The bank teamed up with French quantum computer manufacturer Pasqal and Spanish quantum algorithm specialist Multiverse Computing 18 months ago on the experiments. The first assessed the performance gain offered by quantum computing in the valuation of derivatives. Recent research has shown the benefit of neural networks for this type of calculation. Yet, in several cases, the neural networks are difficult to use because they are too resource intensive in terms of memory and suffer from lengthy processing times. However, algorithmic techniques inspired by quantum computing can be used to optimise the speed and memory required for this training phase, leading to faster valuations and more accurate risk assessments, says the bank. The second experiment sought to measure a quantum computer’s ability to solve a concrete problem and to assess the change in performance depending on the number of qubits used. The bank chose a production use case, providing a real point of comparison: the anticipation of a counterparty credit rating downgrade over a six to 15-month period. Through conventional computer technology and heuristics, good results can be achieve. But, using quantum parallelism, in theory, makes it possible to find optimum solutions more efficiently. Ali El Hamidi, project sponsor at Crédit Agricole CIB, says: “These two Proofs of Concept demonstrated the potential and reality of quantum computing for finance, despite these technologies still being in their infancy. "We took advantage of this initiative to start developing the internal skills to prepare for a technological breakthrough which, if it happens, will have a direct and decisive impact on competitiveness in our sector."