Core banking is, for me anyway, constantly evolving. What I mean by this is what I considered to be included in the definition of core banking has continued to expand as the financial services landscape changes and business and customers demand new services, functionalities, and nontraditional sources of new revenue.
More and more I see the confluence of a couple new and not so new, but radically improved, concepts gaining prominence in the banking landscape. So much so that they have now been included in my expanding definition of core banking and should be considered core to any banking transformation strategy.
You might look at this topic and say nothing new, banks have been dealing with large amounts of data since the first automated systems were created for banking. I will concede that banks do deal with large amounts of traditional data however I will tell you right now that they have only started to scratch the surface of Big Data.
Everyone’s digital footprint is getting bigger by the day; automated payments of various types, social media, group memberships, and the like, messages, e-mails, telephone calls, Twitter posts, location based data related to purchases, meals, and other experiences, immediate feedback on all of these activities. Appropriately engaging with customers to capture this non-traditional data, understand its relevance and to use it appropriately is the corner stone of Big Data. Any Big Data concept should include the three V’s:
We all know that the volume of data continues to increase exponentially. As more and more processes are automated and digitized the volume of data expands daily. Banks understand this concept related to their own systems but have yet to integrate large amounts of external data into their own analytics and processes
Real-time and near real-time are terms that are heard within banking applications more and more. The ability to leverage data at the speed of creation will slowly render the traditional end-of-day processes obsolete. It will also dramatically change the way in which banks are managed.
The majority of the most important data is relatively new. As the Internet, mobile applications, and social media have expanded they have generated a vast amount of new data. As banks continue to transform their traditional core banking systems the amount of new data that did not exist before is substantial. The traditional structured databases are no longer able to store and retrieve this to support the new processes required to utilize the new Big Data affectively.
Personal Financial Management
Personal Financial Management (PFM) is not so new but in my opinion has dramatically improved. Improvements in account aggregation, automated transactional classification, self-categorization and peer placement functionality, gamification, and social media integration are but a few of the areas where PFM has expanded its functionality. On the banking side the ability to integrate PFM into currently existing banking channels, like on-line and mobile, or creating a new portalized experience from PFM functionality can greatly improve customer experience, improve loyalty and overall satisfaction.
But, for me, the greatest part of PFM is the ability to integrate PFM generated and enriched data into a bank’s overall Big Data strategy. Particularly when it comes to the enrichment of payments information and customer segmentation. When you include account aggregation from other financial institutions and social curiosity into your PFM strategy the wealth of data is substantial. Through aggregation a bank is able to see the transactional detail from not only their institution but from other institutions as well. Social curiosity asks customers if they would like to compare their spending habits to those of other customers in their peer group? The data advantage here is that the customer will be asked a series of questions to categorize themselves within a peer group. Basically the customer will provide detailed segmentation information that will help them understand their spending in relation to their peers but also help the bank tailor products and services to them in a more relevant manor. PFM is one of the best first ways a bank can expand the variety of their data.
Real Time Offer Management
How best to leverage your growing big data and generate increased revenue quickly? For me this is a no brainer; Real Time Offer Management (RTOM). Whether you use RTOM for determining next best product or next best action within existing processes and channels or if you are using it to provide merchant funded incentives to customers a well thought out RTOM strategy will be instrumental in driving new revenue while providing relevant offers and service to clients.
What is core to banking is, and will continue to expand rapidly. The confluence of Big Data, Personal Financial Management and Real time Offer Management should be on the radar of every forward thinking transformational banker.