There is no doubt that NFTs are selling like hotcakes (digitally). Christie’s sold a digital collage by artist Beeple for $69.3 million at the NFT auction in March 2021. When you start translating the real into hyper-real, you see endless scenarios that capture people’s imagination. Nevertheless, as with any shiny new toy, there have been fraudsters appearing within the binary code.
The manipulation of NFTs is similar to what we’ve seen with more traditional crypto assets, such as Bitcoins. Hacking wallets and stealing the NFTs is not just another scam, but a process through which it’s possible to assign multiple ownerships to digital designs using the NFTs.
Users have to submit their social media handles for NFT verifications, but the entity submitting these details need not prove ownership. Digital works have been fraudulently mis-sold due to this practice. Did we just create yet another avenue for crypto-crime instead of simplifying it?
Wash trading is pretty widespread on centralized cryptocurrency exchanges, as well as the NFT industry. Our mission is to warn you about the possibilities that keep NFTs a bit too clean. Knowing how to recognize frauds and scams will make it easier to avoid them. Isn’t it? But first, what are NFTs?
Non-Fungible Tokens. Okay, we understand that doesn’t make it clear. Right?
NFTs are a new form of digital asset that operates on blockchain technology. In general, NFTs do not rely on Ethereum, but they use its blockchain. A concept known as non-fungibility is essential to differentiate their function from fungible tokens, such as Bitcoin and Ether, which can exchange like-for-like. You can dwell more on it here!
With that in mind, our next focus point is on how wash trading takes place in NFTs.
When traders engage in a wash trade, they buy and sell securities to create a misleading market signal. When traders and brokers collude, they can make wash trades. Investors can also make wash trades if they act as buyers as well as sellers.
To understand it better, let us see how wash trading happens in the crypto market.
Basically, cryptocurrency wash trading involves companies trading with each other in order to create the illusion of liquidity or manipulate the value of assets being traded. There are strong economic incentives for cryptocurrency exchanges to influence market prices and inflate trading volumes. Cryptocurrency exchanges generate revenue by charging transaction fees to gain market share and attract traders.
As a concept, NFT wash trading applies to the purchase or sale of non-fungible tokens not intended for acquiring something. Below are a few more concrete examples:
Cost-of-attack is an estimate on the losses incurred due to an illegitimate/wash trading that takes place in various industries, stocks, or NFTs.
As a result, the global ecosystem suffers in both the short and long term. How? Let’s dive deep.
Many buyers pay large amounts for the right to acquire virtual collectibles in the form of NFTs, which give them exclusive ownership of digital assets. Why these unique digital tokens have sold for such a high price is a concern for many people.
Some argue that the popularity of NFTs has risen primarily as a result of Bitcoin’s unprecedented popularity. Currently, BTC , the global leader in digital currency, is worth well over $1 trillion market cap, with the current BTC price as $45,000 mark. People who have made significant profits from holding cryptocurrency may now use those funds to purchase digitally scarce NFTs.
It appears that there is a nefarious suggestion now being spread on various Twitter feeds, message boards, and blogs, alleging that the surging prices are due to wash trading, and we can’t deny that.
But, how does it happen? A lot of cases are difficult to prove. Let’s explore more about it.
Bloomberg reports wash trading as crypto’s open secret, and serious concerns have come up about these practices since the advent of crypto assets. It is easy for identities to become abstracted in an all-digital environment, where virtual wallet addresses can have complex alphanumeric symbols, so claiming wash trading may seem plausible but becomes difficult to prove.
It may be necessary to use forensic accounting methods such as Benford’s law. Also, perform a careful analysis of trade size distributions to see how they correspond with mathematical principles such as Pareto-Levy.
The law of anomalous numbers, also known as Benford’s law, or the first-digit law, describes how fractions that appear in real-life numerical data are distributed. Numerical data can be used to detect fraudulent behavior.
As outlined in the Pareto Principle, roughly 80% of outcomes result from 20% of causes, suggesting that inputs and outputs are not equal.
Although the laws claim to help in detection, there is no evidence of something caught in the act of wash trading. But we can explain this better with the LIBOR example.
A wash trade has no commercial value and cancels the other out. The LIBOR scandal used wash trades to pay off brokers who used the LIBOR submission panels to manipulate the Japanese yen. UK authorities alleged that they executed nine transactions with a brokerage firm to generate 170,000 pounds as compensation for its role in LIBOR rate manipulation.
It is also possible to use wash trades to pump out fake numbers for an NFT. Consider the case of a colluded buy-and-sell arrangement between a trader XYZ and a brokerage company ABC. ABC may witness activity by other traders, who may purchase the stock to take advantage of its price movements. The NFTs then become less valued, resulting in profiting from its downward trend.
With that trend, if the NFTs wash trading is detected, it can affect the coin price dramatically. But, there is also a considerable effect on the marketplace.
Regardless of who is involved, illegitimate/wash trading is detrimental. Whether for projects themselves, traders, investors, or a global network of enthusiasts.
In terms of platform growth and reach — Projects no longer have reliable statistics. An essential part of their process is to determine and record the actual use versus fabricated use. It will be incumbent on project workers to maintain realistic expectations and correct misinformed users.
Due diligence has become increasingly challenging as investors had to rely on measurable statistics. Specialists must review the data for discrepancies.
They can’t make an informed decision. It is easy for users to draw uninformed conclusions when misled by misleading statistics and history about a piece of art or collectible.
Communities are the hardest hit. Regulations and mainstream financial services proponents can now use wash trading to counter decentralization. As we accept more social norms (property rights, financial practices, marketing strategies), the technology will be adopted and accepted more widely.
So, with the NFT markets getting affected by the wash trading, Is there a possibility to detect it in the first place? Theories prove it on paper. How’s that?
Early detection is primarily achieved through the use of graph clustering and nearest neighbor algorithms. But a related phenomenon called collusive cliques has also been researched.
On aggregated order volume time series, hidden Markov models, spectral clustering, and correlation statistics are other methods that help. Check out more about how these models can help in identifying complex sequence data, fraudulent activities, and failure detection.
One of the first studies to explicitly examine wash trades in the markets was by Cao et al. According to them, prior studies focused primarily on collusive and correlated trading patterns rather than wash trading’s more specific form.
A given set of trades consists of subsets that result in no position change to the traders involved. Based on their topological structures, these trades comprise a closed cycle. A closed-cycle trade is one that does not engage in exchanges with other economies. Closed economies are completely self-sufficient, which means no goods are imported or exported.
Although this sounds very much sorted on paper, in practice, it needs an ecosystem that can detect wash trading in NFTs for real. Do we have a solution for that? Yes! And the good news is Scour!
With all the good news of Scour, they have come with incredible approaches to identify the fraudulent activities more precisely and practically. Having said that, with multiple methods on the table, when caught, washtraders keep coming up with new ways to washtrade. New wallets are created and new methods of washtrading are tried.
However, Scour reduced the washtraders by over 40% within two months. Unbelievable? How does it happen? Look no further than into the next section.
As far as we learned till now, market manipulators are hard to catch. Even though the tokens are non-fungible, they are still anonymous, making fraud detection difficult. But, Scour upgrades every week to identify the new possibilities of wash trading by extreme research on the NFT activities and keeps a checkmate to them asap.
Scour is a unique product created by BitsCrunch, an AI-powered analytics company that can actively remove wash traders from exchanges.
The Scour index compiles transactions, wallet addresses, and distributions of reward tokens. Using knowledge graphs and AI technology, Scour can identify bogus orders and complex patterns of wash trades. The technology not only secures investors and markets but also solves the open secret of cryptocurrencies.
BitsCrunch built Scour with a detailed knowledge graph that includes a complete index of the NFT markets transactions thanks to partnerships with industry leaders like Covalent, Rarible, and deeplearning.ai.
At its core, Scour is an AI product that flags the spoofing activity among the traders to protect the platform (marketplace) from its market-mining operations. Need to identify complex wash trade transaction patterns? Want to prevent malicious trader wallets? Get in touch with Bitscrunch!
bitsCrunch is the Guardian of the NFT ecosystem. We are one of the top 4 AI companies in Munich, Germany that excels in Blockchain technology. We believe that blending a proven technology like Artificial Intelligence with Blockchain technology can do wonders and make the ecosystem much more safer and reliable ! Our mission is to create impactful insights from intricate data sources, by harnessing predictive analytical systems which are empowering organizations with actionable intelligence.
AI-Enhanced Safety Feature (SCOUR), An AI agent that acts as a watchdog to flag the spoofing transactions that manipulates both volume and price of the assets in the NFT ecosystem.
Digital Asset Forgery Detection System (Crunch Davinci), An AI model that flags forgeries, copycats and bootleg digital art contents thereby protecting the artists and their creations.
Fair Price value estimation for an Asset(Liquify), A fair value estimation & analytics for Digital Assets (NFTs) using AI to empower the community to embrace and value their assets in real-time.