The Bank of England is launching a consortium where private sector finance organizations and artificial intelligence (AI) experts can provide knowledge about the technology Benefits to the sector and risk management.
During an international financial conference In Hong Kong, Sarah Breeden, deputy governor for financial stability at the Bank of England, said regulation must stay one step ahead of AI adoption.
She said this “will help us understand more deeply not only the potential benefits of artificial intelligence, but also the different approaches companies take to manage those risks that may amount to financial stability risks.”
The regulator will then attempt to disseminate best practices, and identify when regulatory guidelines and guardrails are needed. “The power and use of AI is growing rapidly, and we should not be complacent,” Breeden said. “We know from our previous experience with technological innovation in other sectors of the economy that it is difficult to address risks retrospectively once usage reaches a systemic scale.”
The Bank of England and the Financial Conduct Authority (FCA) are tracking how UK financial services firms use artificial intelligence and machine learning. The results of the latest survey, cited by Breeden, covered 120 companies. It found that three-quarters of companies already use some form of AI in their operations.
This includes all major UK and international banks, insurers and asset managers that responded, and represents a 53% increase in the same survey in 2022, it said.
Breeden said that 17% of all use cases use foundation models, including… Large linguistic models Like OpenAI’s GPT4. She added that some of the most common early use cases for AI were “fairly low risk from a financial stability standpoint.” For example, a Bank of England survey found that 41% use AI to improve internal processes, while 26% use AI to enhance customer support.
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But Breeden said many companies are now using AI to mitigate the external risks they face from cyber attacks (37%), fraud (33%), and money laundering (20%).
According to Breeden, the big development from a financial stability perspective is the emergence of new use cases. For example, she said the survey revealed that 16% of respondents use AI to assess credit risk, and 19% plan to do so over the next three years. A total of 11% are using it for algorithmic trading, with another 9% planning to do so in the next three years.
“AI is expected to bring significant potential benefits to productivity and growth in the financial sector and the rest of the economy,” Breeden said. But for the financial sector to harness these benefits, we, as financial regulators, must put in place policy frameworks designed to manage any financial stability risks that accompany them. Economic stability supports growth and prosperity. It would be self-defeating to allow AI to undermine it.
“We do not want to be left in a position of choosing between allowing powerful new technology to threaten financial stability, on the one hand, and preventing its use and loss of growth and innovation – simply because we do not have the policy frameworks to enable its safe adoption,” she said.
Breeden pointed out two issues to watch in relation to Generative artificial intelligence In financial services.
At a micro level, to ensure the safety and soundness of individual companies, she said, regulators must continue to assure themselves that technology-neutral regulatory frameworks are sufficient to mitigate financial stability risks posed by AI, as models become ever more powerful and their adoption increases.
“We need to focus particularly on ensuring managers of financial companies can understand and manage what their AI models are doing as they develop independently under their feet,” Breeden said.
“We must keep our regulatory limits under review if the financial system becomes more reliant on shared AI technology and infrastructure systems,” she added.
