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Vijay Pravin Maharajan, Founder & CEO, bitsCrunch.
Do you know how many blockchain analysis companies exist? Take a wild guess.
At least a few hundreds. And all of them are working towards bringing more transparency to the web3 ecosystem.
Blockchain analytics is the process of analysing, identifying and clustering data on the blockchain and presenting it in a meaningful, actionable, usable information. Additionally, blockchain analytics also models and visually represents data in order to identify vital information about users and transactions.
Blockchain data analysis platforms may provide data for different purposes. A growing use of blockchain analysis is about the NFT data that are being transacted. This can include variables like volume, market capitalisation, sales, trades and many more. NFTs have been gaining a lot of attention and momentum in the past few years and every company in the world, irrespective of the industry, is experimenting with them and launching a new collection. Statista has a graph of total value of sales involving a non-fungible token (NFT) in the art segment worldwide over the previous 30 days from April 15, 2021 to November 15, 2022. This is just an example of how big the NFT industry is as it does not even cover all categories other than art.
Companies like Nike, Prada in the fashion industry have embraced NFTs. It has even made inroads to real life events likeF1 racing, FIFA world cup and major sporting events around the world. Not to be left out having a piece of this pie, blockchains have been busy adding NFT functionalities onto them. Solana was a late entrant but has really got some amazing marketshare already. With all this momentum, things may look really great for the NFT ecosystem but there are some bad actors who are indulging in malpractices and foul play.
NFTs are plagued with security issues & threats like plagiarism, wash trading, copy minting, frauds, scams and cyber attacks like phishing, hacking and many more. A few of them require better use of hardware and software, a few call for more prudence on the internet, and other issues might require NFT data analysis to make better judgement. Threats like washtrading where NFT creators indulge in fake transactions to artificially increase the prices of NFTs, copy minting where someone who is not the original creator of the NFT infringes the IP (intellectual property) of the creator by making fake copies of the original NFT work, or other methods of price manipulation where the fair price of a NFT is masked and traders and buyers end up paying exorbitant prices are all instances of NFT threats that can be detected with reasonable accuracy using AI/ML on the data obtained from the blockchains.
We are seeing an increase in efforts by the stakeholders of the web3 ecosystem who are effectively handling the threats and devising new methods to address any concerns that might negatively impact the NFT transaction experience. But this is all the beginning of a long road where the ecosystem stakeholders have started a cat and mouse game of catching up with the fraudsters and scamsters who are regularly coming up with new techniques to create threats toNFTs. The positive steps are a sign of maturity of the ecosystem and blockchain analysis platforms will play a bigger role in helping NFT marketplaces, lending protocols, traders, artists, buyers and sellers and anyone involved in combating the threats better.
The few instances where these data platforms can help right now are wash trade detection, fair price estimation and forgery detection. A wash traded NFTs’ chart provided by bitsCrunch report shows over $140 million in wash traded volume across three major blockchains in the last 30 days. These NFTs were possibly sold at much higher prices than their actual value, resulting in buyers and traders being defrauded. This projects a negative image of the NFT to buyers and investors and the whole ecosystem will be at a loss in the long term.
Fair price estimation of NFTs will also be possible if wash traded and fictitious transactions are easily identifiable and segregated from the total number of transactions. Moreover, forgery detection can be done by providing some sort of a checkmark to the original creation (verified badge) so that any further copies made can be easily identified. Similarly, methods to find duplicates/forged NFTs should be developed so that they can be easily removed automatically or at least the original creator is informed and they can take an action to remove the forged NFTs from other marketplaces.
As more data is gathered, new use cases will emerge to combat the threats even more effectively. As they say “knowledge is power” and what the best blockchain analysis platforms can do is provide the knowledge to businesses and individuals so that they can achieve better transparency. It’s a relatively new technology and just like any other tech, there are pros and cons in the NFT ecosystem as well. There are people and businesses with malicious intent who are ready to take advantage of the loopholes and lack of global or national standards and regulations. While the government bodies look to figure that out, until then blockchain analysis platforms will play a crucial part in self governance and self developed combat systems against the threats to the NFTs.
Analysing threats is a good start, but we will soon see a spurt of new age blockchain data analysis platforms who will go even further by allowing you to take actions based on that data and work as “guardians of the NFT ecosystem”. The blockchain analysis platforms will continue to evolve and present us with newer safeguards against existing and future NFT threats. The innovation in the space is encouraging and we hope to see many more positive developments and new use cases of NFTs with the rising confidence of robust methods of threat mitigation.
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Views expressed above are the author’s own.
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