THE CLOCK’S RUNNING: MAKING BETTER DECISIONS FASTER WITH BANKING ANALYTICS

After “…quite possibly the greatest Super Bowl in history,” (NFL.com, Feb 2, 2015) it’s not surprising to see how much football talk revolves around analytics. Football is game of inches; and that couldn’t have been more true on Sunday with the last play that ran completely counter to the Seattle Seahawks’ standing as the second best offensive rushing team in the NFL (what was Carroll thinking??). It just shows that regardless of the underlying data, it is how you use those analytics to make timely decisions that determine outcomes.

As in football, many aspects of our lives involve data and analytics. Whether it is the number of steps that a Fitbit dashboard shows (and the number of times you need to walk around the block before dinner) or complex customer engagement analytics from various banking channels. It’s the latter of these two that I will focus on today, as well as the importance of the words “timely and actionable.”

The need for timely Banking Analytics

We’ve all seen and heard the statistics on how much data we produce today compared to any time in human history; that is no different for the banking sector. There is more data available to banks today than ever before; whether it be structured vs. unstructured, internal / external, or from a plethora of other sources like social, customer calls, reviews, and comments. In fact, data has become so important that it not only is a competitive advantage but necessary if you’re going to succeed!

The biggest problem with data today is the process of turning it into “timely and actionable” information. The following graph depicts a typical process and timeline required to get valuable analytics to make quick and nimble strategic decisions to propel your business forward.

You can see from the above, that by the time that data is gathered, compiled and analyzed, it’s pretty tough to describe it as “timely”… Yet this is a typical approach used in many financial institutions—they attempt to make informed and data-driven decisions from banking analytics, but based on stale information.

An alternative is to use transaction data. Transaction data is your rich, “always on” source of intelligence on customer experience and channel metrics. Combined with other data, a system that leverages the constant stream of transaction data provides a pulse on customer activity throughout banking channels and replaces and/or enhances historic data sources. This data treasure trove turns the above scenario to the one shown in the following; where the focus has shifted to making “timely and actionable” decisions rather than waiting weeks or months for key questions to be answered.

There are numerous gains to be made from having an always-on data source in a ready-to-analyze state, and I’ll cover these and provide business impact models in future posts.