We live in interesting times. The whole world currently stands in awe as we witness the fourth industrial revolution. We see significant technological advances in data science, genetics and computer vision that rapidly up the pressure for change, regardless of the industry. Unlike previous industrial revolutions, this one is coming faster and its effects will likely be broader. We are not just seeing automation in manufacturing or service provision. We are seeing a transformation of both services and professions alike.
These advancements are particularly relevant for the Financial Services industry, which currently navigates through an era of fundamental change. We are already coping with a difficult market and interest rate environment. Digital interaction is becoming mainstream. Client behavior is changing rapidly. Traditional universal banking is unbundling with new sources of capital becoming available and eroding benefits of scale – therefore the pressure to innovate is continuous and no one-time event. Add to this the ever-growing and changing risk and regulatory requirements, and you get an idea of the multiple demands that banks have to meet.
While technology is a key driver for the transformation underway, the speed of development is even accelerating the need to adapt and reinvent banking as we know it today. Artificial Intelligence offers a powerful solution for keeping up with the demand and is therefore becoming a competitive space for banks. Many say the growing interest in AI is a hype, as AI per se is not new – computer-based problem solvers and expert systems have been around for several decades. We rather see the current interest in AI as a logical consequence of progress: rapid expansion in the volume and quality of data, together with exponential increases in computer processing power and more available and cheaper storage finally enable us to apply refined machine learning techniques that solve problems in an unprecedented way. Also, we’re far progressed in the understanding and processing of written and spoken natural language.
The latest evolution of AI brings with it the promise of enhanced productivity as it improves customer-related processes and drives efficiency gains in the back and middle office. We are only just beginning to tap into the vast potential that AI holds. It will make our lives simpler through automated decision making, linking personal preferences and customer intelligence with improved user interfaces in areas like customer service, providing insights and managing investment portfolios. In the middle and back office, AI connects very well to our operational excellence strategy. AI will also allow us to better utilize our time and to automate more complex actions in more complex areas that were previously closed off to machines.
Automation itself is likely to evolve in three distinct phases: The first phase is based on the long-standing practice of automating specific processes with macros, usually in a specific desktop application. The second phase will be marked by the development of autonomous, virtual robots that can work on rules-based processes. The final phase will see the rise of smart machines, the likes of IBM Watson, which understand language and can provide insights back to the operator. We are testing such capabilities as part of our innovation and transformation programs.
At UBS there is already excitement about the potential of AI to change banking and financial services and the way banks interact with customers. At the same time, we are considering what these advancements mean for our business model. AI is likely to disrupt banks beyond the internal structure and impact the industry as a whole. AI could even drive market diversity, with more small and medium-sized participants entering the marketplace.
We are constantly looking to augment the client experience and that will continue along our dealings with AI. We are led by a clear vision of what the next decade’s “cognitive bank” looks like. Without this vision, we would not be in a position to prioritize our change efforts and do the right thing. However technology is expensive to implement and takes time and skilled resources. We, and the industry in general, also need to rethink today’s data handling habits with ever increasing amounts of unstructured data likely to move into highly secure clouds or hybrid clouds. So change does not happen overnight but UBS is embracing it well prepared.
What it takes to be human?
Our recent online feature in the New York Times explores the emotional side of Artificial Intelligence and speaks to experts and scientists at the cutting edge of this research. It looks at the progress being made in programming machines to recognize human emotions and asks the ultimate questions: Can robots and machines develop human emotions that people can react to? Can AI recognize human emotions? Can emotionally intelligent machines replace humans in customer service? Find out by chatting to Rose, one of world’s leading chatbots.
