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Comparing minds and machines: implications for financial stability

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  • Buckmann, Marcus

    (Bank of England)

  • Haldane, Andy

    (Bank of England)

  • Hüser, Anne-Caroline

    (Bank of England)

Abstract

Is human or artificial intelligence more conducive to a stable financial system? To answer this question, we compare human and artificial intelligence with respect to several facets of their decision-making behaviour. On that basis, we characterise possibilities and challenges in designing partnerships that combine the strengths of both minds and machines. Leveraging on those insights, we explain how the differences in human and artificial intelligence have driven the usage of new techniques in financial markets, regulation, supervision, and policy making and discuss their potential impact on financial stability. Finally, we describe how effective mind-machine partnerships might be able to reduce systemic risks.

Suggested Citation

  • Buckmann, Marcus & Haldane, Andy & Hüser, Anne-Caroline, 2021. "Comparing minds and machines: implications for financial stability," Bank of England working papers 937, Bank of England.
    • Handle: RePEc:boe:boeewp:0937
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    Keywords

    Artificial intelligence; machine learning; financial stability; innovation; systemic risk;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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