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%)

Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.

To access these options, along with all other subscription benefits, please contact or view our subscription options here:

You are currently unable to copy this content. Please contact to find out more.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to Central Banking? View our subscription options

Most read articles loading...

You need to sign in to use this feature. If you don’t have a Central Banking account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account