How AI is Transforming Traditional Banking

The Fourth Industrial Revolution is well underway and is reshaping the world as we know it. Artificial intelligence and machine learning are busy disrupting global industries – and banking is no exception.

A recent 166-page report by the World Economic Forum with Deloitte, called The New Physics of Financial Services – How artificial intelligence is transforming the financial ecosystem, highlights some of the major disruptions that financial institutions, big and small, are now facing in this new era of intelligent technology.

At the same time, the report underlines just how many of these issues are still up for debate. Some institutions will thrive, according to the WEF – and some may not survive. Which will win out depends on a range of factors, including a company’s willingness and ability to adapt to new ways of working.

Nine new disruptions to the financial system

WEF researchers identified nine significant ways in which AI is transforming the financial sector right now; the impact these changes could have in future; and the unique opportunities they present.

AI creates new profit centers

Once upon a time, back office functions were a necessary but financially draining section of any successful financial institution, required to run everyday operations. In this new age of AI, the companies which can afford to invest first and hard in these new technologies will be able to harness these functions for profit, by turning them into services that less prepared companies pay to use instead.

Data pushes personalization to the forefront

Big Data allows for personalization of services like never before. This could create a new battleground for customer loyalty, as banks eschew the “race to the bottom” in competitive pricing and find new ways to  on finding a service that can offer highly targeted solutions.

AI intermediates raises transparency

WEF predicts the rise of AI-driven intermediates which could locate and recommend products and services tailored to each specific customer, regardless of provider. This would allow customers to easily evaluate providers to find the best solutions using automated, personalized algorithms.

Increased need for security brings collaborations

With more data recorded and made available, and with commercial and third party actors involved, the need for robust fraud prevention measures increases. Co-operation between those inside the financial sector and outside becomes necessary to ensure customer data is protected every step of the way.

AI can help support such protection, by producing anti-money laundering reports and know your customer (KYC) reports which, according to the International Banker, could cut compliance costs by up to 30 percent, saving billions across the sector.

Early AI adoption transforms market structure

Timing is everything at this stage of the game. The institutions that can most quickly adopt AI into their business models are the ones most likely to succeed in the long term, in part because of the rapid pace of change – once a company falls behind, it can be extremely difficult and expensive to catch up. This dynamic favors the biggest institutions the most, alongside small institutions that serve a well-developed niche. Mid-range institutions may suffer the most and find it hardest to prosper in the race towards an AI-driven banking sector. They may be forced to close if they cannot adapt.

Rob Galaski, co-author of the report and Global Leader in Banking and Capital Markets at Deloitte, states, “Markets are already emerging where data sharing is critical to competitive success and first movers are positioned to distinguish themselves by delivering better advice, constant presence, and curated ecosystems. Firms that lag behind are finding that their old strengths may not keep them as competitive as they once were.”

Big data brings new alliances

The modern reliance on data to attract and retain customers will push banks and credit unions into new partnerships that impose new risks. New questions will arise, such as who controls the customer experience? How will smaller firms gain the same insights as big ones?

New developments require new regulations

Data regulation is a fairly new area of law which will have an increasingly significant impact on how data-driven markets such as banking develop. Banks need access to customer information, while at the same time consumers are demanding more control over their data. Furthermore, as a global system, the question of how cross-border data flow is regulated and protected is a huge issue that governments and banks must address sooner rather than later.

New ways of working need new kinds of talents

AI is rapidly changing the ways in which companies work, and this presents one of the major challenges the banking industry faces. How can institutions ensure they have the right talent in place, and how can they nurture that talent and ensure the right culture at work to keep up with a fast paced digitization of the marketplace?

How must financial institutions respond?

Beyond all this speculation, one thing is certain – change is coming, and should be embraced. Institutions cannot rely on the ways of the past, because while previous successes provide a foundation, their business models and culture must be updated for new ways of working. Indeed, an Accenture survey of North American banks in 2018 found that 22 percent of banks surveyed were already using AI and machine learning, and 55 percent planned to do so in the next year.

Research into ways of working found that the companies which embrace new technologies such as intelligent automation could see their revenue rise by 32% over the next five years – alongside a rise in employment of nine percent. This suggests that while technology is undoubtedly disruptive, human workers can adapt to using AI to improve customer relations. AI could even create new long term jobs, for which human qualities such as empathy and judgment are vital and cannot be replaced by technology.

Andrew Woolf, Accenture’s global Talent & Organization lead for financial services, believes that the main challenge for banks is to “pivot their workforce to enter an entirely new world where human ingenuity meets intelligent technology to unlock new forms of growth.”

Conclusion

To prepare banks as they enter this new era of disruptive innovation, it is vital that they understand first of all the sheer scale of change currently underway in this new Industrial Revolution.

As AI weakens the bonds between traditional actors in the banking industry, it opens up huge possibilities for new operating models as it introduces a brand new set of competitive dynamics. These new competitive forces reward companies based on the scale and sophistication of the data they have access to, and their analysis, rather than the old world’s reliance on capital.

In this new world, it may be that some players will lose the game, while others thrive. In order to survive, large banks should strive to channel resources into innovation while smaller institutions may find their best tactic for survival is to come out on top in a specific corner of the market, establishing for themselves a niche in which to serve a sector of the market alone.