Major Manufacturers and Original Equipment Manufacturers (OEMs)

The insurance pricing trends for major manufacturers and OEMs in the first quarter of 2021 are based on:

Key rating factors

Underwriters consider areas including the details of the aircraft or equipment being manufactured, number of units being delivered, number of units in circulation, annual turnover, quantum of hull exposure during production, details of any requirement for test flights, limit of liability, loss history, and self-insured retention.

Insurance market notes

Prime manufacturers and OEM risks offer both high exposure and significant premium opportunity to insurers. There is significant catastrophe potential, and the exposure is also “long tail” as it exists through a product’s life cycle once it has entered service. Recently, the subclass has seen significant manufacturer’s hull and product liability losses, which have drawn considerable attention. A consensus remains among insurers that the premium base needs to be increased to a level deemed sustainable when considering past performance and ongoing exposure levels. Insureds must carefully weigh the optimum risk transfer structure against their ability to retain risk on their balance sheet.

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.