How AI and machine learning help NFT market combat wash trading and counterfeits

The nonfungible token (NFT) market can return to its glory days as a revolutionary asset class, but it must first address several major challenges.

Wash traders inflate NFT prices

To begin with, wash trading remains one of the most significant problems that cast a shadow on NFTs’ potential to foster creativity and transform digital ownership. Wash trading refers to the deceptive practice in which an investor buys and sells an NFT simultaneously to create the illusion of significant trading volume, thus inflating the token’s price to eventually sell it higher.

Unlike traditional cryptocurrencies, NFTs are not a liquid market, making it easier for unscrupulous actors to artificially inflate trading volumes.

Earlier in 2023, a joint report from NFT analytics provider bitsCrunch and Cointelegraph Research, titled “BitsCrunch NFT Wash Trade Report for 2022,” showed that NFT wash trading activity had surged in 2022 by 25 times to about $33 billion. That means more than half of the total $54 billion in NFTs traded on the Ethereum blockchain in 2022 was related to wash trading.

Over half of the $54 billion in NFTs traded on Ethereum in 2022 resulted from wash trading. Source: Cointelegraph Research x bitsCrunch

In February 2023, NFT data aggregator CryptoSlam found that around $577 million worth of NFTs had been suspected of wash trading on Blur, now the second-largest NFT marketplace by trading volume.

Counterfeit NFTs dilute the value of original creations

Another major challenge in the NFT market is the high prevalence of counterfeit or plagiarized NFTs. NFTs have two components — the technical aspect representing the asset with the unique identifier on the blockchain and the digital representation, which can be easily duplicated.

In October 2023, a California federal judge ordered a conceptual artist to pay around $1.5 million in damages to Yuga Labs for copying NFTs from the Bored Ape Yacht Club collection and profiting from them. While major NFT collections have more possibilities to fight counterfeit NFTs, less popular digital artists and creators are at risk.

The problem of NFT forgery dilutes the value of original creations and seriously threatens the integrity and reliability of the entire NFT ecosystem. Authenticity is touted as the cornerstone of the NFT space, but it’s severely compromised by fake art.

These two challenges, wash trading and counterfeit NFTs, lead to a significant loss of trust and perceived value within the NFT market. Many potential users remain skeptical, which hinders the mainstream adoption of NFTs.

As a result, the NFT space deals with missed opportunities in attracting a broader user base, which is essential for its long-term sustainability and upgrade beyond a niche market.

How can AI and machine learning improve NFT market?

Emerging technologies like artificial intelligence (AI) and machine learning (ML) can help to address the main challenges in the NFT market. AI is not only a helpful technology to support creativity and deliver unique digital art, but it also meets the need for better analytics and insight.

AI and ML can take on-chain analysis to a new level, helping the market detect wash trading deals in real time and identify fake NFTs.

Leveraging AI to combat wash trading and fake NFTs

BitsCrunch, an AI-powered NFT analytics platform, combats wash trading to help traders with fair price discovery and developers with reliable NFT decentralized applications (DApps) development. Its wash trading index utilizes AI and ML to detect suspicious trading patterns in real time, safeguarding investors from manipulated market prices and facilitating informed investment decisions.

The index provides a comprehensive overview of wash trading activity across various blockchains, marketplaces, and NFT collections, enabling market analysts and participants to gain valuable insights into the true state of the market. This data empowers informed decision-making, allowing users to discern genuine market trends from artificially inflated volume.

For investors, the wash trading index serves as a crucial tool for assessing the legitimacy of trading activities. By analyzing the index, investors can identify NFT collections with high incidences of wash trading, potentially indicating inflated prices or deceptive marketing practices.

Source: bitsCrunch

Developers and NFT investors can also use other bitsCrunch’s AI-powered tools for many use cases, including:

• Analytics — blockchain and NFT analytics projects have access to the most comprehensive NFT database. bitsCrunch also offers the largest repository of ERC-20 historical data available.
• Fraud detection — bitsCrunch offers fraud detection and alerting mechanisms, helping users detect suspicious trading and set up alerts and notifications.
• Lending — NFT lending tools can use bitsCrunch for accurate collateralization based on data-driven insights.
• Price discovery — Insights on pricing trends can help digital artists price their NFTs appropriately.
• Audience engagement — marketing teams can use bitsCrunch data on buyer preferences and behaviors to improve community engagement strategies.

Source: bitsCrunch

What sets bitsCrunch apart from other data tools is that it uses a community-driven approach, being a fully decentralized network. Saravanan Jaichandaran, co-founder of bitsCrunch, explained:

“Our network is not just a concept. Its vibrant ecosystem empowers users and developers through permissionless participation, meaning anyone can join and contribute without centralized approval, and community-driven growth. The platform grows with its community by continuously adding new features and use cases.”

The ecosystem is powered by BCUT, bitsCrunch’s native token, which plays an essential role in maintaining the integrity of the network.

By providing market participants with clear insights into the authenticity of trading activity, bitsCrunch contributes to a safer NFT environment where investors can navigate with confidence and trust.