My ELFA experience: Capital, AI, and a nasty blind spot uncovered

The ELFA Annual Convention is always a stimulating and thought-provoking event. With Austin in the rearview mirror, I’ve had some time to consolidate my thoughts on the Convention’s speakers, panels, and hallway conversations and I’ve settled on three topics: Capital, AI, and the uncovering of a nasty blind spot for the industry.

It’s no surprise to find capital and AI running through the conference. Capital is the lifeblood of an equipment finance business and AI has been the buzz of every industry event since ChatGPT dropped into our laps in November 2022. Everyone has a ChatGPT story now and this year’s Annual had multiple panels with AI in the title. Capital is always part of keynotes and hallway discussions. However, the topic was even more front and center this year because of reduced availability and increasing costs due to high interest rates and the socio-economic uncertainty of an election year. Bill Phalen and Barry Ripes wisely took advantage by announcing their new venture PrivateCap on day one of the convention. Capital and AI played a leading role in my ELFA experience this year and the combination of the two revealed what I see as a dangerous blind spot for the industry – how others could use capital to disrupt the industry with AI,

Gen Z is poised to disrupt – finally – and will do so with both capital and tech innovation

Peter Zeihan delivered the opening keynote and once again challenged the audience with uncomfortable insights. I love how Zeihan uses demographic data to support his theses. This time he led with the Boomers and “something I have been waiting 20 years to say: the Boomers are done!” He then reminded us that as the Boomers leave so with the availability of the largest wave of capital the world has ever seen. Every generation becomes capital-rich and starts investing when they hit their mid-fifties. The Boomers were such a large group that they have kept capital costs low for the past two decades, but this trend is over and the next generation, Gen X, is way too small to replace the Boomers size of capital or labor. Zeihan summed up his advice in two words: “Borrow and hire!” Capital and labor are both as cheap as they are going to be for the next ten years.

“Ten years” is how long we have to wait for the first Millennials to reach their mid-fifties. As children of the Boomers, the Millennials are an even larger generation and, as reported in the WSJ, are already ahead of their parents in accumulating wealth. They will also benefit from the inevitable transfer of wealth from their parents. When they hit their mid-fifties and begin to invest they will bring a colossal wave of capital with them. But that wave is a decade away: “Borrow now.”

Zeihan also pointed out that Gen Z’s immediate impact is its role as human capital. This was evident throughout the conference this year – perhaps for the first time for me. I tend to search for innovators bringing new products, ideas, and technologies, like AI, to the ecosystem and this year my discussions were almost all with Millennial developers and product advocates. I smiled during these discussions because good, young developers have a natural, humble curiosity and they sometimes don’t see the potential scope or impact of their inventions. But when their efforts are guided by their more tenured colleagues, as was most often the case, I see good things coming – particularly with AI.

Millennials have arrived and have begun to disrupt. They will transform the industry over the next two decades – first as the leading source of human capital bringing innovation and then as investors of capital. But that capital is a decade away so, as Zeihan instructed, “borrow and hire” these change agents if you want to survive this generational transformation.

Risk management is transforming with age and AI is accelerating the process

The Boomers are retiring and taking their experience and insights with them on their way out. But one undeniable thing I have learned is that during their tenure they learned how to do credit better. The Boomers were always careful with their capital. Indeed, their parents grew up during the Great Depression so many experienced or heard firsthand stories about “not having enough money to put food on the table.” The Boomers brought us FICO and PayNet. They brought underwriting fundamentals that expanded lending from localized community banking relationships to national programs driven by objective analysis of data and credit scores. They understood the power of working together, sharing their experiences and data, and transforming the way credit is managed.

But here is very good news in this story – everything the Boomers developed and learned about credit and risk management is captured and readily available in data. When the industry moved off paper to digital workflows the knowledge of risk managers was captured in the data. AI learns both the fundamentals and skills of credit from that data.

The next generation of underwriters has neither the patience nor an interest in taking the time to do “story credits.” They will deploy the experience of the previous generation of underwriters captured in the data via the machine learning and AI tools of their generation. Risk in equipment finance is still quantified by parameters like debt exposure, time in business, and income; but credit analysis is fundamentally the prediction of the behavior of borrowers. AI is prediction so AI-based underwriting is inevitable.

This was conclusion with the thesis of the panel discussion “AI IN COMMERCIAL CREDIT RISK DECISIONING” facilitated by Equifax’s Kelby Spring, VP of Financial Services. Michael Cohen, Chief Credit Officer at Crossroads, talked about the value of expert insight used during the construction of scorecards. Traditionally, scorecards are created a priori by underwriting experts – usually in simple, linear, weighted average models. But now the expert experience and the outcomes of past decisions are encompassed in the historical data of the enterprise. Patricio Hidalgo, Head of Risk Analytics of Crossroads’ partner Kin Analytics, shared how AI learns from that data and then those same experts use their insights to decide how to apply trained predictive models to automated, more precise decision-making. Daryn Lecy, Senior Vice President and COO at Oakmont Capital Services, described how the next generation of underwriters is leveraging past data with AI predictors to make some decisions automatically while digging deeper into others that the predictors call out as needing special attention from their experts.

Risk management fundamentals may not be changing with age, but the way they are applied, and the way AI uses the credit scores and data is changing fast. Better decisions faster and with much more precision is the future.

Our approach to capital has created an AI "blind spot"

During the Q&A session of the AI in credit underwriting panel I came to an uncomfortable realization – an epiphany of sorts - We have an AI blind spot in the equipment finance industry. Spring asked the audience several questions about their engagement with AI. When pressed on when they intend to deploy AI in their businesses the largest group said they would use AI in 3 months and a significant majority of the audience said they would use it within 6 months. Fear of AI is waning, but an awareness of how to use it and how others already use it is still minimal. One audience member asked the panel about the threat of outsiders leveraging AI to enter the equipment finance ecosystem. The usual discomfort with fintech, Amazon, and Apple was cited, but it occurred to me that this industry’s risk-averse approach to capital creates a blind spot.

The biggest threat of AI comes from believers like Marc Andreessen, founder of A16Z, who decide that equipment finance is a worthwhile target market. Venture Capitalists like A16Z don’t dribble out small efforts and they don’t give up easily because they don’t have to. They attack problems with passion and almost limitless capital because they have succeeded so often in the past that investors feel lucky to have the opportunity to participate in their vision. A16Z has invested $44B in technology disruption and is putting another ~$7B into AI. People like Andreessen have lived the success of trial-and-error technology development and he believes in the power of AI to do good. If he decides he is going to disrupt equipment finance, he will. We need to keep our eyes on him and those like him.

I am already looking forward to seeing how these themes play out over the next 12 months and anticipating their impact on the 64th ELFA Annual Convention next year. I am excited to work with the next generation building innovations. Yes, I am one of those Boomers, but I don’t want to “be done” quite yet. I am excited about the increased awareness in the capital markets and the opportunities to use AI to both acquire and deploy capital more efficiently and effectively. But just as anonymity is a poor cyber defense, believing that equipment finance is too small or too niche of a market for the big AI disruptors is naive. Hopefully, we will find a way to fix our blind spot.