French corporate and investment bank Crédit Agricole CIB announced the successful completion of two finance-related quantum computing experiments it undertook almost two years ago with fellow French firm Pasqal and Spain’s Multiverse Computing.
The bank said the successful completion of the experiments demonstrate that quantum computers using new algorithmic techniques already can perform on par with classical computers when tackling certain real-world financial problems, and further suggest that quantum advantage could be achievable for these problems as early as next year.
Crédit Agricole CIB launched its work with Pasqal and Multiverse in June 2021, and the association quickly became a key talking point for each of these quantum computing start-ups as they sought to provide examples of interest by customers and partners in their solutions. Multiverse even hired a Crédit Agricole vet as the general manager for its efforts in the French market. The experiments would take about a year and a half to complete.
In the first experiment the bank worked with Multiverse to assess the performance gain offered by quantum computing in the valuation of derivatives. Though research has demonstrated how neural networks can be used for such calculations, they often can be too resource-intensive in terms of memory and suffer from lengthy processing times.
“However, algorithmic techniques inspired by quantum computing can be used to optimize the speed and memory required for this training phase, leading to faster valuations and more accurate risk assessments,” a statement from the companies said.
The second experiment intended to measure a quantum computer’s ability to solve a concrete problem, given the current state of technology. and assess the change in performance depending on the number of qubits used when addressing a real-world financial use case – the anticipation of a counterparty credit rating downgrade over a six-month to 15-month period. Classical computers and heuristics can be used to achieve good results, but do not work for all problems, and there is no guarantee that the results obtained will be close to the ideal solution, the companies said, adding “Using quantum parallelism, in theory, makes it possible to find optimum solutions more efficiently.”
Regarding the success of the experiments, the companies stated, “A marked improvement in computing time requiring a smaller memory footprint was measured using quantum computing techniques, paving the way for their use in real-world applications in the valuation of derivatives. For the quantum computer, the chosen problem was tackled under real-world conditions. With a quantum processor of only 50 qubits, the results obtained are as accurate as the results in production. Our projections indicate that this performance could be bettered at 300 qubits, a power that should be available industrially in 2024.”
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