Earlier this year, it was reported that an artificial intelligence (AI) robot called Libratus won $1.5m worth of chips from four of the world’s top poker players in a three-week challenge. Whilst this might be seen as a crushing defeat for mankind, it is a huge leap for AI. Machine learning isn’t a brand new concept and when we look specifically at the financial services (FS) sector, its noticeable that it has always been one of the lead drivers of new technology trends with data analytics, mobile banking and new payment methods. However, with the next wave of technology disruption set to come from AI, how can banks and FS providers ensure they exploit the benefits?

Understanding the landscape

Despite the FS market being generally seen as leaders when implementing new technology, some are still struggling with legacy tech such as cloud platforms and applications. However, for some, large-scale analytics platforms on trading floors and mobile payments for consumers are starting to become the norm. In fact, even though AI is being pegged as the big trend this year, smart machines and connected devices have been used by FS organisations for around a decade. The difference now is that the use of AI has been brought to the forefront of technological innovation through the rise of the internet of things and mobile. However, innovation is also being seen with breakthroughs in new hardware infrastructure, which helps to influence and drive improvements in AI technology.

Many technology giants are starting to develop serious AI systems but it will be interesting to see how the FS sector will integrate these into their existing technology architecture. In some cases, larger institutions will struggle and will need to take up a ‘start-up’ mentality. Smaller, more agile financial service providers naturally have a digital first approach. Without older legacy tech, these start-ups have the freedom to implement and trial new AI systems much easier than an established bank.

This however, does not mean it is not possible for larger companies. It simply requires a different approach; to understand how to build AI technology into the platforms already established. An example of how larger firms can be prepared is to set up a venture team or internal ‘incubator’ that is dedicated to bringing ‘start-up’ thinking to corporate organisations. Whilst the technology is being developed, businesses should look ahead and set up new partnerships with designers, developers and coders to help them implement their ideas using new AI platforms.

The benefits of intelligent banking

Banks and financial service providers have undergone sweeping change over the last decade with numerous challenges around regulation, customer experience, start-ups and market volatility. The result of the Brexit vote last June, has also resulted in a lot of uncertainty for FS organisations, particularly from a regulatory standpoint.

The financial services industry is a complicated one but AI can help businesses with executing the more basic processes. Any task considered as ‘high-volume, low value-added’ can be standardised and performed by software applications, which can be scaled up and down as needed. In accounting for example, it could be used for fixed-asset accounting or recording journal entries. Elsewhere AI could be used to audit expense reports and process vendor payments. This enables certain operations to be streamlined resulting in cost savings in the long run.

Advances in data capture through the internet of things can also help businesses with their product profiling. Larger volumes of data and information allows financial services firms to create more accurate models to generate a better fit for different FS products. Having more personalised products and solutions for the customer will enhance their experience but also give financial firms the tools to perform at a higher standard. In insurance companies for example, the data collected from connected devices can facilitate a better understanding of a customer’s risk profile, allowing them to price more accurately and provide a more personalised offering for the customer. AI can also support financial risk management by helping to identify and explain changes in risk exposure.

In a new world of technology, the next generation has found multiple ways of interacting with their environment. FS products and the way we do banking is changing. But it’s not just being driven by the FS sector. Utility companies, such as GE, are starting to develop their equipment to interact with the internet in a more direct way. This has a knock-on effect on FS institutions in terms of how they measure and analyse these different markets.

Supporting regulation challenges

Machine learning is not only good for winning chips at poker. Perhaps the biggest impact will come from how AI can significantly change the way in which financial institutions approach their regulation and compliance challenges. Since Trump was sworn in as President of the United States, he has signed an executive order for the 2010 Dodd-Frank financial regulations to be reviewed, which means the UK could come under pressure to loosen its financial services regulations. Whilst this might seem a positive step as many banks saw its share prices soar following the announcement, it creates another level of uncertainty for businesses.

Whilst many of these regulatory technologies are still in their infancy, the potential is there for banks to utilise AI software to meet regulations more effectively. A regulation is a legal document explaining what was done, by whom, when and how. Sounds simple but it’s all in the detail.

Machine intelligence can interpret these regulations, code necessary rules and automate risk reporting to ensure banks remain compliant. Often, the issues companies face is scale and understanding what legal requirements they need to meet everywhere they do business. Failure to comply can result in fines and sometimes personal legal sanctions. However, AI technology can treat regulatory information like data and therefore can process documents on a large scale. What was once a static process, now becomes dynamic with the technology being able to map various regulatory requirements across the business in different countries.

It’s an exciting time for banks and FS organisations with new AI and internet of things technology opportunities. Whether its supporting customer experience or automating regulatory compliance, FS organisations need to embrace developments in the AI space and plan for how they can support and improve their business in the future.