“32% of the financial sector jobs in the UK are at high risk of automation.”
With the rise of AI coverage in the media, such headlines are becoming more commonplace. While they hold a degree of truth, there are quite a few nuances to think about when considering the impact that AI will have on the financial services industry. This article will take a deeper look at those nuances to elicit a better understanding of the pace and place of disruption as it unfolds over the next few years.
The adoption of AI in different fields is driven primarily by the tremendous efficiency gains that are made possible via automation and possible cost savings that are realized as labor is replaced. Given the massive promise that this technology has to offer, finance has also tapped into deep learning techniques to gain an edge in a highly-regulated, fiercely competitive landscape. For example a survey in 2015 found that false declines, legitimate transactions that are wrongly rejected, cost retailers $118 billion; automated and more efficient fraud detection can help to mitigate these losses. [1a] Automation also allows reduction in costs to meet compliance and regulatory requirements which are currently estimated to cost the industry $270 billion a year.