Year of the Horse: fast and dangerous

These are the trends that will accelerate this coming year.

In the lunar calendar, Years of the Horse are depicted as times of acceleration. Galloping on a stallion is exciting and dangerous, whether it’s kicking up Arabian sands, scaling mesas of the Wild West, or crossing the finish line at Happy Valley racecourse.

There are three trends in ‘tech+money’ that look likely to accelerate this year: financialization, AI, and fragmentation. Moreover, they are interconnected. The thrill of the ride – the pounding of the heart, the terror of being thrown out of the saddle – is in these feedback loops.

Financialization

Financialization is the toxic gift of the neo-liberal age. We may no longer have free markets and unfettered trade, but the role of finance in industry and life continues to expand far beyond the rate of GDP. For decades, now, finance has existed to serve itself, not the real economy.

There are benefits to finance, of course. All people and businesses need access to savings, credit, markets, wealth, and protection. Commercial banks creating money is what enables growth. The outsized nature of derivatives markets and financial engineering provide liquidity, stability, and tools to manage risk—if used and regulated sensibly (and we can argue for a very long time about what ‘sensibly’ means).

But something gets lost as more assets are sliced, packaged, and sold. We’re well past securitizing sub-prime mortgages, all the way to private equity, identity, IP, reputations. Raw capitalism transforms every social activity into an economic one; industries and lives get abstracted on Bloomberg screens. Then, before you know it, your entire manufacturing base has moved to another country, your once-great corporations and institutions are hollowed-out shells dedicated to share buybacks, and your culture is debased into tranches of data streams.

This has been going on since the 1970s when Wall Street began adopting computers. Computers led to digitalization, and now to tokenization, fractional ownership, and programmable credit and money. We now have flats in Dubai and Chinese supply-chain finance tradable on-chain as tokens.

This is great for a new class of investors, it’s great for downstream companies to secure new forms of credit and liquidity, and it’s great for people who live in countries with rickety financial infrastructure to find new ways to save, pay, and invest. New products will create new derivatives markets, and assets and liabilities that can be plugged in like Lego blocks to build better portfolios.

It also is turning every human experience into a gambling opportunity. Once-staid financial markets increasingly resemble a casino. Crypto IS a casino. And actual casinos, like online sports betting franchises, have been recast as securities trading on prediction markets. Moreover, it is creating products that should not be in the hands of retail investors. Private-equity firms, their portfolios bleeding behind their walls of illiquidity, would like nothing more than to dump their positions on retirees for a generous fee.

AI and fragmentation are turbo-charging financialization. AI first. Tech has always gone hand-in-hand with finance in the neo-liberal age, and trading desks have been big users of algorithms for decades. Neural nets gave us machine learning. Now LLMs are able to underwrite risk on thinner data, price and re-price millions of micro-positions in real time, and automate compliance.

So far, AI has only slowly begun to replace many workers in finance, but this will accelerate. More interesting than automation is how AI can reinvent entire verticals: the coordination among institutions, clients, and markets. It allows small teams to provide the same kind of services as lumbering incumbents. In terms of financialization, AI will be the new managerial layer building and designing a deluge of products, assets, liabilities, payments, and trades. It will become the heart and circulatory system for hyper-personalization, pushing out the frontier of financialization.

Fragmentation of global systems is also a boon for financialization. Even as monetary systems, supply chains and trade routes change or collapse, the enhanced complexity of a fractured world will call for new things to broker, to hedge, to use as collateral. Every new risk, every new cross‑border friction, becomes something that can be wrapped in a swap, an option, or a structured token.

Artificial intelligence

AI is becoming the coordination layer that makes this new financialized landscape workable at speed and scale.

For small firms and individuals, AI lowers the operational barrier to entering a financialized world. A solo entrepreneur can now plug into AI‑driven accounting, credit scoring, and portfolio tools that previously required a back office. A retail investor can access algorithmic trading strategies or auto‑rebalancing portfolios via a mobile app.

For large enterprises and banks, AI is more profound. It allows them to operate as networks of human and machine agents, orchestrated by systems that monitor flows, allocate capital, and manage risk in real time. Credit decisions, compliance checks, collateral calls, and cross‑border payments can be routed through AI‑mediated workflows that cross internal silos and external networks. Instead of a stack of discrete systems tied together by manual processes, you get a mesh of services coordinated by models.

Now plug this into financialization: More of the world is turned into tradable risk. AI makes it cheap to originate, distribute, and manage that risk. The marginal cost of adding one more product, one more synthetic exposure, one more layer of leverage, falls.

The feedback loop is powerful. The more financialized the system becomes, the more data it generates. The more data it generates, the better AI gets at spotting patterns and arbitrage. The better AI gets, the more aggressively firms can push into new niches: new tokens, new credit products, new forms of securitization.

The risk, of course, is that we create a hyper‑efficient machine for manufacturing opacity. AI can make complex structures appear seamless and user‑friendly, masking correlated risks and hidden leverage behind clean dashboards and personal recommendations. When many actors run similar models, trained on similar data, their behavior can synchronize. AI complexity without transparency and robust reporting is more likely to create systemic risks, not mitigate them.

We will need AI more, though, in a fragmenting world. The creation of new, non-USD settlement corridors, clearing systems, currency networks, and commodity contracts will require plenty of intermediation, risk management, and market making. Standards will break down while data and legal barriers will rise. The coordination required will be far more complex than anything experienced by the finance industry.

Fragmentation

Fragmentation is going to lead to greater reliance on AI. Routing payments around bottlenecks, arbitraging spreads between rails, gaming different regulatory pockets: these are machine problems as much as human ones. The more fragmented the system, the more valuable good coordination becomes.

Fragmentation is the diminishment of the US-dollar centric world. The dollar, US Treasuries, and New York’s clearing function is both the result of neoliberalism and its facilitator. The dollar remains by far the primary reserve currency because it is the currency of debt, of swaps, of oil. Treasuries are, still, the only safe haven of size. The liquidity and openness of the US financial system has absorbed the massive excessive savings of mercantilist countries.

Although the US is trying to prop up the dollar and demand for Treasuries through stablecoins, this isn’t stopping many efforts around the world to find hedges and alternative mechanisms for moving and storing wealth. The recent volatility in gold and silver prices shows the limits to these efforts, but they will only continue. China now offers a yield on its CBDC, an enticement aimed at getting foreigners to hold a currency that is only convertible upon Beijing’s whim. Such efforts will accelerate. The main impact will be to make it more expensive and difficult to manage money and credit globally.

Financialization and AI are going to support fragmentation, though. AI, as noted, will provide the tools to make managing this fragmented world easier. Financialization will create more products to hedge, invest, and borrow or lend, be it involving dollars, or crypto, or CBDCs, or tokenized deposits.

What makes the Year of the Horse so dynamic is that this is the year when these feedback loops intensify. Financialization creates more ways to slice and dice assets and liabilities, generating data that is used by AI to price and route trades, which encourages further financialization.

Fragmentation creates more complex, multi-rail, multi-currency environments that can’t be managed by hand. AI becomes the coordinator, and as fragmentation becomes easier to navigate, processes of disintegration will accelerate.

The more the global system splinters into blocs, hedges, and parallel rails, the more demand there is for instruments to bridge these gaps: swaps, structured credit, synthetic exposures, stablecoins. This deepens financialization and hands firms more tools to amplify further fragmentation.

The upside of these feedback loops is that capital can be allocated more precisely, small firms can access tools previously only available to big institutions, and incumbents can operate more nimbly. But this is also a world in which shocks will propagate faster, where inequality widens between those who can navigate this landscape and those who are simply exposed to it, and where the foundational assumptions of money, work, and safety nets are in flux and in danger.

The JDB Report wishes our audience a healthy and prosperous Lunar New Year. Ride fast and ride safe!