A first wave of mass GenAI adoption has hit tech and math-based jobs - not necessarily in the finance sector. A Fed vice-chairman charts two paths showing how that could change. 

There is a vague sense of dread coursing through the veins of the email and spreadsheet set worldwide because of now more than two-year-old GenAI frenzy Big Tech has set upon the world. 

In the wealth management industry, you can find the most anxiety-ridden workers in the operations areas as project and change managers, or in risk, compliance, and certain specific staff functions. They are important but not front-line in the way that relationship managers, investment consultants, and market traders are.

Treading a Fine Line

Previous waves of tech-based productivity improvements in the 80s and 90s appeared to hit blue-collar workers hard, but this one seems to be coming directly for the white-collar population, in particular the ones that tread the often amorphous line between the deep technocrat and executive.

However, recent studies suggest that banks aren’t being affected by the goings on as much as conventional wisdom might suggest, as a recent Visual Capitalist infographic shows.

Treasury and Markets

The image is based on an Anthropic analysis of chat assistant Claude, a generate tool that focuses on safety and accuracy and it shows that computer and mathematical professions dominate, taking up 37.2 percent of AI-related conversations despite those jobs accounting for only 3.4 percent of the workforce.

Extrapolating that to the wealth management industry would suggest that it is only affecting the IT departments, and highly specialized functions such as treasury specialists, and market risk.

Still an Assistant

The other early adopters are in office and administrative support, education, and the arts, sports, and media, but they are all at or near the 10 percent adoption rate, or not all that significant yet. Their impact on banking, therefore, is likely to be negligible.

Moreover, 57 percent of the conversations involving Claude show that it was used to help or assist human work while 43 percent involved automation that required minimal intervention by hand. Again, that mostly seems to involve the internal bank technocrat.

The Fed Take

In other words, the white-collar banker can rest easy for now, although that can still change, as a recent speech by Federal Reserve Vice Chair for Supervision Michael Barr indicates.

In it, he charted two hypothetical paths. The first was incremental progress bringing about widespread productivity gains. The second – transformative change.

Local Knowledge

In the former, a small, local bank would leverage GenAI-powered chatbots to provide customized financial advice «rooted in local knowledge» while financial institutions, big and small, would use it for compliance monitoring, fraud detection, risk management, and document analysis.

«The impact will depend on the industry and the nature of the job. GenAI experiments suggest the technology holds the promise of leveling up skills and bringing productivity of lower-performing workers into line with higher-performing workers,» Barr maintained.

Vulnerabilities and Strengths

When it comes to financial stability and other related risks, the incremental scenario could end up amplifying both vulnerabilities and strong points of the system that is currently in place.

«Attractive trades become more crowded, but risk managers gain new insights. Malicious actors gain new tools, but cyber defenders become better armed. So long as financial regulators, enterprise risk managers, and others charged with managing downside risks prioritize efforts to keep pace with the evolving financial ecosystem, there’s nothing to suggest a wholesale transformation of the balance of risks,» he stated. 

Scientist Directing Research 

In the second, more dramatic scenario, the new tech could upend the world as we see it now, becoming one in which the GenAI is no longer a tool for scientists to analyze data but instead, one where «in a sense, it becomes the scientist, directing the research».

That would make, according to him, finance look radically different than it currently does.

Frictionless Intermediation

«Individuals with access to hyper-personalized financial planning and businesses with innovative products and services seamlessly connect with one another through near-frictionless or novel forms of financial intermediation. Trading strategies and risk-management practices are boosted by greater GenAI-based analytic tools that have dynamic real-time access to an enormous knowledge base in both the public and private domains,» Barr said.

That is in all likelihood a bigger scare as it would not only make most wealth management functions redundant, from the front-line to the back office, but it would question the basics of the wider financial industry itself.

New Set of Institutions

Barr himself hints at that saying that the system itself could need a new set of institutions, markets, and products that facilitate transactions between individual clients, businesses, and GenAI agents.

But is the industry helpless should the second scenario become a reality? He doesn’t think so.

Recognize Limitations

Barr argued that each institution including wealth managers and private banks needs to recognize the limitations of the tech, and see where and when GenAI belongs in their processes, «and identify how humans can be best positioned to be in the loop».

They will also have to focus on data quality to make sure that the tools do not amplify or perpetuate biases inherent in any data that are used to train systems – or make faulty inferences.

Not So Laid Back

«Nonbanks may be more nimble and risk-forward in incorporating GenAI into their operations, which may push intermediation to less-regulated, less transparent corners of the financial sector. In addition, this competitive pressure may push all institutions, including regulated institutions, to take a more aggressive approach to GenAI adoption,» Barr said in conclusion.

But in that scenario, it if comes true, it seems unlikely that bankers and financial institutions will be able to stay as laid back about AI as they are now.