Automation at scale has, in recent history, been closely associated with the manufacturing industry and in particular the impact it has had on blue-collar jobs. Robots replaced humans on assembly lines, reducing production costs, increasing productivity and improving quality. Until recently, computers have replaced relatively few white-collar jobs. Some jobs, such as typists, no longer exist, and in banks and exchanges, machines have reduced the number of traders. However, so-called knowledge workers, which have for some time been identified as a bank’s primary asset, have largely been immune. This will soon change. Jobs that involve data analysis — for example, those in areas such as research and compliance — will soon become the domain of artificial intelligence. Intelligent machines will be to banks what robots were to the car manufacturers.
What is artificial intelligence?
Artificial intelligence (AI) is the next big transition in computing and is fundamentally going to revolutionize the way banks operate. The technique, however, is not recent. Over the past 60 years there have been numerous significant advances under the radar in AI. The recent surge in interest — which has finally brought AI into the spotlight — has been due to the dramatically decreasing cost of computing and the availability of exponentially increasing computing power. This, coupled with an explosion in stored data, has opened up the potential to automate tasks that have previously been considered the domain of humans.
Application areas for AI are widespread — for example, understanding natural language, speech recognition, computer vision and heuristic classification. AI has already been applied in a wide range of fields, including medical diagnosis, stock trading, robot control, law, remote sensing, scientific discovery and toys. The greatest advances have been in computer vision, where object recognition and tracking has already become commonplace and is powering advances such as self-driving cars.
The Boston Consulting Group (BCG Expand) has created a useful infographic that provides a taxonomy of artificial intelligence — mapping the field across perceiving, thinking, acting and interacting, with machine learning, natural language processing and computer vision among its branches.
Where should banks apply AI?
Relative to other industries, banks have been slow to harness AI. However, there are many functions today that are performed by humans — such as analyzing information and making decisions or recommendations on what action to take — that can easily be automated. Machines have the ability to absorb information from multiple sources and make decisions much faster than their human counterparts.
Functions such as research have always relied on human analysts to pore over company information and use experience and intuition to make recommendations. This is an obvious candidate for an intelligent machine and will allow investment research firms to cover many more companies and respond quickly to new information as it arrives.