"Better Data to Strengthen Disaster Resilience" - Opening Address by Mr Bernard Wee, Executive Director, Monetary Authority of Singapore, at the 7th Institute of Catastrophe Risk Management Symposium on 21 April 2016
Opening
Professor Haresh Shah, Founding Chairman of ICRM,
Professor Pan, Executive Director of ICRM,
Ladies and gentlemen, good morning.
Thank you for letting me join you this morning at the 7th ICRM Symposium. The theme for this year’s symposium is “Plugging the Natural Catastrophe Data Gap – Thoughts to Action for Nat Cat DAX”. That’s a mouthful, but the idea is really simple (and important). Data is at the heart of robust catastrophe risk quantification and management. This is true everywhere. But it is especially true in Asia, which is growing faster than any other part of the world but data is not catching up.
In keeping with the conference theme, I would like to share some observations on how the region and its ecosystem can collaborate in building greater resilience to the escalating economic losses arising from natural catastrophes.
First, let me talk about Asia’s protection gap
Asia is significantly vulnerable to natural disasters. Compared to the US, Asia is over 60 times more vulnerable to flooding, and 40 times more vulnerable to tropical cyclones1. Countries in Asia Pacific also sit on the Ring of Fire, where roughly 90% of all earthquakes occur.
Over the next 35 years, the Asian Development Bank estimates that 1.2 billion Asians will continue to move into cities situated at coastal areas. That’s staggering. In 50 years’ time (by 2070), Asia will be home to 8 of the world’s 10 megacities most exposed to coastal flooding, including Mumbai, Tianjin, Bangkok and Tokyo2.
Without adequate risk management, the economic losses at these global megacities are expected to surge. Asia’s megacities are expected to account for 50% of all global assets exposed to flood risk by year 20703. If risk management efforts don’t improve, economic losses from just Asian flood disasters could surge to USD 500 billion or more in 2050 from USD 30 billion a year on average today.
If we count all sorts of natural disasters, the numbers are likely to rise exponentially:
- First, there is a growing concentration of infrastructure and assets in urban cities located in disaster prone areas;
- Second, the growing consolidation of production bases, supplier networks and distribution channels also increases the potential accumulation of risks. Events, such as the 2011 earthquake and tsunami in Japan, and the floods in Thailand, demonstrate amply the interconnectivity and risks of global supply chain disruptions.
- Third, climate change is creating greater intrinsic uncertainty about its effect on extreme weather events such as typhoons, storms, tornados, bushfires and floods. In particular, parts of Jakarta, Ho Chi Minh City and Bangkok are expected to sink below sea level in part due to climate-related events, increasing the risks and potential losses that these coastal cities face from floods and tsunamis.
Despite Asia’s increased exposure to natural catastrophe losses, catastrophe insurance penetration has remained low. How low? Between 1980 and 2014, the insurance penetration based on insured losses was just 8%4. The global average is 30%. This means that USD 1.3 trillion5 of uninsured losses have been borne by governments, companies and even households.
As the natural catastrophe protection gap widens, the share borne by ASEAN governments as contingent liabilities could reach nearly one-fifth of budgets in Cambodia, Laos and the Philippines6. That will make it more challenging for governments to continue acting as the “insurer of last resort”.
At a time when global economic growth remains weak and uncertain – emerging market growth forecasts have been lowered to 5.7%7 from 6.0% - governments will have to balance competing priorities like how to sustain growth.
So we need to shift away from relying on ex-post risk financing options, which are unsustainable in the longer term, to an ex-ante approach where risks are managed jointly by the public and private sectors.
What tools can we use to manage catastrophe risk efficiently?
Let me highlight the key ex-ante disaster risk transfer instruments in Asia, which are crucial for financing less frequent but more severe disasters.
- The first is traditional insurance, which plays an important role in mitigating the post-disaster costs. Lloyd’s analysed 7 recent catastrophes in China, Japan, Thailand, UK and US. They found that an increase in insurance penetration of just 1% reduces the damage borne by taxpayers by 22%. They also found that economic activity returned to pre-catastrophe levels long before reconstruction was completed.
- Second, insurance-linked securities such as catastrophe bonds have grown to be increasingly relevant in the current catastrophe market. It accounts for over 20% of the property catastrophe market, providing USD 68 billion of capacity, and is expected to continue to grow in importance. ILS is commonly used in Japan, where the largest catastrophe bond ever triggered was a USD 300 million issue from the Tohoku quake in 2011.
- Third, regional government pools are essential in emerging economies, where affordability is a major concern or where insurance markets are less matured in underwriting and retaining high-value risks. The pool provides for diversification across territories which would be otherwise unachievable, and also scope to strengthen legislative and regulatory frameworks to make insurance affordable for underserved segments.
It is widely acknowledged that ex-ante disaster risk financing instruments are most cost-effective, when the right instrument is deployed to the right risks. For instance, government reserves are the least expensive way to cover high frequency, low severity risks. Other instruments like insurance should be tapped for medium risk layers. Finally, low frequency, high severity events can be financed by catastrophe reinsurance and catastrophe bonds.
This sort of analysis and segmentation can only be enabled by robust quantification of the risk characteristics of the underlying hazards, so as to determine the breakpoints of frequency and severity of losses. However, the design of disaster resilience strategies and workable catastrophe risk solutions remain challenging in Asia Pacific. Why? Because data and expertise remain gappy, and this makes it difficult to measure value at risk. So insurers and reinsurers find it difficult to price risks adequately, or even at all in high risk markets. The lack of data also inhibits the design of alternative risk transfer mechanisms.
We need better data collection, and we need to overcome two barriers to better data:
- First, Asia is highly fragmented, and that makes pooling data difficult. Unlike mature markets, data and expertise do not reside in a few main insurance groups but are scattered. While data can be obtained from the domestic insurers, the risks are spread across these numerous smaller groups that hinder the ability to exchange and analyse the data collectively.
- Second, insurance data on risk exposures is scarcely available due to the low insurance penetration in the region.
The Natural Catastrophe Data Analytics Exchange aims to bridge the data gaps and deliver research to develop effective tools for the region
MAS is pleased be part of the launch of the Nat Cat DAX, the first data facility of its kind in Asia Pacific. It is envisioned to be the leading natural catastrophe data and analytics platform in Asia Pacific. It will aggregate natural catastrophe data obtained from both private and public sectors, and aim to generate new insights for traditional markets and catalyse innovative disaster risk financing solutions for the industry. The Nat Cat DAX will be led by NTU’s Institute of Catastrophe Risk Management, together with the Nat Cat DAX Alliance which consists of the:
- Research and Production Consortium formed by ICRM, PERILS AG and A*STAR;
- Founding Members: Renaissance Re, Aon, MSIG and RMS; and
- Other Key Industry players committed to the vision of the Nat Cat DAX
A prime example of public-private partnership, the Nat Cat DAX will overcome data limitations in the region with the use of advanced computational techniques and developed methodologies in data fusion not currently utilised by the market. High resolution data will be obtained through innovative remote sensing technologies from satellites, drones and UAVs, which would be fused with industry data to bridge the exposure data gap.
The increase in availability of quality Natural Catastrophe data in Asia will support natural catastrophe insurance awareness and penetration in the region in at least three ways:
- It will provide better pricing tools to facilitate the underwriting of catastrophe risks. This will increase commercial market interest’s to stretch insurability frontiers and provide coverage for previously untested markets.
- It will also enable economies and insurers to identify coverage gaps through the development of hazard maps and new models for currently hard to model or un-modelled regions, and to design effective risk transfer solutions
- The Nat Cat DAX will also support and enable the drive for innovation in alternative risk transfer products, for example, development of industry loss based products like catastrophe bonds, industry loss warranties and government pools
Closing
Robust catastrophe risk quantification in the region is essential to closing the rising protection gap. The Nat Cat DAX is an incredible starting point, and reflects Singapore’s commitment to strengthen the disaster risk resilience of the Asia Pacific region.
Thank you.
1 Allianz: “The Megacity State: The World’s Biggest Cities Shaping our Future”.2 OECD Ranking Port Cities with High Exposure and Vulnerability to Climate Extremes
3 Allianz: “Mitigating Flood Risk in Asia” – Asia Insurance Reivew (February 201)
4 Munich Re, Geo Risks Rsearch, NatCatService – January 2015
5 Swiss Re: “The USD 1.3 trillion disaster protection gap: innovative insurance tools exist to support governments to be better prepared” – October 2015
6 World Bank estimate – October 2011
7 ADB’s forecast - 2016