Could Artificial Intelligence Mean The End Of Traditional Banking?
Financial organisations are seeing the realities of AI
The financial world is no stranger to AI and automation. In 2016, it was estimated that 75 per cent of global trade was handled by algorithms. Major companies like Two Sigma, Goldman Sachs and Man Group PLC already use machine learning techniques as a strategic aid and research tool, and smaller businesses are beginning to do the same. The application of AI to financial decisions is yet another indicator that the days of traditional finance are numbered. But how has the technology affected the sector, and what can organisations do to keep up?
AI: a banker’s best friend?
Finance is more or less synonymous with data. Financial companies use data to predict sales, forecast earnings, analyse documents, manage social media, and make strategic decisions. Dealing with this data is notoriously tricky, especially when there’s so much of it. AI, though, is designed to analyse vast quantities of information which can then inform action. One area where AI has found a strong foothold is in hedge fund investments. Hedge funds pool capital from individual investors and investment funds. The hedge fund then has to decide on what to fund, and how much. Unlike other alternatives, a hedge fund can essentially invest in anything. With so many potential options and capital at stake, choosing which assets to invest in is far from simple. Apply AI to the equation, however, and it’s possible to gather insights about the entire financial climate. Handling the capital of multiple parties – and deciding where best to invest it – is suddenly a lot easier with concise data to hand. Quant funds, which select investment options using quantitative analysis (often involving AI), have also become more popular. Since 2010, investment in quant funds has increased by 86 per cent.
AI and the future of finance
AI is helping incumbent institutions to think differently about financial management and investment, which is a positive thing in many respects. But despite the continual growth of the FinTech community, big companies still rely on their legacies. Of course, it would be unfair to suggest that this is their only reason for survival. Established companies have had to adapt, and so far they have done so successfully. As much as AI might seem to be a banker’s best friend, it also presents a challenge to existing business models. As with all new trends, businesses need to form a response that enables the transformation of these strategies. This could involve joining the open innovation movement that aims to share expertise rather than jealously guard knowledge. In theory, this collaborative approach could accelerate development and consequently adoption. As a result, the technology could be offered to a wider user base.
From a business perspective, better information equals better knowledge, and therefore better decisions. Even so, there are reasons not to be so optimistic. A survey conducted by consultancy firm Opimas, for example, suggests that the adoption of AI in finance could mean the loss of 90,000 jobs. As well as employment losses, AI could widen the gap between companies that use the technology and those that don’t. Not all financial businesses will be able to keep up, which could lead to the creation of a financial sector dominated by a handful of firms. Ironically, this could work against diversity. Regardless of the nature of the disruption caused, an increase in the application of AI will necessitate regulatory change – and how long that will take is anyone’s guess.
Artificial Intelligence has certainly made its mark in finance, but in order to successfully dominate the sector, AI powered funds have to prove that they can outperform alternative options. Whether AI is a banker’s best friend or worst enemy depends on how they respond to it – and this doesn’t always mean blind adoption. For now, the attitude seems to be shifting to one of collaboration. Initially, this is advantageous. . . but how long will it be before AI simply doesn’t need us anymore? Considering that Google’s AutoML system can now create its own super accurate child AIs, this might be sooner than we think.
Could AI force financial companies to scrap outdated infrastructures? Will the adoption of AI encourage or stifle diversity? Do incumbents still rely on their legacies? Share your thoughts and opinions.