From vending machines to global finance machines

What are smart contracts?

Definition #1: a

machine

programmed with

rules we could

have defined in a

contract; instead

machine performs

or verifies

performance

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”

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?

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 need to be legally enforceable? (Do courts needs to examine the guts of a vending machine to figure out what the parties intended?)

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, corporate, etc. deeds and charters, or from statutes or regulations, than from contracts: to make more distinctions with our metaphors we can think of “smart property”, “distributed autonomous organizations”, even “smart law”

Fiduciary (trusted) vs. fiduciary

process (smart contract)

If the public blockchain

has the money, it has

to treat it according to

its rules

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 institution(s) for its

integrity

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

Decentralization per computer

science is much more automated

& secure than traditional security

Computer Science

Centralization is insecure

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

partnership with law enforcement

in bringing the criminals to

justice” – J.P. Morgan spokesman

#JPMorgan Hack — Three Men

Charged in Biggest Bank Hack

in History (Identity Theft)

Public and global

Bitcoin Ethereum

Decentralization per computer

science is much more automated

& secure than traditional security

Computer Science

Diversity -> Independence -> Less Likelihood of

Collusion

Geopolitical insecurity (example: gold)

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

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 transfer

• Ethereum: geopolitically secure computer• secure financial instruments

Global Financial Machines

Examples and patterns

Dispute mediation

“Oracles”: input from the fallible world

Assurance contracts

Thought experiment: insurance

Dispute Mediation

2-of-3 multisig transaction between

2 parties

escrow/mediator

“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 happens at the source (hard for oracles to protect against this) LIBOR scandal: manipulating the market itself

Forgery

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

Could it be the

lawyers that will

be replaced by

the robots?

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 seamlessly across borders (public blockchains only)

Don’t need permission of middleman: business is between the claims adjustor(s) & the insured

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

Underwriting:

subjective (more

wet than dry)?

Claims

adjustment:

more wet

than dry

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, corruption, locality

Wet (traditionnal K) vs. dry (smart K) code

Law Software

Logic grounds

on

subjective

minds,

analogy

boolean logic,

bits

Security contempt/impr

isonment

replication +

cryptography

Predictability flexible rigid

Maturity highly evolved

/ many cases

larval / few

experiences

Wet (traditional K) vs. dry (smart K) code

Law Software

Area jurisdictional

silos

(on blockchain)

independence

from financial &

political

institutions &

seamless

operation across

borders

Costs lawsuits:

expensive

extremely low

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

blockchains) are wrong

Purists think we can do everything with

public blockchains are wrong

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)

Simplification?

Conclusion

Vending machine global finance

machine

Wet vs. dry code

Simplification?

Nick Szabo

nick@globalfinancialaccess.com

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