The Role of ERC-3643 in Real World Assets (RWA) Tokenization

Miłosz

12 Jan 2024
The Role of ERC-3643 in Real World Assets (RWA) Tokenization

Historically, the conversion of assets from physical to digital formats has been fraught with regulatory ambiguities and burdensome accessibility for micro-investors. Until recently, technological limitations and a lack of operational legal clarity have hindered the effectiveness of tokenization. The development of ERC-3643 represents a complex yet essential endeavor, traversing practices array while maintaining strict mandates across jurisdictions. Overcoming these barriers seems to have been the driving force behind the creators from the start. Thereupon, we invite you to acquire an impact of ERC-3643 on the RWA tokenization with us!

Redefining RWA Tokenization with ERC-3643

Source: ERC-3643 Association

Diversification: The ERC-3643 standard assigns on-chain representation of broad resources ointment. This involves issuing digital tokens that stand as physical product quantity, value, and profit shares.

Exposure: A fractional ownership feature embedded into the token lowers an entry barrier while supplying more liquidity into the market and attracting less affluent individuals.

Transfer: The process of rights ownership and transfers has been formed into a permission-need framework.

Innovation: ERC-3643 tokens can be structured in the form of a basket of commodities, involving different market segments. Additionally, the protocol enables the creation of commodity-backed stablecoins, providing a lower-risk investment option.

Regulatory Versatility: Programmable token functions, multi-layered access controls, compliance checks, automated reporting, and other security mechanisms - these all prioritize alignment with both current and future regulations.

Find out the RWA definition & examples - we've it covered extensively here!

Integration of ERC-3643 into Global Supply Chains

Traceability: By tokenizing single products or batches, companies can track the journey of items in real time, from manufacturing to delivery. Undoubtedly, this level of validation is crucial for preventing counterfeits and ensuring item quality. 

Automation: ERC-3643 optimizes many supply chain processes including settlements and legal compliance checks. It reduces the need for intermediaries and cuts down project operational costs. Also, minimizes the risk of human error.

Storage Management: A more accurate and real-time view of inventory levels. Tokenization makes it easier to track stock movements and predict supply needs, leading to reduced wastage.

Cross-Border Orders: ERC-3643 may straightforward international transactions by providing a unified system for shipment tracking. This could help in reducing delays caused by customs checks and documentation.

Consumers' confidence: The legitimacy offered by ERC-3643 builds greater trust in brands, in particular, where authenticity and ethical sourcing are paramount.

Integration with IoT and AI: IoT devices can feed real-time data into the blockchain network, so AI analyzes these, which eventually leads to more informed decision-making. 

Security: ERC-3643 token metadata is protected against tampering and unauthorized access, especially due to advanced permissions and restriction features.

ERC-3643 and the World of Art

Revenue Streams: Artists, by selling divided, more affordable fractions of their compositions, generate income while retaining a portion of their creative capital. In regards, enthusiasts who were previously priced out of the market are now fully entitled to participate in this highly valued sector.

Authenticity: One of the perennial industry challenges was to maintain artwork's provenance and genuineness. ERC-3643 embeds more detailed information into the token. This blockchain-based approach ensures a tamper-proof record and appropriate infrastructure for copyright management.

Art Curations: ERC-3643 facilitates innovative exhibition possibilities. Galleries and museums, acting as halls of art, could tokenize or create virtual collections, meanwhile, spreading creator contributions to a global audience.

ERC-3643 Transforms Intangible Assets Offerings

Democratization: ERC-3643 enables the tokenization of IP and patents, also partial, so that inventors monetize licensing or commercialization of the rights in the form of tokens.

Distribution: Smart contracts can be programmed to automatically grant licenses and distribute royalties to token holders whenever the IP is used commercially. This reduces administrative overhead and ensures fair and timely payments to rights holders.

Auditability: ERC-3643 provides unparalleled simplicity in intellectual property trading. It also concerns applications, approvals, and transfers of patents. Immutable transaction statements with protocol security measures prevent disputes over rights ownership and utilization.

Collaboration: The standard facilitates new forms of joint ventures in IP development. Multiple parties can hold stakes in a paten, sharing risks, rewards more equitably, and so on. Spur innovations and continuous refinements motivate ERC-3643 principles then.

AI and ERC-3643 Join Together

Tokenization: Artificial Intelligence raises huge concerns about the authenticity and origin of content. The potential for misuse, such as deepfakes or falsified data, poses risks to publicly accessible information and makes the verification more essential than ever. ERC-3643 standard introduced by Tokeny, leverages a framework that can be instrumental in the AI-generated matter distribution. Blockchain technology's inherent characteristics ensure every piece is traceable back to its source, distinguishing between genuine creations and violent disinformation. Tokenization of AI content via ERC-3643 involves assigning a unique digital token, acting as a digital certificate. Each one contains metadata e.g. creation date, provenance, and any modifications made. ERC-3643's smart contract capabilities can also be programmed in a way acknowledging that specific criteria have been met before proliferation.

Fox Corporation, a mass media production & distribution company, has recently unveiled a prototype of a new open-source protocol named Verify, which is developed on the Polygon network. Publishers register their content and ensure provenance, securely marking each piece with a cryptographic signature. Since ERC3643 tailors mostly for permission-needed transfers, restricted access features, and programmable token lifecycle management rules, its implementation might refine such tools' performance shortly.

Source: Polygon Technology

Symbiosis: Various issues around intellectual property rights management, and data privacy must be carefully considered. ERC-3643 provides a starting point for proposing a legal-adherent tokenization process. Looking ahead, it could become a standard tool for the reliable distribution of trusted and valued sources.

Unraveling the Potential of Tokenized Infrastructure Projects

Accessibility: Generally, infrastructure projects like bridges, highways, or renewable energy have been the domain of institutional investors or government entities due to the substantial capital requirements. ERC-3643 expands these investment opportunities permitting small-scale fractional investment in similar, lucrative initiatives.

Flexibility: Described rather as long-term investments, these projects characterize limited liquidity. Potential secondary markets, introduced through tokenization, could encourage retail investors to consider entering the market despite legacy large-cap requirements. 

Management: A decentralized ledger helps monitor progress, fund allocation, and project profitability.

Financing: Raising capital for infrastructure projects is often a cumbersome and expensive process. ERC-3643 offers wider access to a pool of investors through token sales breaking geographical boundaries and allowing for quicker venture initiation.

Revenue Models: ERC3643 allocates shared yields based on the project income generation and the token ratio owned by the investor, similar to energy sales in solar farms. This model concentrates investor returns and operation success, creating a mutually beneficial scenario.

Cross-jurisdictional Compliance: Given the heavily regulated nature of infrastructure projects, the legal adherence-oriented design of the standard is a key advantage. It ensures contribution to local and international frameworks concerning investments, ownership, and revenue distribution.

Healthcare Enhancements through ERC-3643 Implementation

Research Funding: ERC-3643 facilitates securing funds for medical research and development, thanks to tokenized bonds or tokens issued by clinical examination sponsors.

Facilities: Systematic improvements to the healthcare ecosystem can be accomplished by tokenizing medical equipment or entire centers using the T-REX protocol. 

Data management: Personal data, medical case records, and other sensitive information, in the age of increasing digitization, could be also stored on the blockchain. Ethical aspects of their usage must be always obeyed. Relatedly, the ERC3643 smart contract, upon acquiring patient consent, would provide authorized access and seamless interaction between particular healthcare providers.

Regulations: The compliance-centric architecture of ERC-3643 targets legal integrity while respecting existing personal data processing practices. 

Conclusion

The implementation of ERC3643, as we've seen, extends far beyond the traditional financial instruments. The standard offers a blueprint for tokenizing assets that were once considered challenging.  The capability of ERC3643 to ensure regulatory adherence, coupled with its flexibility and scalability, marks it as an indispensable tool in modern asset management where the boundaries of asset ownership, accessibility, transfer, and utilization are being respected.

If you are interested in utilizing ERC-3643 or other blockchain-based solutions for your project, please reach out to contact@nextrope.com

How does ERC-3643 impact supply chains and art world?

  • ERC-3643 enhances supply chain traceability, automates processes, boosts consumer confidence, and enables fractional ownership in the art world, ensuring authenticity and provenance verification.

What benefits does ERC-3643 offer for intellectual property and infrastructure projects?

  • ERC-3643 facilitates IP tokenization, simplifies revenue distribution, and fosters collaboration. In infrastructure, it broadens investment opportunities, improves project management, and ensures regulatory compliance.

How does ERC-3643 contribute to healthcare and AI integration?

  • ERC-3643 secures funding for medical research, enhances facility management, and ensures data security in healthcare. It also aids AI content verification, ensuring authenticity and origin tracking.

Why is ERC-3643 significant for asset management?

  • ERC-3643 ensures regulatory compliance, offers flexibility and scalability, and provides a framework for tokenizing challenging assets, making it essential in modern asset management.

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Applying Game Theory in Token Design

Kajetan Olas

16 Apr 2024
Applying Game Theory in Token Design

Blockchain technology allows for aligning incentives among network participants by rewarding desired behaviors with tokens.
But there is more to it than simply fostering cooperation. Game theory allows for designing incentive-machines that can't be turned-off and resemble artificial life.

Emergent Optimization

Game theory provides a robust framework for analyzing strategic interactions with mathematical models, which is particularly useful in blockchain environments where multiple stakeholders interact within a set of predefined rules. By applying this framework to token systems, developers can design systems that influence the emergent behaviors of network participants. This ensures the stability and effectiveness of the ecosystem.

Bonding Curves

Bonding curves are tool used in token design to manage the relationship between price and token supply predictably. Essentially, a bonding curve is a mathematical curve that defines the price of a token based on its supply. The more tokens that are bought, the higher the price climbs, and vice versa. This model incentivizes early adoption and can help stabilize a token’s economy over time.

For example, a bonding curve could be designed to slow down price increases after certain milestones are reached, thus preventing speculative bubbles and encouraging steadier, more organic growth.

The Case of Bitcoin

Bitcoin’s design incorporates game theory, most notably through its consensus mechanism of proof-of-work (PoW). Its reward function optimizes for security (hashrate) by optimizing for maximum electricity usage. Therefore, optimizing for its legitimate goal of being secure also inadvertently optimizes for corrupting natural environment. Another emergent outcome of PoW is the creation of mining pools, that increase centralization.

The Paperclip Maximizer and the dangers of blockchain economy

What’s the connection between AI from the story and decentralized economies? Blockchain-based incentive systems also can’t be turned off. This means that if we design an incentive system that optimizes towards a wrong objective, we might be unable to change it. Bitcoin critics argue that the PoW consensus mechanism optimizes toward destroying planet Earth.

Layer 2 Solutions

Layer 2 solutions are built on the understanding that the security provided by this core kernel of certainty can be used as an anchor. This anchor then supports additional economic mechanisms that operate off the blockchain, extending the utility of public blockchains like Ethereum. These mechanisms include state channels, sidechains, or plasma, each offering a way to conduct transactions off-chain while still being able to refer back to the anchored security of the main chain if necessary.

Conceptual Example of State Channels

State channels allow participants to perform numerous transactions off-chain, with the blockchain serving as a backstop in case of disputes or malfeasance.

Consider two players, Alice and Bob, who want to play a game of tic-tac-toe with stakes in Ethereum. The naive approach would be to interact directly with a smart contract for every move, which would be slow and costly. Instead, they can use a state channel for their game.

  1. Opening the Channel: They start by deploying a "Judge" smart contract on Ethereum, which holds the 1 ETH wager. The contract knows the rules of the game and the identities of the players.
  2. Playing the Game: Alice and Bob play the game off-chain by signing each move as transactions, which are exchanged directly between them but not broadcast to the blockchain. Each transaction includes a nonce to ensure moves are kept in order.
  3. Closing the Channel: When the game ends, the final state (i.e., the sequence of moves) is sent to the Judge contract, which pays out the wager to the winner after confirming both parties agree on the outcome.

A threat stronger than the execution

If Bob tries to cheat by submitting an old state where he was winning, Alice can challenge this during a dispute period by submitting a newer signed state. The Judge contract can verify the authenticity and order of these states due to the nonces, ensuring the integrity of the game. Thus, the mere threat of execution (submitting the state to the blockchain and having the fraud exposed) secures the off-chain interactions.

Game Theory in Practice

Understanding the application of game theory within blockchain and token ecosystems requires a structured approach to analyzing how stakeholders interact, defining possible actions they can take, and understanding the causal relationships within the system. This structured analysis helps in creating effective strategies that ensure the system operates as intended.

Stakeholder Analysis

Identifying Stakeholders

The first step in applying game theory effectively is identifying all relevant stakeholders within the ecosystem. This includes direct participants such as users, miners, and developers but also external entities like regulators, potential attackers, and partner organizations. Understanding who the stakeholders are and what their interests and capabilities are is crucial for predicting how they might interact within the system.

Stakeholders in blockchain development for systems engineering

Assessing Incentives and Capabilities

Each stakeholder has different motivations and resources at their disposal. For instance, miners are motivated by block rewards and transaction fees, while users seek fast, secure, and cheap transactions. Clearly defining these incentives helps in predicting how changes to the system’s rules and parameters might influence their behaviors.

Defining Action Space

Possible Actions

The action space encompasses all possible decisions or strategies stakeholders can employ in response to the ecosystem's dynamics. For example, a miner might choose to increase computational power, a user might decide to hold or sell tokens, and a developer might propose changes to the protocol.

Artonomus, Github

Constraints and Opportunities

Understanding the constraints (such as economic costs, technological limitations, and regulatory frameworks) and opportunities (such as new technological advancements or changes in market demand) within which these actions take place is vital. This helps in modeling potential strategies stakeholders might adopt.

Artonomus, Github

Causal Relationships Diagram

Mapping Interactions

Creating a diagram that represents the causal relationships between different actions and outcomes within the ecosystem can illuminate how complex interactions unfold. This diagram helps in identifying which variables influence others and how they do so, making it easier to predict the outcomes of certain actions.

Artonomus, Github

Analyzing Impact

By examining the causal relationships, developers and system designers can identify critical leverage points where small changes could have significant impacts. This analysis is crucial for enhancing system stability and ensuring its efficiency.

Feedback Loops

Understanding feedback loops within a blockchain ecosystem is critical as they can significantly amplify or mitigate the effects of changes within the system. These loops can reinforce or counteract trends, leading to rapid growth or decline.

Reinforcing Loops

Reinforcing loops are feedback mechanisms that amplify the effects of a trend or action. For example, increased adoption of a blockchain platform can lead to more developers creating applications on it, which in turn leads to further adoption. This positive feedback loop can drive rapid growth and success.

Death Spiral

Conversely, a death spiral is a type of reinforcing loop that leads to negative outcomes. An example might be the increasing cost of transaction fees leading to decreased usage of the blockchain, which reduces the incentive for miners to secure the network, further decreasing system performance and user adoption. Identifying potential death spirals early is crucial for maintaining the ecosystem's health.

The Death Spiral: How Terra's Algorithmic Stablecoin Came Crashing Down
the-death-spiral-how-terras-algorithmic-stablecoin-came-crashing-down/, Forbes

Conclusion

The fundamental advantage of token-based systems is being able to reward desired behavior. To capitalize on that possibility, token engineers put careful attention into optimization and designing incentives for long-term growth.

FAQ

  1. What does game theory contribute to blockchain token design?
    • Game theory optimizes blockchain ecosystems by structuring incentives that reward desired behavior.
  2. How do bonding curves apply game theory to improve token economics?
    • Bonding curves set token pricing that adjusts with supply changes, strategically incentivizing early purchases and penalizing speculation.
  3. What benefits do Layer 2 solutions provide in the context of game theory?
    • Layer 2 solutions leverage game theory, by creating systems where the threat of reporting fraudulent behavior ensures honest participation.

Token Engineering Process

Kajetan Olas

13 Apr 2024
Token Engineering Process

Token Engineering is an emerging field that addresses the systematic design and engineering of blockchain-based tokens. It applies rigorous mathematical methods from the Complex Systems Engineering discipline to tokenomics design.

In this article, we will walk through the Token Engineering Process and break it down into three key stages. Discovery Phase, Design Phase, and Deployment Phase.

Discovery Phase of Token Engineering Process

The first stage of the token engineering process is the Discovery Phase. It focuses on constructing high-level business plans, defining objectives, and identifying problems to be solved. That phase is also the time when token engineers first define key stakeholders in the project.

Defining the Problem

This may seem counterintuitive. Why would we start with the problem when designing tokenomics? Shouldn’t we start with more down-to-earth matters like token supply? The answer is No. Tokens are a medium for creating and exchanging value within a project’s ecosystem. Since crypto projects draw their value from solving problems that can’t be solved through TradFi mechanisms, their tokenomics should reflect that. 

The industry standard, developed by McKinsey & Co. and adapted to token engineering purposes by Outlier Ventures, is structuring the problem through a logic tree, following MECE.
MECE stands for Mutually Exclusive, Collectively Exhaustive. Mutually Exclusive means that problems in the tree should not overlap. Collectively Exhaustive means that the tree should cover all issues.

In practice, the “Problem” should be replaced by a whole problem statement worksheet. The same will hold for some of the boxes.
A commonly used tool for designing these kinds of diagrams is the Miro whiteboard.

Identifying Stakeholders and Value Flows in Token Engineering

This part is about identifying all relevant actors in the ecosystem and how value flows between them. To illustrate what we mean let’s consider an example of NFT marketplace. In its case, relevant actors might be sellers, buyers, NFT creators, and a marketplace owner. Possible value flow when conducting a transaction might be: buyer gets rid of his tokens, seller gets some of them, marketplace owner gets some of them as fees, and NFT creators get some of them as royalties.

Incentive Mechanisms Canvas

The last part of what we consider to be in the Discovery Phase is filling the Incentive Mechanisms Canvas. After successfully identifying value flows in the previous stage, token engineers search for frictions to desired behaviors and point out the undesired behaviors. For example, friction to activity on an NFT marketplace might be respecting royalty fees by marketplace owners since it reduces value flowing to the seller.

source: https://www.canva.com/design/DAFDTNKsIJs/8Ky9EoJJI7p98qKLIu2XNw/view#7

Design Phase of Token Engineering Process

The second stage of the Token Engineering Process is the Design Phase in which you make use of high-level descriptions from the previous step to come up with a specific design of the project. This will include everything that can be usually found in crypto whitepapers (e.g. governance mechanisms, incentive mechanisms, token supply, etc). After finishing the design, token engineers should represent the whole value flow and transactional logic on detailed visual diagrams. These diagrams will be a basis for creating mathematical models in the Deployment Phase. 

Token Engineering Artonomous Design Diagram
Artonomous design diagram, source: Artonomous GitHub

Objective Function

Every crypto project has some objective. The objective can consist of many goals, such as decentralization or token price. The objective function is a mathematical function assigning weights to different factors that influence the main objective in the order of their importance. This function will be a reference for machine learning algorithms in the next steps. They will try to find quantitative parameters (e.g. network fees) that maximize the output of this function.
Modified Metcalfe’s Law can serve as an inspiration during that step. It’s a framework for valuing crypto projects, but we believe that after adjustments it can also be used in this context.

Deployment Phase of Token Engineering Process

The Deployment Phase is final, but also the most demanding step in the process. It involves the implementation of machine learning algorithms that test our assumptions and optimize quantitative parameters. Token Engineering draws from Nassim Taleb’s concept of Antifragility and extensively uses feedback loops to make a system that gains from arising shocks.

Agent-based Modelling 

In agent-based modeling, we describe a set of behaviors and goals displayed by each agent participating in the system (this is why previous steps focused so much on describing stakeholders). Each agent is controlled by an autonomous AI and continuously optimizes his strategy. He learns from his experience and can mimic the behavior of other agents if he finds it effective (Reinforced Learning). This approach allows for mimicking real users, who adapt their strategies with time. An example adaptive agent would be a cryptocurrency trader, who changes his trading strategy in response to experiencing a loss of money.

Monte Carlo Simulations

Token Engineers use the Monte Carlo method to simulate the consequences of various possible interactions while taking into account the probability of their occurrence. By running a large number of simulations it’s possible to stress-test the project in multiple scenarios and identify emergent risks.

Testnet Deployment

If possible, it's highly beneficial for projects to extend the testing phase even further by letting real users use the network. Idea is the same as in agent-based testing - continuous optimization based on provided metrics. Furthermore, in case the project considers airdropping its tokens, giving them to early users is a great strategy. Even though part of the activity will be disingenuine and airdrop-oriented, such strategy still works better than most.

Time Duration

Token engineering process may take from as little as 2 weeks to as much as 5 months. It depends on the project category (Layer 1 protocol will require more time, than a simple DApp), and security requirements. For example, a bank issuing its digital token will have a very low risk tolerance.

Required Skills for Token Engineering

Token engineering is a multidisciplinary field and requires a great amount of specialized knowledge. Key knowledge areas are:

  • Systems Engineering
  • Machine Learning
  • Market Research
  • Capital Markets
  • Current trends in Web3
  • Blockchain Engineering
  • Statistics

Summary

The token engineering process consists of 3 steps: Discovery Phase, Design Phase, and Deployment Phase. It’s utilized mostly by established blockchain projects, and financial institutions like the International Monetary Fund. Even though it’s a very resource-consuming process, we believe it’s worth it. Projects that went through scrupulous design and testing before launch are much more likely to receive VC funding and be in the 10% of crypto projects that survive the bear market. Going through that process also has a symbolic meaning - it shows that the project is long-term oriented.

If you're looking to create a robust tokenomics model and go through institutional-grade testing please reach out to contact@nextrope.com. Our team is ready to help you with the token engineering process and ensure your project’s resilience in the long term.

FAQ

What does token engineering process look like?

  • Token engineering process is conducted in a 3-step methodical fashion. This includes Discovery Phase, Design Phase, and Deployment Phase. Each of these stages should be tailored to the specific needs of a project.

Is token engineering meant only for big projects?

  • We recommend that even small projects go through a simplified design and optimization process. This increases community's trust and makes sure that the tokenomics doesn't have any obvious flaws.

How long does the token engineering process take?

  • It depends on the project and may range from 2 weeks to 5 months.