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In light of your experience, what are the major challenges that you have seen in the Banking Analytical space, and what are the emerging trends?
Talking about my experience, I have been in the financial services space, especially in data and MCIF for more than 20 years. I had seen it from its infancy when the whole purpose of the MCIF was to reduce your costs, directly taking your account level information, and rolling it up to enable you to save postage. This information is thus used for segmentation purposes and to drive profitability and revision of product and pricing strategy. However, in today’s age where data has gained massive significance, it is essential to take all siloed data sets—be it about new products, features, their benefits—and identity how do they all come together to give you meaningful information.
Primarily, what I have seen as one of the biggest challenges in the financial industry, particularly in the community-banking sector is the lack of understanding the value of analytics outside of the G/L. It can enhance the potential of a financial institution in terms of profitability, cutting costs, and other factors related to their growth. This is effectuated by using an Analytics expert to answer the “whys” and “hows,” alongside the “what” and “when” addressed by the typical Finance and Accounting areas of the banking sector. The hardships in accessing the siloed data sources and gathering them together to make it meaningful, actionable information has also emerged as a strenuous task for bankers today. The ability to create a dashboard for senior managers to quickly access and evaluate valuable data points, in an automated way, is also of paramount importance.
Could you illustrate with some examples of the strategy that you have adopted to entail the new technologies into your organization’s ecosystem?
I have seen several proficient strategic initiatives coming up in the banking space. However, financial institutions, in their attempt to answer questions, oftentimes, try to tick-and-tie back to a GL answer. Instead, what we need is a relationship, an in-depth look at specific customers who are potentially being impacted. From a community banks perspective, it is just a matter of getting started, someone asking those questions, and using the available software. Unfortunately, there is a lack of a unique, intuitive, and robust systems in the ecosystem. Human workforce and Excel are still in use to pull out data and figure out the answer to the questions—“whys” and “hows”—and decide, “Are we going to do more of it? Are we going to do less of it? Are we going to stop doing it altogether? Do we need to go on a different path?”
"The more we use analytical tools to capture data from these interactions, curate it, and use it to fulfill customer needs in an agile fashion, the better we are providing the banking experience"
If you are fortunate enough to work for an organization that invests in Tableau software or technology like BI or some piece on intelligence, you want to look at data deeper. However, at the end of the day, it is just having that role and having the opportunity to answer those questions. The other element, I think that all banks struggle with is a dashboard piece, which brings all data together. It is so critical in today’s fast-growing banking space. It enables people in different departments to have access to data and ultimately, the workflow.
What would be the piece of advice that you give to your colleagues to guide them in building a powerful strategy for the organization?
It is quite unfortunate that oftentimes, you get management, which states that they know the answer and are looking forward to backfilling it with data. This leads to the destruction of the business. However, I have been very fortunate in my career to work with a lot of great CEOs, COOs, and CFOs, who had gained in-depth knowledge in this arena. Therefore, the piece of advice I can give is “be true to the data; let’s begin with the question, not the answer; let data tell you the answer; be brave enough to go in and lay it out.” Having this strategy in the DNA, you can disagree with the answer and adopt a different direction. However, it is imperative to be prepared to let the data guide you with the answer.
Furthermore, you should be willing to have a valid conversation and step back from your initial statement that you have provided—if it was found wrong—and understand what the underlying question is. This is the basic analysis, and there is nothing super-secret. However, I think oftentimes people get invested in just making sure that they are doing an excellent job in getting the answer. No matter what technology we use, the efficiency of analysis depends upon the depth of understanding we have before we embark on analysis.
Can you please tell our readers how data analytics will shape the future of the banking sector?
I envision that data analytics is emerging to be more significant in not only the banking sector but also in other industry verticals. From the financial industry perspective, the ever-increasing need for the bankers to have a close and interactive communication with their customers and mold themselves accordingly will keep data analytics an ever-time necessity. Evident that traditional face-to-face interactions will not serve today’s need for agile and effective banking, people like to shift toward digital interactions. The more we use analytical tools to capture data from these interactions, curate it, and use it to fulfill customer needs in an agile fashion, the better we are providing the banking experience. In this scenario, banks with worthwhile information and the ability to integrate it into their workflow can stay ahead of the pack. This paves the need for the banking institutions to get out from their legacy “desk-phone-paper” method.
As mobile applications continue to expand in purpose and use the crucial interactions between banker and customer must not get lost in the ether. Taking the insights that you get from a customer who is undergoing these processes and channeling it into useful information is going to be supremely important. Capturing these interactions and channeling them to appropriate workflows will mean the difference between achieving 1:1 sales and service and missing out on an ever-growing avenue of opportunity... Therefore, it is evident that collection, curation, storage, streamlining and accessing data will be incredibly crucial in the banking space.
Collecting data is one major part of the entire process, and I think banks are good at just this part of the analytic process but the real challenge comes when attempting to integrate the many data points necessary for gaining an effective and efficient database. There are many financial service companies out there for helping banks at various stages of this process. And, the reality of community banking is that the costs of doing that on your own are going to be most likely prohibitive. Therefore, there emerges a real golden age for those third-party vendors in the financial sector, extending their services to bankers.