The digitalisation of financial services demands new business models
Analytics from multiple channels of banking customer data delivers insights for new products
Financial services analytics demands immediacy to be at its most effective
The proliferation of online and mobile banking now provides banks with a vast amount of new information on their account holders’ behaviour. CaixaBank*, a leading Spanish financial group in retail banking and insurance, collects more data than most as it’s an international leader in mobile finance apps. With the aim of using analytics to gain customer insights for the business, CaixaBank went shopping for a solution.
It’s easy to see why CaixaBank was looking to upgrade. In the first quarter of 2016 it handled 377 million mobile transactions, up 23 percent compared to the same period in 2015. Of its 14 million customers, it currently serves 5 million online and 2.9 million using mobiles, and today mobile is its second largest channel accounting for 20 percent of all transactions handled by the bank. But this growth is all part of the bank’s strategy to be at the forefront of the digitalisation of financial services, as Chief Data Officer Luis Esteban Grifoll explains: “The millennials, the segment that’s increasing, soon they’ll only use digital devices, so we have to find new models that are relevant to these type of clients.”
“It’s no longer enough to get data at the end of the day or at the end of the month.”
CaixaBank already has considerable expertise in product development, but its goal was to utilise the data generated by clients to create new models that identify customer needs and provide more personalised products. To realise this, it needed a system that could capture data from numerous disparate channels available – ranging from client interaction and app metadata to hot topics at call centres and sentiments expressed on social media – and then perform analytics on this information regardless of data format or location.
To perform these tasks, it chose a big data solution from Oracle* consisting of Big Data Appliance, Exalytics, and Exadata. This interconnected platform enables data to be loaded into the most appropriate environment to suit the type of data or how it’s received. Applications can be developed regardless of where the data is located, given the ease of access made possible by the comprehensive interconnects.
Yet what brings this big data platform to life is the performance of the Intel® Xeon® processors that deliver a real-time capability in processing CaixaBank’s diverse resource of customer data.
“We’ve migrated all the previous analytical platforms to an Oracle architecture on hardware with Intel processors,” says Xavier Gonzalez Farran, director, Big Data Analytical Tools at CaixaBank. “The Intel architecture gives us a great deal of processing power that’s essential to support the projects which we need, for example, real time response or to intake large volumes of data in parallel processes.”
For CaixaBank, it has now achieved its aim to use data from a variety of sources to gain insights on customers and to repackage them for sharing internally throughout the company. Its new platform was never intended to create analytical models exclusive to one particular division but for use to benefit any department. Now armed with this capacity for intensive big data analysis, the analytical models at CaixaBank are swiftly evolving, due in no small part to the power and speed of the Intel Xeon hardware.
“Performance immediacy is something that the business is demanding every day. It’s no longer enough to get data at the end of the day or at the end of the month”, says Grifoll. “The enterprise is asking us to capture information online on what is happening every hour or every minute within our business. Big data is our new mainframe at CaixaBank, and we have to change the culture, so that people transition from the transactional world to the informational world.”
It’s part of a process that Gonzalez Farran sees as necessary steps for the bank to become an “information company”. Evidently, banking is banking on analytics to preserve its fortunes.
*Trademarks are the property of their owners
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