Technological Thoughts by Jerome Kehrli

Big Data technologies are increasingly used in retail banking institutions for customer profiling or other marketing activities. In private banking institutions, however, applications are less obvious and there are only very few initiatives.
Yet, as a matter of fact, there are opportunities in such institutions and they can be quite surprising.

Big Data technologies, initiated by the Web Giants such as Google or Amazon, enable to analyze very massive amount of data (ranging from Terabytes to Petabytes). Apache Hadoop is the de-facto standard nowadays when it comes to considering Open Source Big Data technologies but it is increasingly challenged by alternatives such as Apache Spark or others providing less constraining programming paradigms than Map-Reduce.

These Big Data Processing Platform benefits from the NoSQL genes : the CAP Theorem when it comes to storing data, the usage of commodity hardware, the capacity to scale-out (almost) linearly (instead of scaling up your Oracle DB) and a much lower TCO (Total Cost of Ownership) than standard architectures.

Most essential applications for such technologies in retail banking institutions consist in gathering knowledge and insights on the customer base, customer's profiles and their tendencies by using cutting-edge Machine Learning techniques on such data.

In contrary to retail banking institutions that are exploiting such technologies for many years, private banking institution, with their very low amount of transactions and their limited customer base are considering these technologies with a lot of skepticism and condescension.

However, in contrary to preconceived ideas, use case exist and present surprising opportunities, mostly around three topics :

• Enhance proximity with customers
• Improve investment advisory services
• Reduce computation costs