Finance

How AI and crypto are shaping the future of finance

Published

2 years ago

March 16, 2024

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

Finance

Proximo Congress 2026: US Energy & Infrastructure Finance | Insights | Mayer Brown

Published

7 hours ago

June 3, 2026

Press Room

Proximo Congress 2026: US Energy & Infrastructure Finance | Insights | Mayer Brown

Mayer Brown is a proud sponsor of Proximo Congress 2026. This senior meeting of the US energy, infrastructure, and digital infrastructure finance community is shaped around the questions credit and investment committees are actually asking in 2026: how asset classes are converging, how risk is being priced in a recalibrated policy and geopolitical environment, and how public and private capital are being structured together to deliver projects at scale.

Mayer Brown has also been recognized for three separate awards which will be presented during the event. These awards include:

Proximo North America Transport Deal of the Year 2025 – SR 400 Peach Partners
Proximo North America Rail Deal of the Year 2025 – Brightline West
Proximo North America LNG Deal of the Year 2025 – Port Arthur LNG 2

For more information, visit the event website.

Finance

What are nonconforming mortgages and what are the risks?

Published

18 hours ago

June 2, 2026

Press Room

What are nonconforming mortgages and what are the risks?

If you have ever taken out a mortgage, you’ll know there are a lot of requirements to meet. You may need to put down a certain amount and have a debt-to-income ratio below a certain threshold. You may also run into limits on how much you can borrow or what sources of income the lender will count.

These rules do not apply to all mortgages — just to conforming mortgages, which is what the majority of borrowers take out. However, mortgage lenders are increasingly offering what are known as nonconforming loans, or mortgages that do not “comply with every one of the strict standards put in place after the housing crisis,” said The Wall Street Journal. While “still a small portion,” the “share of mortgages using alternative lending practices” has “doubled in size over the past three years.”

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Finance

Financial Stress Is Changing What Consumers Value in Credit Cards | PYMNTS.com

Published

1 day ago

June 2, 2026

Press Room

Financial Stress Is Changing What Consumers Value in Credit Cards | PYMNTS.com

What U.S. consumers ask of their credit cards has changed. For financially stressed households, it has little to do with rewards.

As more households turn to credit cards to manage liquidity and cover everyday expenses, a new set of practical concerns is driving card behavior: Can the card help avoid a missed payment? Can it make balances easier to track? Can it provide enough visibility into available credit and upcoming obligations to help manage an uncertain month?

Those concerns are beginning to reorder what consumers value most in their credit card relationships.

That evidence is clear in “Winning Top of Wallet: How Credit Card Apps Shape Choice,” a PYMNTS Intelligence and Elan Credit Card report examining how consumers use mobile apps to manage spending, payments and engagement across their credit card portfolios. The report found 30% of consumers primarily use credit cards to build credit or extend purchasing power, while another 22% primarily use cards for cash flow management, together outweighing rewards-based usage.

The divide is more pronounced among financially stressed households. Among consumers living paycheck to paycheck and struggling to pay bills, 40% cited credit dependence as their primary reason for using credit cards. Just 11% pointed to rewards.

For a growing share of consumers, credit cards are functioning less like discretionary spending products and more like liquidity management tools.

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What Matters Most

That evolution is also changing which app features matter most.

Among cash flow-focused consumers, 31% said scheduling payments or autopay encouraged them to spend more on a card, while 27% cited alerts and reminders. Credit-motivated consumers showed similarly high engagement with tools tied to available credit visibility and payment timing.

Rewards still influence spending behavior, particularly among financially stable households. Half of consumers who prioritize rewards said tracking or redeeming rewards through a mobile app encouraged them to spend more on the card.

But the report suggests that financial stress changes the hierarchy of engagement. As household budgets tighten, rewards become less central than predictability, visibility and control.

That shift helps explain why mobile apps increasingly influence which cards become top of wallet.

Among credit-dependent consumers, 77% said the quality of a credit card app influences which card they use most often. Credit-dependent consumers also reported the highest app adoption levels, with 77% using their primary card’s app regularly or occasionally.

The competition, in other words, is no longer simply about card acquisition. It is about becoming the card consumers rely on to navigate everyday financial management.

Digital Experience Becomes a Financial Retention Tool

The report also suggests that digital experience increasingly shapes retention risk.

Nearly 1 in 4 cardholders said a poor app or digital experience contributed to reduced card use. Among Gen Z consumers, that figure climbed to 45%.

At the same time, 7 in 10 cardholders said app quality influences which card becomes their primary card, underscoring how mobile interfaces are becoming embedded directly into consumer payment behavior.

For issuers, the implications extend beyond app design.

Consumers living paycheck to paycheck hold nearly as many credit cards as financially stable households, meaning financially stressed consumers are not disengaging from credit entirely. Instead, they are becoming more selective about which cards feel easiest to manage and most useful during periods of financial pressure.

Rewards and promotional offers still matter, particularly among affluent and financially stable consumers. But for a growing segment of households, the most valuable card may be the one that reduces uncertainty around balances, payment timing and available liquidity.

In a crowded multi-card market, financial visibility itself is becoming part of the product.