According to Bain and Company’s 2019 NPS Prism survey, banks that rank the highest in customer loyalty, have dramatically fewer episodes that annoy customers and often require a human channel to solve, such as disputing a fee or addressing a declined payment during a point-of-sale transaction. Furthermore, McKinsey reports that customer service is increasingly important as new, digital-first institutions enter the market and the rise in remote work increases demand for “reliable service and rapid problem resolution.”
Thus, the problem for banks is how to maintain a high level of customer satisfaction, while also reducing the cost to resolve customer service issues and maintain adequate risk mitigation.
According to Jason Ganovsky, Sr Director of Solution Engineering for Financial Services at Celonis, in today’s ever evolving technology landscape, where competition comes not only from established banking institutions and from new fintechs but also from every “app” that provides a rich, engaging customer experience, financial services firms need to continuously evaluate how well they are servicing their customers. Only the Celonis Execution Management System (EMS) with its embedded process mining technology can help banks identify improvement opportunities and execute on them, Ganovsky said.
For example, process automation and machine learning can be used to identify and group multiple, related cases into a single large-scale problem that is directed to a single team or agent, thereby reducing the overall case volume, and thus, resolution costs. Ganovsky cited internal Celonis data that showed that a large percentage of future service tickets could be avoided by solving related tickets earlier. This can result in significant net-new and incremental labor productivity and cost savings.
Using the Celonis EMS, one of the largest European universal banks was able to:
- Reduce the lead time in the retail process by 30% within 6 months
- Process credit applications 4 times faster
- Open 98% of bank accounts on time