Artificial intelligence has become a very real part of life. Also, the financial services industry is no stranger to the technology. As in other industries, the possibilities in financial services are many and varied, but most companies are just getting started with a process that is set to turn the industry on its head. Many banks and insurance companies are busy testing use cases such as chatbots and AI-based fraud detection solutions. But now it is time to launch the next phase: financial service firms need to develop a clear path forward on how to successfully integrate AI into their business model.

Artificial intelligence (AI) is on everyone's lips, but they're mostly talking about the technology side of things: What can AI do? What do we need in order to use it? Where can we apply it? Yet in the financial services sector, AI is a strategic asset that brings far more than the benefit of the technology itself. For banking and insurance companies, everything revolves around data: there are no physical products, with very few exceptions. The perfect setting in which to use AI, a suite of technologies whose advantages over other analytical techniques come to the fore especially when dealing with huge volumes of data.

That said, there is no standard AI solution for all of the industry's needs and problems. Different business strategies call for different AI strategies. Each company must therefore decide for itself how and to what extent it intends to use the new technologies. An essential decision to make for any player that does not want to risk being left behind by the sheer pace of the AI transformation in the financial services sector. Because without AI that's what will happen. The most basic approach of doing only the bare minimum so as not to miss the hype is not an option for a successful future. Artificial intelligence is much more than mere hype – it is going to change the face of the industry for good.

Three options for financial service providers

There are many ways of using AI in banking and insurance, ranging from analyzing various drivers to improving internal processes to creating products in the sphere of investment consulting, credit management or payment processing. But it's not enough to simply choose something from this palette. The possible AI applications must always be considered as part of a broader strategic objective.

• Used as an element of "Augmented human intelligence", AI technology can serve as a tool to enhance efficiency and performance. Players use data and smart algorithms to automate processes and support their employees, for example by suggesting the next best offer or creating real-time ratings. In this stage, AI is not used to radically change the business model or value chain. Decision making is still strictly limited to humans, albeit supported by recommendations made by the algorithms.
• The second option, "Machine knows best", goes one step further: While AI does not fundamentally change business processes, it does radically alter the way they are executed. Human intelligence is not merely augmented but completely replaced in certain processes and functions. This is achieved with algorithms that learn how to act in a wide range of use cases after being fed on large volumes of internal and external data. An automated call center is one such use case.
• "Data is king" is the third and most disruptive approach and it radically changes the banks and insurance companies that pursue it. Here, AI becomes part of the corporate DNA, and the entire strategic business model uses data and AI to create value. Players are able to offer solutions that are not possible without AI, such as a virtual assistant that advises the customer on financial decisions or even automatically takes such decisions on their behalf. This approach offers the best opportunity for innovative players to differentiate from the competition.

Transforming from a conventional to a completely AI-based financial service provider is not something that will happen overnight, that much is for sure. Some of the possibilities may seem unachievable for now, partly because of regulatory hurdles. But with big data, cloud computing and machine learning advancing at an unprecedented pace, financial services may be overhauled much more quickly than most players would like. So to remain competitive, they must act just as quickly and begin work on a decisive strategy to tackle the issue of AI.