A recent visit with my mother made real for me the significant challenge banks still face in managing data.
Like most retirees, my mother wants to make sure she understands all the details of her hard-earned savings.
So, we set up a meeting with a banker to review her accounts, consolidate funds, and make some simple fixed-income investments. The day should have been informative, productive, and uneventful.
Unfortunately, some of these requests proved to be impossible, even for a senior branch representative from an FDIC-insured institution.
At one point, we needed to print a physical statement for one of her accounts. The statement was not available through the web portal. Then, a limitation in their books and records reporting system and CRM software prevented them from printing the document at the branch office.
For me, a technologist focused on the financial services sector, it was an alarm bell.
Financial services firms are under cost pressure from heightened regulatory oversight and risk controls, placing downward pressure on margins. This, coupled with growing competition from new market entrants and an increasingly diverse customer base, is driving mature firms to reassess their legacy platforms and data requirements.
While firms have spent recent years investing heavily in modernizing their front-end and mobile experiences, they have often neglected the core mainframe systems that process and record most of the world's financial transactions —including 90% of credit card transactions.1
So, while it's clear that banks still have a steep hill to climb to expand services, increase efficiency, reduce risk, and drive innovation, none of this will be possible without first prioritizing work to democratize mainframe data. Democratizing data from the mainframe can transform operational efficiencies and improve compliance by powering access to the valuable information locked in silos.
Organizational silos inhibit data sharing
Numerous factors have led to the current state of data. For starters, most large financial institutions are a collection of diverse businesses created over the past century through M&A activity.
These businesses have built massive and diverse organizations that are highly effective, but in many cases, siloed from each other. The organizational structure has contributed to a complex technology and data stack that makes data sharing across different silos difficult—and, in the case of my mother’s account, impossible for front office staff to access.
In addition, traditional Role Based Access models for data access are proving to be less responsive to business demands than more modern Attribute-based Access Control models, where data and system access is based on business rules instead of more siloed user permissions.