How is Artificial Intelligence influencing financial markets?
Fintech is the new gold rush for investors, growing from 10% in 2016, to a staggering $23.2 billion, with China and USA leading the market. This boost is powered by the growing capabilities of machine learning and artificial intelligence. It is an idea whose time has come, as the computational and storing capabilities available today can record and process the impressive quantities of big data necessary to fuel the algorithms. AI has already proven its capabilities in retail, healthcare, and trading, and therefore, looks like a safe bet. The only question now is just how much ruling power will the algorithms get? Will they replace or just help managers and C-level decision makers?
Before answering this question, it is important to highlight the difference between automation and real artificial intelligence, although both terms are used interchangeably sometimes. Not all tasks performed by a computer or a system can be classified as AI. There is a hierarchy of computer uses in finance and banking. Automating repetitive tasks, AI that supports employees in their daily duties such as verifying compliance, underwriting or responding to clients and deep learning, which, at least in theory, can replace workers altogether.
Applications of AI in Banking, Finance and Risk Management
AI for banks and other financial institutions is expected to trigger similar outcomes to those recorded in e-commerce, which includes better customization of the experience, more efficiency, increased productivity and overall cost reduction. AI has already been used in fintech for high-frequency trading since the late 80s, but new applications are emerging. These include personalized financial advice, fraud detection mechanisms, investment decisions and blockchain.
The chaotic landscape of Wall Street can soon be replaced with the monotonous sound of computers while exponentially growing the volume of operations. Now, three decades after the introduction of the first computer able to handle stock market contracts, it is more about high intelligence than high-frequency. The work of quants – who are basically statisticians building trading algorithms – will be replaced at some point with the work of a neural network, constructing new trading patterns based on previous experience. Currently, the strife is to program predictive capabilities into these systems to make them ready for a change before it happens in the market.
AI is handy as a wise personal assistant. Financial institutions can require programmers to design learning algorithms that use the client’s data to track spending habits and make recommendations. Having your own personal robot-advisor is a service a lot of careless credit card users may value. Balancing your budget based on your behavior is a service that was unavailable at traditional banks, but could improve credit scores significantly.
Chatbots are also implemented by financial institutions to help customers navigate through products and feel they matter. For simple operations, most people wouldn’t be able to tell if they are talking to a real person following a script or a bot driven by AI.
