In Summary Most technologies create value before they create problems, but quantum computing may break that pattern. Imagine two clocks ticking side by side: one measures the time until quantum computers become economically useful, the other the time until they can break the cryptography that underpins the financial system. Which clock strikes first is a genuinely open race. The upside potential is real but narrowly concentrated around derivative pricing and other complex financial simulations. Beyond these areas, its impact on the financial industry is likely limited. Quantum computing accelerates Monte Carlo methods behind financial simulations, while it shows no consistent advantage yet over improving classic methods for portfolio optimization and financial machine learning. Insurers are well positioned as simulation and optimization are at the heart of liability valuation, risk pricing, capital modelling and asset-liability management. Quantum money could use uncopiable quantum states to authenticate value and prevent counterfeiting, although commercial deployment remains remote. The rewards remain theoretical for now, threatened by error-correction overhead and a rising classical benchmark, until large machines exist. But quantum-inspired methods deliver operational value on classical hardware today, and the talent, tooling and know-how built along the way will carry over. Q-day could come sooner than we think: data harvested today can be decrypted later. The recipe for breaking today's encryption has existed since 1994 and waits only for the machine, which is also the smaller one, needing roughly 1,250–1,450 logical qubits vs around 4,700–7,500 for leading financial applications. Health records, classified government information and sensitive financial data must stay confidential for decades, but experts put the probability of Q-day, the point at which a cryptographically relevant quantum computer exists, arriving within ten years at 28–49%. Defensive standards have existed since 2024, and regulators have set dates: The US National Institute of Standards and Technology (NIST)