling average: Accumulate data for the last four quarters and divide by four to get a rolling mean average.