From data deluge to revenue driver: why financial institutions should embrace AI amid trade-driven volatility

Market volatility, triggered by President Trump’s trade tariffs, has sent shockwaves through global financial markets in recent months. Trading volumes have spiked, and financial institutions have been grappling with a familiar yet intensifying challenge: a deluge of data.

To put this into perspective, UBS, BNP Paribas, Barclays and Société Générale, for example, generated around $5.5bn in combined equities trading revenue during the first three months of 2025.^[1]

Meanwhile, ICE reported that it processed more than 1 trillion messages in a day, and NYSE’s opening and closing auctions grew more than 20% to handle over $37bn in trading activity per day.^[2]

The increased activity across equities, commodities, and currencies is generating vast amounts of market and transaction data at an unprecedented pace. For many firms, especially those with legacy systems or siloed data strategies, this influx feels less like an opportunity and more like an unmanageable flood.

Data, however, should not be viewed as a problem but rather as an untapped wealth of vast potential. Financial institutions should not be overwhelmed. Instead, they should be mobilizing to unlock this potential. With the right AI-driven tools, this data can become a strategic asset, powering more informed trading decisions, deeper client insights, and ultimately, enhanced revenues and client experiences.

Volatility as a catalyst, not a crisis

U.S. trade tariffs, whether imposed or merely threatened, have immediate and far-reaching effects on global supply chains, consumer confidence, and corporate earnings. Investors react swiftly, resulting in surges of buy and sell orders, widened spreads, and fluctuating liquidity. For traditional systems, this activity can strain data processing capabilities and decision-making frameworks. Yet for firms that have deployed forward-thinking AI-based solutions, volatility becomes a valuable source of signal – an opportunity to observe market behavior in high-definition.

The power of AI lies in its ability to absorb massive datasets, identify patterns, and make real-time predictions with a level of granularity and speed that human analysts simply cannot match. As volatility rises, so does the richness of the data. With the right AI models in place, financial institutions can extract insights that are not only reactive but also predictive.

Turning chaos into a competitive edge

Financial institutions should be prepared for the fact that the current wave of trading activity might not just be a passing storm, but instead a preview of a more dynamic and uncertain global economic landscape. Firms that hesitate to modernize their infrastructure risk being outpaced by competitors that can adapt in real-time. Harnessing AI allows institutions to process market data, news feeds, economic indicators, and even social media sentiment to detect early trends, arbitrage opportunities, and anomalies that signal shifts in asset values.

Consider a client with significant exposure to tariff-sensitive sectors like manufacturing or agriculture. AI can help identify correlations between tariff announcements, commodity price movements, and sector-specific equities. Instead of simply reacting to price swings, banks equipped with AI tools can proactively advise clients to hedge risk or capitalize on temporary dislocations. This elevates the institution’s role from transaction processor to strategic advisor and partner.

Enhanced customer service through intelligent insights

Beyond identifying trading opportunities, AI also enables hyper-personalized client service. Amid volatility, clients are not only looking for returns – they’re looking for reassurance, market flow insights, and agility. AI can help firms segment clients based on trading behavior, risk appetite, and historical responses to market events. This allows for tailored communication strategies and investment ideas that resonate with individual needs.

For example, during a tariff-induced sell-off, one client might prefer a defensive realignment while another sees it as a buying opportunity. AI-powered front office platforms can trigger timely, relevant alerts for banks to engage each client with personalized guidance, promoting the precise inventory that a client is likely to be interested in. This not only improves client satisfaction and retention but also drives wallet share as clients place greater trust in a firm that demonstrates real-time understanding and responsiveness.

From operational bottleneck to scalable growth

The operational advantages of AI are just as compelling. Many firms still rely on manual data reconciliation, batch reporting, and outdated risk models that simply can’t keep up with the pace of modern markets. AI streamlines these processes, automating reconciliation, enhancing data quality, and enabling continuous risk assessment. This frees up human capital for higher-value strategic tasks and allows firms to scale without proportionate increases in overhead.

Importantly, this transition does not require a wholesale overhaul of existing infrastructure. Modern AI platforms are increasingly modular and API-driven, allowing financial institutions to layer intelligent tools over legacy systems while modernizing incrementally. This “evolution, not revolution” approach makes AI adoption more feasible, even for mid-tier and regional players.

A strategic imperative

In the face of trade disruptions and market volatility, sitting on the sidelines is no longer an option. Financial institutions that view AI as a luxury or future project risk falling dangerously behind. The competitive edge will belong to those who treat data as a revenue-generating asset and AI as the engine that unlocks its value.

Yes, the data volumes are massive. Yes, the market landscape is complex. But with the right AI strategy, these challenges can be reframed as unprecedented opportunities. Not only to drive trading performance and client satisfaction, but to redefine what it means to be a modern, responsive, and resilient financial institution.

The data flood isn’t going to stop. But with AI, firms don’t need to build a dam – they can build a turbine.