Corporate Leaders in Finance and beyond: Who Waits Will Play by Others' Rules

corporates

Jun 23

By Nadine Kugler, QAI Ventures

How will quantum technologies reshape the future of financial services - and are institutions moving fast enough to capture the opportunity?

Spotlight: Quantum in Finance

There was no better place to discuss these questions than London, and no better event than The Economist's 5th Annual Commercialising Quantum Global Summit. The QAI Ventures team was there to join conversations with leaders from finance, technology, government, and industry on what comes next as quantum moves from research labs into real-world applications. At The Economist's Quantum Global Summit, corporate leaders from financial services gathered to compare notes. One phrase recurred: "not if, but when." Quantum algorithms are running in controlled pilots at global banks. Post-quantum cryptography has reached NIST standard status. The race has begun, most boards just haven't noticed. McKinsey calls 2026 a "commercial tipping point": the global quantum market hit $1.9 billion in 2025, and venture capital poured in $4.9 billion, more than double the prior year's record. Between awareness and action, most institutions are stuck.

The discussion made one thing equally clear: the most compelling use cases extend well beyond finance. Life sciences emerged as a frontier of comparable strategic importance, and the barriers to adoption are much the same in both sectors. A parallel panel on quantum technology and geopolitics framed a harder question: the rules of the quantum ecosystem are being written now, will European organisations help write them, or inherit them? QAI Ventures' Chief Commercial Officer Romi Sumaria was direct: "We're sadly not in an open ecosystem world right now."

The real barrier is not the hardware

The technical foundations, hybrid quantum classical ML for fraud detection, quantum simulation for risk models, post-quantum cryptography, are established. The urgency is broadly accepted. Yet innovation leads at nearly every major financial institution report the same friction:

no budget for initial experiments, boards treating quantum as a conference talking point rather than a strategic priority, and governance structures designed for incremental IT projects, not non-linear deep tech investment.

Even getting £15,000 approved for a proof of concept can require months of internal sign-offs. A business leader measured on P&L has little incentive to divert resources to a technology whose impact on the next earnings call is barely quantifiable. That changes when quantum intersects with an existing priority, particularly security.

The invisible threat: why post-quantum security is decided now

Quantum computers cannot break standard encryption today. Recent research has materially compressed the estimated timeline: three papers published between May 2025 and March 2026 revised the qubit requirement to break RSA-2048 from roughly 20 million down to potentially 100,000, moving the relevant horizon significantly closer. What already exists is a different kind of threat: "harvest now, decrypt later." State actors and criminal organisations are collecting encrypted data today, intending to decrypt it once sufficiently powerful machines are available. China has invested heavily in quantum security for years and is significantly ahead. For institutions with long-dated contracts, sensitive client data, and critical infrastructure, this is a live threat, not a future one.

NIST published the first standardised quantum-resistant algorithms in 2024. Singapore, US, and most European countries already have concrete migration timelines. Migrating to post-quantum cryptography is a multi-year programme. Starting when regulation demands it means starting too late. Most institutions compound the problem by lacking a full picture of their own cryptographic estate. The inventory itself takes longer than expected.

The recommended approach is layered abstraction: cryptographic layers that encapsulate existing systems and are modernised incrementally, the same principle that enabled mainframe migrations without halting operations.

Where the value is concrete

The discussion at the summit made clear that valuable use cases extend well beyond finance; life sciences may ultimately prove the more transformative frontier. Pharmaceutical companies have been experimenting with quantum simulation for drug discovery for several years, showing a roadmap to modelling molecular interactions at a precision that classical computers cannot match. The commercial horizon is longer, but the argument is consistent with what the financial sector has already learned: those who build capability before the technology matures will set the terms when it does.

In finance, two areas offer near-term returns: Quantum Maschine learning and Complex risk modelling. HSBC's use of IBM's Heron processor improved bond trading predictions by 34% over classical compute alone in historical backtesting, not yet live trading, but a meaningful signal of direction.
The lesson is consistent: identify well-defined problems, demonstrate value in a controlled environment, then use those results to earn broader organisational buy-in. In insurance, catastrophe modelling is growing more complex as climate-related loss events multiply; classical Monte Carlo methods face similar capacity limits. The same logic, high-dimensional problems where quantum explores a fundamentally larger solution space, applies in energy and weather modelling, and in logistics and materials, where quantum-inspired algorithms running on classical hardware are already delivering measurable value.

Beyond computing and finance entirely, quantum sensing has crossed its own commercial threshold: Q-CTRL demonstrated a 100x performance advantage over classical alternatives in GPS-denied navigation, the first verified commercial quantum advantage in any domain, with direct implications for defence, infrastructure, and precision industries.

How to get there: through industry clusters

Early deep tech investing in quantum followed a horizontal logic. It rarely generated traction. Startups that do not understand how a bank's risk division operates cannot build products it will buy. The more effective model is the industry cluster: bring financial services firms together with startups working on their specific problems, and provide structured access to real use cases alongside capital. QAI Ventures has built accelerator programmes in Switzerland, Singapore, and Canada on exactly this model. The same cluster approach applies in life sciences, where the distance between a quantum algorithm and a validated clinical application demands equally deep domain immersion.

The geopolitical context sharpens the urgency. Almost every major quantum hardware IPO is happening in the United States, with defence procurement and export controls reinforcing the trend. Europe's structural problem is a funding gap that compounds over time: university prototype, Series A, Series B, then an IPO at which point the company is absorbed elsewhere. This the longest remaining window for global organisations to compete in a foundational technology wave. Corporate engagement, through clusters, partnerships, and early procurement, is part of what keeps it open.

The gap that kills most projects

A derivatives pricing project at a major bank used tensor networks to accelerate Monte Carlo simulations. It worked. It never reached production, not because the technology failed, but because no governance pathway existed for a controlled rollout of something this novel. The bank walked away. This pattern repeats across institutions. Those that cross the pilot-to-production gap consistently share one trait: they defined success metrics with the business before the work began, not after.

Three next steps

The window to shape the rules rather than follow them is open, but not indefinitely.

Map your cryptographic estate first. Institutions need visibility into what they are encrypting, under which protocols, and with which third-party dependencies. This work takes longer than expected and should start immediately, regardless of where local regulators stand.
Anchor quantum projects to existing strategic priorities, security, risk reduction, cost, rather than running them as standalone research programmes. Problems defined by the business get funded; problems defined by the technology team often do not.
Engage the regulatory and ecosystem process actively. The FCA's quantum sandbox and its collaborative approach to standard-setting is a model worth following elsewhere. Institutions that participate in shaping standards have far more control over timelines than those who wait to receive mandates.

Those who act now write the rules. Those who wait play by them.

Download the White Paper "Quantum in Finance"