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By: Joel Pruis What is it we as bankers are trying to accomplish? If you have been in the industry for 20+ years, this question may sound ridiculous! We do what we do! We are bankers! What do you mean define what are we trying to do? But that is the question, what is it we are trying to do? I am going to propose we boil it down to the basic/fundamental element – Banks aggregate money from various sources and redeploy these funds to earn a return for the shareholders. Ultimately, our objective is to generate an appropriate return for the shareholders Getting back to the movie Moneyball, Billy Beane and Peter Brand define the objective of the Oakland A’s for the season in terms of projecting the number of wins that are needed to assure, with all probability, that the team makes the playoffs (this would be similar to the objective of banking to generate an appropriate return for the shareholders). But Peter Brand quickly moves into very specific targets that are required for the A’s to make it to the playoffs, namely win 99 regular season games. In order to win 99 regular season games, the A’s offense will need to score 814 runs in the season and defensively only allow 645 runs. Plain and simple. Very objective, very measurable and it is all based upon data, data, data. Let’s break this down. Based upon their conference, the teams in their conference along with the overall schedule, Peter Brand projects that 99 wins are necessary to land a spot in the playoffs. No gut check, no darts or crystal ball but rather historical data that when analyzed provides the benchmark of 99 wins to statistically assure the Oakland A’s that they will make the playoffs. So let’s apply this to banking. Our objective is to generate the appropriate return for our shareholders or the old Return on Equity. So, for example, if our targeted return on equity is 20% (making the playoffs) we need to make sure we generate enough net income (99 wins) through producing the necessary gross yield on assets (814 runs generated by the Oakland A’s offense) less the expected charge offs (645 runs allowed by the Oakland A’s defense). For a quick dive into details, our data would provide for a margin of error on the variable to provide for statistical assurance of achieving the objective (Return on Equity). In the movie there is no guaranty that the 814 runs will win the conference but at the same time there is no guaranty that the Oakland A’s opponents will score 645 runs. Never in the movie does the coach, Billy Beane or Peter Brand tell the team, “You only have to score X number of runs this game, don’t score anymore.” Or even crazier, “You are not letting the other team score enough runs, they need to score 645!” No, the strategy is still to generate as many runs as possible while minimizing the number of runs scored by the opposition. Rather it is the review of the total amount of earning assets of the financial institution and the overall credit quality that we must understand and control to determine our ability to generate the net yield on assets required to generate the return on equity that is required. If we assume too much risk in the portfolio in order to generate the required yield it would be similar to having a poor pitching staff projected to allow 10 runs a game requiring the team to produce 11 runs a game in order to win. It just is not realistic. So basically we need to assess at the high level, are we appropriately structured to allow for the generation of enough profit to provide the appropriate return on equity. At this point, we do not need to complicate it any further than that. Now let’s take a look at the constraints. We know we have them in banking, let’s take a look at probably the single biggest constraint imposed on Billy Beane and the Oakland A’s. In the movie, before Billy Beane is even aware of the Moneyball concept, his is given his constraint by the owner. Beane asks for more money to ‘buy players’ and is flat out rejected by the owner. The owner, in fact, cuts Beane off by asking, “is there anything else I can do for you?”. Net result is that the Oakland A’s have $38 million dollars for payroll vs. the New York Yankees at $120 million. Seriously it does not seem fair. How can you attract the needed talent when you cannot pay the type of salary needed to get the necessary players to win a championship? Let’s rephrases this for banking… How can a bank be expected to deploy its assets when such a high rate of return is required? Boiling it down to a specific example, “How can I originate a commercial loan at this rate of interest when the competition is ½ to 1% lower than our rates?” Up next – Why will 99 games get us to the playoffs? How do we assess the environment?
A recent study comparing financial differences between men and women found that, overall, women are better at managing money and debt. Differences between the two populations include: Men have 4.3 percent more debt than women Men have a 2 percent higher credit utilization amount Mortgage loan amounts for men are 4.9 percent higher Men have a higher incidence of late mortgage payments by 7 percent Read more details from the analysis — including an infographic and statistics by city and state. Source: Women Flexing Their Financial Muscles; Women's Credit is in Better Shape Than Men's Credit
By: Joel Pruis Times are definitely different in the banking world today. Regulations, competition from other areas, specialized lenders, different lending methods resulting in the competitive landscape we have today. One area that is significantly different today, and for the better, is the availability of data. Data from our core accounting systems, data from our loan origination systems, data from the credit bureaus for consumer and for business. You name it, there is likely a data source that at least touches on the area if not provides full coverage. But what are we doing with all this data? How are we using it to improve our business model in the banking environment? Does it even factor into the equation when we are making tactical or strategic decisions affecting our business? Unfortunately, I see too often where business decisions are being made based upon anecdotal evidence and not considering the actual data. Let’s take, for example, Major League Baseball. How much statistics have been gathered on baseball? I remember as a boy keeping the stats while attending a Detroit Tigers game, writing down the line up, what happened when each player was up to bat, strikes, balls, hits, outs, etc. A lot of stats but were they the right stats? How did these stats correlate to whether the team won or lost, does the performance in one game translate into predictable performance of an entire season for a player or a team? Obviously one game does not determine an entire season but how often do we reference a single event as the basis for a strategic decision? How often do we make decisions based upon traditional methods without questioning why? Do we even reference traditional stats when making strategic decisions? Or do we make decisions based upon other factors as the scouts of the Oakland A’s were doing in the movie Moneyball? In one scene of the Movie, Billy Beane, general manager of the A’s, is asking his team of scouts to define the problem they are trying to solve. The responses are all very subjective in nature and only correlate to how to replace “talented” players that were lost due to contract negotiations, etc. Nowhere in this scene do any of the scouts provide any true stats for who they want to pursue to replace the players they just lost. Everything that the scouts are talking about relates to singular assessments of traits that have not been demonstrated to correlate to a team making the playoffs let alone win a single game. The scouts with all of their experience focus on the player’s swing, ability to throw, running speed, etc. At one point the scouts even talk about the appearance of the player’s girlfriends! But what if we changed how we looked at the sport of baseball? What if we modified the stats used to compile a team; determine how much to pay for an individual player? The movie Moneyball highlights this assessment of the conventional stats and their impact or correlation to a team actually winning games and more importantly the overall regular season. Bill James is given the credit in the movie for developing the methodology ultimately used by the Oakland A’s in the movie. This methodology is also referred to as Sabermetrics. In another scene, Peter Brand, explains how baseball is stuck in the old style of thinking. The traditional perspective is to buy ‘players’. In viewing baseball as buying players, the traditional baseball industry has created a model/profile of what is a successful or valuable player. Buy the right talent and then hopefully the team will win. Instead, Brand changes the buy from players to buying wins. Buying wins which require buying runs, in other words, buy enough average runs per game and you should outscore your opponent and win enough games to win your conference. But why does that mean we would have to change the way that we look at the individual players? Doesn’t a high batting average have some correlation to the number of runs scored? Don’t RBI’s (runs batted in) have some level of correlation to runs? I’m sure there is some correlation but as you start to look at the entire team or development of the line up for any give game, do these stats/metrics have the best correlation to lead to greater predictability of a win or more specifically the predictability of a winning season? Similarly, regardless of how we as bankers have made strategic decisions in the past, it is clear that we have to first figure out what it is exactly we are trying to solve, what we are trying to accomplish. We have the buzz words, the traditional responses, the non-specific high level descriptions that ultimately leave us with no specific direction. Ultimately it allows us to just continue the business as usual approach and hope for the best. In the next few upcoming blogs, we will continue to use the movie Moneyball as the back drop for how we need to stir things up, identify exactly what it is we are trying to solve and figure out how to best approach the solution.
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With the National Automobile Dealers Association (NADA) Show set to kickoff later this week, it seemed fitting to explore how the shifting dynamics of the used vehicle market might impact dealers and buyers over the coming year. Shedding light on some of the registration and finance trends, as well as purchasing behaviors, can help dealers and manufacturers stay ahead of the curve. And just like that, the Special Report: Automotive Consumer Trends Report was born. As I was sifting through the data, one of the trends that stood out to me was the neck-and-neck race between Millennials and Gen X for supremacy in the used vehicle market. Five years ago, in 2019, Millennials were responsible for 33.3% of used retail registrations, followed by Gen X (29.5%) and Baby Boomers (26.8%). Since then, Baby Boomers have gradually fallen off, and Gen X continues to close the already minuscule gap. Through October 2024, Millennials accounted for 31.6%, while Gen X accounted for 30.4%. But trends can turn on a dime if the last year offers any indication. Over the last rolling 12 months (October 2023-October 2024), Gen X (31.4%) accounted for the majority of used vehicle registrations compared to Millennials (30.9%). Of course, the data is still close, and what 2025 holds is anyone’s guess, but understanding even the smallest changes in market share and consumer purchasing behaviors can help dealers and manufacturers adapt and navigate the road ahead. Although there are similarities between Millennials and Gen X, there are drastic differences, including motivations and preferences. Dealers and manufacturers should engage them on a generational level. What are they buying? Some of the data might not come as a surprise but it’s a good reminder that consumers are in different phases of life, meaning priorities change. Over the last rolling 12 months, Millennials over-indexed on used vans, accounting for more than one-third of registrations. Meanwhile, Gen X over-indexed on used trucks, making up nearly one-third of registrations, and Gen Z over-indexed on cars (accounting for 17.1% of used car registrations compared to 14.6% of overall used vehicle registrations). This isn’t surprising. Many Millennials have young families and may need extra space and functionality, while Gen Xers might prefer the versatility of the pickup truck—the ability to use it for work and personal use. On the other hand, Gen Zers are still early in their careers and gravitate towards the affordability and efficiency of smaller cars. Interestingly, although used electric vehicles only make up a small portion of used retail registrations (less than 1%), Millennials made up nearly 40% over the last rolling 12 months, followed by Gen X (32.2%) and Baby Boomers (15.8%). The market at a bird’s eye view Pulling back a bit on the used vehicle landscape, over the last rolling 12 months, CUVs/SUVs (38.9%) and cars (36.6%) accounted for the majority of used retail registrations. And nearly nine-in-ten used registrations were non-luxury vehicles. What’s more, ICE vehicles made up 88.5% of used retail registrations over the same period, while alternative-fuel vehicles (not including BEVs) made up 10.7% and electric vehicles made up 0.8%. At the finance level, we’re seeing the market shift ever so slightly. Since the beginning of the pandemic, one of the constant narratives in the industry has been the rising cost of owning a vehicle, both new and used. And while the average loan amount for a used non-luxury vehicle has gone up over the past five years, we’re seeing a gradual decline since 2022. In 2019, the average loan amount was $22,636 and spiked $29,983 in 2022. In 2024, the average loan amount reached $28,895. Much of the decline in average loan amounts can be attributed to the resurgence of new vehicle inventory, which has resulted in lower used values. With new leasing climbing over the past several quarters, we may see more late-model used inventory hit the market in the next few years, which will most certainly impact used financing. The used market moving forward Relying on historical data and trends can help dealers and manufacturers prepare and navigate the road ahead. Used vehicles will always fit the need for shoppers looking for their next vehicle; understanding some market trends will help ensure dealers and manufacturers can be at the forefront of helping those shoppers. For more information on the Special Report: Automotive Consumer Trends Report, visit Experian booth #627 at the NADA Show in New Orleans, January 23-26.
The automotive industry is constantly changing. Shifting consumer demands and preferences, as well as dynamic economic factors, make the need for data-driven insights more important than ever. As we head into the National Automobile Dealers Association (NADA) Show this week, we wanted to explore some of the trends in the used vehicle market in our Special Report: State of the Automotive Finance Market Report. Packed with valuable insights and the latest trends, we’ll take a deep dive into the multi-faceted used vehicle market and better understand how consumers are financing used vehicles. 9+ model years grow Although late-model vehicles tend to represent much of the used vehicle finance market, we were surprised by the gradual growth of 9+ model year (MY) vehicles. In 2019, 9+MY vehicles accounted for 26.6% of the used vehicle sales. Since then, we’ve seen year-over-year growth, culminating with 9+MY vehicles making up a little more than 30% of used vehicle sales in 2024. Perhaps more interesting though, is who is financing these vehicles. Five years ago, prime and super prime borrowers represented 42.5% of 9+MY vehicles, however, in 2024, those consumers accounted for nearly 54% of 9+MY originations. Among the more popular 9+MY segments, CUVs and SUVs comprised 36.9% of sales in 2024, up from 35.2% in 2023, while cars went from 44.3% to 42.9% year-over-year and pickup trucks decreased from 15.9% to 15.6%. 2024 highlights by used vehicle age group To get a better sense of the overall used market, the segments were broken down into three age groups—9+MY, 4-8MY, and current +3MY—and to no surprise, the finance attributes vary widely. While we’ve seen the return of new vehicle inventory drive used vehicle values lower, it could be a sign that consumers are continuing to seek out affordable options that fit their lifestyle. In fact, the average loan amount for a 9+MY vehicle was $19,376 in 2024, compared to $24,198 for a vehicle between 4-8 years old and $32,381 for +3MY vehicle. Plus, more than 55% of 9+MY vehicles have monthly payments under $400. That’s not an insignificant number for people shopping with the monthly payment in mind. In 2024, the average monthly payment for a used vehicle that falls under current+3MY was $608. Meanwhile, 4-8MY vehicles came in at an average monthly payment of $498, and 9+MY vehicles had a $431 monthly payment. Taking a deeper dive into average loan amounts based on specific vehicle types—as of 2024, current +3MY cars came in at $28,721, followed by CUVs/SUVs ($31,589) and pickup trucks ($40,618). As for 4-8MY vehicles, cars came in with a loan amount of $22,013, CUVs/SUVs were at $23,133, and pickup trucks at $31,114. Used 9+MY cars had a loan amount of $19,506, CUVs/SUVs came in at $17,350, and pickup trucks at $22,369. With interest rates remaining top of mind for most consumers as we’ve seen them increase in recent years, understanding the growth from 2019-2024 can give a holistic picture of how the market has shifted over time. For instance, the average interest rate for a used current+3MY vehicle was 8.0% in 2019 and grew to 10.2% in 2024, the average rate for a 4-8MY vehicle went from 10.3% to 12.9%, and the average rate for a 9+MY vehicle increased from 11.4% to 13.8% in the same time frame. Looking ahead to the used vehicle market It’s important for automotive professionals to understand and leverage the data of the used market as it can provide valuable insights into trending consumer behavior and pricing patterns. While we don’t exactly know where the market will stand in a few years—adapting strategies based on historical data and anticipating shifts can help professionals better prepare for both challenges and opportunities in the future. As used vehicles remain a staple piece of the automotive industry, making informed decisions and optimizing inventory management will ensure agility as the market continues to shift. For more information, visit us at the Experian booth (#627) during the NADA Show in New Orleans from January 23-26.
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