By the looks of it – a lot of effort.

A joint paper recently published by UK Finance and Microsoft provides some useful insights in the context of implementing AI by financial institutions. These are just a few:

  1. AI is not a mere technology tool. Principles of fairness, privacy and security, transparency, and accountability are a starting guide to consider in the context of broader implications of AI and its appropriate use.
  1. Organisations must a) insist on processes to identify bias in datasets and ML algorithms, b) be transparent around how AI models make decisions so that others can judge and challenge definitions of fairness. Explainability of AI/ML is vital for customer reassurance and increasingly it is required by regulators.
  1. Without appropriate testing, governance and control, a rapid growth in AI models could have significant reputational impact and subsequent reductions in consumer trust.
  1. AI skills and expertise should not just be in the domain of technology teams. The drive for AI adoption needs to start at the top of the organisation and filter down to all levels.
  1. By focusing on small incremental wins with a clear Return on Investment, while building an AI driven culture, organisations can maximise the opportunity that AI brings.