The effects of technology on the way we work have been widely discussed in recent years, particularly as advances in smart technology become apparent in our daily lives.
AI is already playing a role in the finance sector, from fraud detection, to algorithmic trading, to customer service, and many within the industry believe this role will develop rapidly within the next few years.
Hedge fund managers were among the earliest adopters of machine learning several decades ago, recognising the advantages of using technology to analyse market data, both in terms of speed and volume.
Professor Stephen Roberts is Director of the Oxford-Man Institute of Quantitative Finance and Professor of Machine Learning in the University of Oxford’s Department of Engineering Science, and an expert on the application of machine learning approaches to data analysis in finance.
‘Most of the techniques that form the backbone of modern AI and machine learning, that really have impact in industry and commerce, have their roots in algorithms that were known about 20 years ago,’ says Professor Roberts. ‘What has changed dramatically in the last two decades is computing power and data volume.
‘Traders today have access to a reservoir of data that is beyond human ability to analyse without computers – everything from real-time shipping data and weather reports to global commodity demand and regional news updates.’
Traders use algorithms to distil insight from this data, which, combined with their own understanding of financial markets, can help them make better decisions, hedge risk and make the right calls in terms of the assets that they are trading.
‘Algorithms are extremely good at teasing out the patterns and correlations in these very large, unstructured, disparate datasets, then proposing potential trade options to people who can implement them live into the markets,” adds Professor Roberts. ‘This is a discovery that I think we’ve only seen the tip of the iceberg of.’
Despite the superior analytical power of AI systems, Professor Roberts doesn’t see humans being completely replaced any time soon – but he does see the way we work continuing to be reshaped by technology.
‘AI is augmenting human capability, acting as an extra conduit of knowledge and helping professionals make the right decisions in a quicker time, and this aspect of AI is a big area of development at the moment.
‘It is also opening up new products and trade opportunities. Finance houses are extending their remit of data acquisition to include the weird, wild and wonderful information, not just price series that would have been the mainstay of finance a few decades ago. This could include possible links between social media sentiment in a country and the output of products from that country.”
Nir Vulkan is Associate Professor of Business Economics at Oxford University’s Saïd Business School, as well as the creator and director of the Oxford Online Programme on Algorithmic Trading and the FinTech programme. He also sees AI as increasingly augmenting the skills of traders rather than replacing them.
‘Algorithmic trading is a powerful tool for traders with experience and good knowledge of their sector, but it can be more risky if used by less experienced traders,’ he says.
‘A major advantage is that algorithmic trading removes the emotion from trades, helping to guide traders who may be nervous or excited. A computer only looks at data, and most successful trades are based on solid market data.
‘Over their careers most traders develop a set of rules that guide them. AI is a natural development of this method, which is why most traders are happy to use AI tools.’
Like Professor Roberts, he has also seen the application of AI opening up new opportunities across the financial sector.
‘The financial sector is going through a “syntax revolution” at the current time,’ says Professor Vulkan. ‘Pressure on regulators from the government to work with startups rather than against them has led to an explosion in their numbers. New companies such as Funding Circle, Monzo and TransferWise are offering new ways of funding that weren’t available previously.
‘All of these companies are based on algorithmics, enabling them to use technology to remove barriers to funding through the same application of AI to lending as traders have been using for investments for years. London is leading the way in this sector.’
Following this trend, Professor Vulkan notes that banks are also starting to use this technology in the services they provide to customers. Banks have been buying up the most successful of these smaller companies to incorporate their technologies into their own service offering. For example, HSBC has introduced an app that nudges customers if they have spent more or less than usual based on previous spending habits, to alert them to any problems early.
‘This is a particularly exciting area of growth because this sector has needed more funding for a long time,’ he adds. ‘Banks have not been innovative enough or lent enough for some time now.’
This technology helps banks to reduce their exposure to risk while also making funding available to people and businesses that were excluded from lending before. AI is making the lending market both more effective and inclusive, encouraging new businesses to grow. It has become apparent that lending to risky ventures works, which is good news for entrepreneurial students.
‘Britain is ahead of the curve in this sector,’ says Professor Vulkan, ‘and it’s rewarding to see the role that Oxford spinout companies have played in making that happen.’