Analytics in an Openbanking Era

Analytics  descriptive or predictive is normally associated with data that has accumulated over time banks went digital with introduction of computers in operations. Data thus accumulated grew to big data which is the foundation for analytics. However with open banking  this is changing.  

Openbanking does not have bigdata as a startpoint for analytics. Yet, analytics is the sole saviour for banks that now compete in a transparent world. This is very much akin to a live hockey match with players analysing realtime onfield information and strategising the next move.  This is real time digital analytics in its purest form and at its best. 

The competing banks are both strong and vulnerable. Possibly a bank has the best products, loyal customers and attrition is never on the horizon. Come the API world of open banking, this cutting edge can in quick time become blunt with the banks launching products that are more attractive vying for a larger wallet size.  Factor in the fintechs it is the hare winning. 

Let me introduce two new terms unique to openbanking.  The Active Provider- the bank that offers AISP and PISP services on its own portal and its customers prefer this over other providers.  The APIs draw information from other banking relationships that the customer has. The Passive Provider- the bank that offers information to the 'Active Provider'. 

The Active Provider will be in a position of advantage to trace the digital footprints of a customer. This answers questions as simple as, how often a customer visited the portal and as complicated as what was the banking activity while in there, such as account activity for payments. From this point onwards the data scientists will have a field day applying the concepts of central tendencies, standard deviations, confidence intervals; name it, it will be there.

The strategy for banks is to be an 'Active Provider' with strong digital engagement / analytics platform. Open banking is a high stake winner takes all poker game. A strong case for 'Deep Learning' by applying principles for serendipity, if it does exist.