Royalties give NFT creators a way to keep getting paid for their work, even after the original sale of the NFT.
Nonfungible tokens (NFTs) have been a key technical paradigm and a building block of the Web3 ecosystem. While the rise of NFTs was really led by the Ethereum community through 2020 and 2021, other chains like Solana and even Bitcoin have followed suit with major projects launching on these blockchains.
Creators have historically looked for different forms of income from their work. While there are laws pertaining to protecting intellectual property in the Web2 world, enforcing these laws and protecting creators’ interests has been hard to achieve.
Royalty payments are passive income that goes toward a creator on each transaction of their finished product. The product could be music, art, game utilities or any other form of digital asset. While creators earn from the primary sale of their NFTs, royalties are paid to the creator for each subsequent purchase as well.
As more institutions explore digital assets, the need for on-chain analytics platforms has never been higher.
Compliance experts, investigators and regulators employ these blockchain analytical tools to better understand the patterns and entities in cryptocurrency transactions.
To learn more about the tools and how they fit into broader cryptocurrency adoption, Cointelegraph sat down with Tom Robinson, the co-founder and chief scientist at analytics firm Elliptic; and Eray Akartuna, a senior cryptocurrency threat analyst at Elliptic.
Cointelegraph: What are the typical use cases you see for on-chain analytics for institutional clients?
Tom Robinson: Anti-Money Laundering (AML) and sanctions compliance for crypto exchanges and other businesses handling crypto assets: Our crypto transaction and wallet screening tools help businesses remain compliant with regulations and to reduce fraud.
Due diligence on crypto businesses: Our Discovery product provides risk profiles of exchanges and other crypto services based on analysis of their blockchain transactions. This is used by crypto businesses and financial institutions to gain insights into the businesses they are transacting with.
Investigating crypto transactions: Investigator — our blockchain investigations software — allows graphical exploration of crypto wallets and the transactions between them. Law enforcement investigators use this to “follow the money” and link criminal activity to individuals. It is also used by crypto businesses to investigate potential illicit activity by their customers.
CT: How is Anti-Money Laundering in crypto different from mainstream AML within banks for fiat?
TR: The main difference is that most crypto transactions are visible on the blockchain. This makes it much easier to identify whether funds have originated from criminal activity by tracing them using blockchain analytics tools.
CT: Do you see a role for artificial intelligence (AI) and machine learning to play within on-chain analytics? Particularly within fraud prevention and AML?
Eray Akartuna: Yes, we already use machine learning within our blockchain analytics products. However, it’s very important to ensure the accuracy of these techniques through extensive testing.
There are certain aspects of blockchain transactions where we can use machine learning to understand or identify certain patterns. Patterns seen on the Bitcoin blockchain may not necessarily be the same as patterns on the Ethereum blockchain; they work in slightly different ways. I would point out the use of heuristics.
There are certain aspects of the blockchain transactions where we have common spend that will help us know whether the addresses are owned by a single entity or not — if I want to identify illicit activities and illicit actors on a blockchain — and identify their wallet addresses.
For instance, the North Korean cyber hackers were using a programmatic way of laundering. The hack was conducted in 2018, where they used about 113 wallets to disassociate funds from the original theft in an automated fashion. We could programmatically analyze the timestamps of those individual transactions to understand exactly how this automated software works.
If we are analyzing dark web markets or terrorist entities, etc., using heuristics can help us identify if a wallet address has been associated with a certain illicit entity. We can then use those heuristics to understand what other wallet addresses may also belong to or be associated with that entity.
We’ve got a risk score which fits into predictive analysis. When we look at the incoming and outcoming transactions to a cluster of wallets, we can see ultimately where they ended up. Entities identified as belonging to an exchange, a terrorist group or a dark market can be spotted when they are transacting with particular entities that we’re focusing on.
Let’s say about 50% of that crypto has gone to a certain dark web market; we can actually use that to provide a risk score of how risky the wallet is. The risk score is then used by exchanges and banks to decide if they want to do business with these wallet holders or not.
CT: What are the most complex problems you are solving at Elliptic? Why are they complex, and why is it important to solve them?
TR: The most complex and important problem we have solved recently is how to identify proceeds of crime in crypto, even when they have been laundered cross-asset and cross-chain. Criminals now move their proceeds between assets, using decentralized exchanges; and between blockchains, using cross-chain bridges.
We developed holistic screening as a way of automatically tracing crypto funds between assets and blockchains. This unique capability is now absolutely essential; otherwise, money launderers will exploit businesses’ lack of visibility into their activity.
CT: How do you see banks adopting digital assets and with that on-chain analytics? What has the uptake been so far?
EA: We are seeing slow but steady adoption, but compliance is top of mind for banks. Blockchain analytics is seen as an essential part of the puzzle and a way to assuage the concerns of regulators.
If institutions want to get involved in the decentralized finance (DeFi) space and plan to invest clients’ funds, they need to know whether the liquidity pool that they are investing in is credible and has the right risk profile. If the liquidity pool has illicit funds going in and out of it, there is a compliance issue there. That is a key use case for institutions who are looking to get involved in DeFi.
The other use case is where some challenger banks like Revolut are allowing their customers to hold and trade cryptocurrencies. These banks will need compliance and AML capabilities before offering these products to customers.
CT: Have you had any interactions with regulators that would affect how you would serve the financial services industry, and what are the key areas of interest from a regulatory perspective?
TR: We have a constant dialogue with regulators around the world, many of whom use our products. It’s important that they understand how our blockchain analytics solutions function so that they can have confidence in the compliance programs run by the exchanges and banks that use our products.
Cardano is one of the largest layer-1 blockchain solutions by market capitalization. The project is being driven by Input-Output (a Charles Hoskinson company), Emurgo and the Cardano Foundation. The chain was named after the Italian mathematician Gerolamo Cardano and its token ADA is named after the 19th-century mathematician Ada Lovelace.
Cardano uses Ouroboros, a proof-of-stake (PoS) consensus mechanism where ADA holders can delegate their funds to stake pools. The cumulative stake allows each pool to verify transactions, create blocks and govern the network.
Ouroboros uses cryptography, combinatorics, and mathematical game theory to guarantee the protocol’s integrity, longevity and performance. These validators are paid by the Ouroboros protocol with a fixed pool cost and an optional margin. Ouroboros also directly assigns staking rewards to all delegators.
Combinatorics is the study of counting and arrangements, while mathematical game theory analyzes strategic interactions between rational decision-makers.
Staking allows ADA holders that do not have the skills or desire to run a node to participate in the network and be rewarded in proportion to the amount of stake delegated. Staking pools are a solution for users who want to stake their tokens onto their respective blockchains but do not necessarily play the role of validators on the network.
This article breaks down the steps involved in staking ADA in a self-custodial wallet, the tools needed and the rewards available for the users.
What are self-custodial wallets?
Self-custody is a method to hold cryptocurrencies or nonfungible token (NFT) assets in a wallet that only the user typically can access and control. The alternative option is to hold these assets on centralized exchanges where the users are exposed to counterparty risks if the exchange fails.
Nonetheless, most self-custodial wallets still require users to hold on to their private keys. Private keys are necessary for users to maintain control over their crypto assets. Unlike when stored on centralized exchanges, self-custody eliminates counterparty risk. This is why it is generally regarded as an ideal option for Web3 users, especially after the collapse of several exchanges in 2022.
Most layer-1 ecosystems have their native wallet solutions. For instance, Ethereum and ERC-20 assets primarily rely on MetaMask, while many Solana users rely on Phantom wallets.
When Cardano launched in 2017, there was a full-wallet implementation with IOHK’s Daedalus. Two years later, Emurgo launched the Yoroi light wallet. Since the Shelley mainnet hard fork in 2020, the wallet landscape in the Cardano ecosystem has expanded significantly.
There are full-node and light wallets for Windows, Linux and Mac as sovereign applications, browser plugins or mobile apps. Moreover, Cardano wallet apps can handle both single- and multi-address wallets. This is because Cardano is UTXO-based like Bitcoin and not account-based like Ethereum.
In addition, Cardano has native tokens: each user’s wallet can hold not only ADA but also thousands of other tokens and NFTs. Another functionality provided by Cardano is metadata additions as part of transactions.
Nami Wallet specializes in NFTs, while Flint Wallet builds bridges between various chains and technologies. On the other hand, Typhon and Etrnl wallets are highly advanced implementations that offer many features, such as support for multiple accounts within a user’s wallet, staking, voting, and the ability to transfer an unlimited number of assets to multiple recipients within a single transaction.
A key feature of custodial wallet staking in Cardano is the wallet owner never lets their ADA tokens out of their hands, retaining complete control over them at all times. Delegation is based on the amount of ADA in the wallet on the last epoch boundary (five days).
How to create a self-custodial wallet on Cardano?
The Yoroi wallet is one of many wallets that can be used to self-custody Cardano assets. Here are the steps to create a Yoroi wallet.
The Yoroi wallet can be downloaded as a browser plugin here.
Once the browser plugin is downloaded and installed, clicking on the plugin opens the Yoroi application page.
On the application page, clicking the “Add New Wallet” option kickstarts the wallet creation journey.
The next screen offers three options: Connect to hardware wallet, Create wallet, Restore wallet
To create the first Cardano wallet, choose the “Create wallet” option.
Next, users select “Cardano” as the currency, and the subsequent screens will prompt them to provide a name for their wallet and a corresponding password.
The next step is setting up the recovery phrase, which must be noted down in order and confirmed in the following step.
The wallet is now ready to accept Cardano assets.
To add some ADA to the wallet, users can click on the “Receive” tab that gives the wallet address.
Users can transfer ADA to the wallet from an exchange to kickstart the staking process.
How to stake ADA, and what are the staking rewards?
As previously mentioned, validating transactions on the Cardano network heavily relies on the staking of ADA by validators and other holders through staking pools. In return, the network offers staking rewards to these stakeholders. Holders of ADA who can’t run validators “delegate” their ADA to staking pools.
When staking began, pool operators and delegators received 5% in staking rewards. Over time it has slowly declined to around 4% due to the planned gradual reserves consumption. Of the 34.7 billion ADA in circulation, nearly 24.5 billion ADA (69% of circulating supply) are staked. Over 70% of ADA are staked by ADA holders through staking pools.
Holders can choose from over 3,000 staking pools on the Cardano network. To stake, holders can follow these steps from within the Yoroi wallet interface or any other Cardano wallet.
On the wallet page, the “Delegation list” provides a choice of delegates
Pool operators can also contribute to the pool, reflected by the “Pledge column.” A higher pledge shows higher skin in the game.
Holders who want to stake can choose a pool by clicking the “Delegate” button.
How to stake via Daedalus wallet?
Daedalus is another wallet for the users of the Cardano network. These are the steps to stake ADA using the Daedalus wallet:
When opened on a laptop, the app offers the option to either restore an existing wallet or create a new one.
The user is prompted to provide a wallet name and password.
Choosing the create option gives a 24-word recovery phrase that the user must note down and confirm.
The wallet is created and syncs with the blockchain.
Once the syncing is complete, the user must click on the “Staking” tab to start the staking process.
Clicking on the “Delegation” button takes the user to the delegation center, where they can choose from several staking pools.
The stake pool is chosen, the amount of ADA the user wants to stake is entered, and the confirmation is submitted.
Once the transaction is processed, the user’s ADA will be delegated to the pool.
From now on, the selected pool takes care of packaging transactions into blocks and validating the chain.
At the end of each five-day epoch, the Ouroboros protocol, not the pool’s operator, takes automatically distributes the rewards from the reserves to all ADA wallets.
Troubleshooting common issues with self-custodial ADA staking
Here are some common problems that users may encounter when staking ADA in a self-custodial wallet, along with some potential troubleshooting steps:
Stake pool not found: If users cannot find a suitable stake pool to delegate to, they can try using a stake pool search tool or increasing their search parameters to include more options. There are dedicated stake pool portals like PoolTool, and explorers like Cardanoscan and Cexplorer that allow a more detailed look at the history and performance of all stake pools.
Wallet synchronization issues: If a user’s wallet is not syncing correctly or displaying inaccurate information, the user can try restarting the wallet or using a different device. They can also check for any updates or patches that may be available for their wallet software.
Transaction errors: If users encounter an error when attempting to delegate their ADA or withdraw their rewards, they must ensure that they have entered the correct information and that they have sufficient funds in their wallet to cover any transaction fees. Users can also try clearing their cache or using a different browser.
Staking rewards not received: To receive staking rewards, users must confirm that their delegation is active and that the pool they have delegated to produces blocks, as no blocks being produced means no rewards will be received. Users should also try refreshing their wallet or checking the blockchain explorer to verify that the rewards have been distributed.
Users should be aware that if they cannot use one of the ADA wallet apps, the recovery phrase can be used to restore the wallet in another wallet app at any time, allowing access to all their ADA and native assets. If users encounter any other issues when staking ADA in a self-custodial wallet, they can contact their Cardano wallet app support team or consult online forums and communities for guidance.
Also, it’s crucial for users never to share their wallet recovery seed words or a screenshot with anyone who claims to help with their wallet. Additionally, users should not believe anyone telling them to transfer their funds to a new address and should be cautious of scammers.
Although cryptocurrencies are often promoted as investment opportunities, their primary purpose was originally to serve as an alternative form of currency. Considering this narrative, the rules of supply and demand apply to cryptocurrencies as to fiat currencies.
An undergraduate economics student might say the basics of money, economy and market forces is balancing supply and demand. How much of an asset is in circulation versus the demand — how many people want that particular asset — helps decide its price. This equation between supply and demand underlies the fundamentals of all economies and also applies to cryptocurrencies.
Deflationary cryptocurrency is one where the value of the crypto increases due to a reduction or stagnation in supply. This ensures that the coin’s market value is attractive for more people to invest in and can be used as a store of value. While deflationary cryptocurrencies look more attractive, not all are designed that way.
Many well-known cryptocurrencies are not deflationary. In addition, there is often no supply limit to them. Some are disinflationary because inflation gradually reduces over time due to its tokenomics. Bitcoin (BTC), for instance, won’t be deflationary until all 21 million coins have been mined. Ether (ETH) was not deflationary until the “Merge” happened in September 2022.
The rise of ChatGPT has been nothing short of spectacular. Within two months of launch, the artificial intelligence (AI)-based application reached 100 million unique users. In January 2023 alone, ChatGPT registered about 590 million visits.
In addition to AI, blockchain is another disruptive technology with increasing adoption. Decentralized protocols, applications and business models have matured and gained market traction since the Bitcoin (BTC) white paper was published in 2008. Much needs to be done to advance both of these technologies, but the zones of convergence between the two will be exciting to watch.
While the hype is around AI, a lot goes on behind the scenes to create a robust data infrastructure to enable meaningful AI. Low-quality data stored and shared inefficiently would lead to poor insights from the intelligence layer. As a result, it is critical to look at the data value chain holistically to determine what needs to be done to get high-quality data and AI applications using blockchain.
The key question is how Web3 technologies can tap into artificial intelligence in areas like data storage, data transfers and data intelligence. Each of these data capabilities may benefit from decentralized technologies, and firms are focusing on delivering them.
It helps to understand why decentralized data storage is an essential building block for the future of decentralized AI. As blockchain projects scale, every vector of centralization could come to haunt them. A centralized blockchain project could suffer governance breakdown, regulatory clampdown or infrastructure issues.
For instance, the Ethereum network “Merge,” which moved the chain from proof-of-work to proof-of-stake in September 2022, could have added a vector of centralization to the chain. Some have argued that major platforms and exchanges like Lido and Coinbase, which have a large share of the Ethereum staking market, have made the network more centralized.
Another vector of centralization for Ethereum is its reliance on Amazon Web Services (AWS) cloud storage. Therefore, storage and processing power for blockchain projects must be decentralized over time to mitigate the risks of a single centralized point of failure. This presents an opportunity for decentralized storage solutions to contribute to the ecosystem, bringing scalability and stability.
But how does decentralized storage work?
The principle is to use multiple servers and computers worldwide to store a document. Simply, a document can be split, encrypted and stored on different servers. Only the document owner will have the private key to retrieve the data. On retrieval, the algorithm pulls these individual parts to present the document to the user.
From a security perspective, the private key is the first layer of protection, and the distributed storage is the second layer. If one node or a server on the network is hacked, it can only access part of the encrypted data file.
Major projects within the decentralized storage space include Filecoin, Arweave, Crust, Sia and StorJ.
Decentralized storage is still in a nascent state, however. Facebook generates 4 petabytes (4,096 terabytes) of data daily, yet Arweave has only handled about 122TB of data in total. It costs about $10 to store 1TB of data on AWS, while on Arweave, the cost is about $1,350 at the time of publication.
Undoubtedly, decentralized storage has a long way to go, but high-quality data storage can boost AI for real-world use cases.
Data transfer is the next key use case on the data stack that can benefit from decentralization. Data transfers using centralized application programming interfaces (APIs) can still enable AI applications. However, adding a vector of centralization at any point in the data stack would make it less effective.
Once decentralized, the next item on the data value chain is the transfer and sharing of data — primarily through oracles.
Oracles are entities that connect blockchains to external data sources so that smart contracts can plug into real-world data and make transaction decisions.
However, oracles are one of the most vulnerable parts of the data architecture, with hackers targeting them extensively and successfully over the years. In one recent example, the Bonq protocol suffered a $120 million loss due to an oracle hack.
Besides smart contracts and cross-chain bridge hacks, oracle vulnerabilities have been low-hanging fruit for cybercriminals. This is mainly due to a lack of decentralized data transfer infrastructure and protocols.
Decentralized oracle networks (DONs) are a potential solution for secure data transfer. DONs have multiple nodes that provide high-quality data and establish end-to-end decentralization.
Oracles have been used extensively within the blockchain industry, with different types of oracles contributing to the data transfer mechanism.
There are input, output, cross-chain and compute-enabled oracles. Each of them has a purpose in the data landscape.
Input oracles carry and validate data from off-chain data sources to a blockchain for use by a smart contract. Output oracles allow smart contracts to carry data off-chain activity and trigger certain actions. Cross-chain oracles carry data between two blockchains — which could be fundamental as blockchain interoperability improves — while compute-enabled oracles use off-chain computation to offer decentralized services.
While Chainlink has been a pioneer in developing oracle technologies for blockchain data transfer, protocols like Nest and Band also provide decentralized oracles. Apart from pure blockchain-based protocols, platforms like Chain API and CryptoAPI provide APIs for DONs to consume off-chain data securely.
The data intelligence layer is where all the infrastructure efforts of storing, sharing and processing data come to fruition. A blockchain-based application using AI can still source data from traditional APIs. However, that would add a degree of centralization and could affect the robustness of the final solution.
However, several applications are tapping into machine learning and artificial intelligence in crypto and blockchain.
Trading and investments
For several years, machine learning and artificial intelligence have been used within fintech to deliver robo-advisory functionalities to investors. Web3 has taken inspiration from these applications of AI. Platforms source data on market prices, macroeconomic data and alternate data like social media, generating user-specific insights.
The user typically sets their risk and returns expectations, with the recommendations from the AI platform falling within these parameters. The data required to deliver these insights is sourced by the AI platform using oracles.
Bitcoin Loophole and Numerai are examples of this AI use case. Bitcoin Loophole is a trading application that employs artificial intelligence to provide trading signals to platform users. It claims to have over 85% success rate in doing so.
Numerai claims it is on a mission to build “the world’s last hedge fund” using blockchain and AI. It uses AI to collect data from different sources to manage a portfolio of investments like a hedge fund would.
A decentralized AI marketplace thrives on the network effect between developers building AI solutions at one end, and users and organizations employing these solutions at the other end. Due to the application’s decentralized nature, most commercial relationships and transactions between these stakeholders are automated using smart contracts.
Developers can configure the pricing strategy through inputs to smart contracts. Payment to them for using their solution could happen per data transaction, data insight or just a flat retainer fee for the period of use. There could also be hybrid approaches to the price plan, with the usage tracked on-chain as the AI solution is used. The on-chain activities would trigger smart contract-based payments for using the solution.
SingularityNET and Fetch.ai are two examples of such applications. SingularityNET is a decentralized marketplace for AI tools. Developers create and publish solutions that organizations and other platform participants can use through APIs.
Fetch.ai, similarly, offers decentralized machine learning solutions to build modular and reusable solutions. Agents build peer-to-peer solutions on this infrastructure. The economic layer across the entire data platform is on a blockchain, enabling usage tracking and smart contract transaction management.
NFT and metaverse intelligence
Another promising use case is around nonfungible tokens (NFTs) and metaverses. Since 2021, NFTs have been viewed as social identities by many Web3 users using their NFTs as Twitter profile pictures. Organizations like Yuga Labs have gone one step further, allowing users to log in to a metaverse experience using their Bored Ape Yacht Club NFT avatars.
As the metaverse narrative ramps up, so will the use of NFTs as digital avatars. However, digital avatars on metaverses today are neither intelligent nor do they bear any resemblance to the personality that the user expects. This is where AI can add value. Intelligent NFTs are being developed to allow NFT avatars to learn from their users.
Matrix AI and Althea AI are two firms developing AI tools to bring intelligence to metaverse avatars. Matrix AI aims to create “avatar intelligence,” or AvI. Its technology allows users to create metaverse avatars as close to themselves as possible.
Althea AIis building a decentralized protocol to create intelligent NFTs (iNFTs). These NFTs can learn to respond to simple user cues through machine learning. The iNFTs would become avatars on its metaverse named “Noah’s Ark.” Developers can use the iNFT protocol to create, train and earn from their iNFTs.
Several of these AI projects have seen an increase in token prices alongside the rise of ChatGPT. Yet, user adoption is the true litmus test, and only then can we be sure that these platforms solve a real problem for the user. These are still early days for AI and decentralized data projects, but the green shoots have emerged and look promising.
The new year began with the news that notable Web3 entrepreneur Kevin Rose fell victim to a phishing scam in which he lost over $1 million worth of nonfungible tokens (NFTs).
As mainstream financial institutions begin to provide services related to Web3, crypto and NFTs, they would be custodians of client assets. They must protect their clients from bad actors and identify whether client assets have been obtained through illicit activities.
The crypto industry hasn’t made it easy for Anti-Money Laundering (AML) functions within organizations. The sector has innovated constructs like cross-chain bridges, mixers and privacy chains, which hackers and crypto thieves can use to obfuscate stolen assets. Very few technical tools or frameworks can help navigate this rabbit hole.
Regulators have recently come down hard on some crypto platforms, pressuring centralized exchanges to delist privacy tokens. In August 2022, Dutch police arrested Tornado Cash developer Alexey Pertsev, and they have worked on controlling transactions through mixers since then.
While centralized governance is considered antithetical to the Web3 ethos, the pendulum may have to swing in the other direction before reaching a balanced middle ground that protects users and doesn’t curtail innovation.
And while large institutions and banks have to grapple with the technological complexities of Web3 to provide digital assets services to their clients, they will only be able to provide suitable customer protection if they have a robust AML framework.
AML frameworks will need several capabilities that banks must evaluate and build. These capabilities could be built in-house or achieved by collaborating with third-party solutions.
A few vendors in this space are Solidus Labs, Moralis, Cipher Blade, Elliptic, Quantumstamp, TRM Labs, Crystal Chain and Chainalysis. These firms are focused on delivering holistic (full-stack) AML frameworks to banks and financial institutions.
For these vendor platforms to deliver a holistic approach to AML around digital assets, they must have several inputs. The vendor provides several of these, while others are sourced from the bank or institution they work with.
Data sources and inputs
Institutions need a ton of data from varied sources to effectively identify AML risks. The breadth and depth of data an institution can access will decide the effectiveness of its AML function. Some of the key inputs needed for AML and fraud detection are below.
The AML policy is often a broad definition of what a firm should watch for. This is generally broken down into rules and thresholds that will help implement the policy.
An AML policy could state that all digital assets linked to a sanctioned nation-state like North Korea must be flagged and addressed.
The policy could also provide that transactions would be flagged if more than 10% of the transaction value could be traced back to a wallet address that contains the proceeds of a known theft of assets.
For instance, if 1 Bitcoin (BTC) is sent for custody with a tier-one bank, and if 0.2 BTC had its source in a wallet containing the proceeds of the Mt. Gox hack, even if attempts had been made to hide the source by running it through 10 or more hops before reaching the bank, that would raise an AML red flag to alert the bank to this potential risk.
AML platforms use several methods to label wallets and identify the source of transactions. These include consulting third-party intelligence such as government lists (sanctions and other bad actors); web scraping crypto addresses, the darknet, terrorist financing websites or Facebook pages; employing common spend heuristics that can identify crypto addresses controlled by the same person; and machine learning techniques like clustering that can identify cryptocurrency addresses controlled by the same person or group.
Data gathered through these techniques are the building block to the fundamental capabilities AML functions within banks and financial services institutions must create to deal with digital assets.
Wallet monitoring and screening
Banks will need to perform proactive monitoring and screening of customer wallets, wherein they can assess whether a wallet has interacted directly or indirectly with illicit actors like hackers, sanctions, terrorist networks, mixers and so on.
Once labels are tagged to wallets, AML rules are applied to ensure the wallet screening is within the risk limits.
Blockchain investigation is critical to ensure transactions happening on the network do not involve any illicit activities.
An investigation is performed on blockchain transactions from ultimate source to ultimate destination. Vendor platforms offer functionalities such as filtering on transaction value, number of hops or even the ability to identify on-off ramp transactions as part of an investigation automatically.
Platforms offer a pictorial hop chart showing every single hop a digital asset has taken through the network to get from the first to the most recent wallet. Platforms like Elliptic can identify transactions that even stem from the dark web.
Monitoring risk where multiple tokens are used to launder money on the same blockchain is another critical capability that AML platforms must have. Most layer 1 protocols have several applications that have their own tokens. Illicit transactions could happen using any of these tokens, and monitoring must be broader than just one base token.
Cross-chain transaction monitoring has come to haunt data analysts and AML experts for a while. Apart from mixers and dark web transactions, cross-chain transactions are perhaps the hardest problem to solve. Unlike mixers and dark web transactions, cross-chain asset transfers are commonplace and a genuine use case that drives interoperability.
Also, wallets that hold assets that hopped through mixers and the dark web can be labeled and red-flagged, as these are considered amber flags from an AML perspective straightaway. It wouldn’t be possible just to flag a cross-chain transaction, as it is fundamental to interoperability.
AML initiatives around cross-chain transactions in the past have been a challenge as cross-chain bridges can be opaque in the way they move assets from one blockchain to another. As a result, Elliptic has come up with a multitiered approach to solving this problem.
The simplest scenario is when the bridge provides end-to-end transparency across chains for every transaction, and the AML platform can pick that up from the chains. Where such traceability is not possible due to the nature of the bridge, AML algorithms use time value matching, where assets that left a chain and arrived at another are matched using the time of transfer and the value of the transfer.
The most challenging scenario is where none of those techniques can be used. For instance, asset transfers to the Bitcoin Lightning Network from Ethereum can be opaque. In such cases, cross-bridge transactions can be treated like those into mixers and the dark web, and will generally be flagged by the algorithm due to the lack of transparency.
Smart contract screening
Smart contract screening is another crucial area to protect decentralized finance (DeFi) users. Here, smart contracts are checked to ensure there are no illicit activities with the smart contracts that institutions must be aware of.
This is perhaps most relevant for hedge funds wanting to participate in liquidity pools in a DeFi solution. It is less important for banks at this point, as they generally do not participate directly in DeFi activities. However, as banks get involved with institutional DeFi, smart contract-level screening would become extremely critical.
VASP due diligence
Exchanges are classed as Virtual assets service providers (VASPs). Due diligence will look at the exchange’s overall exposure based on all addresses associated with the exchange.
Some AML vendor platforms provide a view of risk based on the country of incorporation, Know Your Customer requirements and, in some cases, the state of financial crime programs. Unlike previous capabilities, VASP checks involve both on-chain and off-chain data.
AML and on-chain analytics is a fast-evolving space. Several platforms are working toward solving some of the most complex technology problems that would help institutions safeguard their client assets. Yet, this is a work in progress, and much needs to be done to have robust AML controls for digital assets.
Bitcoin NFTs — aka Bitcoin ordinals, aka digital artifacts — are a way to inscribe digital content on the Bitcoin blockchain.
The Bitcoin ordinals protocol was launched in January 2023 by Casey Rodarmor. The protocol allows inscribing of digital content like art onto the Bitcoin blockchain. Unlike nonfungible tokens (NFTs) on Ethereum and other blockchains, Rodarmor wanted to create an immutable on-chain presence of a piece of art, text or video. The genesis ordinal was a pixel art of a skull that Rodarmor inscribed on Dec. 14, 2022.
As the NFT space based on Ethereum’s ERC-721 standard skyrocketed in 2021, Rodarmor, who was a programmer and an artist, saw the opportunity to create a similar yet unique experience on the Bitcoin blockchain. His solution was Bitcoin ordinals, based on ordinal theory, which he went on to implement through 2022.
Ordinal theory concerns itself with satoshis, giving them individual identities and allowing them to be tracked, transferred and imbued with meaning. The ordinals hype really kicked off in February 2023, six weeks after the genesis ordinal was created.
The number of inscriptions doubled every week for a few weeks. However, the number could have been much higher if the infrastructure to inscribe and trade ordinals had been better planned and executed.
The rise of Bitcoin ordinals has seen the Bitcoin network explode in terms of usage, fees and storage space as shown in the chart above. This may also be the first big breakthrough for the Bitcoin application tier and can help move the narrative from a pure “store of value” to something more utilitarian.
Crypto launchpads bring together the ethos of decentralized ecosystems and the ability of that community to make trustless investments.
The cryptocurrency industry and Web3 have been a hotbed of innovation that has put the community at the forefront. It thrives on the proliferation of decentralized ecosystems, breaking away from central hegemony by various incumbent bodies. The advent of crypto launchpads could be the beginning of a decentralized venture capital model.
The era of Bitcoin (BTC) and Ether (ETH) paved the way to new altcoins. However, by the end of 2022, there were over 16,000 cryptocurrencies. How can an enthusiastic investor pick good projects from so many? True to its ethos around decentralization, one of the most fascinating innovations that brings together investors, projects, innovators and the retail audience is a crypto launchpad. What do these launchpads do?
Crypto launchpads facilitate investments and empower investors to make informed decisions through rigorous due diligence. They take the pain of curating investment opportunities from retail investors and offer them the ability to invest into cryptocurrency projects at preferential terms on valuations.
Retail investors who want to participate in these investment rounds will buy the tokens of the crypto launchpads. Depending on token holding quantity, investors are typically bucketed under tiers that determine the access and valuations they get with investment opportunities.
Terms that investors get from these launchpads vary from preferential to exclusive. Preferential investment terms are generally in line with what other investors get. However, launchpad tokenholders get first preference to invest into those opportunities. Exclusive terms are those that are offered only to launchpad tokenholders. Either way, launchpad participants benefit from the structure.
NFTs can be used in supply chains to make them more transparent and efficient, leading to several billion dollars being saved. This is yet another space where Web3 technologies can have real-world applications.
The supply chain is an integral part of any business. Right from pharmaceutical giants and fast-moving consumer goods (FMCG) behemoths to local direct-to-customer brands, most businesses are dependent on efficient and resilient supply chains to deliver their products and services effectively. Despite being a vital cog in the wheel for organizations, supply chain networks are far from efficient on a global scale.
One of the key applications of blockchain technology has been traceability in a supply chain. This feature of the technology has been experimented with in trade finance use cases by banks such as HSBC. This is a use case that relies more on smart contracts and blockchain infrastructure layers like the Ethereum and Solana blockchains.
While nonfungible tokens (NFTs) as a technology paradigm were not necessarily planned to disrupt supply chains, they can bring about a massive transformation of pain points in this space. NFTs can act as “digital twins” of real-world goods and can help traceability within supply chains.
Here are a few numbers, statistics and narratives to put things into perspective.
49% of businesses have zero knowledge of what’s happening at key touchpoints in their supply chain due to a lack of visibility.
Counterfeiting goods cost global brands more than $232 billion in 2018.
In industries such as pharmaceuticals, the counterfeit market alone could be close to $200 billion per year.
The scale of the problem can be understood from the numbers above, and NFTs can offer solutions to these inefficiencies. Adding to this, there are also other interesting use cases that lie at the convergence of blockchain and supply chain, which is discussed later in this article.