JBA writes about modelling flood risk in emerging markets

With premiums set to rise a further 8% by 2017 (Swiss Re 2015), emerging markets continue to represent the fastest growth areas for global insurers and reinsurers. Increasing insurance penetration, burgeoning middle class populations, and global supply chains are all key drivers of market growth in South America, Asia, Africa and the Middle East.

With rapidly increasing exposure, there is the urgent requirement for greater risk management, particularly to weather related perils such as flooding. However, there remain challenges in the industry to model catastrophe risk in these emerging markets. This includes a scarcity of vendor CAT flood models, high aggregated insured exposure data and the high cost of catastrophe risk management service.

In this article we discuss some of innovative approaches and methodologies that can be utilised to better classify aggregate insured risk, from underwriting through to reinsurance placement and capital requirement.



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Catastrophe Models

Probabilistic models provide the most effective method of fully capturing an insurer’s/reinsurer’s portfolio exposure to a natural peril. Catastrophe models can provide guidance on appropriate re/insurance pricing as well as giving the client a view of their capital exposure at key return periods. JBA has developed models to allow insurance data to be modelled, at numerous spatial levels, including zip code, province, and lat/long. Running on JBA’s modelling platform, JCalf®, Monte Carlo sampling is undertaken to fully quantify the relative uncertainty of financial loss. JBA has developed cat models covering key emerging markets such as Thailand, Malaysia, India, and Sri Lanka.

Scenario Models

Where a re/insurer may have accumulated assets in one region, it is important to explore how exposed the client may be to a single event, given that the insured loss potential may be greatly increased. This can be based on either recreating historic events or else, providing a scenario of what could happen. With this in mind, JBA has developed hypothetical flood footprints in emerging markets to help clients assess this exposure. For example, the JBA Pearl River Delta scenario model is available at 30m resolution in GIS format to look at the impact of 1 in 200 year flood event in the highly industrialised Guangdong province of China. Clients can assess their overall accumulation of risks within the hypothetical extent as well as the level of potential flooding per grid cell.


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There is no substitute for the precise geocoding of exposure data. Unfortunately, in many emerging markets, this information is not available to insurers. In this circumstance, re/insurers may be required to use alternative approaches, such as precautionary loading of insurance lines or cautious Probable Maximum Loss (PML) assumptions. Such practice may result in either over or underestimating the realistic flood risk exposure in many emerging market economies. To help provide a better assessment of potential flood risk exposure, JBA has devised FloodStat™. This dataset provides a statistical overview of the relative flood risk at various levels of aggregation and for multiple return periods. FloodStat™ is based on underlying data from JBA’s high resolution flood maps and is available globally. Users are able to assess their relative aggregate exposure against key flood risk metrics such as the maximum and minimum possible depth of flooding as well as the proportion of the area flooded.


Graph 3


Industry Loss Database (ILD)

In many circumstances, reinsurers in emerging markets lack detailed location data on their insured exposure. Because of this, they are often forced to make high level assumptions about the level of potential exposure that can significantly under or over-represent the real flood risk. For this very purpose, JBA have developed the ILD, an Industry Loss Database.

Re/insurers can use the ILD to provide key catastrophe loss information about the entire insurance market. With knowledge of their own proportional share of that insured market, clients are able to baseline their potential market exposure, as well as identify low risk areas where more premium could be written without impacting their capital exposure. The ILD includes financial loss information on Average Annual Loss (AAL), Exceedance Probability (EP), and a 10,000 Year Loss Table (YLT) and is provided at various geographic levels. The ILDs are delivered in database format and are available for Thailand, Malaysia, Sri Lanka and India.


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