(Laura Williams, American Institute for Economic Research) If you buy anything at all online these days, you might have noticed the sudden influx of “flexible financing” options. Everything from bed sheets to plane tickets to software is now priced as “$55 OR $9.99/mo (6 mo) at 30 percent annual percentage rate (APR).”
Buy-now-pay-later vendors have partnered with sellers and financial institutions to provide these options right in the purchase interface. Klarna and Uplift specialize in flight financing, either allowing customers to buy a ticket now and pay in installments, or to place them on layaway and pay leading up to the trip. Apple recently launched Apple Pay Later, with no interest or fees. Services from PayPal, Affirm, Uplift, Zip, Postpay, Afterpay and others seem to be popping up everywhere, offering options to pay for daily purchases in installments.
The availability of freestanding credit (rather than an ongoing credit card or line of credit) for small purchases has surged in the past couple of years, as customers have become comfortable with digital payments in general, and the e-commerce checkout process in particular. Integrating financing options into that process, whether through a direct partnership, a browser extension, or a payment app, faced little resistance.
Key to this shift has been the availability of consumer data, and the analytics required for lenders to quickly assess consumer creditworthiness and offer financing options that are likely to be workable for both parties.
People serious about personal finance have understandable concerns about this development, as micro-credit makes it easier to buy more than you can afford, and get stuck in a debt-trap akin to what we see with irresponsible credit card use or other overborrowing for consumption. If the easy availability of credit leads people to overspend or accumulate debt at relatively higher interest rates, the already financially vulnerable may be exposed to more risk than through traditional lenders (who may offer them low spending limits, or say no to a new card).
That said, from a public choice point of view, vendors are clearly meeting customer demand for more flexible payment options. Small businesses who can offer a low-cost (or, for them, revenue-positive) lending option through a partner organization are likely to see more sales and attract more customers, without taking on the risk or headache of extending individual lines of credit themselves. For someone who needs to travel, but can’t afford to pay for a flight upfront, extending the purchase over several months may be a relatively low-cost way of accessing something that would have been off-limits — say, a student’s choice to fly home for a big event, or the chance to visit a sick family member who won’t be around long enough to budget the necessary savings, or the ability to attend some potentially lucrative networking or professional event that is expected to pay off later. Overall, increased and democratized access to credit represents a general good for consumers, especially those of limited means, as long as it is handled responsibly.
Perhaps counterintuitively, people who earn higher incomes carry more credit-card debt than those with lower incomes, perhaps because they have higher expenses, and the cushion to absorb and pay off balances regularly. People with higher earnings and net worth also likely have higher spending limits on credit accounts, meaning perhaps lower-income people would spend more if they could access funds. Credit scores (as a measure of creditworthiness) and income are very weakly correlated. But high income and access to credit, as well as improved rates of loan approval, are more closely related. In turn, access to credit has a positive effect on individual income and financial outcomes, especially for the self-employed.
Some concerns emerge around data privacy, and the amount of data that such tech-platform partnerships require to be exchanged or shared, often with minimal customer understanding of those agreements. When purchasing, vetting credit risk, establishing rates, extending offers, and servicing consumer loans are spread out over many companies, the risks of data breach and negative consumer impacts rise.
Like any financial tool, small-credit lending can be used wisely or recklessly. For a significant amount of the population though, these new, often AI-based, data-heavy lending tools can expand opportunities. According to federal data (PDF), people outside the racial majority have significantly less access to credit, are less likely to apply for traditional credit, and are more likely to be turned down when they do apply. Recent immigrants and young people just starting out also may have trouble establishing credit, regardless of their responsible financial habits.
One of the great leaps forward of AI/big-data-based lending has been the novel types of data that can be considered for creditworthiness: if you’ve never had a credit card, loan, or mortgage, but you do have top-notch Etsy ratings, a regular flow of PayPal customer orders, and the UPS receipts to prove you’re doing a brisk trade, small business funding may become available to you when it wasn’t before. The politics of access to capital — who has it, who gets it, who controls it, who decides who’s worthy — have moved off the desk of a mid-level bank branch manager and deep into an algorithm, which can consider millions more data points. Insofar as this frees the question from personal bias, it’s a step forward. But all too often, the original biases or discriminatory practices simply become encoded in the AI algorithm, which then lends a veneer of objectivity.
Overall, the proliferation of lending tools for small purchases, and the expanded access to credit they represent, are likely a win for public choice, economic freedom, and individual empowerment. But, as ever, individual responsibility and responsible business implementation will matter a great deal.