Expert of the Week   for  01 - 07 Jun 2015

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Julia Hall

Senior Consultant

Risk Management Solutions (RMS) Expertise:  Catastrophe modelling techniques and solutions. Insurance. Disaster risk reduction.

As a manager in the consulting team, Julia advises on the use of catastrophe modelling techniques and solutions. Although based in London, she has worked with many global (re)insurance companies and public and academic partners on disaster risk management. She has recently worked on a joint project with the ODI and CRED to make recommendations for the post-2015 UN frameworks on setting, measuring and monitoring targets for Disaster Risk Reduction. During the World Conference on Disaster Risk Reduction in Sendai this year, she gave a talk on ‘The Challenges of Measuring Disaster Risk’ and presented on a panel on ‘Measuring Disaster Resilience’. Julia holds a MSci in Natural Sciences, with a specialism in geology, from the University of Cambridge.

The use of modelling for Disaster Risk Reduction

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QQuestion by Mr Paul Sawyer

What academic preparation, coursework, degrees and licensing are required to be succesful in your field of Risk Management?

Mr Paul Sawyer Science Teacher | Harmony Science Academy- Dallas
United States of America

APosted on 05 Jun 2015

For catastrophe modelling, a strong academic background in science and maths at school is essential and a quantitative subject at university is beneficial, such as engineering, earth sciences, meteorology/climatology, physics or maths. An interest in technology and problem solving can be demonstrated through coursework.

In general, an analytical mindset is essential but there are many different roles in risk management, which require a variety of skill sets. Soft skills, such as strong communication and presentation skills, cannot be underestimated. For working in model development, focusing on a particular peril such as hurricane or earthquake, advanced research and computer skills in atmospheric sciences or earthquake engineering or similar is often required.


APosted on 05 Jun 2015

For catastrophe modelling, a strong academic background in science and maths at school is essential and a quantitative subject at university is beneficial, such as engineering, earth sciences, meteorology/climatology, physics or maths. An interest in technology and problem solving can be demonstrated through coursework.

In general, an analytical mindset is necessary but there are many different roles in risk management, which require a variety of skill sets. Soft skills, such as strong communication and presentation skills, cannot be underestimated. For working in model development, focusing on a particular peril such as hurricane or earthquake, advanced research and computer skills in atmospheric sciences or earthquake engineering or similar is often required.


QQuestion by Ms Debbra Johnson

1. Cost-benefit hurdles can be based on profit expectations that are outdated and obstruct progress. What can we do to help those DRR champions inside companies to introduce new business models that allow for a set of metrics that are more in line with current world realities?

2. Should something akin to "producer responsibility" apply when measuring DRR progress?

Ms Debbra Johnson Prncipal | DAKJ, LLC
United States of America

APosted on 05 Jun 2015

In terms of your first question, you raise an important point. Two thoughts:

1) We live in a world where risk is changing, whether from climate change or from urbanization or the growth of a company. When a cost benefit analysis is undertaken that concerns reductions in future disaster impacts as a result of some action, then it is important to consider how risk costs/benefits are expected to change into the future. Modelling can be helpful to understand this.

2) For DRR, it can be more relevant to quantify risk on a company’s balance sheet, and to qualify DRR actions in terms of reducing this risk. For example, modelling can help companies understand the implications of their actions, such as building energy plants or buying/using factories in high risk flood or earthquake zones. Employees can help their companies understand that measuring the risks faced (of their buildings, clients and supply chains) is important. This still needs to include how risk is expected to change, not simply what is the level of risk today.  

A good example of a failure to perform a proper risk analysis concerns the inadequate flood defences around the major industrial parks in Thailand before 2011.  Electronics supplies were depleted around the world. A producer of a one-third of the world’s hard disks lost almost half of its shipments, whilst car manufacturers had to shut down their operations in other countries due to lack of supplies from Thailand. 

As well as good risk management, the level of risk also affects companies’ insurance premiums. Risk modelling companies, insurance companies and brokers should be able to help companies understand and measure their risks, and how to mitigate them.


In response to your second question:

To encourage DRR progress, I would definitely look towards innovative strategies, an example being “producer responsibility”.  It makes sense for companies to demonstrate to their suppliers that they are taking their disaster risk into consideration, and encourage their suppliers and clients to do the same.  In terms of specific company actions or investments it should be possible to show how these can affect the level of future risk. 

QQuestion by Ms Steven Ramage

Is dealing with unaddressed areas globally a challenge or an issue for dealing with disasters (for preparedness, response or reconstruction)?

Ms Steven Ramage Director | what3words
United Kingdom

APosted on 05 Jun 2015

Unaddressed has two meanings – 1) not covered by the models and 2) buildings without addresses. We can try to address both questions. 

1) Inevitably the biggest disasters tend to occur in those locations which have some of the poorest information on the building exposure, for example. Also the investment in developing models has tended to be concentrated where there is the greatest financial interest in the results of the models – which tends to be in OECD countries. However that is changing with increased investment in developing models for poorer countries. 

2) For models which measure the disaster risk of a location, city or country, the more detail about the location the better. Certain perils, such as flood, require detail on where, for example, the building is situated, to give an accurate representation of the risk. The best resolution of location data is at the coordinate level, rather than postcode or county level. Therefore, as long as there are coordinates, addresses are not necessary. 

However, for dealing with disasters in terms of response, I suggest getting in touch directly with disaster charity networks, such as the START network, to see whether there are any issues with having coordinates rather than actual addresses.


QQuestion by Mr Roberto Pizzi

Hi, could you please tell me your opinion about the operational research methodologies applied to disaster assessment? In particular, do you think that techniques such as AHP and ANP could be applied or are actually applied in this field?
Many thanks,
Roberto

Mr Roberto Pizzi Geologist | Presidenza del Consiglio dei Ministri - Dipartimen
Italy

APosted on 05 Jun 2015

Disasters are messy and complex, often occurring in situations where there is a great shortage of accurate data (as for example on the true status of the application of building codes). However we would encourage you to look into a situation (like the question of the level of risk and actions to reduce risk in a particular city) to discover what methodologies are most appropriate including operational research.  

QQuestion by Mr Paul Sawyer

What academic preparation, coursework, degrees and licensing are required to be succesful in your field of Risk Management?

Mr Paul Sawyer Science Teacher | Harmony Science Academy- Dallas
United States of America

APosted on 05 Jun 2015

For catastrophe modelling, a strong academic background in science and maths at school is essential and a quantitative subject at university is beneficial, such as engineering, earth sciences, meteorology/climatology, physics or maths. An interest in technology and problem solving can be demonstrated through coursework.

In general, an analytical mindset is essential but there are many different roles in risk management, which require a variety of skill sets. Soft skills, such as strong communication and presentation skills, cannot be underestimated. For working in model development, focusing on a particular peril such as hurricane or earthquake, advanced research and computer skills in atmospheric sciences or earthquake engineering or similar is often required.


APosted on 05 Jun 2015

For catastrophe modelling, a strong academic background in science and maths at school is essential and a quantitative subject at university is beneficial, such as engineering, earth sciences, meteorology/climatology, physics or maths. An interest in technology and problem solving can be demonstrated through coursework.

In general, an analytical mindset is necessary but there are many different roles in risk management, which require a variety of skill sets. Soft skills, such as strong communication and presentation skills, cannot be underestimated. For working in model development, focusing on a particular peril such as hurricane or earthquake, advanced research and computer skills in atmospheric sciences or earthquake engineering or similar is often required.


QQuestion by Ms Sharon Rusu

What modelling applications do you view as useful for African countries at vastly different levels of development and why?

Ms Sharon Rusu Head UNISDR Regional Office for Africa alil | UNISDR
Kenya

APosted on 03 Jun 2015

Thank you for your question. As you mention, there are very different levels of development across Africa – and similarly there are variable levels of modelling applications. However, due to the relatively low insurance penetration (models up until recently have generally been built where there is a need from insurance companies), Africa is the continent with the lowest coverage of detailed catastrophe models. Examples of those used in the insurance industry include earthquake in North and East African countries and windstorm in South Africa.

 
Given this, a question is how can catastrophe models help countries in which there is little insurance activity. Models can be used both to assess the level of risk but they really come into their own when they are used to help demonstrate how risk can be diversified – through risk sharing mechanisms. In this regard there are both weather index models that have been developed to support local African crop insurance pilots and most significantly drought insurance as through the African Risk Capacity, which has developed models for the regional distribution of drought.
 
In terms of the future of modeling in Africa, the level of detail needed completely depends on what the models are used for. For country level assessments, the UNISDR’s GAR15 website is a great place to start, which show results from probabilistic modelling (i.e. average losses expected overtime) by country for different hazards, but not for drought. It would be useful to see how these country results change over the timeframe of the Sendai Framework and SDGs.
 
Here are a couple of suggestions to improve risk modelling in Africa: 

1) Improved and standardised risk data collection at a government level would help improve the level of modelling possible. To model disasters, risk data is needed e.g. hazard information, details on the buildings (such as construction type / how many storeys high) and where they are located.


2) Once there is enough data for more detailed models, incentivise private companies and academic institutions to work with the UNISDR to develop models further for disaster risk reduction. Beyond drought, the big need is for high quality African flood models. 

THIS SESSION CONCLUDED ON

07
June
2015