As the equipment finance industry evolves, technological advancements must explore emerging technologies as a solution to greater control of risk.
During the ELFA Business Live 2020 Keynote, author Peter Zeihan argued that our industry should not plan on a return to normalcy until 2022, at the earliest. And the assumption that our industry will return to exactly what it was pre-COVID, warts and all, is an utter fantasy. Equipment finance is an analog industry being faced with the reality that we are, going forward, in a digital finance economy and we’re not going back.
As a result, our existing models and processes must be reevaluated for efficacy, and it’s also critical to separate risk from uncertainty. Risk is quantifiable; we can use data and math to prove why one loan has more risk of default than another. Scott Nelson, Chief Digital Officer with Tamarack Consulting, discusses how uncertainty is not understood statistically, but we make assumptions and choices based on “fear of the unknown” instead of investigating and proving the assumption. This distinction is critical, and Nelson caps his point with the new rule that “Past financial behavior is not relevant to future financial behavior”.
If risk can be understood as a statistical function that can be mathematically evaluated and mitigated, it should be clear that greater data access offers the path to more accurate equations. The reality is that we’re not “moving on” from COVID; we’re adapting to life in a world reshaped by it. The “risk” as we historically measure it hasn’t shifted so much as the uncertainty surrounding how we interpret that risk did.
Luckily, equipment finance is well equipped to manage such a landscape, despite being woefully behind in terms of modernization. The typical customer journey provides ample opportunity to remain engaged and learn more about customers’ needs. In fact, it may be the persistence of the industry to keep relationship the cornerstone of origination and servicing that can change the way equipment finance considers and manages risk on new and maturing contracts.
Better Relationships Through Data
Equipment finance is a business built on relationships forged through trust and relevance, which will lead to substantially more data availability. Insights learned from this data bring organizational benefits such as a dramatic reduction in risk in your decision-making during origination and servicing. The key is the technology that enables real-time data collection and dissemination.
Let’s be frank about the state of technology in equipment finance. Prior to 2020, many companies were “on the path” towards digitizing processes and gaining more efficiencies and security as a result. Of course, that “path” is probably an overly charitable characterization, given that digitization for many companies meant adopting e-Signature tools or moving their environments to a private “cloud” and calling it a day. It’s this kind of narrow thinking that has led the industry to the point it is today: a quarter century or more behind other industries in terms of modernization, and desperate to catch up in the face of broad uncertainty.
The equipment finance industry is littered with companies that will try to keep one foot in both worlds; realizing they need to invest in technology at some level, but refusing to go all-in with digital transformation because of the cost, the time investment required, or even just because it’s perceived to be difficult. Buy-in must come from the top, and it’s time to start dramatically increasing your business investment in exploring and adopting innovative technologies.
The technology trends dominating 2020 are largely driven by making meaningful connections with users and present a useful roadmap going forward. After all, these gains in technology are designed to get us closer to our customers, both in terms of ease of doing business and staying connected with our customers long past a transaction is completed. In terms of risk, staying close has the added benefit of giving us more insight to the value of our assets while the deal is maturing. If these are our goals, technologies like IoT (Internet of Things) offer a natural path forward.
Core system modernization, modern business application platforms, and even IoT connected equipment create true systems that can “talk” to one another. When systems and devices communicate with relevant data, they can gather data, analyze it, and take action based on what it has learned. For the Alexa in your kitchen, you tell it to “play a song” and it connects the data it’s received with its artificial intelligence center located across the internet, processes the request, and voila the song plays. More inputs allow for more complex actions, like how Tesla uses numerous sensors, GPS signals, and publicly available data to power their self-driving automobiles. This new connected data infrastructure is a path to solving our reliance on stale, historical data, offering whole new avenues to evaluating, managing, and ultimately reducing risk.
Data Alone Is Dumb
Capturing data is step one; step two is changing how we think about our customers and about our industry. “Data is inherently dumb,” Peter Sondergaard, Senior VP with Gartner said. “It doesn’t actually do anything unless you know how to use it; how to act with it.” Unpacking Sondergaard’s point, knowing that a person watched “Raiders of the Lost Ark” eight times last year might not tell you anything by itself, but Netflix uses data points like this to build personality profiles on users. Through their streaming platform, they pull insights through millions of data points that measure time of day, how many times you paused, when you paused, and many more that those of us outside of their walls would never even think to measure.
Compare this example to Netflix’s once-mighty analog competitor: Blockbuster. In theory, Blockbuster had access to some of the same data points (how many times they rented, when did they rent it, how long did they keep it, etc.), but the only way they could put that data to use was in marketing flyers, posters, and in deciding how many of each title to stock. As connecting to customers became more important, Blockbuster faded into obscurity. Not because they didn’t have the ability to gain the technology needed to connect to customers (remember Blockbuster Online?), but because they lacked the ability to translate those data points into actionable insights.
Digital Finance Requires Personalized and Accurate Data
Equipment finance is well-equipped to capture more data in a manner that engenders trust and reliance, builds relevance, and adds little friction to the customer service process. There are tons of data points that are available through the systems and assets our industry is already leasing. The best part is that the technology needed to capture and process this data, such as modern integrated core systems and business intelligence solutions are getting cheaper and easier to implement.
The logical conclusion is that the time is right now to invest in these technologies. The effort to discover how these solutions can deliver new methods of engaging with and being more relevant to our customers must define our risk management and technology investment strategy in 2021 and beyond. True cloud computing, core system modernization, modern data estates, machine learning, and other emerging technologies represent a path forward to a fundamental rethinking of risk, more opportunities for profit, and potentially new revenue streams both during origination and servicing. The other side of that coin is that if we fail to adapt, we risk not only losing value on our existing contracts, we risk losing out of a bigger piece of the commercial lending pie. With relevant relationships at the core of the industry, we’re well positioned to adopt these tools and get fast value from data that is already within our grasp.
True Cloud computing, core system modernization, modern data estates, machine learning, and other emerging technologies represent a path forward to a fundamental rethinking of risk, more opportunities for profit and potentially new revenue streams; both during origination and servicing! The other side of that coin is that if we fail to adapt, we risk not only losing value on our existing contracts, but we risk losing out of a much bigger piece of the commercial lending pie. With relevant relationships at the core of the industry, we’re well-positioned to adopt these tools and get fast value from data that is already within our grasp.
About the Author
Sean Scampton is Director of Sales & Marketing at Leasepath
Citations:
Nelson, Scott; “Risk Management Must Consider New Data to Survive in Post-COVID Economy”
This article originally appeared in the Nov/Dec 2020 edition of NEFA Newsline. For more information, see the NEFA Newsline website.