The importance of digital banking and electronic commerce has proven all the more important during the pandemic. Online shopping is the only choice in many cases for conducting commerce. A recent McKinsey report, pre-COVID 19 outbreak, revealed that retail digital banking acceptance was already high. It has increased to the point where 60% of customers under the age of 70 use digital channels. That number increases to 75% for those under the age of 50.
As the demand for more digital, intuitive financial services capabilities accelerates (and extends to those that have not yet been as digitally inclined), a personalized, low-friction interaction will become more critical to retain and cross-sell products and services to customers. The good news is that digital interaction itself drives the opportunity for a more personalized experience. As customers interact more digitally, there is more data available to collect and analyze to help inform the next interaction.
More and more, financial services are using data, analytics, and machine learning to help facilitate an enhanced digital experience including predicting and anticipating customer interactions. These organizations are collecting customer data from multiple sources, combining and correlating real-time mobile-banking or market data streams with account activity, borrowing history, core banking, investments, and call center data, to form a more complete understanding of the customer and their needs. By doing this, they are better addressing the customer expectations for a personalized experience that has become the norm in other areas of their digital lives.
Key Customer Examples
Gaining a good understanding of customers to better serve them is exemplified by one of Cloudera’s leading Australian banking customers. They are aggregating data from over 100 different systems and sources to create a comprehensive and complete profile of their end consumers. Against this broad set of information, they are applying analytics and machine learning to effectively introduce the “next best conversation” into the customer interaction workflows. As a result, they are able to present timely and relevant conversations/offers to the customer that in turn drives increased satisfaction and incremental revenue.
Another one of our customers, Rabobank, one of the largest financial services institutions in the Netherlands, has implemented a very compelling use case where they are using real-time data to provide up-to-date insights to customers on their finances. Using loan repayment patterns and up-to-the-minute transaction records, Rabobank customers have more timely information and to better understand their financial situation.
Some other customer examples that demonstrate how financial services companies are transforming their business models include a Bank in the UK that has used data and analytics to drive a 15% increase in the customers approved for credit card offers. They have integrated data from diverse sources and built machine learning models to identify relevant financing opportunities to consumers that otherwise may not have been targeted for offers. Another Cloudera customer, a large US bank, has transformed and modernized their customer service options by introducing a chatbot with Cloudera as the underlying data and analytics platform.
Enhance the Customer Experience while Driving Efficiency
The fast pace of technology evolution is particularly challenging for financial services firms that manage a plethora of technologies – old and new. Going forward, the growing preference for digital interactions combined with the need for safety will drive digital acceptance and the need for enhanced digital experiences related to financial transactions and services.
Cloudera enables over 500 financial service providers to utilize the power of data, analytics, and machine learning to transform their business in order to optimize the customer experience, effectively manage risk, address regulatory compliance, and fight financial crime.
The Cloudera Data Platform (CDP) is an enterprise data cloud that supports any type of data (structured, unstructured), regardless of where it lands — at the edge, on-premise at a branch, in the data center, or in any public, private, or hybrid cloud. CDP delivers self-service analytics across these hybrid environments, along with sophisticated and granular security and governance policies that meet the requirements of IT and data leaders.
For more information about improving the customer experience using data and analytics, join our upcoming webinar.