In 2008, the global economy virtually collapsed due to the sub-prime mortgage crisis, brought on by loose credit policies and the propensity of the public to engage in the acquisition of homes well beyond their debt service capabilities. Sub-prime credit companies took an unprofitable customer base of major chartered banks, offered them below market mortgages, given their credit worthiness, all driven by “proprietary algorithms” which were marketed as being capable of identifying “hidden” credit worthy borrowers.
Subprime firms operated at losses to start. Banks had no qualms about the emergence of these companies due to the fact that they only initially ceded unprofitable customers to those companies. At first, equity capital was raised in the markets, during a period of low interest rates, to fund ongoing losses at a time of buoyant equity markets. This capital enabled subprime firms to expand the money losing mortgage divisions. As revenues grew, sub-prime firms found a second additional avenue for capital raising, the securitization of sub-prime mortgages. All of this created a great revenue stream.
The combination of multiple streams finally caught the attention of the major chartered banks; unable to make money off of subprime customers, bank CEOs determined they must have been missing something in the customer base that the subprime companies identified. And sub-prime companies offered a ready answer: “proprietary algorithms“. Eager to invigorate their own mortgage and credit divisions, banks completely accepted the “we’re smart and you are dumb” premise and acquired any and all subprime firms on the market, buying trillions in equity/assumed liabilities. The banks bought back the very customers that they gave away, plus added overhead in the form of hundreds of thousands of staff and acquired computer systems that were incompatible with banking legacy systems.
Upon purchase, it was revealed the propriety algorithms were garbage, essentially serving as a diversion from the true real business model. Subprime mortgage companies posted ever rising revenue figures due to old fashioned hard marketing on an unsophisticated customer base, willing to push the boundaries of leverage, all subsidized through periodic equity underwritings and loan securitizations. The business model was entirely built on loose monetary policy and looser regulations.
In 2021, a new breed of loan has started to intrigue investors, the “buy-now, pay later” (BNPL) loan. Issued by private companies, they offer individuals the opportunity to purchase a pair of shoes, a sweater, an exercise bicycle, a vacuum cleaner, almost any form of consumer retail item available online, with a short term installment plan less than one year in duration. BNPL companies are unregulated because they do not directly charge interest on consumer loans. BNPL companies levy an upfront customer documentation or origination fee, sometimes they receive a kickback from the seller of the consumer item, often a hybrid stream combining both. So long as the fee is not designated to be interest, BNPL firms escape most forms of regulatory oversight.
Technically speaking, BNPL represents a very short term consumer/business loan specifically arranged to avoid credit reporting. It is a variation on a layaway purchase. With a traditional layaway, the retailer levies an upfront fee, warehouses the item on their premises until the customer rounds up the remaining funds and then transfers ownership. Upfront layaway fees are charged in lieu of credit interest.
A conventional layaway business model is profit challenged due to the fact that consumers greatly prefer immediate possession of an item. Savvy investment bankers dusted off regulations and determined that items purchased on layaway do not impact one’s credit score. They further determined no regulations govern where the layaway item is to be stored. Seizing upon the oversight, they came up with a business model whereby a consumer or business, wanting to purchase an item but lacking either funds or available credit, arranges a financing company to buy that item on behalf of the consumer and ship it to the consumers home for “warehousing”. The storage contract requires a set number of payments to be made to the finance company, typically ranging over a term of 90 to 364 days. Upon completion of the contract, ownership of the item is transferred from the finance company to the homeowner/business storing the item.
The name “buy-now, pay later” seems nostalgic, evoking imagery of trusting retailers and honest consumers. “Buy-now” actually means that a 3rd party financing company purchases the item; the “pay-later’ refers to the obligation of the consumer to pay for the item from the financing company. The item is bought and sold twice over a very short period of time. This third party purchase of a desired consumer item from a retailer, to be shipped to a consumer for temporary storage, until the payments are completed and title changes to the hands of the consumer; this escapes traditional credit reporting and therefore is of no interest to regulatory agencies. The fact that the item being stored has been removed from its packing container and is now being used, well, that’s between the actual owner of the item, which is the financing firm and the consumer. Some social media describe the arrangement as a variation on the “lease to own” model; it differs because a lease to purchase is a reportable item for credit agencies, BNPL completely skates through the loophole.
The present crop of BNPL firms are unprofitable. Short term lending on consumer items to credit challenged individuals is historically very risky and only marginally profitable; losses on uncollectible loans eat up the high fees for most companies. BNPL firms claim to have licked the loan loss problem due to “proprietary algorithms, powered by AI, that permit the firms to offer loans to only the very best customers“. A more youthful element of the investment public, funded by generous and, what seem to be recurring, government direct stimulus payments, accept the premise at face value. Maybe the credit arbitrage model is legit, maybe the model is legit but not profitable, maybe the model is not legit at all. It is too soon to say.
In any event, so as to scale up an unprofitable business model, BNPL firms intend to raise as much equity capital, as quickly as possible. This will enable companies to increase market penetration and pave the way towards building a short term loan book large enough to begin securitization. Once securitization commences, yield hungry buyers will purchase as much short term debt as is available for a yield pickup, increasing both the buzz and further legitimizing the appearance of the business model to the investing public.
Having lived through the credit driven S&L blowups of the late 1980s, the subprime mortgage crisis of 2007-2009 as well as a host of other systemic shocks brought on by finance greed and the “greater fool” theory, my sonar is pinging. However, I note the point made by economist Daniel Kahneman- “Intuition cannot be trusted in absence of stable regularities in the environment”. BNPL firms are capturing market attention and attracting capital for a reason. Done right, perhaps a real business opportunity exists. Rather than dismiss the business model out of hand, or applaud it as the next big thing, it is more applicable to do look at positive attributes as well as areas of pushback.
Positives.
1. Provided that net costs of BNPL are lower than net interest/processing charges levied against the consumer and to the retailer, BNPL offers a form of competition to conventional credit cards, and this may result in lower overall costs for consumers and retailers to transact. Capital costs in the equity and debt markets are almost free to credit worthy borrowers, or to borrowers that capture market appeal. So long as credit remains almost free, the best time to engage in credit arbitrage between a financial firm, a desperate retailer and a credit challenged consumer, is right now.
2. BNPL offers a degree of identify theft or credit fraud protection for the buyer of an item. Those who purchase items using conventional credit cards run into periodic unauthorized charges on their card thereafter. Just as Paypal operates as a middleperson to protect the integrity of consumer data on a retail purchase, so too does BNPL.
3. Legitimacy is being conferred upon BNPL firms through agreements with more established payment processors such as Adyen NV to include the BNPL option in their system. PayPal is rolling out its own BNPL program, internally owned and operated, in Australia. For now, PayPal states that their service is a no fee, no charge option, essentially experimenting with the model as a loss leader.
4. Differing from credit, which if not paid fully, revolves forever at an assumed interest rate; BNPL loans do end and therefore, those who have difficulty budgeting might find total annual costs of debt service will decline, provided that they use BNPL instead of credit.
Negatives
1. BNPL firms hope for a partial displacement of credit card use by consumers (either/or). Isn’t it equally plausible that consumers may choose to supplement existing credit card and rack up off-book debts via BNPL advances (both), pushing consumer leverage well beyond the ability to repay?
2. BNPL companies silo their data, hence the term “proprietary” (not being shared with other BNPL companies). As BNPL advances are not considered credit or typical loans that fall into credit reporting, the possibility exists that multiple firms will inevitably wind up offering the same customer multiple installment loans and be completely unaware of the total debt profile, leading to the potential for massive increases in short term debts by consumers. Utilizing a BNPL loan doesn’t impact ones credit rating. How long will it take before non-credit worthy consumers start abusing the model and ramping up their leverage?
3. Because the BNPL companies own the items being stored at the home of the consumer, this produces potential issues should the payments fall into default. How does one go about repossessing a $2,000 Stella McCartney handbag? The action is not nearly as clean as repossessing a car or a home, because the customer doesn’t actually own the item until fully paid, they are just warehousing it.
4. Buy now, pay later loan companies don’t acknowledge the potential for loan losses due to “porch pirates”; what happens when a loan is made on an item that is shipped and stolen before delivery? Why would a customer make monthly installment payments on an item never received? Up to 15% of deliveries in major urban centers never reach their intended customers after purchase; this dwarfs loan loss ratios on credit card issuers by a whopping margin.
5. BNPL firms may also have not fully considered the likelihood of large scale commercial crime impacting their business model. What prevents a sophisticated crime ring from purchasing hundreds of thousands of dollars of marketable, higher value consumer items, selling those items as received, making a payment on each to keep the inventory flowing, and then defaulting on all the payments and walking away with buckets of ill-gotten cash? Maybe this has been factored into the “proprietary data driven AI algorithm, designed to only do business with the right people”. I wonder.
6. What is the probability of future regulatory risk? The entire business premise is based upon the circumvention of traditional credit assessment; the business model only exists due to an exploited loophole. As the consumer does not own the item until all payments and fees are completed and the finance company assumes the credit risk until ownership transfers, a single consumer could theoretically wrack up tens of thousands, or perhaps even hundreds of thousands of dollars of indirect purchases on BNPL plans, without having any of this short term liability reflected upon a personal credit report. If banking regulators were to step in and close the loophole, the business model also changes.
7. What happens if the model is legitimized and suddenly, Amazon and Paypal opt to roll it out internally on a global basis? Barriers to entry are almost non-existent; the firms with the lowest cost of capital, in possession of the customer base, will win any capital contest.
8. Credit cards offer perks for usage, such as accumulation of airmiles, cash rebates, warranty extensions, travel health insurance, etc. The assumed value of such discounts range from 1%-3% of annual credit card usage. BNPL offers no discounts; customers purchasing items on BNPL pay full retail. There is no financial benefit, given the current interest rate environment, for credit worthy customers, to utilize a BNPL plan versus a credit card, provided that credit card charges are paid in full monthly. Given the low interest rate environment, the earnings to be had offering a BNPL loan appears largely insufficient to offer a competitive discount package, to more capably compete with credit cards.
The total market for BNPL seems considerably more limited than for conventional credit purchases. BNPL will be of most appeal to those who are credit challenged. There is some potential for BNPL on the purchase of goods, less so on services, although there would be nothing specifically preventing one from paying for a “French Laundry” $350 Prix Fixe luncheon over 4 to 12 easy installments, provided that a firm would offer such a feature. It is difficult to determine a wholesale displacement of credit card usage with BNPL. Buy Now, Pay Later looks to be a niche category for now. How large that niche is, or is not; that’s the uncertainty facing equity investors looking to participate in the business model.
What Could Possibly go Wrong With off Book Consumer Loans?
Looking down the road ever so slightly, what degree of probability has been built into proprietary AI algorithms to estimate, due to the extremely short term nature of the loans, that once one loan goes into default, ALL consumer loans by that customer, including credit card debts, will almost simultaneously go into default? That is when it goes bad, not just for BNPL firms, but for any creditor of that consumer in general, leading to the potential for a systemic credit event.
These observations/questions are entirely valid and critical to determine the ultimate profit and investment potential of buy now, pay later loan shops. Is BNPL a useful, essential, game-changing service, or are exploitive loan companies busting open a tiny regulatory oversight that may potentially result in a credit event for indebted consumers? Should we fully trust the “proprietary, industry changing, AI driven algorithms?”
Will the Banks Buy Handfuls of Magic Beans Once Again?
The exit strategy of any unprofitable/marginally profitable business is to make the business appear profitable, for a time, then find a buyer for the entire company. This requires a multipronged strategy of accessing capital to acquire many marginally profitable customers, branding an ordinary, freely competitive business under the guise of a disruptor and creating consumer hype as bait for M&A departments. What supports any short-term investment case for BNPL are loose monetary policies and a strategy for expansion taken directly from the subprime mortgage business playbook; raise equity capital, loan that capital out, potentially securitize loans and avoid regulation.
In the case of BNPL firms, if they catch hold, even temporarily, with the investment public, the ultimate, best case scenario buyers for BNPL companies will, once again, be major chartered banks. Bank CEOs might soon wonder “why didn’t WE make any money from these customers, what are we missing”, to which BNPL CEOs respond: “we have proprietary AI driven algorithms to determine which customers are least likely to default”. Bank CEOs, awash with capital in a loose credit cycle, hearing the term AI in prefix form (placing AI in front of ANY word makes it sound cutting-edge) might feel threatened enough to bulk up and purchase entire companies. Upon purchase, banks could quickly determine that they have bought nothing more than magic beans, are left holding hundreds of billions of bad installment loans and write off the entire purchase.
When a bank CEO, in the next credit event, brought on by inane M&A behavior, sits in front of a US Senate hearing and stammers the reason for a near wholesale wipe-out of the global economy and requirement for massive coordinated intervention is due to the fact that “our modelling failed to anticipate”, know this, AI driven algorithms are responsive but seldom anticipatory. Therefore, that CEO is not telling a congressional committee anything novel, he is merely describing the world as it is, modelling is reactive, not predictive. Providing unregulated loans, using a rudimentary form of credit arbitrage isn’t the slightest bit hi-tech, it makes credit reporting more suspect, not less. If not handled carefully, too many off-book loans don’t fix a problem, they create one.
One thing that seems relatively safe to predict, sadly, is that major chartered banks, having extended massive corporate loans to oil and gas firms at cyclical tops, having extended too much credit in every housing bust at interest rate bottoms, having participated in almost every rollup of competition at cyclical highs, almost destroying the capitalistic economies of the western worlds at least thrice in the last 50 years as a result, they are THE marks for BNPL companies, because banks, just like AI data centers, operate almost entirely on an inductive reasoning system.
Banks do not act, they react. Reactive decisions are typically poorly thought out and done in haste. While exceptions do exist, equity investing and haste don’t always meld well.
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