With artificial intelligence being deployed at scale in many financial services firms, scrutiny has increased on the measurable impacts of the technology.
According to a recent survey by Nvidia, nearly 70% of financial leaders said that AI had driven a revenue increase of 5% or more for their organizations, and there was a marked year-over-year increase in the number of respondents who said their firm realized a 10% to 20% revenue boost.
In addition to the revenue gains, more than half of the respondents said AI has played a significant role in reducing annual costs by 5% or more. Nearly all of the leaders said they will increase their spending on AI infrastructure this year.
Efficiency Gains
In terms of return on investment, the respondents cited trading and portfolio management as the top use case for generative AI. The ability of artificial intelligence to aggregate investment data and apply the insights to portfolio management is one of the main reasons AI has disrupted the wealth management industry.
The industry has seen a surge in “robo-advisors” that can perform automated trades on their users’ behalf. Wealth managers have also used AI to help them manage customer calls, such as in the Morgan Stanley Debrief program.
“Debrief exemplifies the AI transformation,” Gregory O’Gara, Lead Digital Wealth Analyst at Javelin Strategy & Research, told PaymentsJournal. “The program is expected to save advisors approximately 30 minutes per meeting across one million annual client calls—a significant aggregate efficiency gain that allows advisors to focus on higher-value activities.”
Agentic Adoption
The efficiency improvements derived from introducing AI into the customer experience will likely drive more firms to adopt the technology. According to the Nvidia report, the use of generative AI in the customer experience, particularly through chatbots and virtual assistants, has more than doubled, up from 25% in 2023 to 60% last year.
Nvidia predicted accelerating adoption of agentic AI, which are systems that can analyze vast amounts of data from various sources and autonomously solve complex problems. The artificial intelligence firm suggested that banks and asset managers could use agentic AI systems to enhance their risk management protocols, automate compliance processes, optimize investment strategies, and personalize customer service.
