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Helen Lu says AI can reduce service costs and increase demand for financial services

Banking / opinion
Helen Lu says AI can reduce service costs and increase demand for financial services

By Helen Lu*

Large Language Models (LLMs) like ChatGPT are shaking up the world of finance.

Morgan Stanley is testing an OpenAI-powered chatbot to assist their financial advisors. The bot, trained on the bank’s own research reports, offers rapid access to their extensive proprietary knowledge base.

Private equity firms and insurers were also early adopters, using these innovations for pre-screening investments and automating claims. As LLMs steadily diffuse throughout the finance industry, we need to thoughtfully embrace and adapt to this game-changing shift.

Substitutes or complements?

Against this backdrop, it’s natural to wonder if finance professionals could become obsolete. However, this apprehension arises from a simplistic view of AI as a substitute for humans. Large language models should not be seen as a replacement for skilled professionals, but rather as a powerful tool that can enhance their abilities.

By complementing human expertise with AI-driven insights, tools like ChatGPT can help financial professionals make better decisions, automate mundane tasks, and stay ahead of the curve in an increasingly competitive market.

Both a productivity booster and an equaliser

Contrary to the common association of innovation with inequality, early evidence suggests that adopting LLM-enabled technologies has levelled the playing field at work.

In call centres of large software companies, chatbots improved the productivity and quality of underperforming workers more than that of "superstars."[1] 

In a separate study, researchers conducted experiments and found that ChatGPT substantially improved the productivity of university-educated professionals in writing tasks, particularly benefiting the slower writers.[2]

Lower cost, higher demand?

With this boost in productivity comes the potential to reduce the cost of providing services. This increased efficiency allows financial professionals to focus on high-value activities, such as client relationship management and strategic decision-making.

Moreover, as technological innovations like LLMs make financial services more affordable and accessible, the demand for these services could grow due to their newfound affordability and accessibility, ultimately leading to an increased need for financial professionals.

Revolutionise knowledge sharing and flatten the organisational structure

The rise of interactive LLMs democratises access to knowledge. These AI models allow people of all computer literacy levels to tap into vast repositories of information. Moreover, by using this technology to mine emails, recorded discussions, and other resources, we can facilitate seamless sharing of organisational “know-how”. This can reduce the need for specialisation and prompt a re-evaluation of traditional organisational structures.

Instead of viewing such AI as substitutes for human workers, we must recognise their potential to reduce service costs and increase demand for financial services. By making professional advice more accessible, we could create a world where many more financial professionals are needed.

How should professionals prepare?

To prepare for the impact of large language models, finance professionals (and professionals in other industries) should focus on cultivating organisational AI literacy. Here are some steps to consider:

1. Encourage entry-level professionals to use models like ChatGPT, providing training to help them understand the technology's strengths and limitations.

2. Develop a strategy to turn institutional “know-how” and culture into easily accessible information with the assistance of LLMs.

3. Anticipate initial impacts on work efficiency and quality, addressing any discontent among "superstars" who might not benefit as much from the technology.

4. Rethink team organisation, taking advantage of decreased specialisation requirements to create more versatile and adaptive structures.

5. Alleviate apprehension about AI by highlighting its potential to improve overall productivity and job satisfaction.

Ultimately, the integration of LLMs into the finance sector has the potential to revolutionise the way that professionals access and share knowledge. By embracing AI and adapting to its implications, finance professionals can secure their place in a rapidly evolving industry.

[1] Augmented Intelligence: Effects of AI on Productivity and Work Practices (2022), working paper, E. Brynjolfsson and L. Raymond

[2] Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Available at SSRN 4375283.

*Helen Lu is a Senior Lecturer in accounting and finance at the University of Auckland Business School. Dr Lu’s research Relative Valuation with Machine Learning is featured in the March 2023 Journal of Accounting Research.

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