October 29, 2018
By Dr. Sven Ludwig, Managing Director, Global Head of Subject Matter Experts and Advisory, FIS
The promise of total digitalization in banking is fast becoming a reality thanks to artificial intelligence (AI) and machine learning solutions designed to better serve clients while accelerating growth. With more AI solutions unfolding, is the day coming that a full-service IT/AI bank requiring little to no human interaction could exist on a server? It could happen sooner than you think.
Digitalization of banking is comparable to the industrial age, but different.
Today’s transformation in banking is similar to the production of the Model T during the industrial revolution. Simplifying the production process made it possible for all parts of the automobile to be manufactured and assembled on sight at less expense – so much so that cars could become mainstream.
The key difference between the transformation taking place in banking and industrialization is that, in banking, we not only break up the value chain, we “decomponentise” the bank. The bank orchestrates the production line but the production belt does not remain within the bank. Instead, it leaves the bank where it runs through suppliers’ production plants and then returns to the bank for subsequent components. The process enables individual production stations to become highly efficient since they represent very small components. By using machine learning and AI each of the components within the bank and outside the bank can be digitalized and become infinitely scalable.
On the “orchestrating” production line, we transfer data only. Nothing else. We transform data, merge it, and assess it. Banks can specify a core business model on some components. These components can be offered across many banks making them infinitely scalable.
The bank can transform its business model and essentially become an IT company with a banking license. Total digitalization in banking could result in a full IT/AI bank – and it is not unrealistic to predict that a bank could exist on a server with no human oversight.
Machine learning already used successfully in banking.
Consider where machine learning and AI are already being used in banking ̶ documentation analysis, customer profiling for marketing purposes, virtual assistants, fraud detection, and managing customer data, for example. We can easily predict that AI technology will replace agents in call centers for standard issues.
But what about tasks requiring high-skill expertise? Already, some of these can be solved with machine learning and AI. For example, portfolio optimization requires a high degree of skill and expertise. Picking the right rebalancing strategy across multiple portfolios is crucial for the overall fund performance. In highly competitive markets, like passive index tracking funds, it is essential for outperforming competitors. Another example is the identification of potential sources of risks. True risks are often overlain by data issues. It is critical to identify risks caused simply by data issues but identifying them is a complex task. Terabytes of data must be put into context and the interaction of market data, valuations and aggregations must be identified or at least estimated. In both examples, machine learning can provide a much faster and more robust, complete and lean process with little use of valuable experts’ time – an often-unexpected bonus of machine learning.
The 2018 FIS Readiness Report indicates that machine learning and AI tools, combined with improved data management, will give organizations better understanding of their operational environment. Innovation in this area offers banks the opportunity to make improvements ranging from meeting regulatory compliance requirements to responding to market conditions faster and addressing changing client demands promptly. Two-thirds of the Readiness Leaders have moved applications to the cloud, and 64 percent are piloting AI solutions. Outsourcing has become commoditized.
The journey of transformation is not about to start. It has begun. Remember, a full transformation of the bank is possible. And today, there is no comparable traditional industry.
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