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Aerospace Insurance Market: Aviation Refuellers

The insurance pricing trends for aviation refuellers in the first quarter of 2021.

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

Key rating factors

Underwriter considerations include the limit of liability required, whether into-plane refueling takes place, type of aircraft refueled, presence of a Tarbox agreement, geographical split of operations, and loss history.

Insurance market notes

Historically, insurers viewed refuellers as an attractive risk based on relatively benign losses. There were typically numerous insurers available to offer coverage for refuellers on a 100% basis, or as part of capacity aggregating facilities/consortiums. Insurers’ attitudes to refueling risks has become more cautious; while loss performance remains better than other subclasses, insurer consensus is that the overall premium base compared to capacity deployed is inadequate. Pricing increases are being disproportionately applied to smaller refuellers that require a high limit (such as US$1 billion). Insurers say this is needed as they seek to increase the minimum premium charged for the limit/capacity deployed.

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.