Complex Customer Journey
Customer interactions have become increasingly complex to map and understand in omni-channel banking. Ask any bank and they will tell you it is a colossal undertaking. On average, consumers leverage 3-4 channels to interact with their bank – from web chat, mobile apps, devices, call center, IVR, ATM and branch. When you factor in the number of banking products, volume of transactions, types of inquiries that a bank receives (predominantly in the form of unstructured data) and the number of geographic locations involved – the complexity factor very quickly multiplies.
There is the added challenge of fragmented systems and data silos that are pervasive in the banking industry. Making it virtually impossible to consolidate, blend and analyze multiple sources of unstructured and structured data in a cost-effective and timely manner. On average, most financial institutions are accessing 3-5 percent of their data versus 100 percent – leading to limited insights.
Consumers Set New Standards
Banks must also contend with the fact that consumers have raised the bar on speed, ease of use and consistent service in a digitized world. Consumers expect personalized, targeted and contextually relevant interactions anywhere and anytime. Moreover various surveys indicate that when consumers receive the same level of service across omni-channel touch points, they are more likely to be engaged with their banks. An enhanced client experience will often go a long way in driving satisfaction, loyalty and wallet share.
Proven Value with Cloudera Enterprise
Leading banks are using Cloudera Enterprise to drive customer insights for a true 360-degree view. Built on Apache Hadoop, Cloudera Enterprise provides a unified platform for aggregating, blending and analyzing any volume and type of unstructured and structured data – in a highly secure environment.
Financial institutions of all types and sizes are using Cloudera Enterprise to drive multiple customer experience management and marketing initiatives including up-sell/cross-sell, next best offer, attrition reduction, loyalty and proactive customer care programs. For instance, they are able to correlate CRM, branch, mobile, geo-location and transactional data with external data sources such as data stemming from social media and 3rd party sources to better understand spending patterns and behaviors, preferences and sentiments with greater precision. By tapping into the full breadth and depth of data, they are able to deliver contextual and personal experiences that are more closely aligned with individual needs and expectations.
For instance, Royal Bank of Scotland (RBS) – a global bank with over 30 million customers and 700 retail branches – chose Cloudera Enterprise for its customer 360 initiatives. In an article published in American Banker, RBS’s head of analytics talks about the bank’s big data strategy and how it’s recreating that personal touch to enhance customer engagement. For more details, please read “Can Big Data Recreate Personal Touch of Bygone Banking? RBS Thinks So”.
I would also like to invite you to our joint webinar with RBS on April 21, 2016 at 3:00PM GMT/10:00AM ET. You will have an opportunity to learn more about RBS’s big data strategy and use of Cloudera Enterprise. The webinar will provide many take-away lessons. To register, kindly visit: RBS Drives Customer Insights with Big Data Analytics and Hadoop.