FIS Horizons 2023 Brochure - Riding the wave - Flipbook - Page 10
The use of AI and
machine-learning
in financial services
John Salmon
Partner, London
Michael Thomas
Partner, London
Julie Patient
Counsel, London
Diana Suciu
Associate, London
Daniel Lee
Associate, London
Melanie Johnson
Senior Knowledge Lawyer, London
The UK financial services regulators, the Bank of England (BoE), the Prudential
Regulation Authority (PRA) and the Financial Conduct Authority (FCA) have
been taking a closer look at the increasing use cases for the safe and
responsible adoption of artificial intelligence (AI) and machine-learning
across financial services.
The discussions around the benefits and risks
related to the use of AI in financial services are
focused on consumer protection, competition,
safety and soundness of firms, insurance
policyholder protection, financial stability
and market integrity.
A key area of consideration for the regulators
is looking at where existing legislation, rules
and guidance can help to mitigate the risks
associated with an increased use of AI and
machine-learning across firms.
The existing FCA and PRA rules and guidance
implementing the SM&CR emphasize senior
management accountability and responsibility
which are relevant to the use of AI and the
risks the regulators are looking to circumvent.
This Engage article examines how the
SM&CR could be fine-tuned to provide an
oversight and governance framework for AI
systems in firms.
Article correct as of 30 November 2022.
The new Consumer Duty sets a higher
standard of behavior for financial services
firms directly or indirectly interacting with
retail customers in the UK. This Engage
article (article correct as of 28 October
2022) explores the potential for AI in an
outcomes-based approach to the Consumer
Duty and considers how much space firms
should make for AI in their interactions with
consumers. When used properly AI can,
improve firms’ compliance with the Consumer
Duty and ultimately create more positive
outcomes for consumers, though this will
certainly not be a case of “one size fits all.”
