Page 155 - ITU-T Focus Group Digital Financial Services – Technology, innovation and competition

ITU-T Focus Group Digital Financial Services
Technology, Innovation and Competition

4.3 Opportunities and challenges with smart contracts

The potential benefits of smart contracts include low contracting, enforcement, and compliance costs. They
consequently make it economically viable to form contracts for numerous low-value transactions. Smart
contracts then could be successfully applied in e-commerce, where they can significantly facilitate trade by
reducing counterparty risk and the costs of transacting by minimizing the human factor in the process.

In a practical use case example, where a contract between parties to purchase a property asset is written into
a blockchain and a set triggering event, such as a lowering of interest rates to a certain level is reached, the
contract will execute itself according to the coded terms and without any human intervention. This could in turn
trigger payment between parties and the purchase and registration of a property in the new owner’s name.

The smart contract may also make the need for escrow redundant. The legal impact is established through the
smart contract execution, without additional intervention. This methodology contrasts with the conventional,
centralized ID database in which rules are set at the entire database level, or in the application, but not in the
transaction.

In another example, national IDs could be placed on a specific blockchain, and the identifiable person could
embed (smart contract) rules into their unique ID entry, allowing only specific entities to access their ID for
specific purposes and for a certain time. The person can, through the blockchain, monitor this use.

Potential risks to smart contract technology include: A reliance on the computing system itself that executes
the contract; flaws in the smart contract code; or the reliance on an external ‘off chain’ event or person ‒ to
integrate with and execute ‒ the embedded terms of the smart contract. 60
Although ‘digital events’ may seamlessly trigger a smart contract, initiation of a digital event from the physical
(external) world could be problematic. For example, if a smart contract retrieves some information from an
external source, this retrieval must be performed repeatedly and separately by each user node. But, because
this source is outside of the blockchain – known as ‘offchain,’ there is no guarantee that every node will receive
the same answer, and at the same time. Or, as has been suggested, perhaps the source will change its
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response in the time between requests from different nodes, or perhaps it will become temporarily unavailable.
In either of these scenarios, the consensus necessary for the blockchain to be in sync may be broken. Three
possible solutions have been proposed ‒ multi-signature transactions, prediction markets, and oracles
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– but all require the intervention of humans, in a group or individually. This need does undermine the DLT
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goal of a decentralized automated system. Automated performance also does not guarantee that parties will
always, or even often, be capable of determining all eventualities, as what happens after parties strike a deal
is often unpredictable. 67

60 See further, Kakavand, H (2016) The Blockchain Revolution: An Analysis of Regulation and Technology Related to Distributed
Ledger Technologies, available at https:// ssrn. com/ abstract= 2849251.
61 This may be particularly pronounced with DLTs with high latencies, whereby the nodes all need to be communicated with, and
their responses obtained.
62 See Olickel, H (2016) Why Smart Contracts Fail: Undiscovered Bugs and What We Can Do About Them, available at https:// goo. gl/
0PTBIm .
63 Multi-signature transactions require a trust agent to be involved to ensure that the conditions for triggering the contract
between the parties have been met and the contract can be executed. LTP (2016) Blockchain-Enabled Smart Contracts: Applica-
tions and Challenges, available at https:// goo. gl/ fzwLSR .
64 The accuracy of prediction markets rests in the idea that the average prediction made by a group is superior to that made by any
of the individuals in that group. The economic incentive can be built in a way so that it rewards the most accurate prediction. For
an example of implementation of predictive market technology built on the Ethereum blockchain, see www. augur. net. See also
LTP (2016) ibid; and Needham (2015) ibid.
65 Oracle services are third-parties that are verifying the outcome of the events and feed the data to smart contracts data services.
However, the issue of trust of these oracles has been raised. LTP (2016) ibid.
66 See Shabab, H (2014) What are Smart Contracts, and What Can We do with Them?, available at https:// goo. gl/ xpG0FS ; and
Wright, A and De Filippi, P (2015) Decentralized Blockchain Technology and the Rise of Lex Cryptographia, available at https://
ssrn. com/ abstract= 2580664.
67 Shabab (2014) ibid

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