How Tech Can Help Banks Accelerate Legacy Transformation

During a meeting with the CIO of a Top 5 bank in Germany, I was introduced to a lady who was retiring that same weekend. The CIO averred that she was the last employee in the bank who knew the nitty-gritty of a certain mainframe application.

This was music to my ears. The company I was working for at the time had a framework that could significantly automate the transformation of legacy applications to open systems.

I immediately seized the opportunity to pitch for a legacy transformation pilot on the back of this framework.

My message resonated with the CIO. He promised to discuss the high level details of moving from legacy to open systems internally and get back to me soon with a date for presenting our framework to his team.

This was in 2002.

Fast forward to 2014: The bank still uses the same old mainframe application.

From this incident, it’s easy for me to conclude that banks are stuck in the old world of legacy technology and join the ranks of the digerati in predicting doomsday for the future of traditional banks.

But I won’t do that because it would be turning a blind eye to the other side of the problem: Legacy transformation hurdles posed by technology.

There are at least six issues with open systems that hamper legacy transformation. I’ll cover three of them in this post. They are:

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#1. Impractical Open Standards

Banks in developed nations embraced IT four to five decades ago, if not earlier. Thier IT landscapes are extremely heterogeneous. For example, the payments IT landscape at a Top 5 European bank comprises 84 disparate systems. This precludes compliance with somewhat bookish open system standards like BIAN.

#2. Buggy Code

Modern systems have very short update cycles. For example, my social media archiving software releases new updates every 15 days. Most updates fail to install on the first time. This causes anxiety and loss of productivity. Were the same thing to happen with banking software, it would result in outage, loss of reputation and penalties. The leading retail industry analyst RSR Research puts it nicely in its article RSR Software Quality: What the Heck Has Happened?: “…as we move into the Cloud, I really hope we keep our feet on the ground and our heads OUT of the clouds.”

failwhale#3. Low Uptime

Not to single out Twitter, but its “fail whale” epitomizes frequent outages of cloud software. A C-level executive at a leading payments processor told me that, with the best of intentions, they were unable to deliver more than 80% uptime for its card management software. As one who is wont to whipping out his calculator and doing quick-and-dirty calculations, I was dumbfounded by the implications of this figure. As I highlighted in blog post entitled Skating Away With Online Payments, one in 12 payments would fail at 98% uptime. Now, if one of these systems were to have an uptime of as low as 80%, the end-to-end success rate falls precipitiously to 74% (0.98*0.98*0.98*0.98*0.80). In other words, the failure rate quadruples to four in 12 payments i.e. one in three payments would fail, which is an unacceptably high failure rate for a mission-critical business like banking / payments.

In Part 2 of this post, I’ll cover the remaining three open system issues that hamper legacy transformation. Watch this space and, meanwhile, feel free to share your thoughts in the comments below.