By Madhvi Mavadiya,
The leading web resource for financial technology
Bobsguide 1 february 2016
“Artificial intelligence is not a technology solution, it is a business solution.”
Following the recent breakthrough of artificial intelligence (AI), many have been wondering how this form of technology can be implemented in the financial services. As newer products emerge, it questions how popular the traditional legacy financial institutions will remain or perhaps, fintech startups will gain an increased number of customers, in a similar way to how Uber affected the taxi industry. bobsguide spoke to Josh Sutton, global head of artificial intelligence practice at technology company Sapient about how AI is set to transform business and finance, alongside how banks are already implementing a technology that has been around for 30+ years, but its true potential hasn’t been seen until now.
According to CNBC, nearly $700 million has been invested in artificial intelligence over the past two years and Sutton explored how it is important to work with the C-suite of a company to give them a roadmap of the capabilities AI has as it provides a way to increase revenue, reduce cost and minimise risk. “Increased investment in AI has been over 30 years coming and technology has caught up to the conceptual promise of what could be done. If you look at all the products deployed by machine learning today, these are not new concepts by any means, but the processing power of the machines has finally reached a point where it is cost effective and time effective enough to generate real results from that information,” Sutton highlighted.
Sutton continued to explain how AI has been extensively used by government and academic institutions, but banks have started to use it in order to monitor their risk related to illegal insider trading activities. A large global bank has already implemented AI instead of using the historical approach of having a team review trade information and police it in a human manner, Sutton revealed. “The platform that they built combined big data, machine learning and causal intelligence and that aggregates all the trade data and communication data from various traders and people they interact with across the various divisions.”
Alongside this, artificial intelligence will benefit different parts of an organisation in different ways. Sutton said that leveraging AI would “systematically accelerate certain portions of the core middle and back offices to automate everything from trade processing through to KYC and AML.” This ties into the long standing debate that has been occurring over the past year about whether human workers will be needed if technology becomes increasingly sophisticated. The stage that we are at the moment is that there needs to be a mixture of tasks completed by people and the rest by machine learning, but Sutton explored how the number of people required to fulfil the function of the middle and back office will eliminate the need for people.
“I think there will always be a need for people to identify and review the high priority activities but I do think that a substantial amount of work that is done today that is relatively trainable can be replaced via technology over the coming decade,” Sutton said. On the other hand, the front office is an area where Sutton believed that human interaction is necessary as finance is an industry that is very relationship centric as people leverage financial advisors and wealth managers to provide customised advice. “I do believe that artificial intelligence will enable financial advisors to be much more effective in their interactions so, if you look at the job of a financial advisor, a significant portion of their time goes to understanding their individual customers, what is going on in their lives and what advice they can provide.”
“What you’ll see in the traditional wealth group, financial advisors will be able to take on a greater number of clients and the entire industry will expand as it becomes a cost effective tool that people can have that they haven’t traditionally. If you look at a good disruptive example, like Uber, the model has changed the way that the industry works and it has dramatically increased the amount of money that gets spent.” Sutton predicts that this “Uber Effect” will occur with artificial intelligence and the financial industry, especially in the retail banking industry where there will be a blur between retail banks and wealth managers.
“I think what you’re starting to see is a lot of fintech players trying to nibble around the edges of that,” Sutton highlighted as he went on to say that artificial intelligence will be ubiquitous in our day to day life, so much so that you are not even aware that you are using AI. However, to get to this point, there are many obstacles that must be overcome, one which concerns how the financial services industry are focusing on big data when it comes to implementing AI, rather than seeing it as a business tool.