Artificial Intelligence is nothing new in capital markets. Analysts have been using AI to determine credit scores and predict market movements since the 1980s. “Quant” firms such as Renaissance Technologies have used advanced models to build multi-billion dollar equity funds.
Now investors are betting that the technology will transform capital markets themselves. Half of all Venture Capital funding in the final quarter of 2024 went to AI-focused firms1, many of which use the technology to sort vast quantities of data into clear and actionable signals.
At present however, financial firms are primarily using the technology to improve existing processes. Cybersecurity and detection are the most common applications of AI, according to a survey by FSI. 60% of business leaders have already deployed AI to manage operational risk, with 50% having used the technology to augment risk models.
60%
of business leaders have already deployed AI to manage operational risk, with 50% having used the technology to augment risk models.
Yet AI’s ability to identify anomalies in huge data sets is beginning to fundamentally alter the mechanisms underpinning capital markets. Securities processing, for example, no-longer occurs after markets close but in real-time, alerting traders to gaps in a contract and helping them adjust their positions instantly. This not only makes markets safer but also more liquid.
Generative AI may be even more transformational. Investment banks have already developed models to sift through complex securities and loan agreements to find salient information; a big deal when you consider that 60% of this information is stored on email or paper forms.2 “This means you may be able to onboard new customers and start servicing their deals more rapidly,” says Andres Choussy, executive vice president of Trading and Asset Services at FIS. “More broadly, AI may help you receive near-instant answers from data rather than having to log into different systems, read through multiple spreadsheets or request information from colleagues.”
This represents an inexorable shift for capital markets. As analysts become accustomed to operating with AI as a co-pilot, companies will require automation as standard from third party technology firms. A platform that doesn’t include an AI assistant may not cut it.
The breadth of AI’s integration into capital markets raises two critical questions for firms. First, how do you maintain an informational advantage? While open-source AI can provide a greater degree of flexibility when building HR or other back office systems, business leaders are right to be wary when it comes to using proprietary data sets. The key is knowing where to invest in closed models, explains Mr Choussy. “These contain only their own data and sit safely behind their own firewalls.”
The second question is how companies can maintain their advantage over other AI-powered operators. In 2024, Alex Kim, a PhD student at the University of Chicago, attempted to answer the question by challenging investors to build $1000 portfolios using AI analysis of earnings-call transcripts. He found that while less experienced investors still saw an average 2% gain, more sophisticated investors averaged around 10%, making better use of insights into R&D spending, operating profits and share repurchases.
Human experience shouldn’t be undervalued. As of yet, no computer is capable of scrutinising qualitative factors like leadership or culture, let alone contextualising it within a complex (and often irrational) world.
Big picture recognition
Nevertheless, the rapid advance of AI has triggered calls for greater government oversight of capital markets. In a report published in October 2024, the International Monetary Fund warned that even the most advanced AI models struggled with unstructured geopolitical events such as Covid-19, and may have exacerbated market volatility.
How jurisdictions respond will determine where AI will take root. In Hong Kong, where the regulator encourages companies to integrate AI into credit assessment, fraud detection, and compliance monitoring, 70% of business leaders use the technology for risk modelling, compared to 54% in the UK and US1 where regulation is less hands-on.
Consider making AI an integral part of a holistic IT strategy that helps meet your business objectives.
Andres Choussy, executive vice president of Trading and Asset Services at FIS
Understanding whether governments are likely to encourage AI adoption or curb the technology’s use should push companies to adopt a long-term technology view. “Consider making AI an integral part of a holistic IT strategy that helps meet your business objectives,” says Mr Choussy. This is not only going to drive innovation but make money work harder.
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