Delivering (geoinformation about) risk. Dr James O Brien Risk Scientist Risk Frontiers Macquarie University
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1 Delivering (geoinformation about) risk Dr James O Brien Risk Scientist Risk Frontiers Macquarie University
2 Overview Who are Risk Frontiers & what we do? Where are the risks? Address based risk rating National Flood Information Database Our risk & catastrophe loss models Disseminating the knowledge Risk Loss Web & Mobile
3 Introducing Risk Frontiers Help insurers and reinsurers better understand and price natural hazard risks in the Asia-Pacific region Develop Probabilistic Catastrophe Models Provide an independent view on catastrophe risks Undertake research in natural hazards Perform post-event reconnaissance Increase public awareness of natural perils & aid policy development
4 What Do We Have To Share? Multi-Peril Workbench version 3 and beyond Flood Exclusion Zones (FEZ ) National Flood Information Database (NFID) Earthquake and volcanic loss models for New Zealand and Japan Tropical cyclone loss model for South Korea Developing Flood models for SE Asia Post-Event reconnaissance of Christchurch Earthquakes, Queensland Floods, Tropical Cyclone Yasi, Tasmanian & Victorian fires Normalisation of ICA loss data (2011/2012) Invited submission to the Royal Commission on the 2009 Victorian fires Invited submission to the 2011 National Disaster Insurance Review
5 Knowledge / Data Flow Aerial imagery Satellite data Risk Rating DB Risk Frontiers PerilAUS DB Risk Frontiers Loss Models Private Data Sources Government Data Sources Fieldwork Social media Risk Frontiers Loss Models Insurer s Pricing Reinsurer s Pricing Cost / Benefit Analysis Reports Government Agencies etc. KNOWLEDGE Map Production Online Maps Printed Maps Mobile Maps
6 Finding the Risks : Looking Back Source: PerilAUS; Crompton & McAneney, Environ. Science & Policy)
7 Finding the Risks : Looking Forward
8 Risk Rated Address Tool
9 Risk Rated Addresses Applied Percentage of portfolio per postcode compared to the proportion of total addresses in particular hazard categories
10 National Flood Information DB 12M addresses Aggregation of inconsistent data into a common format 60+ study areas 1-5 flood surfaces / flood extents Metadata & QA checks
11 Risk Communication : Flood Intelligence State Emergency Service required a review of flooding in a region Flood depth / extent data collection Examine behavioural factors Review Flood Response Plans Develop mobile apps for first responders
12 Sample Risk Map Data Mapping Risk On the Fly Process a collection of data to rapidly produce regional risk assessments Inconsistent (but regularly updated) data sets (e.g. updated flood modeling, changing population or infrastructure data) Variable client reporting requirements Need for summary statistics by regions Easily updated / modified Easily run by non-experts Minimal process supervision required Reproducible analysis 1 map/min Publishable to mobile & web Sample Risk Map Data
13 Risk Frontiers Multi-Peril Workbench Suite of Catastrophe loss models for Australia & selected Asia-Pacific countries Calculates exceedance probability curves for all major Australian catastrophe risks Varying Input resolutions: address, postcode or larger Combines curves of different perils, flexible reinsurance modelling
14 General Model Framework Risk = f (Hazard, Exposure, Vulnerability) Mean damage (%) Annual Exceedance Probability Hazard Exposure Hazard intensity Vulnerability Loss ($ Million) Impact
15 Catastrophe Loss Models
16 Loss Visualisation : Google Earth
17 What About The Web? Portfolio risk visualisation Hazard / Risk / Exposure Maps Automated Reporting
18 What About The Web?
19 Tasmanian Fires Aerial Photography & Field Survey
20 Conclusions Access to high quality data is important Must be able to communicate the knowledge Web & mobile significant growth areas Maturing APIs make deployment faster & easier
21 Thank you - james.obrien@mq.edu.au
22 Mobile Mapping & Dissemination m Garrigue Steppe Agricultural - terraced Watercourse vegetation Agricultural Abandoned agricultural Maquis
23 FloodAUS Loss Model Beyond NFID Catchment Historical Data Vulnerability Addresses Water Depth, Return Intervals ARI,Loss ($) Combined Exposures (Addresses) NFID Company Data
24 Application Risk Selection Effect on EP-Curve Original portfolio Removed high risk addresses Blue: Market-distributed portfolio EP-Curve Red: Removed properties less than 100m of the bush
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