Although Artificial Intelligence (AI) was originally introduced in the 1950s, it has achieved new prominence recently as computational power has increased and the amount of and access to data has exploded. Everything from business operations, customer service, and marketing to risk management and compliance are starting to benefit from the applications of AI. As pressure mounts due to factors like rising regulatory requirements, competition from new market entrants, heightened expectations from consumers, increasingly sophisticated digital threats, the financial services industry is expanding its use of AI technologies.
AI is technology aimed at doing things normally done by people (specifically, people acting intelligently). It is a large ecosystem with many categories. Traditional financial services firms are in the early stages of adopting AI technologies that can positively transform traditional processes for the better. For those firms not adopting AI, challenges such as fear of failure, siloed data sets, and regulatory compliance would turn out to be a major hurdle.
AI has been creeping into financial services under a variety of names, assisted in no small part by related technologies such as digitalization, interactive voice response and image recognition and data mining for personal identity validation. On the consumer side, AI is enabling people to make better financial decisions with augmented recommendations. Financial service apps like mTrackr let users track their spending and increase their savings with automated, personalized recommendations by tracking spending patterns, offering advice and finding the best financial product through their smartphone app. According to research firm Gartner, nearly $2 billion in online sales will be performed exclusively by mobile digital assistants by the end of 2016.
It is the early days of AI in the financial services industry but the technology is increasingly going to be more important to organizations to innovate and remain competitive. AI can improve communications with staff and customers, analyze data in multiple disparate locations to find patterns or connections that a human couldn’t find and answer questions about investments in real-time via natural language. If you haven’t already, it is time to start learning about AI technologies and strategizing for the future—better late than never.