Is Retail Banking Ready for the Quantum Computing Revolution?

Retail banks process massive amounts of data daily, from transactions and credit histories to market trends. Despite their power, traditional computing systems struggle to process and analyse this data efficiently for critical decision-making. Quantum computing promises to change that by enabling unprecedented computational speed and accuracy. 

Why retail banking stands to benefit 

Quantum computing leverages the principles of quantum mechanics to perform calculations infeasible for classical computers. Unlike traditional bits, quantum bits (qubits) process vast amounts of information concurrently by existing in multiple states. This enables quantum computers to handle complex datasets and intricate variables commonly found in financial services. 

Retail banking workloads frequently involve significant combinatorial problems, high-dimensional data, and tight latency requirements. Examples include real-time fraud detection across millions of transactions, credit scoring with many interacting variables, optimising cash and liquidity across branches, and securing customer data against future quantum threats. 

Quantum hardware offers algorithmic paradigms, such as quantum annealing and gate-model quantum algorithms, that can reframe these problems and, in some circumstances, produce improved solutions or faster exploration of solution spaces than classical techniques. 

Practical Applications of Quantum Computing in Retail Banking 

Although quantum computing is still emerging, retail banks actively explore its potential to address persistent challenges. The following applications highlight how quantum computing could transform retail banking operations. 

• Fraud Detection and Prevention 

Fraudulent activities pose significant challenges to retail banks. They must balance false positives that frustrate customers with false negatives that increase losses. Quantum approaches, such as quantum machine learning formulations and QUBO (quadratic unconstrained binary optimisation) encodings, are being tested to accelerate pattern discovery and classifier training on transaction data. Researchers have demonstrated QUBO-based SVM classifiers on real quantum hardware for credit card fraud datasets, showing a practical research path toward hybrid quantum-classical fraud systems. These experiments suggest hybrid solutions complement classical models in production pipelines. 

For instance, HSBC, in collaboration with Quantinuum, is exploring quantum computing applications in fraud detection, aiming to develop more accurate and efficient systems. 

• Portfolio Optimisation 

Managing diverse investment portfolios requires balancing risk and return across various assets. Quantum computing can optimise this process by evaluating numerous variables and scenarios simultaneously, enabling more informed and precise investment strategies. A 2023 report by McKinsey & Company, Quantum Technology Use Cases as Fuel for Value in Finance, highlights that quantum computing could significantly enhance portfolio optimisation by efficiently handling complex calculations that traditional systems struggle with. 

• Risk Assessment and Credit Scoring 

Traditional credit scoring relies on limited data, often overlooking critical factors. Quantum computing integrates diverse sources for more accurate risk assessments, enabling banks to build precise models for improved lending decisions. 

According to a 2025 report by the World Economic Forum, banks are already piloting quantum-based risk forecasting models. For example, Yapı Kredi, a leading customer-centric financial services group in Turkey, used quantum computing hardware from D-Wave. The system simulated thousands of interconnected risk scenarios involving its small and medium-sized enterprises network. The bank could pinpoint businesses especially vulnerable to cascading failure modes, computations that would take classical systems much longer to resolve. 

• Algorithmic Trading 

In trading, speed and accuracy are paramount. Quantum computing processes market data in real-time, helping banks develop adaptive algorithms that identify trends and execute trades at optimal moments. 

• Quantum-Safe Encryption 

As quantum computing power grows, so does the urgency to secure sensitive financial data against potential quantum attacks. Classical encryption methods like RSA and ECC could become vulnerable once quantum systems achieve sufficient scale. To prepare, banks are beginning to invest in quantum-safe encryption strategies that ensure long-term resilience. 

Building this resilience involves focusing on several critical approaches: 

1. Post-Quantum Cryptography (PQC): Algorithms designed to withstand quantum attacks, many of which are being standardised by agencies such as NIST in the U.S. and ENISA in the EU. 

2. Quantum Key Distribution (QKD): A method of securing communications using the principles of quantum mechanics, making it virtually impossible for eavesdroppers to intercept without detection. 

3. Quantum Random Number Generation (QRNG): Generates truly random numbers using quantum processes, enhancing the unpredictability of cryptographic keys compared to classical methods. 

Quantum in Action 

Leading banks and technology providers are piloting projects demonstrating how quantum algorithms can improve fraud detection, optimise portfolios, enhance risk assessment, and secure transactions. For example:  

• JPMorgan Chase: A global banking and financial services firm headquartered in New York City has established an internal quantum research team focused on algorithms for finance, AI, optimisation and cryptography. The bank runs in-house experiments and partnerships to move promising algorithms toward production readiness. 

• D-Wave Systems: A Canadian company specialising in quantum annealing and hybrid quantum services, has collaborated with European banks such as BBVA and Bankia, demonstrating hybrid solvers for financial optimisation challenges. These vendor–bank pilots provide practical templates for designing proofs of concept with external partners. 

• Goldman Sachs: A leading global investment bank, has proactively identified quantum algorithms for pricing, optimisation, and risk where quantum advantage may emerge, publishing R&D reports and aligning hardware requirements with financial algorithms. 

• HSBC: A global banking and financial services leader, has successfully piloted quantum-safe technology to secure transactions involving tokenised physical gold. This initiative marks a significant step in safeguarding digital assets against future quantum computing threats. The bank collaborated with Quantinuum, integrating PQC and QRNG to enhance the security of its digital asset platform. 

• Intesa Sanpaolo: One of Italy’s leading banking groups, Intesa Sanpaolo is exploring advanced quantum computing techniques to enhance its financial operations. By employing variational quantum circuit (VQC)-based classifiers, the bank has enhanced the accuracy and efficiency of identifying fraudulent transactions, outperforming traditional models with fewer data features. This approach has led to a reduction in false positives and improved operational efficiency. 

  
  

Challenges and Considerations 

While the potential benefits of quantum computing in retail banking are substantial, several challenges must be addressed: 

• Infrastructure Requirements: Quantum computers require specialised environments, including low temperatures and isolation from electromagnetic interference, which complicates and increases the cost of their deployment. 

  
  

• Integration with Existing Systems: Merging quantum computing with legacy banking systems requires substantial modifications and investments. 

  
  

• Talent Acquisition: The shortage of professionals skilled in quantum computing presents a challenge for banks seeking to develop and implement quantum solutions. 

  
  

• Regulatory and Ethical Considerations: Integrating quantum computing prompts questions about data privacy, security, and adherence to financial regulations. 

The Future of Quantum in Retail Banking 

As quantum computing technology advances, its applications in retail banking are anticipated to grow. Banks proactively investing in quantum research and development will be better positioned to capitalise on their advantages, providing enhanced customer service. 

AgileIntel, with its expertise in digital transformation, is dedicated to guiding financial institutions through this quantum evolution, ensuring they fully harness the potential of this groundbreaking technology. 

Conclusion 

Quantum computing is poised to revolutionise retail banking. By tackling complex challenges and unlocking new opportunities, it presents a transformative path for financial institutions. Embracing this technology will enhance operational efficiency and redefine customer experiences in the digital age.