The Two Sides Of Digitalization

Hella Tobias-vom Scheidt

There are two sides to every story. And when it comes to digital transformation, you should be telling both—cost reduction and customer experience, to be precise. My banking colleagues often tell me with great enthusiasm about the digital initiatives they’re deploying, which typically focus on addressing one or the other of these two issues. But true digitization should improve both.

Digital disruption and and new technologies resulting out of affordable availability of almost infinite computing capacity have accelerated the pace of business and the art of the possible for banks, particularly when it comes to lowering costs and improving the customer experience. Yet for most financial services institutions, the cost income ratio remains too high, and the process of modernizing customer interactions or properly leveraging real-time data insights to improve customer experience are still fledgling projects. Only a handful are running at the top of their game.

But it’s not all bad news. The innovative opportunities around machine learning are providing banks with a new way to serve customers and address back-end costs by having a quick impact on the bottom line. For example, machine learning can implement internal collaboration workplaces, making the back-end workload much more efficient for different teams, more cost-effective for the bank as a whole, and intelligently anticipating and accelerating the customer experience.

As the volume, variety, velocity, and veracity of data increases at an exponential rate, banks can make use of the wealth of data they own. Rather than being a cost overhead, this data can (and must) be used as a strategic, competitive advantage. For example, rather than playing a stop/start transactional role, effective digitalization lets banks integrate into the client’s value chain so they’re perfectly poised to offer additional services and advice to corporate clients at the most opportune times.

Machine learning enables banks to very quickly harness valuable insights to reduce risk, automate processes, improve customer engagement, and compete, as well as collaborate with, tech-savvy fintechs. Doing so has never been cheaper, easier, or more effective.

And the cognitive automation capabilities of robotics and chatbots provide the ultimate automation potential. By intelligently connecting people, things, and businesses, technology can put data into a business context, providing transformative insights and smoothing the digital transformation path.

With all the technology now available at your fingertips, my hope is that we’ll see an end to projects where cost reduction and customer experience are divorced from each other. The two are inextricably linked, in my view. As digital transformation continues to mature across the banking sector, projects that focus on one without the other will hopefully become a thing of the past.

You can see numerous financial services use cases and learn more about leveraging the benefits of machine learning by visiting us at Sibos at booth D44.

Hella Tobias-vom Scheidt

About Hella Tobias-vom Scheidt

Hella Tobias-vom Scheidt is General Manager of the Financial Services Industry Business Unit, Middle and Eastern Europe, at SAP. She joined SAP in May 1997 as a senior consultant and project manager for banking in Germany. Since 1999, Hella has held various senior management roles at SAP including head of Financial Services Consulting in Germany, EMEA, and globally; senior program executive for Deutsche Bank; and head of Custom Development Sales for Germany. Hella also spent five years as a systems analyst at Westfalen Bank and Software AG in Germany, where she developed banking solutions.