Banks using generative artificial intelligence tools could boost their earnings by as much as US$340 billion annually through increased productivity, according to consultants hoping to help the industry adapt in this fast-moving area.
This would amount to a 9% to 15% increase in operating profits, according to a McKinsey Global Institute report published Tuesday. Corporate and retail banks have the most to gain, the authors claimed.
Generative AI was popularized last year when OpenAI’s ChatGPT tool launched, offering users sentences, summaries or even poetry based on simple prompts. The technology is trained on vast quantities of existing material that is used to generate its responses.
Tools like this could eventually take over repetitive tasks from most human workers, according to McKinsey’s research on 63 use cases across industries. While the initial efficiencies are set to be within companies — and the timeframe for adoption is unclear — the finance sector can expect the AI shift in the future “to be a lot more on the customer facing side,” McKinsey senior partner Gokhan Sari said in an interview.
Sales and marketing, software engineering, and call centre roles are among those most likely to be affected, said senior McKinsey partner Jared Moon. As many as 70% of business activities will have automated parts, which will leave only “a very small proportion” of jobs untouched, Moon added.
“They’re taking the productivity gains to implement code faster, write better content for clients, freeing up time to spend with customers,” he said. While he’s not yet seen companies using AI to “materially reduce the workforce,” over time “the jury is still out” on job losses.
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Wall Street has already dived into AI as a way to overhaul its working practices and potentially cut costs. Goldman Sachs Group Inc is using an AI-based tool to automate the labour-intensive elements of coding, the Wall Street Journal has reported. Citigroup Inc. has used generative AI to analyze more than 1,000 pages of new capital rules. Derivatives trading, fraud detection and even performance reviews are among banks’ other experiments.
So far, the speed of technological change since ChatGPT launched has left firms with the challenge of finding skills in emerging areas, such as prompt engineering and model tuning. According to Moon, companies are training their existing data science teams to specialize in generative AI.
“This creates a catalyst for more firms to invest in AI and there’s even more value in AI. So banks will need more AI talent,” Moon said.
