Operational Excellence in Banking
Simplify Further, Engineer Smarter and Automate at Scale
Regardless of the industry, the “operations” domain correlates to an institution’s “productivity.” Banks across Middle East and Africa working hard to excel at operations. Research by Digitopia and Union of Arab Banks (UAB) suggests that operations run mostly smoothly; however, further integration and simplification are steps ahead.
Operations is a complex domain, so it makes sense to break it down to components for better analyses and management. Below are four interrelated components of operations from a banking perspective.
Foundation: A solid foundation is a board-level thinking about how to prepare for the impact new technologies will have on the bank’s operations. It requires having a clear direction aligned with company goals. Moreover, the direction should be led by a strong leadership and of course supplemented with the necessary resources, including talent, budget etc.
Channels: Becoming omni-channel requires designing processes across channels with customer experience as the focal point. To deliver that experience, companies must identify and track certain quality metrics, integrate channel flows for seamless journeys, and automate processes to the highest degree possible. Therefore, the channels component feeds into an “enhanced customer service.”
Processes: A frictionless and harmonious functioning of the whole mechanism requires focusing on processes. This means increasing automation and the use of digital labour and intelligent systems across core services, support functions and internal processes. It also requires establishing modern and secure IT systems that enable integration with third parties to support open banking, fintech and insurtech ecosystems. All in all, the processes component serves “increased efficiency, speed and diversity of services.”
Analytics: Analytics capabilities refer to how operational data is captured, organised, analysed, and used for better operations. Leveraging real-time data, machine learning, and artificial intelligence to make predictive and preventive decisions
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