Weitere ähnliche Inhalte Ähnlich wie D1Conf 2018 |The incumbents view: how is the insurance industry using blockchain? | Magdalena Ramada Sarasola, Willis Towers Watson (20) Kürzlich hochgeladen (20) D1Conf 2018 |The incumbents view: how is the insurance industry using blockchain? | Magdalena Ramada Sarasola, Willis Towers Watson1. Are incumbents taking the leap?
D1 Conference
Prague, October 2018
Dr.rer.Pol. Magdalena Ramada
Director – Willis Towers Watson Insurance Consulting and Technology
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The insurance industry and blockchain
2. Disclaimer
1
Please read carefully and note that:
I am NOT a registered investment advisor, nor an attorney, nor a tax advisor.
During this presentation I will mention firms that are relevant to the examples that
I am presenting. The opinion expressed on those companies is solely my own, it
is based on publicly available information and DOES NOT constitute professional
or investment advise, nor should be used to value or invest in these companies.
None of the opinions shared today with you should be understood as nor used in
the context of any past, current or future ICO.
You should NOT rely on anything I say today as investment advice.
You should NOT act upon any information presented on this presentation without
seeking proper professional and/or legal counsel.
The opinions expressed by me here today are solely my own and not the views of
my employer.
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3. This document was prepared for marketing, training and/or general information purposes only and
should not be considered a substitute for specific professional advice. In particular, its contents are not
intended by Willis Towers Watson to be construed as the provision of specific investment, legal,
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Disclaimer
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4. willistowerswatson.com
Squeezing the Risk to Capital value chain
Why?
3
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5. The Risk to Capital Journey
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6. The Risk to Capital Journey
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5
Decentralized Autonomous Risk
Placement
Risk vs. Uncertainty
Information, data self-sovereignty
and the underserved
As we all know…
… blockchain is an innovation that
empowers trustless, digital peer-to-
peer networks to transact value in a
decentralized way, without the need
for a third party.
What if we could transact Risk in the
same way?
7. The long-term vision: a unified P2P risk transfer protocol
6
Towards the tokenization of social capital, behavior and risk
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Social Capital
Builds trustworthiness ratings in a
trustless system by using identity
solutions and harnessing social
capital. Leverage behavioural
analytics. Selective data
disclosure, ZK proofs.
Prediction Markets
Combine prediction markets
with risk pooling and risk
placement. Use prediction
markets to assess and price
risk.
Oracles, Provenance
and Data providers
Connects to IoT devices and
trusted data providers to feed
Smart Contract Automation
Automation through
Smart Contracts
Builds DAOs compressing the risk to
capital value chain by handling claims
and investments & connecting data
sources with smart contracts and AI.
Requires Capital side solutions.
Blockchain
enabled P2P
risk transfer
8. willistowerswatson.com
From semi-trusted to trustless ecosystems
How do we get there?
7
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9. The short-term reality: synchronization and automation
Likely effects of blockchain over time
8
Operational improvements
and ecosystems of
value
Automation: improved speed
and cost-efficiency through self-
executing Smart Contracts
Distributed databases:
Increased efficiency, transparency
and fraud protection within and
among insurers, reinsurers and
regulators, through shared
blockchain-based relational
databases
Short term Longer termMedium term
True disruption to the value
chain
True Peer-to-peer business
models: increased disintermediation
through distributed and autonomous
organizations of participants and
networks
Automated risk matching
platforms between customer and
carrier*, with more risk handled via
smart contracts rather than traditional
policies
Innovative new products for new
risks
Better data and measurement of
risk
Provenance and identity: safeguarding
data/asset provenance and enabling data
portability and auditability, through its
chronological and immutability attributes
Selective disclosure, ZK,
Bulletproofs
Risk transparency: improved ability to
calculate and price risk through new,
verifiable and secure sources of data,
IoT+Blockchain+AI
*For less complex risks, this may happen
sooner
Synchronization
& automation
New infrastructure,
for new Analytics Autonomous insurance
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10. InsurTech and Blockchain investment activity
Category
Examples
Membership in external
initiative or consortium
Light touch involvement
Corporate venture fund
Capital investment with little
direct engagement
Innovation center
Total engagement
Incubator
Long term guidance and
development
Accelerator
Intense short term
engagement
9
Blockchain specific Agnostic
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11. © 2018 Willis Towers Watson. All rights reserved. Proprietary and Confidential. For Willis Towers Watson and Willis Towers Watson client use only. 10
RiskBlock™ Alliance
80+ systemically important
financial institutions
Largest collaborative
group working on
blockchain-solutions
Corda – proprietary DLT
platform
May: raised $107M (Series
A funding from 40
institutions)
Dedicated insurance
vertical (CoE) since April
30 risk management and
insurance industry
organizations
Awards at Insurance
Industry Innovator Award
(2017 ACORD Insurance
Innovation Challenge
(AIIC))
Excess of loss PoC
Presented prototype
reinsurance platform at
2017 Monte Carlo RDV
23 new members to test it
a.o.
Blockchain Insurance
Alliance (SMEs)
Financial Blockchain
Shenzhen Consortium
Industry efforts: mostly seeking back-end efficiency
12. willistowerswatson.com
Corda dominates de incumbent driven blockchain ecosystem
11
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14. willistowerswatson.com
Example 1: Selective data sharing and real-time data synchronization
… e.g. avoiding double insurance fraud
13
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Entity 1
Systems
Entity 1
Distributed Ledger AKA blockchain
Entity 2
Systems
Entity 2
Entity n
Systems
Entity n
…
Passport Number: ABC123456
Vehicle ID Number: GE778423
34FGU67FP98NG20VCXS1956B44
15. willistowerswatson.com
Example 2: Process standardization and automation in a semi-trusted
environment – Risk assessment and Placement
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Example 3: Process standardization and automation in a semi-
trusted environment – Settlement
Payment processes in international
fronting for captives
Real-time clearing and settlement of
securities – e.g. ILS
Real-time synchronized Subrogation
industry utility: no reconciliation
Smart contract enabled claims triage
Smart contract enabled billing and
invoicing
Shared ledger in response to crisis
situation (mass shooting, pandemics)
17. willistowerswatson.com 16
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Example 4: Smart Contract Insurance Policies – Cat Risks,
Parametric, Provenance solutions
Cat Swaps, Cat Bond issuing
Cat Microinsurance
(Earthquakes)
Life-Microinsurance
IoT & SC enabled Marine
Insurance (e.g. Coldchain)
Proof of insurance, insured
interest provenance,
authenticity
19. 18
Disintermediation
Potential consequences of underwriting without
underwriters:
Unbreakable escrow and solvency models
Too big to fail: scalability of P2P risk mutualization
may lead to systemically important DAOs
Who is responsible in the event of a catastrophic
event/black swan?
Broker vs. Insurance Carrier vs. community or risk
sharing “administration platforms”
New models may introduce new risks or transfer old ones
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20. Even what looks as “mere automation” brings in “new” risks
19
Event-triggered
smart contracts
Unbreakable Escrow and increased cyber risk exposure
How safe are Oracles?
Risk transfer to Blockchain frontier
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21. 20
Better pricing and
risk assessment
More accurate and personalized risk assessment:
Portable identity and provenance solutions
Data Self-Sovereignty
Tokenization of assets, behavior and social capital
Prediction markets as source of new actuarial data
Obsolescence of current predictive analytics engines
Pool of one is not a pool.
Model exhaustion leading to uninsurable people?
Even in the context of self-sovereign and selective data
sharing we will need governance for dark-side of analytics
Data Self-Sovereignty and the dark side of analytics
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22. Threats: Risks of using blockchain for insurance
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Risks of disintermediation
• Governance, liability and solvency in the context of autonomous
organizations
Risks of automation
• Internal automation – data sources, bugs, cyber risks
• Intra ecosystem automation – above + contractual risks
• DAO like automation – above + governance risks
• Hitting the blockchain frontier – temporary scope and scale risks
Risks of new data models
• Sustainability of product personalization
• Individuals ability to be fully liable for data
• Dark side of analytics
• Obsolescence of current architecture for data analytics
…well, actually, these risks apply to any industry using blockchain…
23. Opportunities: How many of these risks are insurable?
22
Cryptocurrency specific risks
“The” blockchain does not exist
Different types of risk along the different layers of the DLT stack
• Inherent design risks
• Implementation risks
• Operational and functionality risks
• Ecosystem design risks
Are you covering Silent Blockchain Risks?
Environmental risks
• Industry specific risks
• Regulatory uncertainty risks
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24. Opportunities: Providing risk capacity and actuarial expertise
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Solvency: solid reserving
What does a decentralized P2P “insurer” need to be sustainable?
Strong underwriting: Solid UW rules, actuarial models
Asset-Liability Management: capital efficient solutions
Ratemaking: accurate and competitive risk pricing
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Black-Swans: reinsurance
26. 25
Incumbents are thinking about blockchain
As a way to streamline existing intra and inter industry processes
As a way to generate scalable and cheaper automated products
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As a risk they may need to insure
As an ecosystem that could use industry expertise and enablement
27. 26
Incumbents are struggling to see blockchain
As a mechanism for decentralized P2P risk placement
As an enabler of a business model that can be monetized
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As a way of dealing with complex sources of risk
Getting the scope and scale it needs to actually become diversified and risk
resilient
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Thank you!
Magda Ramada
Magda.Ramada@willistowerswatson.com
@blockchain.magda.ramada
@MagdaRamada Magdalena
@WTWrisk Ramada Sarasola, PhD