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Aerospace Insurance Market: Aircraft Maintenance, Repair, and Overhaul (MRO)

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

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

Key rating factors

Underwriter considerations include the maximum value of aircraft in the insured’s care, custody, and control; criticality of the works undertaken; the split between military and civil aircraft; the split between fixed wing and rotor wing aircraft; contractual indemnities in place; loss history; and limit of liability.

Insurance market notes

MROs combine a wide range of exposures, especially liability to third parties if an aircraft is damaged while in their care, custody, and control. In some instances, the value of aircraft on site can run into the hundreds of millions of dollars, a major accumulation risk for insurers to consider. Longer-tail products liability exposure is a factor as litigation remains possible long after an aircraft has left the MRO and returned to service. Some exposures can be contractually limited, but MRO is regarded as “loss active” by insurers due to the high frequency of claims compared to other subclasses.

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.