Quantum computing is emerging as a transformative force in banking, with the potential to redefine financial performance across multiple dimensions. According to McKinsey & Company, leading banks are already exploring applications that go beyond traditional computing to optimise portfolios, assess risk and bolster cyber-security.
In the realm of optimisation, quantum methods such as annealing help solve complex decision-making problems that conventional algorithms struggle with. Banks are using them to refine portfolios, allocate collateral and enhance credit-risk models. For example, partners including Citi Innovation Labs have tested quantum-approximate optimisation algorithms (QAOA) for asset allocation. Additionally, quantum Monte Carlo techniques promise faster and more precise credit-risk evaluation, which could improve capital efficiency and regulatory stress-testing outcomes.
Quantum machine learning (QML) is another frontier. Banks are leveraging QML to detect fraud, forecast customer behaviour and generate anonymised synthetic data. For instance, Intesa Sanpaolo is working with IBM to use quantum models for fraud detection – achieving better accuracy and fewer false positives. On the cyber-security front, quantum communication techniques like quantum key distribution (QKD) and post-quantum cryptography (PQC) are being piloted to protect banking infrastructure from future quantum threats.
McKinsey estimates that quantum computing could unlock between $400 billion and $600 billion in value for financial-services firms by about 2035. While full-scale, fault-tolerant quantum computers remain some years away, banks are advised to develop a quantum-action plan, invest in skills and partner with technology providers now so they are not caught unprepared once the technology matures.
The critical question remains: when quantum advantage becomes practical, how many banks will have the organisational readiness to capitalise on it and avoid being out-paced by more agile competitors?
