Quantum computing is being explored as a solution for complex financial modeling, with HSBC and IBM pioneering its use in algorithmic bond trading. Their project simulated competitive bidding using historical trading data and IBM’s System 2 quantum machine with Heron processors, achieving significant improvements over classical models, particularly in predicting bond prices. This aligns with industry views that financial markets present ideal test cases for quantum approaches due to their complexity.
Experts from academia and industry acknowledge the progress but warn that quantum computing remains nascent in routine finance operations. IBM stresses the current experiments are preliminary, and transitioning quantum techniques to commercial environments involves challenges such as integration, algorithmic refinement, and cost. Financial institutions like HSBC, JP Morgan, Standard Chartered, and BBVA are at the forefront of exploring this technology.
Looking forward, quantum computing is unlikely to replace classical systems soon or become ubiquitous across all banking operations. The technology will likely be specialized for specific applications, combining classical and quantum algorithms. High costs and limitations currently restrict adoption to a few leading institutions, highlighting the need for continued research and gradual implementation to realize long-term benefits in financial markets.
👉 Pročitaj original: CIO Magazine
