Ghosts in the machine: Artificial intelligence, risks and regulation in financial markets
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Ghosts in the machine: Artificial intelligence, risks and regulation in financial markets

A global survey of 424 senior executives from financial institutions and fintech companies, and interviews with leading experts in the field, reveal tension as artificial intelligence (AI) is pioneered across financial markets.


All systems go



Many senior executives from financial institutions and fintech companies see AI as a tool that will help improve financial institutions’ risk management, for example through more in-depth assessment of risk in portfolios and more incisive, comprehensive and informed credit-risk assessment. In these applications, AI promises not reckless speed or loss of control, but rather an unprecedented depth and breadth of insight, and the ability to act on information and learn from its actions.

However many experts also acknowledge a degree of risk surrounding the use of AI.

Research results

Are regulators up to speed?

ai regulation

When asked if financial regulators are “keeping pace with advances in technology”, an overwhelming 76% of survey respondents say no. Nearly seven in ten express little or no confidence that “regulators have sufficient understanding of financial technologies and their impact on the financial services sector today.” One respondent comments that “Regulators are woefully under-skilled in AI and need to boost their understanding or risk being marginalised.”

But regulators do not anticipate rules specific to AI to be written anytime soon.



From thinking fast to thinking smart


Renewed interest in AI is evident from increasing investments by major financial institutions, as well as technology and fintech companies. Fund managers such as BlackRock, Two-Sigma and Renaissance Technologies have been busy poaching the best data scientists from around the world. They compete and collaborate with a growing batch of technology companies including Context Relevant, Sentient Technologies and Kensho, as well as the giants of AI, such as Google, Facebook and Microsoft. 

Within trading and investment management, firms such as Aidiya and Sentient Technologies are pioneering AI trading programmes. They employ a combination of machine learning techniques and evolutionary algorithms to crunch huge amounts of data, in order to recognise obscure patterns, which others have not identified. 


AI in Action

Over the next three years, the most dramatic changes will be felt in the areas of trading, financial analysis and IT, according to 64%, 60% and 60% of respondents respectively. Large numbers also expect machine learning to materially affect risk assessment (59%), credit assessment (57%) and investment portfolio management (52%). Risk assessment and financial research are the areas where companies are most likely to experiment with machine learning applications in the next three years.


Risks: From Moore's Law to Murphy's Law


Technology will not be able to remove the risks inherent in some financial activities, such as making bets on future events. These are likely to persist, regardless of whether humans or algorithms do the work.As Arun Srivastava, Partner at law firm Baker & McKenzie argues, "Financial institutions have been fined billions of dollars because of illegality and compliance breaches by traders. A logical response by banks is to automate as much decision-making as possible, hence the number of banks enthusiastically embracing AI and automation. But while conduct risk may be reduced, the unknown risks inherent in aspects of AI have not been eliminated."


Deep-dive into the data

The survey data yielded many interesting findings and insights into how AI technology is being introduced, managed and perceived by executives from around the world. Here you can find some of the other interesting findings of the survey.




Most of our survey respondents are cautiously optimistic about AI’s future role in financial markets. The optimism derives from the recognition of the great opportunity that awaits successful applications. However, like with all technology, it will largely depend on how it is wielded that will ultimately determine the risk and reward.


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