Physical Climate Risk Analytics

Physical Risk Analytics
Are we there yet?
Sharanjit Paddam – spaddam@deloitte.com.au 0439499414 – IGCC Workshop 6 June 2018

Climate Risk Analytics – IGCC 6 June 2018 2© 2018 Deloitte Touche Tohmatsu. All rights reserved.
How do we report?
Outputs – Metrics & targets
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
Repair Unavailability Cross Dependency
Increase of 1% - 5% p.a.
in expenses due to
physical risk
Primarily in Asia
Australian
commercial
property
Asian
infrastructure
Majority is in
additional
repair costs
to property
infrastructure
Growing
issues of
cross
dependency

How do we respond strategically and operationally?
Outputs – Strategy
Lending & credit policy examples
• Identification of high-risk segments
• Changes in credit policy and acceptance
processes
• Strategic policy
• Focus on new & growth industries arising
from transition
• Avoiding anti-selection from exclusion by
competitors
Products
• Reduction in insurance premiums for
resilience measures undertaken by
insurance customers
• Post-event resilience improvements
• Resilience loans to fund adaptation options
• Savings products for purchasing new
home when existing home no longer
inhabitable
• Extending insurance to coastal inundation
coverage
• Green bonds
Public policy
• Identifying problem geographic areas and
economic sectors and working with
government on adaptation measures
• Lobbying for better land use and planning
by government

Connecting scenario choices, physical & transition risk modelling, credit risk modelling
and financial impacts on the balance sheet
Our approach for banks and insurers

Why is physical risk modelling and pricing so hard?
Emissions
scenarios
Climate
Projections
Exposure Vulnerability
Hazard
models
Financial
Impact
Adaptation
Strategy
• Multiple steps in process, with different combinations of skills needed at each stage
• Significant data requirements at all stages of the process
• Need for granularity and detail, approximations are hard to do well
• Science is incomplete and there are very few integrated approaches

Future projections of climate variables based on emissions scenarios
Climate Projections
Outputs:
Mean and extremes over time of:
• Temperatures
• Precipitation/Rain
• Wind
• Tides & waves
Data Issues:
• Lack regional downscaling to sufficient level of
granularity
• Choice of GCM within emissions pathway
• Lack of RCMs
• Need extremes not means
Insurance: • Little capability
Risk screening: • Usually good coverage
Over the next 20 years, different emissions scenarios will have little impact. Physical risks are already baked
into the system. RCP 8.5 should always be considered.

What physical assets are in our portfolio, and where are there?
Exposure
Outputs:
Consider current and future assets:
• Need physical characteristics: floors, walls, roofs etc
• Growth in assets is correlated with economic factors
– transition risk
Data Issues:
• No easily available exposure data, even if you own
the assets
• Some publicly available data, but not necessarily up
to date
• Need granularity – house at bottom/top of hill
Insurance: • Generally good
Risk screening: • Varies
If you are an asset owner or manager, begin capturing this information within your asset management
systems today, especially risk characteristics.

How much damage will be caused by different sizes of hazard events?
Vulnerability
Outputs:
Current and future:
• Damage curves for each hazard and exposure
type combination
Data Issues:
• Different types of vulnerability: roofs, water
ingress, foundations, electricity, availability,
cross dependency, etc.
• You could be in the middle of a flood zone and
be totally fine!
Insurance:
• Generally good, but based on historical
performance
Risk screening:
• Often done on the basis of benchmarks, but this
can be misleading
Source: https://www.domain.com.au/news/is-this-queenslander-the-house-of-the-future-20110715-1hgsg/
In practice this is the most important steps and requires good engineering skills

What are the hazards we face and how will they respond to climate change?
Hazard modelling
Outputs:
Consider current and resulting changes in:
• Frequency
• Severity
• Location
• Type of damage
Data Issues:
• Significant data requirements
• Flood maps, coastal inundation maps not
easily available or consistent
• Proxies can be very poor: e.g. Cyclone is
combo of heat, precipitation + wind
• Historical is NOT enough. e.g. Floods and
cyclones will happen in completely new areas
Insurance:
• Good for most hazards, but not prospective
or up to date
• Not everything is insured – coastal inundation
Risk screening:
• Generally done on the basis of proxies, e.g.
precipitation as a proxy for flood, which
reduces accuracy significantly. Source: https://commons.wikimedia.org/wiki/File:Global_tropical_cyclone_tracks-edit2.jpg
Scientists need to focus on this problem and improve their prospective modelling of hazards. It’s a modelling problem as well as a data problem.

What is the financial value of the impact of natural disasters?
Financial impact
Outputs:
Current and future:
• Repair/replacement costs
• Unavailability/useability of asset costs
• Cross-dependency of asset
Capital value driven by NPV of future costs
Data Issues:
• Need to have replacement value of your asset
• Utmost importance for pricing and assessing
financial resilience
• Understand business model of asset. E.g. Heat
good for shopping centres, but bad for transport
• Cross-dependency is really hard without data on
assets you depend on, and often the biggest
cost
Insurance:
• Generally good, but only cover repair and some
unavailability
Risk screening: • Risk scoring ≠ financial value
0
5
10
15
20
25
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
Repair Unavailability Cross Dependency

What is my avoided cost for each adaptation option?
Adaptation
Outputs:
• Reduction in all three costs from investment in
adaptation on an NPV basis
• Can extend to wider socioeconomic value when
considering government
Data Issues:
• Needs all preceding steps done well first
• Must be done at an asset level
• “Desktop adaptation” isn’t a viable approach
Insurance: • No capability
Risk screening: • No capability

Capability: Climate Projections Exposure Vulnerability Hazard Modelling Financial Impact Adaptation Strategy
Description:
Future projections of climate
variables based on emissions
scenarios
What physical assets are
in our portfolio, and
where are they?
How much damage will be
caused by different sizes
of hazard events?
What are the hazards we
face and how will they
respond to climate
change?
What is the financial value
of the damage?
What is my avoided cost
for each adaptation
option?
Outputs:
Mean and extremes over time
of:
• Temperatures
• Precipitation/Rain
• Wind
• Tides & waves
Consider current and
future assets:
• Need physical
characteristics: floors,
walls, roofs etc.
• Growth in assets is
correlated with
economic factors –
transition risk
Current and future:
• Damage curves for
each hazard and
exposure type
combination
Consider current and
resulting changes in:
• Frequency
• Severity
• Location
• Type of damage
Current and future:
• Repair/replacement
costs
• Unavailability of asset
costs
• Cross-dependency of
asset
• Reduction in all three
costs from investment
in adaptation
• Can extend to wider
socioeconomic value
when considering
government
Data
Issues:
• Lack regional downscaling to
sufficient level of granularity
• Choice of GCM within
emissions pathway
• Lack of RCMs
• Need extremes not means
• No easily available
exposure data, even if
you own the assets
• Need granularity –
house at bottom/top of
hill
• Different types of
vulnerability: roofs,
water ingress,
foundations, electricity,
availability, cross
dependency, etc.
• Significant data
requirements
• Flood maps, coastal
inundation maps not
easily available or
consistent
• Proxies can be very
poor
• Historical is NOT
enough
• Need replacement
value of asset
• Utmost importance for
pricing and assessing
financial resilience
• Understand business
model of asset
• Cross-dependency is
really hard, and often
the biggest cost
• Needs all preceding
steps done well first
• Has to be done at an
individual asset level
Insurance:
• Little capability • Generally good • Generally good, but
based on historical
performance
• Good for most hazards,
but not prospective or
up to date
• Not everything is
insured
• Good for repair/
replacement costs,
some unavailability of
assets, but not cross
dependency
• No capability
Risk
screening:
• Usually good coverage • Varies • Based on benchmarks • Generally done based
on proxies
• Risk scoring ≠ financial
value
• No capability

Getting value from your choices
1 . Goal is to get to financial impact and adaptation strategy
2 . Most required capabilities are still at an early stage
3 . Different tools provide varying combinations and levels of
capabilities
4 . No tool can do it all (yet)
5 . Really important to know what you need
6 . And how you want to get there (internal capability
development vs external specialist expertise)
7 . How much do you love your asset? Adopt a corresponding
approach
8 . Don’t be distracted by the data problem, you can still do
valuable and effective analysis today
9 . Risk screening is usually not enough as it doesn’t provide
financial impact nor adaptation strategy, but can help you
identify where the material risk is likely to be in your
portfolio
10 .You don’t need full capability everywhere – focus your
detailed financial analysis on the risky part of your portfolio
All the risk is concentrated in
a small part of your portfolio
For a significant proportion of
your portfolio, the risk is not
likely to be material
Don’t be distracted by the
mean or average impact on
your portfolio

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