The World Economic Forum has just published its latest research study titled ‘The New Physics of Financial Services - How Artificial Intelligence is Transforming the Financial Ecosystem’, based the culmination of one year’s worth of research, including more than 200 interviews with subject matter experts (including the Deutsche Bank team) and seven global workshops, in collaboration with Deloitte.

“Artificial intelligence is fundamentally changing the physics of financial services. It is weakening the bonds that have held together the component parts of incumbent financial institutions, opening the door to entirely new operating models and ushering in a new set of competitive dynamics that will reward institutions focused on the scale and sophistication of data much more than the scale or complexity of capital,” notes the report.

flow: Clearly your report is very in-depth and far reaching across various sectors of financial services, where do you see it impacting banks and their corporate clients?

JMcW: “We’ve talked with a number of banks who are using AI in interesting ways to change the way that they work. Traditionally they have tried to process transactions for clients faster and cheaper, but there’s a sense in which that has become a ‘race to the bottom’ as back office excellence becomes more and more commoditised, and prices become more comparable. This is where AI can potentially allow banks new ways to distinguish themselves and provide more valuable services to their clients, such as predictive analytics, to help corporate clients with their business challenges.

flow: What do people really think artificial intelligence is?

JMcW: I don’t think they specify a particular approach or technology, but AI to them means a set of capabilities that allows them to run their business in a new way. This is usually a suite of technologies, enabled by adaptive predictive power and exhibiting some degree of autonomous learning, that have made dramatic advances in our ability to use machines to automate and enhance decision-making, pattern detection, prediction, modelling and interaction.

flow: Can you share some examples you came across in the study where large corporates are already using AI?

JMcW: Yes, we noted that some banks are increasing capital efficiency for their clients through better risk modelling and real-time risk monitoring, for example:

• Swiss Re is using IBM Watson to analyse the impact of broad market trends on its portfolio and better price risk
• Concirrus Quest Marine provides live marine weather, fleet and port data to insurers (e.g. warning when a vessel enters an exclusion zone)
• OmniScience enables faster model runs for insurers – reducing the cost of risk management and improving overall risk metrics
  

flow: You talk in the report about how AI in financial services will change the financial ecosystem, but what are the game-changers

JMcW: Future customer experiences will be centred on AI, and I think we will see more of the self-service currently underpinning personal banking featuring in transaction banking services. And once every financial institution is vying for diversity of data, managing partnerships with competitors and potential competitors will be critical – and will need careful handling.

flow: There are implications for pricing, speed of service and access as well, aren’t there?

JMcW: Yes, the trend is a move towards price discovery, so that everyone can see what a transaction service costs. This places pressure on margins and there is a danger of a “winner takes all” environment for an institution able to provide the lowest price – in other words a race to the bottom. The norm will be instant and real-time fast services and as the move to digital distribution accelerates, extensive branch and broker networks look set to make way for digital connections (e.g. via apps) to become the norm.

flow: What can financial institutions do about this?

JMcW: AI frees financial institutions from the need to make trade-offs between better service and cost, and provides a new playing field where competition will be on how well offerings are customised, and how collective development of data from multidimensional platforms that include their customers and third parties allow them to differentiate and deepen client relationships.

flow: A lot to think about. Any final thoughts to share on important next steps around this topic for the industry?

JMcW: We could see from the findings how collaborative solutions built on shared datasets could radically increase the accuracy, timeliness, and performance of non-competitive functions. We believe it is important to further investigate these solutions and get on with creating mutual efficiencies in operations and improvements to the safety of the financial system.”

To download the full report, visit the WEF website here.