Multiple Australian Insurers - 95% flood prediction accuracy in Brisbane, Australia
In 2011, severe floods hit Queensland, Australia, causing an estimated A$2.38 billion damage to the city of Brisbane and the surrounding area. More accurate flood data could have helped reduce damage and allowed for a better prepared emergency response.
The Challenge
The existing national flood dataset used by the Australian government proved to be highly inaccurate in predicting the extent and duration of the flooding. It was based on a commonly used dataset which proved to be nowhere near as accurate and comprehensive as it needed to be.
Our Solution
We carried out a validation test using actual inundation data and comparing the flood profile predictions from the commonly used national dataset as well as the data from our own 1-in-100 year
Flowroute-i™ model.
Our model was considerably more accurate, achieving around 95% accuracy as opposed to just 37% in the older model. In simple terms that means our data missed just 1 in 20 damaged properties whilst the other dataset missed almost 2 in every 3 of the properties which flooded.
The Outcomes
The data we produced forms part of our Australia FloodMap™ which covers every Australian capital city at high resolution and the entire country at lower resolution. It provides the most complete view of flood risk available today, enabling underwriters, planners and others to make far better decisions and improve control over losses.
The Brisbane flooding of 2011 left 38 people dead and 200,000 people affected.
Australia FloodMap™ The most complete view of flood hazard in Australia enables underwriters, planners and others to make better decisions and improve control over losses.
Australia FloodCat™
Improve capital allocation, strengthen flood underwriting strategy and optimise your reinsurance with Australia FloodCat™.
Flood Modelling
Our own Flowroute-i™ proven flood modelling software helps us predict flood risk with 85% accuracy.
We’re evolving and will become part of Twinn. Check out www.twinn.io as we make the transition. 