TrustNFT is on a mission to unlock the full potential of NFTs. To achieve this dream, we partnered with highly-experienced pricing and analytics experts to innovative technological solutions for some of the most challenging aspects of the NFT ecosystem.
The long-term goal is to deliver AI tools for the price evaluation of NFTs and use them as credible collateral for loans. We reach our objective using on-chain and off-chain data sources to set more accurate and data-based prices for NFT assets.
NFTs as loan collateral
It’s a process that will benefit NFT collectors and investors by providing liquidity and accurate pricing for NFTs, promoting portfolio variety, and opening up a new market of possibilities with other DeFi applications.
However, the critical component is accurate pricing, which TrustNFT’s AI evaluation tool ensures. Without proper evaluation, solutions involving the use of NFTs as collateral are impossible, which is why we’ve focused all of our resources and attention on solving this issue.
An AI-powered NFT Evaluation Machine
We plan on fully launching the TrustNFT AI evaluation tool by 2022 Q4. The road to success involves multiple stages as outlined below:
- Marketplace and manual lending — 2022 Q1
- Introduction and training of AI model — 2022 Q2
- Delivery of autonomous AI tool — 2022 Q4
TrustNFT’s approach towards NFT pricing is unique. TrustNFT AI tool will be using on-chain and of-chain data to define a price per given NFT.
Understanding TrustNFT: How it works
TrustNFT is a two-sided platform with features for borrowers and lenders. Let’s look at the two components.
1. A P2P marketplace for NFT-collateralized loans. This feature allows borrowers to put up assets for loans and lenders to make offers to lend in return for interest.
2. An automatic lending pool. This feature allows lenders to loan their assets to community members in exchange for guaranteed yield in TrustNFT tokens.
The process: When an owner wants to evaluate an asset(s) using the TrustNFT Evaluation Machine, they have to choose one (or a few) of their NFTs, and then the platform will determine the maximum borrow limit. If the user agrees to this loan term and LTM, the asset is locked in a TrustNFT smart contract until the loan is completely repaid.
Additionally, if the collateral value increases, the holder can sell their NFT to pay back the loan faster during the contract period.
A systematic approach to valuation and pricing
The correct estimation of an NFT’s price plays a crucial role in the technical process. To achieve this goal, our team uses artificial intelligence with historical data from open ledgers, such as previous transfers, transfers of owners, and so on.
We also include an evaluation of the NFT creator’s popularity and the NFT’s growth on social networks, search engines, and other resources. To build a mathematical model that can correctly ascertain asset price, we used machine learning algorithms that utilize unsupervised learning, ML, or regression algorithms.
Four questions with our AI Developer, Liutauras Petrucionis
We sat down for a quick video chat for our Youtube channel with Lead AI Developer Liutauras Petrucionis to gather more insight about his new AI venture and why it matters for the greater NFT community.
1. Why did you decide to join the team?
“A friend showed me the whitepaper, and it seemed like a good opportunity. I also knew three TrustNFT founders, so I felt this was a big advantage. Not to mention and a good way to help the community. Essentially, they had a complicated data problem that required a lot of transparency. But luckily, I knew this was an issue I could fix.”
“Today’s NFT market today is like the “Wolf of Wall Street” scenario. It was about stock markets back then, but the same rules apply to the NFT space today. If I look at other NFT projects, I see they are working on a similar problem — peer-to-peer funding. The issue is transparency. The assets aren’t priced accurately, and we can’t see how the price evolved. Once we solve this issue, I think it will be a big step forward for the market itself.”
2. What is your personal opinion about NFTs vs. traditional art, and what does the future hold for non-fungible tokens?
“There is little inherent difference between art and NFTs themselves. I find it interesting that most physical artworks are not displayed anywhere. Usually, they are stored in freeports to avoid taxation. On the other hand are NFTs. Since they are digital images, you can always view them. When comparing traditional art and NFTs, this is one of the primary advantages and a good reason they should have more store of value.”
“However, one of the more significant issues is that secondary markets only resell one-fifth of NFT assets. For me, this shows the value is not accurate, meaning the seller is not happy with the price offers. There is an issue with the transparency of the pricing process, and I think we can make NFTs superior, even to traditional art pieces.”
3. How do NFTs make for practical loan collateral?
“For NFTs in general, it’s all about the issue of pricing because when you think about it, it’s very tough to price an asset accurately for an individual sell (or seller). What we’re trying to do is provide more transparency. And when we think about debt, there has to be better transparency.”
“Regarding the stock market, the main innovation was increased transparency and accessibility. These concepts apply to NFTs also. Instead of valuing the NFT yourself or buying that service from another party, we want you to swap the asset instantaneously and see how the price evolves. This process should reassure you that your collateral is well protected. It’s our job to take care of the pricing because it’s in our interest to maintain transparency and representation of our clients.”
4. What sets TrustNFT apart from other NFT and DeFi projects in the market?
“In my professional opinion, the AI tool that we’re building will solve the NFT price evaluation problem. The issue isn’t overly complicated; we just need to address a few concerns. It doesn’t matter if you’re pricing an asset on a platform like TrustNFT or a financial market — the core concepts are the same. You’re always trying to evaluate how people value certain latent features. Maybe you like a certain NFT artist or a specific stock. Then, you try to aggregate that to become a presentation of a price.”
“One distinct aspect we should mention is that there is a difference between valuation and pricing. A good example is your house. Often owners add extra value to their homes. Maybe it’s designed well, or there are features with intrinsic value. The issue is that there’s no way to standardize this value for outside parties.
“Our goal is to fuse the process into a systematic approach where pricing is a data-driven decision. Eventually, we’ll arrive at a price suitable for everyone. The next step is to track the price over time so we can repeatedly come back and see how it evolves and changes due to market supply.”
