With this article, we are embarking on a series about the fascinating world of wallet labels on the Ethereum blockchain, where we will gradually dive deeper into this topic and its exciting use cases for startups, (institutional) investors and not least crypto enthusiasts like you and me.
What is wallet labeling?
Wallet labeling is the process of categorizing and organizing blockchain wallet addresses based on specific attributes and past transaction behavior to provide a clearer understanding of the current transactions and interactions of those wallets within the respective blockchain ecosystem.
In the traditional finance domain, there are various levels of privacy and confidentiality depending on the type of transaction and the parties involved. This is in stark contrast to most blockchain-based systems, where all transactions can be viewed and analyzed by anyone on the network at any given time.
Such an unprecedented degree of transparency has enabled both new insights into investment behavior as well as many data-driven business models (more examples below) that capitalize on the information needs of an ever-growing crypto user base.
For example, as the Ethereum ecosystem grows to over 225 million unique addresses, 424,000 daily active ones, and over 1 million daily transactions, it has become essential to get a clear and navigable mapping of the sprawling Ethereum landscape.
This is where wallet labeling comes in. By assigning on-chain, behavior-based labels to actors (more specifically, to their wallet addresses), we can draw a comprehensive and navigable map of this vast digital terrain. This essentially equips us with the necessary tools to demystify the intricate Ethereum expanse, opens up interesting avenues for transformative academic research, and enables us to create innovative, user-centric digital offerings.
What is the purpose of labeling wallet addresses?
Labeling wallets in the manner described above is neither a simple nor a one-off task. It requires the untangling of complex transactions, the continuous identification and analysis of newly created wallets, contracts, and evolving transaction patterns.
Today, platforms like Amberdata, Chainalysis, CipherTrace, Elliptic, Etherscan or Nansen are already investing significant resources into the labeling of wallet addresses. Their objective is to deliver valuable insights into the crypto ecosystem: By accurately labeling wallets almost in real-time, they track illicit activities, support informed investment decisions, and aid regulatory compliance thus helping to combat the $3.9 billion lost to fraud and scams in 2022.
Yet, there is an even wider range of use cases for wallet labeling, including:
- Market Analysis: Investors and market analysts can label wallets to understand market trends and behaviors. For example, wallets can be labeled as ‘whale’ wallets if they hold a significant amount of a particular token. Monitoring the activity of these ‘whale’ wallets can provide valuable insights into potential market movements.
- Risk identification: Both crypto exchanges and individual investors can use wallet labeling for anti-money laundering (AML) efforts and scam avoidance. By flagging suspicious patterns like potential pump-and-dump schemes or abnormal money transfers, they can better secure their platforms and investments. For instance, an exchange could label and monitor wallets linked to irregular transactions, enhancing its AML procedures and protecting users from scams.
- User Behavior Analysis: Decentralized applications (dApps) and DeFi protocols can label wallets based on user behavior to improve their services. For example, DeFi protocols can apply wallet labeling to identify “smart money” wallets. These wallets, typically owned by experienced traders or investors, are frequently engaged in complex trading strategies or early adoption of promising protocols. Labeling these wallets helps platforms understand their user base and tailor services to meet these sophisticated needs more effectively.
- Community Behavior Analysis: Developers and community managers can use wallet labeling to understand the behavior of their user base. For example, a token project could label wallets based on the amount and frequency of their token holdings to identify core supporters or potential token hoarders.
- Smart Contract Interaction: Decentralized exchanges (DEXs) can label wallets based on their interaction with specific smart contracts. For instance, a decentralized exchange could label wallets that frequently interact with certain liquidity pools. This can provide insights into which pools are most popular and potentially guide future development efforts.
- Tax Compliance: Wallet labeling can assist individuals and businesses in maintaining accurate records for tax purposes. By labeling wallets based on their income sources (such as mining rewards, staking income, or token sales), users can simplify the process of calculating their taxable income.
- Law Enforcement: Wallet labeling can aid law enforcement agencies in tracking illicit activities. For example, during the investigation of the Silk Road black market, law enforcement agencies labeled and tracked wallets associated with the marketplace, which contributed to the eventual arrest of the site’s operator.
- Blockchain Forensics and Analysis: Investigators and researchers can use wallet labeling as a tool to map out transaction patterns and uncover hidden connections within the blockchain. For example, during the investigation of the 2016 DAO hack on the Ethereum network, wallet labeling played a crucial role in tracing the path of stolen funds.
…and many more. In essence, wallet labeling is a versatile tool that can add value in a multitude of contexts, with its potential applications expanding as the blockchain ecosystem continues to evolve.
As this ecosystem continues to mature and diversify, there is a growing need for a universal framework for wallet labeling, as current approaches are often designed for specific use cases and niche audiences, limiting the generalizability of insights.
We have therefore created our own approach to establish an overarching umbrella for the discipline of wallet labeling, and we call it Blockbrain WARP (an acronym for our core analysis dimensions – Wealth, Activity, Profile & Risk).
By creating such a framework, we aim to democratize access to the valuable insights which are hidden within the millions of transactions that happen on various blockchains every day. Our vision with Blockbrain WARP is to empower every participant, regardless of their level of expertise, with the necessary tools to navigate the complex blockchain landscape confidently and efficiently. By doing so, we believe we can foster greater transparency, inclusivity, and participation in the blockchain ecosystem, thus contributing to its ongoing growth and evolution.
Blockbrain WARP structures wallet labels using behavior-based categories (see figure 1), highlighting different aspects of a wallet’s activity. These categories serve as an initial layer of distinction, based on observable actions associated with each wallet.
In addition there are three complexity levels (see figure 2) which offer different lenses through which users can look at the behavior-based categories. This stratification acknowledges that not all behaviors or activities are equally straightforward to interpret or analyze. Some require simple metrics, others need more advanced calculations, and still others might demand predictive modeling based on historical data.
Our behavior-based categories label wallets based on the following categories:
- Wealth: Imagine a crypto “Forbes List” that ranks wallets as high-net-worth individuals, retail investors, or whales
- Activity: Wallet addresses sorted by their trading patterns, akin to a crypto athlete’s performance stats
- Risk: A “wanted list” that flags wallet addresses linked to hackers, scammers, or other bad actors
- Profile: Think of it as a LinkedIn for wallets, separating institutional investors, private individuals, DeFi platforms, and others
We further subdivide the behavior-based categories based on their complexity as follows:
- Descriptive: Simple aggregations or heuristics (e.g. wealth categories, wallet age, etc.)
- Augmented: Advanced, crypto-asset specific calculations (e.g. smart money flags, portfolio diversification or performance scores, etc.)
- Predictive: Predictive insights based on past behavior (e.g. scam probability, etc.)
In essence, this two-dimensional structure – behavior-based categories crossed with complexity levels – provides a robust and nuanced framework for wallet labeling, accommodating a wide spectrum of wallet activities and analysis depths.
Blockbrain WARP will be accessible for free in its basic form for our platform’s users and will also encompass paid tiers for advanced, AI-enhanced features. For even more advanced users we might offer dedicated analyses as well as corresponding API endpoints.
The way forward
At Blockbrain, we are deeply committed to our vision of harnessing the power of wallet labeling to create value for all users in the crypto space. Therefore, we recognize that our end-users are integral to shaping our offerings and fine-tuning our platform’s capabilities.
In order to better illustrate the practical application and utility of wallet labeling, we’re going to examine the iconic CryptoPunks NFT collection and its holders over the coming months. This exploration will allow us to delve into each aspect of our Blockbrain WARP framework, thereby deepening our collective understanding of its functions and benefits.
Over the course of our next posts, we’ll be diving into:
- “Cracking the CryptoPunks Code: Your Starter Guide to the Data“
In this introductory article, we’ll lay the foundation for the data we’re using and dissect the diverse landscape of CryptoPunks holders.
- “From Whales to Shrimp: Decoding Wealth on the Blockchain“
Here, we’ll delve into how wallet labeling illuminates the wealth spectrum among CryptoPunks owners, revealing the dynamics between ‘whales’, ‘dolphins’ and other big fishes in the ecosystem.
- “The Beat of the Blockchain: Unraveling Activity within CryptoPunks“
This piece will demonstrate how wallet labeling unravels the intricate dance of transactions, identifying wallets with distinct activity patterns within the CryptoPunks community.
- “Danger in the Depths: Risk Assessment in the Crypto Universe“
In this article, we’ll showcase how our wallet labeling framework helps flag potential risky entities within the CryptoPunks ecosystem, keeping participants informed and vigilant.
- “Who’s Who in the Crypto Zoo: The Profile of Key CryptoPunks Holders“
Finally, we’ll use our wallet labeling approach to categorize and profile the different types of participants in the CryptoPunks ecosystem, shedding light on the vibrant, diverse community behind the screens.
Most importantly however, we want to learn from you. We value your feedback and your innovative ideas for wallet labels. We therefore invite you to join our Discord, where we can discuss your thoughts and suggestions in the feedback channel. This exchange will enable us to continue improving our platform and make our wallet labels more transparent, accessible, and navigable for everyone.
Stay tuned for our next post, and join us on this exciting journey through the world of wallet labeling!
About the author:
Oliver is PhD researcher at the joint “DeFi Risk Advisor AI project” of Ulm University & Blockbrain, specializing in the convergence of decentralized finance, Non-Fungible Tokens (NFTs), and AI. His professional journey as a seasoned strategy consultant in digital transformation and AI, coupled with the academic rigor of his doctoral studies, has honed his insight into the transformative potential of distributed ledger technologies. Today, he applies this expertise to his role at Blockbrain, concentrating his efforts on leveraging blockchain technology for the broader common good.