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of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum
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By: Tom Hannagan Apparently my last post on the role of risk management in the pricing of deposit services hit some nerve ends. That’s good. The industry needs its “nerve ends” tweaked after the dearth of effective risk management that contributed to the financial malaise of the last couple of years. Banks, or any business, can prosper by simply following their competitors’ marketing strategies and meeting or slightly undercutting their prices. The actions of competitors are an important piece of intelligence to consider, but not necessarily optimal for your bank to copy. One question is regarding the “how-to” behind risk-based pricing (RBP) of deposits. The answer has four parts. Let’s see. First, because of the importance and size of the deposit business (yes, it’s a line of business) as a funding source, one needs to isolate the interest rate risk. This is done by transfer pricing, or in a sense, crediting the deposit balances for their marginal value as an offset to borrowing funds. This transfer price has nothing to do with the earnings credit rate used in account analysis – that is a merchandising issue used to generate fee income. Fees, resulting from account analysis, when not waived, affect the profitability of deposit services, but are not a risk element. Two things are critical to the transfer of funding credit: 1) the assumptions regarding the duration, or reliability of the deposit balances and 2) the rate curve used to match the duration. Different types of deposit behave differently based on changes in rates paid. Checking account deposit funds tend to be very loyal or “sticky” – they don’t move around a lot (or easily) because of rate paid, if any. At the other extreme, time deposits tend to be very rate-sensitive and can move (in or out) for small incremental gains. Savings, money market and NOW accounts are in-between. Since deposits are an offset (ultimately) to marginal borrowing, just as loans might (ultimately) require marginal borrowing, we recommend using the same rate curve for both asset and liability transfer pricing. The money is the same thing on both sides of the balance sheet and the rate curve used to fund a loan or credit a deposit should be the same. We believe this will help, greatly, to isolate IRR. It is also seems more fair when explaining the concept to line management. Secondly, although there is essentially no credit risk associated with deposits, there is operational risk. Deposit make up most of the liability side of the balance sheet and therefore the lion’s share of institutional funding. Deposits are also a major source of operational expense. The mitigated operational risks such as physical security, backup processing arrangements, various kinds of insurance and catastrophe plans, are normal expenses of doing business and included in a bank’s financial statements. The costs need to be broken down by deposit category to get a picture of the risk-adjusted operating expenses. The third major consideration for analyzing risk-adjusted deposit profitability is its revenue contribution. Deposit-related fee income can be a very significant number and needs to be allocated to particular deposit category that generates this income. This is an important aspect of the return, along with the risk-adjusted funding value of the balances. It will vary substantially for various deposit types. Time deposits have essentially zero fee income, whereas checking accounts can produce significant revenues. The fourth major consideration is capital. There are unexpected losses associated with deposits that must be covered by risk-based capital – or equity. The unexpected losses include: unmitigated operational risks, any error in transfer pricing the market risk, and business or strategic risk. Although the unexpected losses associated with deposit products are substantially less than found in the lending products, they needs to be taken into account to have a fully risk-adjusted view. It is also necessary to be able to compare the risk-adjusted profit and profitability of such diverse services as found within banking. Enterprise risk management needs to consider all of the lines of business, and all of the products of the organization, on a risk-adjusted performance basis. Otherwise it is impossible to decide on the allocation of resources, including precious capital. Without this risk management view of deposits (just as with loans) it is impossible to price the services in a completely knowledgeable fashion. Good entity governance, asset and liability posturing, and competent line of business management, all require more and better risk-based profit considerations to be an important part of the intelligence used to optimally price deposits.
Meat and potatoes Data are the meat and potatoes of fraud detection. You can have the brightest and most capable statistical modeling team in the world. But if they have crappy data, they will build crappy models. Fraud prevention models, predictive scores, and decisioning strategies in general are only as good as the data upon which they are built. How do you measure data performance? If a key part of my fraud risk strategy deals with the ability to match a name with an address, for example, then I am going to be interested in overall coverage and match rate statistics. I will want to know basic metrics like how many records I have in my database with name and address populated. And how many addresses do I typically have for consumers? Just one, or many? I will want to know how often, on average, we are able to match a name with an address. It doesn’t do much good to tell you your name and address don’t match when, in reality, they do. With any fraud product, I will definitely want to know how often we can locate the consumer in the first place. If you send me a name, address, and social security number, what is the likelihood that I will be able to find that particular consumer in my database? This process of finding a consumer based on certain input data (such as name and address) is called pinning. If you have incomplete or stale data, your pin rate will undoubtedly suffer. And my fraud tool isn’t much good if I don’t recognize many of the people you are sending me. Data need to be fresh. Old and out-of-date information will hurt your strategies, often punishing good consumers. Let’s say I moved one year ago, but your address data are two-years old, what are the chances that you are going to be able to match my name and address? Stale data are yucky. Quality Data = WIN It is all too easy to focus on the more sexy aspects of fraud detection (such as predictive scoring, out of wallet questions, red flag rules, etc.) while ignoring the foundation upon which all of these strategies are built.
In a continuation of my previous entry, I’d like to take the concept of the first-mover and specifically discuss the relevance of this to the current bank card market. Here are some statistics to set the stage: • Q2 2009 bankcard origination levels are now at 54 percent of Q2 2008 levels • In Q2 2009, bankcard originations for subprime and deep-subprime were down 63 percent from Q2 2008 • New average limits for bank cards are down 19 percent in Q2 2009 from peak in Q3 2008 • Total unused limits continued to decline in Q3 2009, decreasing by $100 billion in Q3 2009 Clearly, the bank card market is experiencing a decline in credit supply, along with deterioration of credit performance and problematic delinquency trends, and yet in order to grow, lenders are currently determining the timing and manner in which to increase their presence in this market. In the following points, I’ll review just a few of the opportunities and risks inherent in each area that could dictate how this occurs. Lender chooses to be a first-mover: • Mining for gold – lenders currently have an opportunity to identify long-term profitable segments within larger segments of underserved consumers. Credit score trends show a number of lower-risk consumers falling to lower score tiers, and within this segment, there will be consumers who represent highly profitable relationships. Early movers have the opportunity to access these consumers with unrealized creditworthiness at their most receptive moment, and thus have the ability to achieve extraordinary profits in underserved segments. • Low acquisition costs – The lack of new credit flowing into the market would indicate a lack of competitiveness in the bank card acquisitions space. As such, a first-mover would likely incur lower acquisitions costs as consumers have fewer options and alternatives to consider. • Adverse selection – Given the high utilization rates of many consumers, lenders could face an abnormally high adverse selection issue, where a large number of the most risky consumers are likely to accept offers to access much needed credit – creating risk management issues. • Consumer loyalty – Whether through switching costs or loyalty incentives, first-movers have an opportunity to achieve retention benefits from the development of new client relationships in a vacant competitive space. Lender chooses to be a secondary or late-mover: • Reduced risk by allowing first-mover to experience growing pains before entry. The implementation of new acquisitions and risk-based pricing management techniques with new bank card legislation will not be perfected immediately. Second-movers will be able to read and react to the responses to first movers’ strategies (measuring delinquency levels in new subprime segments) and refine their pricing and policy approaches. • One of the most common first-mover advantages is the presence of switching costs by the customer. With minimal switching costs in place in the bank card industry, the ability for second-movers to deal with an incumbent is not one where switching costs are significant issues – second-movers would be able to steal market share with relative ease. • Cherry-picked opportunities – as noted above, many previously attractive consumers will have been engaged by the first-mover, challenging the second-mover to find remaining attractive segments within the market. For instance, economic deterioration has resulted in short-term joblessness for some consumers who might be strong credit risks, given the return of capacity to repay. Once these consumers are mined by the first-mover, the second-mover will likely incur greater costs to acquire these clients. Whether lenders choose to be first to market, or follow as a second-mover, there are profitable opportunities and risk management challenges associated with each strategy. Academics and bloggers continue to debate the merits of each, (1) but it is the ultimately lenders of today that will provide the proof. [1] http://www.fastcompany.com/magazine/38/cdu.html
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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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