PERILS, the Zurich-based organisation that provides industry-wide catastrophe insurance data, has released its third loss estimate for the Australia Christmas Storms, estimating the insurance industry loss at AU$1.563bn (US$1.044bn).
The storms occurred between 23 and 29 December 2023, driven by a low-pressure system and its associated cold front, which collided with hot, humid, and unstable air masses over the East Coast of Australia.
This caused an extended period of severe convective storm activity, including large hail, intense winds, flash floods, and tornadoes. These conditions impacted Queensland, New South Wales, and Victoria.
This new estimate represents a slight increase from PERILS’ second loss estimate, issued three months after the event, pegged at AU$1.547bn. Its initial loss estimate, issued six weeks after the event, was AU$1.395m.
Darryl Pidcock,
Head of Asia Pacific at PERILSData was collected from the majority of the Australian insurance market to produce the estimate. The loss information in this third report provides a breakdown of property and motor hull losses by postcode and is also divided further by residential and commercial lines.
Personal lines property losses account for 72% of the total industry loss, commercial lines property losses account for 17%, and motor losses represent 11%.
Queensland was the most affected state, contributing 71% of the total industry loss. New South Wales and Victoria contributed 24% and 5%, respectively.
Darryl Pidcock, Head of Asia Pacific, commented, “Australia experienced a relatively benign period of major natural catastrophes in 2023 in comparison with previous years.
Notwithstanding, it highlights the increasing risk not only of severe convective storms along coastal regions but, as we observed in this case, the potential for competing air pressure systems prolonging storm activity over an extended period.”
PERILS will provide an updated estimate of the market loss from the Australian Christmas Storms on 2 January 2025, twelve months after the event’s end date.
