1. Emerging Risk Management
Peter Grewal
Chief Risk Officer, Reinsurance
June 2017

2. Agenda The process: Emerging risk detection and mitigation
The context: Global macro trends
The driving forces: Technology changes
The impacts: four relevant emerging risk examples and their associated risks
Energy production & distribution
Cyber attack
Use of new material
Use of autonomous vehicles
CRO Forum Emerging Risk Initiative
Questions and Answers

3. Emerging Risk process 1 Emerging risk detection and mitigation
Swiss Re’s Group has an established emerging risk process called “SONAR”. It ensures the early identification, assessment and mitigation of risks as well as exploring business opportunities.
Identification
Assessment
Implementation
Monitoring & control
Emerging Risk Mgmt (ERM) responsible
Emerging Risk Mgmt support on demand
UPSIDE
Think tanks
Media
Internet
External initiatives
Univer-sities
Swiss Re business & staff
Product and/ or strategy development
Product launch and marketing
Pre-assessment, prioritisation and clustering
Internal supplement with further background
Business plan
Unrealised opportunity
Seized opportunity
Early signal
Emerging risk
Signal is fading
DOWNSIDE
Uncontrolled risk
Controlled risk
Consolidation and interpretation of early signals in annual report
Risk spark
Development
of mitigation
measures
Implementation
of mitigation
measures
Loss scenarios
Time

4. Global macro trends shape tomorrow’s risk landscape2
Global macro trends
Global macro trends shape tomorrow’s risk landscape
Swiss Re scans every year the external environment and has identified 22 global macro trends that are likely to have a high impact on the re/insurance industry over the next years.
Growing middle class in HGM
Longevity & radical medical innovation
Connected & collaborative society
Mass migration & urbanisation
The future of work & talent gaps
Rising social inequality
Political Environment
Societal Environment
Public sector moving risk to private sector
Protectionism & fragmented regulation
Increasing nationalism
Instability of geopolitical & economic systems
Low yield environment & risk of inflation
Re/insurance value chain disaggregation
Convergence of alternative & traditional capital
Strategic partnerships with non-insurance companies & institutions
Regional champions going global
Increasing digital customer interaction
Competitive & Business Environment
Technological & Natural Environment
Climate change & resource scarcity
Structural change of energy production, distribution & consumption
Massive expansion of cyber risk
Technology application as efficiency play
Disruptive digital technologies
Autonomous transportation & robotics
SR has identified 22 global macro trends likely to have a high impact over the next 5-10 years
We will focus on technological trends, which are also influence by their natural context; in particular the “new” power production and distribution which can be endanger by specific natural catastrophes like Solar Storm or cyber risk attack, when focus on critical infrastructure. These as having some of the biggest short-term and long-term impact on P&C UW risk. 3

5. Technology has three major implications for the insurance industry3
Technological changes
Technology has three major implications for the insurance industry
Technological advancements
(e.g. internet of things, blockchain)
Implications for the industry 1 2 3
Change in risk pools (e.g. new risks)
Transformation of value chain
(e.g. automation)
Disruption of industry structure
(e.g. changing roles, new ecosystems)
Change in risk pools:
eg Cyber risks and risks for new products e.g. 3 D printing or autonomous cars
also fewer low severity risks: Improved prevention by use of sensors at home or in manufacturing, but increased high severity risks: interconnectivity thus higher risk accumulation
Transformation of value chain:
New distribution
Efficiency and automation throughout
Disruption of industry structure:
New entrants
New partners for distribution
Catalysts / Inhibitors
(e.g. technological diffusion, regulation, consumer, competitors)

6. Power blackout as result of a Solar Storm4
Tomorrow’s risk landscape
Power blackout as result of a Solar Storm
Event/Impact/Likelihood
Most relevant effects
Largest solar flare ever recorded (NASA, April 2, 2001)
Power failures / blackouts
Interdependent power networks between energy producer (i.e. utilities) and consumers …
New forms of energy production like wind or solar parks …
New technology usage, with more satellites, electronics in airplanes …
Risk quantification remains basic ...
Power blackout risks need to be mitigated as far as possible and risk dialogue is important
History/storyline
Power blackout resulting from a solar storm has a long story, with higher and lower recognition overtime along the news communication on the solar activities. After its detection through the sonar process, it entered into the risk identification process and mitigation actions in September 2009 (P&C risk dashboard). This long standing process demonstrates the needed and existing sustainability into the risk management for such “exotic” topic.
- Initial high level discussion in term of potential impact (R3/Rapid Risk Research with a potential trillion of economic loss) has resulted into a high level agreement that this topic justifies additional resource and research to estimate better the potential material impact with a increased ranking to high risk early 2012.
- Mitigation actions were split and spread overtime in several parts: create awareness around the risk, improve evaluation and estimation, development a model in this regard, monitoring and/or additional actions (close the gap, exclusions, specific cover…).
- Awareness internally/externally through e.g. internal workshops 2012, Flyer/infographic 2014, hearing 2016, sonar publication and presentation like this
- Evaluation/model. Initial study what already exist in the market as study (MIT, Paul Scheerer institute…). Development of the model internally with NA focus and earth impact in 2016.
Key message
- Power black out resulting e.g. from a solar storm is a relevant risk despite its exotic touch and as natural phenomenon won’t disappear. It needs to be priced and to be kept at a manageable size, being for the insurance, reinsurance industry and the states. All actors of the chain have to play their role.
Power blackout like cyber has ‘silent’ exposure – potential for property damage and BI losses

7. Infrastructure outage4
Tomorrow’s risk landscape
Cyber risk exposure
Estimated premium growth of at least 15% over next 5-10 years
Most material scenarios identified for SR
Scenario
Interruption
Denial of Service - Interruption of Operations
Critical infrastructure
Breach
Privacy/data loss
Internet outage
Infrastructure outage
USD Billions
Demand for insurance protection against cyber risks is increasing due to growing hazards, widening sources of vulnerability and heightened regulatory pressure.
Premium estimates vary, but suggest an annualised cyber insurance premium growth of at least 15% over the next 5 to 10 years.
We have identified 3 material scenarios for SR:
Denial of service, ie non physical damage caused by IT failure or cyber attack
Critical infrastructure ie physical damage caused by IT failure or cyber attack
Privacy / data loss related to personal or financial data
Dedicated cyber insurance typically provides cover against:
data and network security breaches and associated losses
Denial of Service losses.
PRA found that ‘silent’ exposure to cyber is material and implicit within all policies and likely to grow.
Key area where there could be silent exposures would be in physical damage covers which do not include a specific cyber exclusion, - a cyber event could trigger physical damage eg cyber attack takes out the cooling system in a power plant.
See latest sigma: Cyber - getting to grips with a complex risk
Cloud security gap
 Cyber risk is continually evolving, through digital transformation, hyper connectivity and evolution of threat actors.

8. Casualty risk accumulations – e.g. Nano material4
Tomorrow’s risk landscape
Casualty risk accumulations – e.g. Nano material
Risk is constantly evolving. Events are driven by economic, societal & legal environments. Often linked to multi-line events eg Deepwater Horizon.
Increasing connectivity & dependencies between industries, insureds and countries increases risk eg supply chains span countries and companies.
Technology and scientific advances are changing at lightning pace. Impacts uncertain.
New forms of litigation make courts more accessible (eg class actions outside of the US may arise).
Risk quantification is basic. Insurers adding more cumulative risk year-on-year, generating huge hidden accumulations.
Risk modelling difficult as future developments more relevant eg what new products could cause harm? Effects take longer to manifest themselves and impact multiple UW years. Accumulations could be worldwide.
Nat cat models are well embedded in how we price and allocate capital for our property book of business. Models well developed / not undergoing radical redevelopments.
Casualty accumulation ("Casualty Cat") risk is one of the most underestimated risks in the insurance industry and a source of significant protection gap for customers. 
For Casualty there are numerous challenges which make it harder to identify and quantify potential accumulations, especially systemic losses.
Historical experience is maybe not as relevant as future changes eg new pharmaceuticals or products which could be introduced, changes in legislation etc. This makes it more important to monitor trends in developments and think about potential future outcomes.
Potential exposure from a Casualty accumulation is only growing with globalisation / increasing interconnectedness. Events also tend to cross multiple lines of business – eg Financial Crisis triggered investment losses and Financial lines claims, Deepwater Horizon event also triggered Property Claims.

9. 2. Probabilistic – forward-looking models4
Tomorrow’s risk landscape
Casualty risk accumulations – the move towards forward looking risk models
1. Deterministic
2. Probabilistic – forward-looking models
3. Steer portfolios
Extreme-scenario analysis, based on expert views of tail events (eg new asbestos, financial crisis).
So where are we coming from and where are we trying to get to?
Companies mainly rely on deterministic methods for assessing potential losses from ‘tail’ events / scenarios. These are often used to parameterise internal models used for calculating regulatory capital requirements. Companies may also monitor exposure to certain product lines, sectors, geographies etc to try to keep portfolios diversified.
The ability to develop forward-looking stochastic models to help quantify risk and steer portfolios is an industry recognized issue. Within SR we have been developing models for the Casualty accumulation risk since 2011 and have engaged with clients since 2015 to strengthen understanding of these exposures on the basis of our proprietary models. We have a well developed model for assessing and pricing risk clash events. Our L-Cat model will be an expansion of this and include also more systemic risk factors. The Casualty R&D team and the Casualty underwriters are available to engage in dialogue with clients on the Casualty accumulation risk.
Note: Willis, Arium and Lloyd’s have launched new Casualty accumulation models this month.
The diagram illustrates the types of factors considered within the model for a product liability risk. The ultimate objective will be to gain a strong understanding of the existing risk on our books and what risk new business adds, in order to steer portfolios to where we want to get to.
At Swiss Re we have developed our own pricing model (LRD) incorporating the various liability risk drivers and allowing overlay of our own exposures. Covers Limited Liability Cats (Risk Clash events).
We are developing the L-Cat model, which will also incorporate Unlimited Liability Cats (systemic aggregations). This model will be available for clients.
Steering actions take longer to have effect!

10. Impact of autonomous vehicles on the industry4
Tomorrow’s risk landscape
Impact of autonomous vehicles on the industry
1. Projected impact on insurance premium
2. Impacts on underwriting risk
Claims
Safety benefits lead to fewer claims
Type of vehicle and safety features become more important than the driver
Pricing
Help identify faulty party in accidents.
Calculate premiums based on only when a person is driving
Telematics
Legal & liability considerations
Legal framework will dictate speed in introducing autonomous vehicles
Product liability or motor third party liability cover triggered in accidents
Source: Swiss Re projections, for highly aggressive growth scenario
Even if vehicles are much safer than anticipated, we still predict a sizeable insurance market over the next decade.
Note this scenario does not include aftermarket kits that transfer existing vehicles into autonomous vehicles. These systems could cause disruption. It has to be seen how regulators will deal with these systems.
Even under aggressive automated vehicle growth scenario we still predict a sizeable insurance market over the next decade.
There are positives coming out of the automation:
lower claims as safety benefits reduce the likelihood for accidents
new types of insurance covers will be needed – growing need for product liability and cyber risk covers
We may however need to change the way we assess the risks:
consider more the type of car than the driver (pricing)
how to detect when the person is driving or the ‘machine’ is driving (handover points) – for proof of liability in claims assessment
Product liability / cyber risk
Growing demand for these covers

11. Emerging Risk examples: Cyber Risks, European debt crisis4
Tomorrow’s risk landscape
Emerging Risk examples: Cyber Risks, European debt crisis
It is in the nature of emerging risks that not all such risks will eventually materialise. However, many identified emerging risks have occurred. Two examples show the life cycle of ERs.
Identification
Assessment
Implementation
Monitoring & control
UPSIDE
Cyber Risks
First risk notions between
First reported in internal SONAR report 2010
Main trigger for scenarios was Stuxnet in 2010
Cyber Risks
First risk scenarios (around data theft, industrial impacts, cyber war) in 2010
Detailed assessments in the following years
Cyber Risks
Cyber Risk UW Strategy
Cyber product development
Cyber Risks
Monitoring market development
Con’t cyber product development
Unrealised opportunity
Seized opportunity
Cyber Risks
Risk Accumulation
WEF GRR 2012, 2013 & CROF Cyber Resilience publication 2014
Cyber Risks
Swiss Re Sigma Cyber publication 2017
Monitoring new emerging cyber risk exposures
Early signal
Emerging risk
DOWNSIDE
Sovereign debt crisis
First risk notions between
First reported in internal SONAR report 2010
Risk understanding focused on countries
Generic examples over the life cycle of an emerging risk
Sovereign debt crisis
First risk scenarios (around EU triggered debt crisis) in 2010
Detailed assessments in the following years
Uncontrolled risk
Controlled risk
Sovereign debt crisis
Concrete country related ad-hoc task forces
Eurozone working group since 2012
Sovereign debt crisis
Eurozone working group monitoring tasks
Time

12. 5
CRO Forum – Emerging Risk Initiative
CRO Forum – Emerging Risk Initiative (ERI) Risk Radar and Industry Position Papers
CRO Forum ERI Risk Radar, Oct 2016
CRO Forum ERI – Industry Position Papers
Water Risks (2016)
The Smart Factory (2015)
Pushing the limits (2014)
Food and its impact on the risk landscape (2013)
Endocrine disruptors (2012)
Power blackout (2011)
Longevity (2010)
Nanotechnology (2010)
Environmental liabilities (2009)
Critical information infrastructure (2008)
Climate change (2007)

14. Legal notice
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The information and opinions contained in the presentation are provided as at the date of the presentation and are subject to change without notice. Although the information used was taken from reliable sources, Swiss Re does not accept any responsibility for the accuracy or comprehensiveness of the details given. All liability for the accuracy and completeness thereof or for any damage or loss resulting from the use of the information contained in this presentation is expressly excluded. Under no circumstances shall Swiss Re or its Group companies be liable for any financial or consequential loss relating to this presentation.