In this month’s post, George Neal explains deriving new information, insights, and the learning process behind intelligent pricing that benefits both the bank and its customers.
If you have small children, as I do, you’ve experienced the “why?” chain of questions at some point. “Why” followed by another “why” – the cycle is endless until the little one is tired or distracted by something more fascinating. Their wondering minds will quickly challenge the depth of your understanding of any given topic. Young children are the best at collecting information, being full of energy and uninhibited by the fear of not knowing, and trust you to be engaged and share your knowledge with them.
Children collect a massive volume of information. Particularly in their early years, many are evaluated on just how much information they collect. Over time, as they mature through their academic years, more focus is placed on their ability to transform that information into insights. Finally, reaching the age to enter the workforce, the focus pivots to turning the information and insights into action and value. At some point, most of us learn that the value of information is within the insights we create and the resulting ability of those insights to influence and change behaviors. Information without insight is trivia. Insight without action is a dream. While trivia can be fun, and dreams are important, action drives value (aside from the occasional free wings and beer, a good trivia night might net you).
We see this same process in many organizations with whom we interact. Every forward-looking organization wants to reach a point where they know their customers intimately. As advisors to financial institutions, we are often asked, “Why can’t we recommend products and services for our customers and their financial needs the same way Amazon suggests products or Netflix suggests programming?”
The answer is, of course, you can. Moreover, financial institutions are uniquely positioned to know more about their customers and their specific product needs than almost any other industry. Why? Because other organizations see only small amounts of information presented in direct transactions. Meanwhile, financial institutions have a much broader view of their clients’ activity, behaviors, and needs. One of the reasons account primacy is essential is the associated information share. This same reason is also often overlooked.
So why are many of the best financial institutions still stuck in the same cycle as early childhood to mid-adolescence school kids when it comes to getting to know their customers better? They have massive amounts of information at their fingertips but struggle with transforming that data into meaningful insights. Even more frustrating is producing insights only to be unable to transform them into action, value, and improved customer relationships.
Turning information into action requires you to do a few things very well. First, collect the data, which most organizations and systems currently do as table stakes. For software providers and their infrastructure, it's practically expected that they can account for the entirety of that information and EVERYTHING that happens within their systems.
This wealth of information leads to the second point; you must be able to transform that into ready-to-use data. The ability to seamlessly connect data across systems, processes, and channels are necessary if you want a full 360-view of your customer. This includes several touchpoints throughout a customer's journey, including the behavior of your institution and its representatives.
This is a significant roadblock for many organizations and the common denominator that causes them to fall short. However, if you have successfully completed this transformation, congratulations! Your company has effectively graduated from elementary school. In other words, you have taken that data understand how it ties together, and are ready to start developing unique, personalized insights, effectively landing you at the “secondary school” level.
Many of us develop our ability to reason, deduce, infer, and theorize during these years. We were expected to synthesize what we had previously learned and use our views of the world. We were encouraged to augment our knowledge and form conclusions, similar to transforming information into insights.
This is a common stagnation point in the financial services industry. Many organizations find themselves heavily investing in data environments, modeling teams, visualization, and business intelligence (BI) platforms, resulting in the accumulation of an overwhelming amount of valuable data, but cannot utilize it successfully.
Legacy systems, their execution limitations, and even internal bureaucratic processes ultimately delay or prevent transforming insights into actions to the point that the value is lost in market changes. The systems and behaviors you are focused on influencing are instead converting your crucial insights into trivia.
This brings me back to my point, “How do we send our data to on-the-job training and ensure it is working productively?” We must transition from knowing something to acting on it, recognizing that something different needs to be done while that knowledge is still relevant.
In banking, few things are as valuable as insight into pricing. They are also incredibly time sensitive and subject to unexpected market changes.
How do we take new information, derive insight, adjust the price, and get that price into the market – all while the wisdom still holds its maximum value and learning from the process along the way? This is the challenge Nomis Solutions has embraced with our platform and is the direction we encourage when advising. Ultimately this results in intelligent pricing that benefits both the bank and its customers.
George Neal is the Chief Product Officer at Nomis Solutions, where he oversees strategy and development for new and existing products across all Nomis Solutions industry verticals. Prior to Nomis, George served as VP of Data Products at Q2, a digital banking solution. He previously spent several years as the Chief Analytics Officer at PrecisionLender, which was acquired by Q2 in 2019. George also has extensive technological and financial experience from his time at American Savings Bank, HEI, Aon Corporation 2G Consulting, and UBS.
