Swiss Re Ag · SIX:SREN
Swiss Re — Investor Presentation (2016)
39 slides from Swiss Re's investor presentation, 2016
Slide 1: From vending machines to global finance machines
From vending machines to global finance machines
Slide 2: What are smart contracts?
What are smart contracts? Definition #1: a machine programmed with rules we could have defined in a contract; instead machine performs or verifies performance
Slide 3: What are smart contracts?
What are smart contracts? #2: two parties agree to run software between them, or one party and the blockchain #3: long-lived blockchain process that handles money & blockchain-titled assets “distributed application” or “fiduciary process”
Slide 4: Tech often challenges legal categories
Tech often challenges legal categories • “UberCab” vs. ride-sharing • Bitcoin: currency or commodity? • Vaping: smoker or non- smoker? • “Are smart contracts enforceable”? Is that even a meaningful question?
Slide 5: Relationship between smart contracts and traditional law
Relationship between smart contracts and traditional law • A smart contract, like the repo man, is a security protocol that controls the burden of lawsuit • If “possession is 9/10 of the law”, then a cross-border, blockchain-based financial smart contract may be 99%+ of the law • Do smart contracts
Slide 6: Smart vs. traditional contracts
Smart vs. traditional contracts Traditional contract: verbal text on paper text on computer – wet code interpreted by brain Smart contract: rules / conditions analyzed & executed, as in vending machine -- dry code interpreted by machine Some dry rules are more like rules from property, cor
Slide 7: Fiduciary (trusted) vs. fiduciary process (smart contract)
Fiduciary (trusted) vs. fiduciary process (smart contract) If the public blockchain has the money, it has to treat it according to its rules
Slide 8: Why smart contracts?
Why smart contracts? Secure a wide variety of desiderata Costs of trust and security Especially keen across borders: different languages, laws, jurisdictions Security = vulnerability minimization = trust minimization e.g. a financial transaction that minimizes need to trust human instituti
Slide 9: Trusted strangers are security holes
Trusted strangers are security holes • Tempting in security protocol design, but it’s a cheat: “And then a miracle occurs” • Must be plugged by highly evolved institution or blockchain Minimize trust assumptions
Slide 10: You can trust me; do we really need a contract?
YOU CAN TRUST ME; DO WE REALLY NEED A CONTRACT? WEEKLYDESIGNGRIND Sos b 5
Slide 11: Decentralization is more automated and secure than traditional security
Decentralization per computer science is much more automated & secure than traditional security Computer Science
Slide 12: Centralization is insecure
Centralization is insecure
Slide 13: Insecurity drives up costs and gets you stuck inside national silos
Insecurity drives up costs and gets you stuck inside national silos Biggest reason traditional finance is stuck inside national silos: it depends on governments for its security. "We appreciate the strong #JPMorgan Hack — Three Men partnership with law enforcement Charged in Biggest Bank Hack in bri
Slide 14: Public and global
Public and global Bitcoin Ethereum
Slide 15: Decentralization is more automated and secure than traditional security
Decentralization per computer science is much more automated & secure than traditional security Computer Science
Slide 16: Diversity -> Independence -> Less Likelihood of Collusion
Diversity -> Independence -> Less Likelihood of Collusion
Slide 17: Geopolitical insecurity (example: gold)
Geopolitical insecurity (example: gold)
Slide 18: Geopolitically insecure finance
Geopolitically insecure finance Russian holdings of Treasury bonds Goldman Sachs collateral for DRs etc. between U.S. and Russia: $100s of millions Visa & Mastercard for credit card clearing between U.S. and Russia : $100s of millions Off on technicality: Argentine debt default
Slide 19: Global Finance Machines
Global Finance Machines Security that: • Doesn’t depend on politics, jurisdiction, or law • Works seamlessly across borders: same rules in Albania and Zimbabwe, Estonia and Venezuela, China and the United States Examples: • Bitcoin: geopolitically secure currency • secure asset registry / title tran
Slide 20: Global Financial Machines
Global Financial Machines Ethereum Network Nodes Nodes seen during the last 24 hours (Total: 394 Nodes) @ AlethOne © AlethZero © eth Geth © Gsoil © pyethapp
Slide 21: Examples and patterns
Examples and patterns Dispute mediation “Oracles”: input from the fallible world Assurance contracts Thought experiment: insurance
Slide 22: Dispute Mediation
Dispute Mediation 2-of-3 multisig transaction between 2 parties escrow/mediator
Slide 23: Oracles: input from the fallible world
“Oracles”: input from the fallible world On-chain programs can check for some obvious kinds of fraud and error Traditional source of fiduciary data: Birth and death certificates Stock prices Cryptography can protect integrity of transmission from source to blockchain Fraud usually happen
Slide 24: Pools & assurance contracts
Pools & assurance contracts e.g. Kickstarter Many parties send transactions to on- blockchain pool Blockchain code keeps track of total When total > threshold funds distributed to beneficiary Expires without total > threshold funds sent back to donors
Slide 25: Could it be the lawyers that will be replaced by the robots?
Could it be the lawyers that will be replaced by the robots?
Slide 26: Thought experiment: let's try to replace the insurance industry
Thought experiment: let’s try to replace the insurance industry Insured pays into blockchain pool Insured makes claim Claims adjuster(s) decide whether claim is valid & amount of damages damages released from pool to customer Benefits: Public / transparent / auditable Payments works se
Slide 27: Problems with "smart insurance"
Problems with “smart insurance” Problems: Trustworthiness of & law governing claims adjusters Who sets rates & based on what actuarial criteria (underwriting) How are claims adjusters paid
Slide 28: Underwriting: subjective (more wet than dry)?
Underwriting: subjective (more wet than dry)?
Slide 29: Claims adjustment: more wet than dry
Claims adjustment: more wet than dry
Slide 30: Interpretation & complexity
Interpretation & complexity Dry code –> harsh results in presence of unanticipated exceptions Anticipating edge cases: More conditions more complicated dry code (software) & more reliance on fallible external data Fewer conditions more role for human mediators more bias, whim, corrupti
Slide 31: Wet (traditional K) vs. dry (smart K) code
Wet (traditionnal K) vs. dry (smart K) code Law Software Logic grounds subjective boolean logic, on minds, bits analogy Security contempt/impr replication + isonment cryptography Predictability flexible rigid Maturity highly evolved larval / few / many cases experiences
Slide 32: Wet (traditional K) vs. dry (smart K) code
Wet (traditional K) vs. dry (smart K) code Law Software Area jurisdictional (on blockchain) silos independence from financial & political institutions & seamless operation across borders Costs lawsuits: extremely low expensive
Slide 33: Lessons from our thought experiment
Lessons from our thought experiment To take best advantage of blockchain, we need to use best of blockchain tech (public blockchains) with best of traditional finance (claims adjustors, stable investments, etc.) Finance industry people who want to operate with crippled blockchains (private block
Slide 34: aiiiliitth
aiiiliitth fl \ 5 ae “They presented us with an ironclad contract that we were able to totally reinterpret.”
Slide 35: Lessons from our thought experiment
Lessons from our thought experiment Smart contracts on blockchain provide plumbing for financial aspects of service which can seamlessly cross trust boundaries (e.g. national borders) Smart contracts don’t solve “wet” problems (e.g. claims adjustment & estimating risks -> setting fees)
Slide 36: Simplification?
Simplification?
Slide 37: Conclusion
Conclusion Vending machine global finance machine Wet vs. dry code Simplification?
Slide 38: Nick Szabo
Nick Szabo [email protected]
Slide 39: Basic Copyright Notice & Disclaimer
Basic Copyright Notice & Disclaimer ©2016 This presentation is copyright protected. All rights reserved. You may download or print out a hard copy for your private or internal use. You are not permitted to create any modifications or derivatives of this presentation without the prior written permiss