Original article: "IOSG Weekly Brief | NFT-Fi startup boom led by new entrant Blur (Industry Map) #162"

By Sally, IOSG Ventures

This article is original content of IOSG and is only for industry learning and communication purposes. It does not constitute any investment reference. If you need to quote, please indicate the source. If you want to reprint, please contact the IOSG team to obtain authorization and reprint instructions.

Preface As the NFT market gradually recovers, the competition for users in the trading market has gradually developed and entered a white-hot stage. So far, the transaction volume of the emerging NFT aggregator project Blur has steadily exceeded Opensea. Source: NFTScan At the same time, the TVL of NFT lending protocols represented by Benddao is constantly setting new highs. As of February 20, according to Deflama data, BendDAO's total TVL has exceeded $200M, and the gap between the total amount of EVM on the chain and Synthetix is ​​gradually narrowing. Source: Defillama On the other hand, other leading projects in the NFT Fi track, such as X2Y2, NFT.Fi, JPEG’d, etc., have also seen a sharp jump in macro lending transaction volume since the end of last year. Source: Dune @ahkek

This may indicate that the NFT Fi track, which has attracted much attention since last summer but has not yet exploded, is about to usher in a wave of real systemic opportunities.

Theoretical framework of NFT financialization

Concept deconstruction:

In previous articles, we have pointed out that the significance of NFT financialization is to help expand and enhance the consensus and demand for NFT. After recognizing the significance and importance of NFT financialization, the next more core question is - how should we understand the concept of NFT financialization?

From a purely economic perspective, we are trying to propose an interesting but not necessarily correct viewpoint, which is to divide NFTs into two categories: A and B: Category A is NFTs with viewing and collection value; Category B is NFTs with use value. On this basis, the financialization of Category A NFTs is compared with the financialization of artworks, and the financialization of Category B NFTs is compared with the financialization of commodities:

NFTs such as Punk, Azuki, Doodles, and avatars, as well as pure art paintings, can all be simply classified into Class A, which are NFTs that only have viewing and collection value. The logical commonality between these NFTs and artworks is that:

Non-fungible Without utility Without fundamentals Valuation based on personal sentiment

Membership token NFTs issued by brands like Starbucks Odyssey and gaming NFTs that support the internal operation of entertainment products like StepN sneakers can all be considered Class B, that is, NFTs with use value. The logical commonality between them and commodities is that:

Semi-fungible With utility With certain fundamentals Valuation based on functions

Industry Deconstruction

After understanding and discussing the concept, we also need to further examine the industrial structure of NFT Fi vertically according to the segmentation direction. Although there are many discussions on the NFT Fi landscape in the market, we prefer to divide it into three layers from top to bottom:

The first layer is the direct transaction layer for NFT and FT exchange provided by Marketplace, Aggregator, AMM, etc.

The second layer is an indirect transaction layer that provides NFT custody and mortgage financing for lending, renting, crowdfunding, etc.

The third layer is the financial derivative layer such as options, futures, indexing funds, etc. that increase trading risks and leverage.

The evolution of these three levels, from direct transactions to indirect transactions and then to financial derivatives, is also the embodiment of the financial deepening of NFT from commoditization to financialization and then to securitization.

We believe that NFT liquidity solutions that combine a reasonable pricing mechanism, smooth user experience and sustainable trading model will ultimately lead to the continuous consolidation of NFT Fi's complete industrial structure until it takes off.

NFT financialization track map

Based on the above theoretical framework, we scanned 152 projects that are still operating in the current track and drew the following track map for reference:

Direct transaction layer (52 projects)

For the NFT trading market (Marketplace), we will mainly divide it into three categories based on its functions:

The General Marketplace, a full range of NFT trading markets distributed on different chains, represented by OpenSea, LooksRare, and X2Y2. The vertical NFT trading markets for practical games, represented by Trove and Nifty Gateway. The vertical NFT trading markets for art, represented by KnowOrigin and makersplace.

For NFT transaction aggregators, we mainly divide them into two categories based on their accessibility:

NFT aggregators such as Blur, Gem, and Genie are open to all users. NFT aggregators such as NFTNerds and TraitSniper are paid membership-based.

For NFT automatic market makers (AMMs), we mainly include AMMs based on Bonding Curve represented by Sudoswap, Caviar, etc. As an important decentralized solution for achieving instant liquidity of FT and NFT, we believe that it will play a more core role in future direct transactions.

Marketplace vs. Aggregator

As more and more players enter the market, an obvious trend is that people are putting forward higher demands on the transaction speed and purchase efficiency (liquidity) of NFTs. In OpenSea or other traditional NFT markets, the model of slowly waiting for projects to go online and slowly waiting for auctions has become slightly outdated. In aggregators like Blur, more professional data analysis functions allow people to sell and buy at a faster pace, so it is more like an "exchange". The market has proved that NFT players are obviously more in favor of "efficiency first" at present. At the same time, we have also noticed that with users' higher requirements for NFT transactions and the influx of professional DeFi traders, the combination of data analysis functions and aggregator categories is becoming closer and closer.

Aggregator vs. AMM

Although Blur's bid-to-earn model has largely subverted the traditional liquidity incentive method and has increased the aggregation speed by 10 times compared to Gem, there is no moat to support its long-term traffic. When the emerging aggregators gradually align their bidding models, improve the user experience (add more trader-friendly features at the same time), and even further launch vampire attacks, it is difficult to predict whether Blur can always maintain its leading position. This is exactly what we doubt about centralized exchanges that rely on the order book model.

Assuming that people's core demand is to seek the "fastest way to trade", AMM is likely to be a better choice because it can achieve instant exchange between NFT (erc721) and ETH (erc20) by removing bidding and centralized matching, and such functions are also easier to modularize and integrate into other platforms such as NFT lending in the form of SDK. We can use DeFi AMMs such as Uniswap as a good benchmark case for reference: Compared with CEX, Uniswap's advantages mainly lie in: higher exchange transaction efficiency (especially for long-tail assets), better user experience, better composability, fair incentive system, and no permission. We expect that after multiple market polishing and iterations, the advantages of these DeFi AMMs will also be fully realized on future NFT AMMs.

Indirect transaction layer (70 items)

For NFT lending protocols (Lending), we first divide them into over-collateralized lending and uncollateralized lending based on their lending models.

At present, most NFT lending paradigms are basically the three existing in protocols such as Compound and Aave: peer-to-peer matching, liquidity pools and stablecoins, providing functions such as over-collateralized lending or flash loans. Emerging unsecured private lending such as BNPL may introduce a more diverse user base on the demand side. We can more intuitively understand the two vertical categories of secured lending and unsecured lending from the following figure:

Deposits, borrowing and loans are the most basic components of any banking system. We believe that it is the most reasonable choice to first focus the indirect transaction layer on NFT lending.

For NFT liquidity providers (Market Makers), solutions represented by MetaStreet have been deeply involved in all aspects of the NFT ecosystem.

For NFT fragmentation (Frantionalizaton), we divide it into:

Traditional solutions such as unic.ly and nibbl that divide NFT into multiple tokens to lower the threshold for holding. Crowdfunding solutions such as partybid that divide ownership by co-holding to lower the threshold for speculative schemes

As for NFT rental, we believe that it is still more suitable for development and has a certain scale of audience in the vertical gaming track. The demonstration and exploration in other scenarios are still limited by the lack of NFT categories, and it is difficult to find PMF (Product-market fit) in a short period of time.

Collateralized Lending vs. BNPL

Leasing is actually the time-based splitting of third-party payments. The difference between buy now, pay later (BNPL) and ordinary leasing is that: 1. The payment actions are completed by different entities 2. The time of payment is distributed.

As the on-chain credit system matures and credit demand grows, we need more diversified credit products to meet the needs of different cryptocurrency user groups. The decentralized "credit certificate" system represented by Maker is likely not a transferable solution in the NFT scenario:

On the one hand, NFTs are usually sold as a complete commodity and have a higher selling price than FTs (for most PHP NFTs); on the other hand, NFT holders/players are different from Defi users (there may be some overlap), but the general inference is that without the temptation of huge investment returns, most NFT collectors will not have much motivation to participate deeply in a complex lending system.

In other words, if the traditional DeFi lending model is transferred to the NFT scenario, the audience will be very limited and subsequent growth will be relatively weak.

We believe that BNPL solutions like Cyan are a good entry point for NFT users to participate in the lending system. NFT BNPL platforms may also cooperate with Maker, CreDA, etc. to establish a complete cryptocurrency credit system in the future (such as establishing a larger credit delegation system similar to Aave). Therefore, even though such products are still in their infancy and the risk management model is untested (it is not known whether it will still work when a large number of users pour in), we still believe that this may be the most promising direction for the next cycle and will continue to pay attention.

Financial derivatives layer (16 projects)

Since the overall NFT financial derivative layer is still in its early stages, we have only included three categories here: options, futures, and indices. Compared with options, futures derivatives trading may invest less in user education costs and is easier to obtain traffic.

Compared with fragmented solutions, in traditional financial markets, it is more common to package illiquid assets such as real estate and artworks into indexes for investment. As for artworks, common art indexes include: Mei Moses Art Index, Art Market Researcher Index, Art price indices, etc. As for commodities, common indexes include: International Major Commodity Index, CRB Commodity Index, S&P Goldman Sachs Commodity Index GSCI, etc.

This indexing method can not only help institutions and ordinary investors diversify their portfolios, but also has satisfactory performance in terms of returns. In the 40 years from 1950 to 1990, the actual return rate of art investment was 8.2%. During the same period, the interest rates of the S&P 500 Index, the Dow Jones Index, government bonds, corporate bonds, and treasury bonds were 8.9%, 9.1%, 1.9%, 2.2%, and 1.3%, respectively. In the past 10 years, the average annual return rate of art has been as high as 8.5%, which has slightly exceeded stocks.

Projects represented by NFTX and NFT20 are creating an emerging asset class in Web3 similar to art/commodity indexes. On this basis, LiquiFi Labs and others use ML pricing technology to eliminate the volatility factors of wash trading and build a safer and more reliable index category. We also look forward to more index products entering the public's field of vision in the future.

Final Thoughts

David Ricardo, a representative of the Austrian School, pointed out in his Principles of Political Economy and Taxation that the value of some commodities can be determined only by scarcity, and labor cannot increase their quantity, so their value does not decrease due to an increase in supply. The art finance survey released by Deloitte also showed that 80% of collectors believe that buying and selling art is an investment. The arms dealers in the movie Tenet even evaded taxes by trading art in the Geneva Free Port.

IOSG believes that the financialization of NFT is likely to become the next detonator leading the growth of web3 in the era of fat applications, and encourages more collectors, builders, and developers to join us in exploring broader financial application scenarios of NFT.

More follow-up track segmentation research content will be disclosed in the full version of "NFT Fi Report".