Data quality and staff skills are greatest AI challenges – benchmark respondents

Privacy and algorithmic fairness are also concerns

Central banks adopting artificial intelligence (AI) and machine learning (ML) techniques face a number of challenges, including addressing data-quality issues and staffing skills. 

Officials from 17 central banks answered questions on their greatest concerns associated with the use of AI/ML tools in the Fintech Benchmarks 2022. 

Data quality and acquiring relevant skills were voted as the biggest issues by 76% and 71% of central banks, respectively. Privacy (41%) and algorithmic fairness (35%)

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