Asset Administration by Smart Contracts

Buterin’s white paper [Buterin 2014] described smart contracts as “systems which automatically move digital assets according to arbitrary pre-specified rules”.  [ISO 2019] defined an “asset” anything that has value to a stakeholder and a “digital asset” as one that that exists only in digital form or which is the digital representation of another asset. Similarly, a “Token” digital asset as representing a collection of entitlements. The tokenization of assets refers to the process of issuing a blockchain token (specifically, a security token) that digitally represents a real tradable asset—in many ways similar to the traditional process of securitization [Deloitte 2018]. A security token could thus represent an ownership share in a company, real estate, or other financial asset. These security tokens can then be traded on a secondary market. A security token is also capable of having the token-holder’s rights embedded directly onto the token, and immutably recorded on blockchain. Asset administration using smart contracts is emerging as a viable mechanism for digitized or tokenized assets though smart contracts may also have other purposes.

Recall that smart contracts started as an enhancement providing a programmable virtual machine in the context of blockchains, and the initial applications of blockchains were cryptocurrencies. Cryptocurrencies have been recognized as commodities for the purpose of regulations on derivatives like options and futures. High-value smart contracts on cryptocurrency derivatives require substantial legal protection and often utilize standardized legal documentation provided by the International Swaps and Derivatives Association (ISDA). Smart contracts managing cryptocurrency derivatives aim to automate many aspects of the provisions of the ISDA legal documentation [Clack 2019]. There have been a number of efforts to extend blockchains and smart contracts beyond cryptocurrency applications to manage other types of assets. Initially these were custom dApps, but as interest in smart contracts for specific types of assets grew, then a corresponding interest developed in having common token representations for particular types of asset, enabling broader interoperability, and reducing custom legal and development risks and costs. Rather than having specialized blockchains for supply chain provenance and other for smart derivatives contracts, different tokens representing those asset classes can be managed by a smart contract independently of the underlying blockchain technology.

Not all tokens are intrinsically valuable, many derive their value by reference from some underlying asset. [Bartoletti 2017] classifies smart contracts by application domain as financial, notary (leveraging the immutability of the blockchain to memorialize some data), games (of skill or chance), wallet (managing accounts, sometimes with multiple owners), library (for general purpose operations e.g. math and string transformations) and unclassified (The financial and notary categories had the most contracts.). The notary smart contracts enabled the smart contracts to manage non cryptocurrency assets. [Alharby 2018] classified smart contract literature using a keyword technique into: security, privacy, software engineering, application (e.g. IoT), performance & scalability and other smart contract related topics.  The application domains were identified as: Internet of Thing (IoT), cloud computing, financial, data (e.g., data sharing, data management, data indexing, data integrity check, data provenance), healthcare, access control & authentication and other applications. [Rouhani 2019] categorized decentralized applications in seven main groups include healthcare, IoT, identity management, record keeping, supply chain, BPM, and voting. However, the blockchain-based applications are not limited to these groups. Keywords and application identification, provide a view of the breadth of applications, but these are not exclusive or finite categories – new applications or keywords  can always be developed extending those lists. Token based music platforms have been proposed [Mouloud 2019]. Networked digital sharing economy services enable the effective and efficient sharing of vehicles, housing, and everyday objects utilizes a blockchain ledger and smart contracting technologies to improve peer trust and limit the number of required intermediaries, respectively [Fedosov 2018]. The tokenization of sustainable infrastructure can address some of the fundamental challenges in the financing of the asset class, such as lack of liquidity, high transactions costs and limited transparency [Uzoski 2019]. Tokens can also be useful from a privacy perspective. Tokenization, the process of converting a piece of data into a random string of characters known as a token, can be used to protect sensitive data by substituting non-sensitive data. The token serves merely as a reference to the original data; but does not determine those original data values. The advantage of tokens, from a privacy perspective, is that there is no mathematical relationship to the real data that they represent. The real data values cannot be obtained through reversal [Morrow 2019]. If the costs of tokenizing and marketing new asset classes are lower than costs of traditional securities offerings, then this can enable securitization of new asset classes. The ability to subdivide the some types of tokens may enable wider markets through reduced minimum bid sizes.

In 2004, early proposals were made for XML data type definitions to capture electronic contracts [Krishna 2004]. In 2015, the Ethereum developer community adopted ERC-20 (which specifies a common interface for fungible tokens that are divisible and not distinguishable) to ensure interoperability [Vogelsteller 2015]. While the initial token applications may have been for cryptocurrencies, blockchains (especially ethereum) are being applied in a lot of other domains, and so assets administered by the smart contracts are being stretched beyond their original purpose to enable new applications. Studies of trading patterns would need to distinguish whether those tokens were all being used to represent the same kind of asset to be able to make valid inferences about a particular market for that asset. Stretching beyond the fungible cryptocurrencies to enable popular new blockchain applications like tracking supply chain provenance requires a a different kind to token, a non-fungible token. Non-fungible tokens (NFTs) are a new type of unique and indivisible blockchain-based tokens introduced in late 2017 [Regner 2019]. The Ethereum community in 2018 adopted ERC-721 which extends the common interface for tokens by additional functions to ensure that tokens based on it are distinctly non-fungible and thus unique. [Entriken 2018].

In 2018, [FINMA 2018] identified 3 classes of tokens – payment tokens, asset tokens and utility tokens. A utility token as intended to provide access digitally to an application or service, by means of a blockchain-based infrastructure. This may include the ability to exchange the token for the service.

In 2019, [Hong 2019] proposed a non-fungible token structure for use in hyperledger, and [Cai 2019] proposed universal token structure for use in token based blockchain technology. Also in 2019,  an industry group, the Token Taxonomy Initiative, proposed a Token Taxonomy Framework [TTI 2019] in an effort to model existing and define new business models based on it. TTI defines a token as a representation of some shared value that is either intrinsically digital or a digital receipt or title for some material item or property and distinguishes that from a wallet which is a repository of tokens attributed to an owner in one or more accounts. TTI classifies tokens based on five characteristics they possess: token type (fungible or not), token unit (fractional, whole, singleton), value type (intrinsic or reference), representation type (common or unique), and template type (Single or hybrid). The base token types are augmented with behaviors and properties captured in a syntax (the token formula). Particular token formulae would be suitable for different business model applications – e.g. loyalty tokens, supply chain SKU tokens, securitized real property tokens, etc.   This Token Taxonomy Framework subsumes the functions, features and distribution aspects of the FINMA token model, enabling those regulatory perspectives as well as other properties of particular value in enabling different token-based business models.

The immutable, public Ethereum blockchain enables study of the trading patterns in ERC-20 tokens, revealing trading networks that display strong power-law properties (coinciding with current network theory expectations) [Soumin 2018]. Even though the entire network of token transfers has been claimed to follow a power-law in its degree distribution, many individual token networks do not: they are frequently dominated by a single hub and spoke pattern. When considering initial token recipients and path distances to exchanges, a large part of the activity is directed towards these central instances, but many owners never transfer their tokens at all [Victor 2019]. There is strong evidence of a positive relationship between the price of ether and price of the blockchain tokens. Token function does impact token price, over a time period that spans both boom and bust. The designed connection can be effective; linking a project that has a value, with a token that has a price, specifically in the absence of a legal connection or claim [Lo 2019]. From these preliminary studies, tokens seem to exhibit some of the trading properties of regular securities. Many of these initial tokens have no or untested legal connections to the underlying assets. While consistent behavior in boom and bust is important for an investment, from a legal perspective, the predictability of outcomes for asset recovery during more stressful events (e.g. bankruptcy) may be more important.

A point of concern is understanding how tokens representing value will remain linked to the real asset that they represent. For example, imagine if you own tokens representing a small fraction of a set of gold coins at a bank, and some coins are stolen. Or the reverse – who owns the gold coins if the account keys are lost or the token destroyed? Being able to rationally predict what happens to your token and to the other token owners is crucially important, since the value of tokens becomes greatly undermined if they cannot be proven to be linked to real-world assets [Deloitte 2018]. In these types of cases, off chain enforcement action is required. A typical legal tool for representing such interests in real assets would be recording security interests and liens in real property under the UCC.  One approach would be to update the lien recordings for the new owner after each transaction. There are at least two difficulties with this approach. First, the smart contract of today may not be able to interact with manual off-chain legal recordation processes for security interests. Secondly, if the purpose of tokenizing the asset was to increase liquidity, frequent transactions may result in a high volume of updates overloading off-chain manual recordation processes. Another approach would be to use some centralized custody agent (similar to physical custody) and have them hold the lien in the public records as a trustee (perhaps keeping account records reflecting updates from transactions on a blockchain). If the smart contract was a legal entity (e.g., a Vermont style BBLLC), then the BBLLC could be the entity with the security interest in the public records directly. However – the smart contract would need to be able to respond to legal actions on the lien; and may incur other obligations when acting as the custodian (e.g., reporting, insurance, licenses, etc.). The asset custodian as a traditional entity vs the BBLLC dApp provides alternatives for consideration. Traditional asset custodians provide an identifiable party from whom reparations can be sought in the event of asset loss or degradation. Asset custodians are commonly held to a fiduciary standard of care. A BBLLC approach emphasizes a digital distributed trust model; BBLLC’s, however, may be challenged with off-chain enforcement actions and physical custody operations (e.g., physical asset audits). BBLLC custodians may require insurance to protect asset owners in the event of asset losses/degradation.   

If ownership of an asset, such as a building, is split among thousands of people, there is little incentive for owners to bear the costs associated with that asset, such as maintenance and ensuring rent is collected [Deloitte 2018]. One can certainly imagine a smart contract detecting that rent has not been credit to an account, but what then can be done in terms of off-chain enforcement? While IoT blockchains can enable significant cyberphysical functionality, typical landlord capabilities of self-help and legal dispossessory actions would seem technically difficult or socially problematic. Some classes of contracts requiring off-chain enforcement actions may not be a good fit for complete implementation by dApp smart contracts at this stage; and may still require human physical agents or other legal entities for some actions.

Because the transaction of tokens is completed with smart contracts, certain parts of the exchange process are automated. For some classes of transactions, this automation can reduce the administrative burden involved in buying and selling, with fewer intermediaries needed, leading to not only faster deal execution, but also lower transaction fees [Deloitte 2018]. Elimination of intermediaries sounds financially efficient; eliminating all intermediaries, however, may not be wise for some classes of assets. An intermediate entity may be useful as a liability shield for remote owners. Consider a tokenized mobile asset (e.g., a drone or terrestrial vehicle) owned and operated via a smart contract, which injures another or their property; most remote owners would insist on some limited liability entity or insurance. While smart contract operated vehicles may not be computationally feasible in the short term, even immobile asset classes like real estate can result in liabilities for the owner (e.g., premises slip and fall).  The point being that for some set of physical asset classes, the existence of at least one intermediate entity for the purpose of liability shielding may be desirable.   The actions of smart contracts on public blockchains may also raise privacy concerns 

By tokenizing financial assets—especially private securities or typically illiquid assets—these tokens can be then be traded on a secondary market of the issuer’s choice, enabling greater portfolio diversification, and capital investment in otherwise illiquid assets. Tokenization could open up investment in assets to a much wider audience through reduced minimum investment amounts and periods. Tokens can be highly divisible, meaning investors can purchase tokens that represent incredibly small percentages of the underlying assets. If each order is cheaper and easier to process, it will open the way for a significant reduction of minimum investment amounts [Deloitte 2018]. Token markets to date have often been via exempt ICOs that are restricted to accredited investors, minimizing regulatory filings, etc. Investment minimums are unlikely a major driver for accredited investors, though enabling investment in diverse, but otherwise illiquid asset classes may be of interest for portfolio diversification. Enabling liquidity for mass market investors would require security token investments to meet the necessary higher regulatory standards for filings and disclosures to bring those investments to the larger public markets. Smart contracts offer efficient process automation for trading and other transactions based on tokenized assets. While this can provide market efficiencies, not all asset classes are ready for tokenization without further consideration. Smart contracts may also need to take on additional behaviors to reflect the increased importance of their role in administering assets. Asset administration using smart contracts is emerging as a viable mechanism for digitized or tokenized assets.

References

[Alharby 2018] M. Alharby, et. al., “Blockchain-based smart contracts: A systematic mapping study of academic research (2018).” Proc. Int’l Conf. on Cloud Computing, Big Data and Blockchain. 2018.

[Bartoletti 2017] M. Bartoletti & L. Pompianu. “An empirical analysis of smart contracts: platforms, applications, and design patterns.” International conference on financial cryptography and data security. Springer, Cham, 2017.

[Buterin 2014] V. Buterin, “A next-generation smart contract and decentralized application platform.” white paper 3 (2014): 37.

[Cai 2019] T.Cai, et al. “Analysis of Blockchain System With Token-Based Bookkeeping Method.” IEEE Access 7 (2019): 50823-50832.

[Clack 2019] C. Clack, & C. McGonagle. “Smart Derivatives Contracts: the ISDA Master Agreement and the automation of payments and deliveries.” arXiv preprint arXiv:1904.01461 (2019).

[Deloitte 2018] Deloitte, “The tokenization of assets is disrupting the financial industry. Are you ready?  “ (2018)

[Entriken 2018] W. Entriken, et.al.,  ERC 721 Non-Fungible Token Standard (2018)

[Fedosov 2018] A. Fedosov, et. al., “Sharing physical objects using smart contracts.” Proceedings of the 20th Int’l Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct. ACM, 2018.

[FINMA 2018] FINMA Guidelines for enquiries regarding the regulatory framework for initial coin offerings (ICOs), Report, Swiss Financial Market Supervisory Authority.

[Hong 2019] S. Hong, et. al., “Design of Extensible Non-Fungible Token Model in Hyperledger Fabric.” Proc. of the 3rd Workshop on Scalable and Resilient Infrastructures for Distributed Ledgers. ACM, 2019.

[ISO 2019] ISO, “Blockchain and distributed ledger technologies — Terminology”, ISO/DIS 22739:2019

[Krishna 2004] P. Krishna, et.al., “An EREC framework for e-contract modeling, enactment and monitoring.” Data & Knowledge Engineering51.1 (2004): 31-58.

[Lo 2019] Y. Lo, et. al., “Assets on the Blockchain: An Empirical Study of Tokenomics.” Available at SSRN 3309686 (2019).

[Migliorini 2019] S. Migliorini, et. al., “The Rise of Enforceable Business Processes from the Hashes of Blockchain-Based Smart Contracts.” Enterprise, Business-Process and Information Systems Modeling. Springer, Cham, 2019. 130-138.

[Morrow 2019] M. Morrow, & M. Zarrebini. “Blockchain and the Tokenization of the Individual: Societal Implications.” Future Internet 11.10 (2019): 220.

[Mouloud 2019] K. Mouloud, “Blockchain in the Music Industry: A Study of Token Based Music Platforms” S. Diss. Aalborg University, 2019.

[Soumin 2018] S. Somin, et. al., “Network analysis of erc20 tokens trading on ethereum blockchain.” International Conference on Complex Systems. Springer, Cham, 2018.

[Regner 2019] F. Regner, et.al., “NFTs in Practice: Non-Fungible Tokens as Core Component of a Blockchain-based Event Ticketing Application.” (2019).

[TTI 2019] Token Taxonomy Initiative“Token Taxonomy Framework Overview”, Nov 2019

[Uzoski 2019] Uzsoki, David. “Tokenization of Infrastructure.” (2019).

[Victor 2019] F. Victor, & B. Lüders, “Measuring Ethereum-based ERC20 token networks.” International Conference on Financial Cryptography and Data Security. Springer, Cham, 2019.

[Vogelsteller 2015] F.Vogelsteller & V. Buterin,  ERC-20 Token Standard (2015)