The largest impact was experienced in Canberra which suffered from hailstones up to 6cm in size
PERILS has released the industry loss footprint for the January 2020 Australian hailstorms. The industry loss data covers the hailstorms which occurred between 19-21 January 2020 which amount to A$1.8 billion. The figure is based on detailed loss data collected from the majority of the Australian insurance market.
This report is released six months after the series of hailstorms struck the Australian states of Victoria, New South Wales, Queensland and the Australian Capital Territory. The event was unusual given that it impacted all three states and the Australian Capital Territory within a three-day period. The largest impact was experienced in Canberra which suffered from hailstones up to 6cm in size. Insurance losses during the three days were most severe in the Australian Capital Territory, accounting for 55% of the industry loss, followed by Victoria (25%), New South Wales (16%), and Queensland (4%). Across the affected areas, motor losses contributed 47% of the total industry loss.
PERILS’ earlier loss estimate of A$670m did not include motor, so the increase is primarily due to the inclusion of motor losses (A$849m), and a 44% increase in property losses (A$962m).
In this third report, a detailed breakdown of property and motor losses by postcode is provided, with the data further divided by residential and commercial lines and loss amounts split into buildings, contents and business interruption losses. It is complemented with information on damage degrees and hail intensities based on radar measurements by the Australian Bureau of Meteorology.
Darryl Pidcock, head of PERILS Asia-Pacific, commented: “This release is of particular market relevance as it is the first time hail motor losses, split into private and commercial LOBs, are included in a postcode-level loss footprint by PERILS. This follows the Australian insurance industry’s support for the inclusion of motor, a measure which will further enhance its understanding of underlying risks and enabling improvements in modelling. This is only possible due to that support from our insurance partners and we are grateful to them for providing their data.”