Finance
How AI and crypto are shaping the future of finance
Over the last three years, the crypto space has undergone massive upheavals. Alongside the boosting from stimulus packages in 2021, venture capital (VC) firms had invested $33 billion in crypto and blockchain startups.
The following year, the Federal Reserve triggered a domino of crypto bankruptcies with its interest rate hiking cycle, starting from the Terra (LUNA) crash and culminating in the FTX Ponzi scheme collapse.
The promise of DeFi lost its luster, not helped by over $3 billion lost in DeFi hacks during 2023. The ongoing Bitcoin bull run shows the lack of altcoin confidence as the so-called Altcoin Season is yet to manifest.
In June 2023, BlackRock’s head of strategic partnerships, Joseph Chalom, noted that DeFi’s institutional adoption is “many, many, many years away”. However, there is a case to be made that the emerging AI narrative can fuse with blockchain technology and its applications.
Taking in lessons from the previous cycle, what would that AI-crypto landscape look like?
Laying the AI Foundation with Crypto Composability
Looking back, it is safe to say that “DeFi” was subsumed by companies on top of tokenized layers, such as Celsius Network or BlockFi, rendering DeFi into CeFi. These companies successfully drove crypto adoption as such, only to end up sullying the very word “crypto”.
A renewed DeFi v2 should then focus on a superior user experience that doesn’t spark the demand for centralized companies to make it so. Most importantly, DeFi security must be fortified. The most promising solution in that direction is the zero-knowledge Ethereum Virtual Machine – zkEVM.
By abstracting chain transactions via zero-knowledge proofs (ZKPs), zkEVM increases network throughput and reduces gas costs. On top of that, zkEVM simplifies the user experience by facilitating alternative token payments for gas fees. In other words, zkEVM-like solutions pave the road to scalability needed for AI applications.
AI applications inherently involve high volumes of data, making it a potential bottleneck for blockchain networks. With this obstacle ahead, Polygon zkEVM makes it possible to generate AI artwork via the Midjourney image generator. In this process, the results could be tokenized as NFTs with low fees.
Building further on smart contracts of other kinds, the crypto space has laid the groundwork for AI with composability and permissionless access. Combined, this creates an autonomous and efficient infrastructure for financial markets. As every piece of market action can be disassembled into smart contracts, composability brings innovation across three composability layers:
- Morphological – components communicating between DeFi protocols, creating new meta-features.
- Atomic – ability for each smart contract to function independently or in conjunction with other protocols’ smart contracts.
- Syntactic – ability for protocols to communicate based on standardized protocols.
In practice, this translates to Lego DeFi bricks. For instance, Compound (COMP) allows users to supply liquidity into smart contract pools. This is one of DeFi’s revolutionary pillars as users no longer require someone’s permission to either loan or borrow. With smart contracts acting as liquidity pools, borrowers can tap into them by providing collateral.
Liquidity providers gain cTokens in return as interest. If the supplied token is USDC, the yielding one will be cUSDC. However these tokens can be integrated across the DeFi board into all protocols compatible with the ERC-20 standard.
In other words, composability creates opportunities for the multiplicity of yields, so that no smart contract is left idle. The problem is, how to efficiently handle this rise in complexity? This is where AI comes into play.
Amplifying Efficiency with AI
When thinking of artificial intelligence (AI), the main feature that comes to mind is superhuman processing. Financial markets have long ago become too complex for human minds to handle. Instead, humans have come to rely on predictive algorithms, automation and personalization.
In TradFi, this typically translates to robo advisors prompting users on their needs and risk tolerances. A robo advisor would then generate a profile to manage the user’s portfolio. In the blockchain composability arena, such AI algorithms would gain much greater flexibility to siphon yields.
By reading the market conditions on the fly as they access transparent smart contracts, AI agents have the potential to reduce market inefficiencies, reduce human error, and increase market coordination. The latter already exists in the form of automated market makers (AMMs) that deliver asset price discovery.
By analyzing order flows, liquidity and volatility in real-time, AI agents are ideally suited to optimize liquidity supply and even prevent DeFi flash loan exploits by coordinating between DeFi platforms and limiting transaction sizes.
Inevitably, as AI agents increase market efficiency through real-time market monitoring and machine learning, new prediction markets could emerge as liquidity deepens. The job of humans would then be to set bots to arbitrate against other bots.
At $42.5 billion across 2,500 equity rounds in 2023, AI investments have already outpaced the crypto peak of 2021. But which AI-crypto projects showcase the trend?
Spotlight on AI-Crypto Innovators
Since the launch of ChatGPT by OpenAI in November 2022, AI has been an attention grabber. The attention previously reserved for memecoins became diverted into AI advancements in reasoning, art generation, coding and most recently, text-to-video generation via Sora.
Across these fields of human interest, they all rely on the scaling of data centers. Unlike crypto tokens, which are smart contracts, AI tokens are the base blocks of text that the AI agent disassembles into relationship units. Depending on the attunement of each AI model, these tokens represent contextual windows for the relationships between concepts.
For each user prompt, it is challenging to allow maximum processing capacity. When the AI model breaks the text into tokens, the output relies on the token size. In turn, the token size determines the quality of the generated content, whatever it may be.
Obviously, the larger the token size, the larger the potential for an AI model to consider the greater number of concepts when generating content. Given such inherent limitations, AI tokens naturally fit blockchain tech.
Just as Web3 gaming tokenizes in-game assets for decentralized ownership, tradeable currency and reward incentives, the same can be done with AI. Case in point, Fetch.AI (FET) is an open-access protocol to connect Autonomous Economic Agents, via the Open Economic Framework to the Fetch Smart Ledger.
The FET token aims to monetize network transactions, pay for AI model deployment, reward network participants and pay for other services. And just as people connect with DeFi services via wallets, they can connect with Fetch.AI’s agentverse with a Fetch Wallet to take advantage of deployed AI protocols.
For instance, one of the many AI agents currently in beta agentverse is PDF Summarization Agent.
As a prospective pathway to democratizing AI agent access and deployment, FET token has gained 300% value since the beginning of the year. According to Market Research Future, AI agents market is forecasted to grow to $110.42 billion by 2032 from $6.03 billion 2023. This represents a compound annual growth rate (CAGR) of 43.80%.
Ultimately, we are likely to see an ecosystem of AI agents interacting with DeFi protocols and other services that would benefit from automating real-time decisions. This may expand to AI agents aiding self-driving EVs or even helping execute delicate surgeries and patient care. Pediatric surgeon Dr. Danielle Walsh at the University of Kentucky College of Medicine in Lexington said:
“A patient who wakes up at 1:00 in the morning 2 days after a surgical operation can contact the chatbot to ask, ‘I’m having this symptom, is this normal?’”
In medical diagnostics, Massachusetts-based Lantheus Holdings (LNTH) had already deployed its PYLARIFY AI imaging agent for early prostate cancer detection. With AI-crypto projects like Fetch.AI, many such services could be tokenized to full extent.
The Road Ahead: Challenges and Opportunities
Ahead of AI integration, blockchain platforms face the same problem – institutional adoption. Do smaller protocols have a chance to penetrate the mainstream, or is this reserved for institutions?
DeFi may have paved the way for tokenized financial markets, but big players are likelier to instill public confidence.
For instance, the Canton Network, which is supported by Big Bank and Big Tech, may supplant smaller DeFi fish. Eventually, the convenience of same-day bank transfers could be seamlessly integrated into blockchain networks. This is especially pertinent given that Microsoft is powering the Canton Network with Azure cloud while developing AI products.
At the same time, plenty of users would prefer to stay within open-access ecosystems, riding the value appreciation of AI-crypto tokens. Moreover, crypto protocols don’t have to be directly geared toward AI agent deployment. Case in point, The Graph (GRT) could be used for AI apps as a blockchain data indexing service.
Based on this speculation, this “Google of Blockchain” has gained a 103% boost year-to-date. One of the most prospective crypto projects aiding AI could be Injective Protocol (INJ). As it “injects” AI algorithms into aforementioned DeFi market actions, Injective aims to simplify and automate complex DeFi operations.
At the base layer of the AI-crypto intersection could be Allora Network, using its zero-knowledge machine learning (zkML) and federated learning to build AI apps for augmented DeFi experience.
If the rollout of these open apps is successful, institutional networks such as Canton would have diminished appeal. This dynamic will largely depend on regulatory agencies, which are yet to materialize rules even for the crypto space.
Conclusion
AI is poised to make data more intelligible, actionable and pertinent to a specific user. On the other hand, blockchain technology formalized and decentralized the logic of human action into self-executing smart contracts.
When the two spheres meet, we get AI agents with a renewed purpose. A new generation of tokenized robo-advisors that take full advantage of DeFi composability. And as AI agents explore new possibilities, new markets will emerge.
From predictive analysis to injecting liquidity into on-chain markets, AI agents are ready to craft a hyper-financialized future where, starting from Bitcoin itself, humans will encounter plenty of building blocks to capitalize on.
Mentioned in this article
Stuart Litwin will be speaking at the Auto Finance Capital Summit taking place May 11-12 in Nashville, TN. This event brings together capital markets, finance, and treasury leaders across the $1.5 trillion auto finance industry to tackle critical funding challenges — from securitization and warehouse lending to liquidity management, private credit, and capital efficiency.
For more information about the event, please visit the event page.
Red squirrel characters have a history in the public information game. Older UK readers may recall Tufty, who taught children about road safety in the 1970s. His chum, Willy Weasel, regularly got knocked down by passing cars but clever Tufty always remembered to look both ways.
Now comes Savvy Squirrel, who, with backing from the chancellor and a multi-year lump of advertising spend from the financial services industry, will try “to drive a step-change in how investing is understood, discussed and adopted”, as the blurb puts it. In translation: don’t squirrel everything away in a boring cash Isa but try taking an investment risk or two if you value your long-term financial health.
As with preventing road traffic accidents, the cause is noble. Every study on long-term financial returns reaches the same conclusion: inflation is the investor’s enemy and there is a cost to holding cash for long periods.
One statistical bible is the Equity Gilt Study published by Barclays, and a few numbers demonstrate the point. From 2004 to 2024, cash generated a return of minus 40.5% in real terms (meaning after inflation and including interest paid). By contrast, a conventional diversified portfolio comprising 60% UK equities and 40% gilts increased by 21.6% in real terms. A missed opportunity of 62.1 percentage points is enormous
Rachel Reeves’s interest in promoting the virtues of investment lies not only in helping savers but in greasing the wheels of the capital markets. Fair enough: a healthy economy needs a healthy stock market, including one that makes it easy for retail investors to participate. It is slightly ridiculous that the colossal sum of £610bn is estimated to be sitting in cash savings in the UK; it can’t all be rainy-day money or cash parked awaiting a house purchase.
Many Americans famously follow the stock markets closely and discuss their 401(k) pensions savings plans but, even by European standards, the UK’s retail investment culture lags. Sweden has popularised investment with tax-breaks and other changes. Even supposedly cautious Germans are less inhibited. So, yes, one can applaud the ambition behind the campaign.
But here’s the doubt: it all feels terribly tame.
One can imagine an alternative launch in which Reeves tried to create a buzz by cutting stamp duty on share purchases. There are good reasons to adopt that policy anyway, as argued here many times, but a cut now would grab attention. True, rules for banks and investment firms on giving “targeted guidance” are being loosened to allow more useful advice alongside the “capital at risk” warnings. Yet the current news flow in Isa-land is about HMRC’s pernickety interpretation of the tax treatment of cash held within stocks and shares account. That just creates bad vibes in the wings.
Meanwhile, the campaign’s goals read as wishy-washy. It’s all about “helping people build confidence over time”, apparently. Well, OK, that’s what the market research suggests, but “creating more opportunities for everyday conversations” is limp when, in the outside world, teenagers are trading crypto on their phones and the world is awash with smart apps. The intended audience can surely handle more directness.
As for the squirrel, it may get lost in the forest of meerkats and other CGI creatures deployed by financial services firms. For a campaign that is supposed to be doing something distinctly different, why go with a character which, on first glance, looks generic?
Back in the pre-smartphone 1970s, there was a certain shock value for the average five-year-old in seeing Willie Weasel lying injured in the road. At least the message about bad consequences was clear and memorable. One wishes the Savvy campaign well, but one fears a conversational squirrel may struggle to be heard.
Last weekend, several thousand people took to the streets in Munich to demonstrate against abortion and assisted suicide. One speaker made an extremely dramatic plea against what he called the “culture of death” that has allegedly taken hold in Germany. One sign of this, the speaker argued, was that the government is planning to abolish a regulation known as “spousal tax splitting.”
Is tax law really relevant to deep philosophical debates on the sanctity of life? It is even a matter of life and death at all? Surely we needn’t go that far? In any case, the intense political uproar surrounding the new debate on whether to abolish spousal tax splitting is notable, even by today’s standards of populist outrage.
An advantage for couples with widely divergent incomes
The row was sparked by Germany’s vice chancellor and finance minister, Lars Klingbeil, of the center-left Social Democratic Party (SPD), who said he wanted to abolish and replace the joint taxation of spouses’ income, a system that has been in place since 1958.
How exactly does spousal tax splitting work? In Germany, married couples (and since 2013, couples in civil partnerships), can choose to have their income assessed jointly by the tax authorities.
It means that the taxable income for both spouses together is halved – as if both partners had each earned an equal half of the income. Their tax liability is then determined by simply doubling the income tax due on one half.
As people who earn more pay higher taxes in Germany, this system benefits couples where one partner (and often this is still the man) earns significantly more than the other (in practice often the woman).
Costs of up to €25 billion per year
If for example one partner earns €60,000 ($70,512) a year and the other partner earns nothing, the couple will be taxed as if they earned €30,000 each. In this example, the couple would save nearly €5,800 in taxes per year compared to the amount they would owe if both partners filed their taxes separately. According to the Finance Ministry, spousal tax splitting costs the government a total of up to €25 billion annually.
Some critics have long viewed splitting as a tool to keep women out of the labor market, because the more a woman earns, the larger her tax burden becomes. Klingbeil seems to agree, arguing on ARD television in late March that the system was “out of step with the times.” The spousal splitting system reflects “a view of women and families that is completely at odds with my own,” he said.
Chancellor Merz said to be in favor of splitting
On Monday of this week, Klingbeil got some surprising support on this from Johannes Winkel, head of the youth wing of the conservative Christian Democratic Union (CDU).
“Given the demographic reality, the government should create incentives to ensure that both partners in a relationship are employed,” Winkel told the Funke Media Group. “In the future, tax relief should primarily be granted to married couples when they are facing hardships related to raising children.”
But the chancellor is a vocal skeptic of the proposal. “I am not convinced by the claim that joint filing for married couples discourages women from working,” Friedrich Merz said at a conference organized by the Frankfurter Allgemeine Zeitung newspaper. “Marriage is a relationship based on shared income and mutual support. And in a marriage, income must be treated as a joint income for tax purposes, not separately.”
Klingbeil’s alternative plan
At around 74%, the labor force participation rate for women in Germany is one of the highest in Europe, but half of them work part-time.
Klingbeil’s idea is to replace the existing system with a more flexible approach: Both partners would be able to distribute tax-free income among themselves in such a way that it minimizes their tax liability. This would allow the couple to continue enjoying a tax advantage, albeit not to the same extent as before. And whether one partner earns more than the other would become less important.
However, it remains to be seen whether Klingbeil will be able to push through his proposal. Aside from Germany, similar regulations offering tax benefits to couples exist in Poland, Luxembourg, Portugal and France.
This article was originally written in German.
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