Bridging Analytics and Business Strategy in Consumer Finance

With a Master of Applied Statistics degree from The Ohio State University and over three decades of experience, Dan has built a career in consumer finance by bridging the gap between analytics and business strategy. Known for making complex data accessible, he has led transformative initiatives in predictive modeling, underwriting and portfolio optimization while also serving as an adjunct faculty member.

I began my career in the early 1990s as a statistical analyst, developing marketing response and spend predictive models for retailers. Over time, I built my career from the ground up, ultimately establishing myself in the field of consumer finance. A pivotal realization throughout my journey has been the importance of bridging the gap between analytics and business strategy. I’ve consistently recognized the need for someone to interpret what analytics is telling us, communicate its implications clearly and guide its application to drive bottom-line impact. Every advancement in my career has been rooted in my ability to communicate complex analytical insights in a way that resonates with business stakeholders.

Making Analytics Simple and Useful

Throughout my career, I’ve observed two distinct types of analytics professionals: those who are highly technical and capable of building sophisticated models but may lack a deep understanding of the business context, and those who, while less technical, excel at aligning analytical projects with strategic business needs. Since I’m not the most technical person in the room, I’ve managed my career by being the 2nd type of analyst.

In particular, I have spent a lot of my evening time as an adjunct faculty member of a few universities, teaching math and statistics on the side. This experience has sharpened my natural ability to explain complex concepts in accessible, nontechnical language—an area where I truly excel. We let the results drive decisions. It’s ok to have a warm and fuzzy feeling about how a program may work, but my motto is “if you can’t measure it, how do you know if it’s working?”

  A pivotal realization throughout my journey has been the importance of bridging the gap between analytics and business strategy  

Any model we implement, any new idea we have, gets tracked on a dashboard. We want to make sure we measure the impact of what we are producing. The dashboards have to be simple and intuitive enough that a non-technical person can understand what they are looking at.

Explaining Risk Models Through Business Impact

At my current company, 1st Franklin Financial, one example is that we have overhauled the entire direct mail process of soliciting new customers. We replaced the “warm and fuzzy” business rules with a set of true machine learning models to predict who would respond to direct mail and who would pay back the loans we offer. In the process, we have cut our customer acquisition costs in half and lowered the overall risk to those who become our customers. When communicating complex risk models and analytics, I focus on explaining their direct impact on the business. You have to explain these types of things in terms of the impact on the business. Business leaders don’t care about model fit metrics, parameters in the model or the modeling technique used. They want to know how these things positively impact the business. As I stated earlier, I’ve spent my career explaining these items.

You really need a well-rounded team consisting of people who understand data, people who can build models and people who understand both modeling concepts and business applications. I feel that at 1st Franklin, we have an excellent mix of all of these types of people.

I’ve also found that it is very motivating for these individuals to have access to the most up-to- date technology available, including computers, servers, software and cutting-edge training. For future leaders in consumer finance, the most important skill is learning how to communicate. The adoption of software that autonomously creates models is already underway. The key will be how the information is used and the benefit it brings to the business. Software can be your technical ally, but be your own communicator of the output.