Myopia vs. Mastery

It is the power of the mind to be unconquerable. – Seneca

What’s that? You want to talk about the future of intertemporal choice in the age of automation? I thought you’d never ask.

Look around at all the humans today, making decisions for themselves, perfectly optimizing their choices, weighing their actions against the utility it will bring. Rational beings we are. A cold, calculating species, unhindered by emotion. Perfect economic agents without the slightest inconsistencies. What Richard Thaler calls “Econs”.

Or at least we’ve been modeled that way. This is where actuality and academics collide. Where the avocado toast for $13 now, is more appealing than than the $1.50 avocado and $2.00 loaf of bread at the store, waiting to be toasted at home in the future (three sections in and already with econ avocado toast jokes?). The reality is much more sober, and the implications far reaching. It touches policy decisions like, are we making healthy choices? Are we saving enough for retirement? Are we optimizing our finances?

For many of us, the data says no. And at the heart of the problem is that many of us, despite having all the data, despite knowing full-well the consequences, fail to optimize trade-offs between different points in time. We are present biased.

Everyone of us is locked in a battle. Our present self versus our future self. Myopia vs Mastery. We’ve all been there, whether it’s a work assignment, an errand, an outfit for an event, or an article deadline (present company). We will put off the task until the latest possible moment. Behavioral economists refer to people as either a sophisticated or naive agents. The sophisticated agent understands that she will change her mind in the future and optimizes based on this assumption. Conversely the naive agent does not realize she will change her mind in the future, assumes more self control that reality affords and truly believes that her future self will follow through on her plan. The naive agent wants to do one something, expect to do it, but actually choose to do another. This procrastination leads to a failure to optimize according to one’s own preferences.

In short, we’re flawed, we don’t act rationally, and that wouldn’t be a problem per say, in the short run. The trouble is that slight impatience in the short-run, implies absurd impatience in the long run.

Add to that the magic of compound interest and we’ve got a problem on our hands.

Nowhere are the stakes more dangerous for this misbehaving, than when debt and interest are involved. Leverage and the lackadaisical should not mix.

Enter credit cards, or revolving credit, which is perhaps a better term (who uses physical cards anymore now that Amazon Prime delivers the farmer’s market to you without the need to slide a three inch piece of plastic through the square terminal attached to the phone of your local craft humus purveyor?) You know how the Consumer Financial Protection Bureau (CFPB) describes credit cards? The largest and most complex market of any financial product. According to the data, the average household has $130,922 in debt, $15,762 of which, is in the form of credit cards. As if that wasn’t scary enough, cohort analysis of 2003 and 2015, point to increased debt between two groups over the time period. No not millennials. Those 35–55 and 65 and above (apparently if you’re 55–65 you don’t go out). I won’t bore you with the details (the rise in the cost of living has outpaced income growth over the past 12 years, while the average household is paying 9% of income on interest).

Wait, but all my friends are smart, they’re opening Chase Sapphire cards, hacking points, and flying to Southeast Asia for free, you might say. Ah, but remember that part about not optimizing for the future? Here’s the part where I hit you facts. Nearly half of all credit card users (43%) carry a balance from one month to the next. Every tenth of a second, a credit card late fees is charged, costing Americans $11 billion each year.

There is now more than $1 trillion of revolving consumer debt in the U.S. $1 Trillion, let that sink in.

– Bill Malloy, Founding General Partner, Sway Ventures

For many, debt becomes a trap. Unable to make progress against APR’s in the high teens, they turn to balance transfers, or consolidations as a means to end debt. The only problem with those options, is their ability to act rationally. They cannot put their future self first. In a recent study of consumers with credit card debt, 70% of those who transferred balances or consolidated debt were in the same or worse position than they were three years prior. In fact the average credit card debt among these individuals nearly doubled. Perhaps that’s why 81% said these theoretical solutions actually make it easier to accumulate more debt.

This is nothing new, businesses have always been capitalizing on our procrastination for a while. (Cough, cough…Equinox gym membership). Entire industries are built around maximizing their profit due to our inability to optimize choices. It seems to many that the credit card system is engineered for consumers to fail, holding them in debt, and creating a population of “revolvers” — someone who takes out a large balance and then makes minimum payments over time vs. paying off the balance in its entirety.

Whether it’s teaser rates or seductive points systems, the game is rigged against us.

Here’s the part where I tell you it’s going to be fine. But I’m not, humans have had their chance, and despite their best efforts, they cannot move out of myopic thinking.

My advice? Do nothing, let the machines sort it all out.

The solution to all this fiscal irrationality is to remove choice from the equation, to remove the human from the equation.

Automation doesn’t have emotions, it can calculate and optimize future states nearly instantaneously. Automation isn’t biased towards the present, it doesn’t procrastinate, it doesn’t bargain with its future self. It’s ideally suited for decision making, for intertemporal choice.

It is possible to design better outcomes. Some call this “nudging” and it’s having its moment of late with policy makers. So let’s design our own system right now for the credit problem.

First we’ll need some guidelines. Ask an economist, and we’ll likely say three three key components of crafting an ideal “nudge” policy are: 1) automated enrollment, 2) automated escalation, and 3) good defaults.

Automated enrollment: we’d need to have people sign up for a service that uses automation to enroll them into the optimal decision. Software can optimize this, but we should also utilize it to actually make the choices, not just offer them up as suggestions (we all know how that will go).

Automated escalation: next we should have the system respond to the decisions (whether good or bad) of the person making them. We can’t assume people will curb their desire to utilize credit for purchases, and we don’t need to. Our focus is to optimize the payment structure of the credit. Again software optimization can help us here

Good Defaults: lastly the system should default to the ideal optimization patterns as well as provide the ideal solution tailored to the individual.

If only there were a company out there that could incorporate these three pillars of policy. Oh wait, didn’t we invest in this company called Tally? That’s right. Tally makes it easy to stay on top of credit cards. Scan your cards, and they give you a line of credit to help manage all the payments, and put automation to work.

And today they came out of Beta with some amazing results. Of the several hundred Tally Beta users, an impressive percentage are exhibiting smarter behavior with their credit cards. 40% of users pay Tally’s recommended payment amount (can you say automated enrollment?), on track to pay down their balances in two years or less (you’re welcome future self). In fact 81% of Tally users pay more than their minimum monthly payment (the average user pays 13x that minimum), expediting their path to being balance-free (that sounds a lot like automated escalation). Users who follow Tally’s recommended payment strategy, save on average $8,000 in lifetime interest charges and paying off their balances on average 7.9 years faster (you guessed it, good defaults). 30% of Tally’s users don’t carry a balance and leverage Tally as an easier way to stay on top of their cards, negating the need to fret about multiple due dates. These users continue using their cards, racking up perks and rewards, and Tally takes care of managing their bills. In fact pretty much everyone reported that Tally makes them feel more confident when managing their credit cards (thanks software automation!).

The key difference between Tally and other personal finance management apps is that Tally actually does the hard work for you. It makes decisions.

Rather than telling users what they can or might do to manage their credit cards, Tally eliminates the anxiety associated with credit cards by actually managing your cards and payments. Automation is the key to Tally’s app, applying an advanced algorithm to make the right payment, to the right card, at the right time, helping you make the most financially optimal decision and pay down your balances as efficiently as possible. Leave it to two University of Chicago, Booth School alums to pioneer “automated paternalism” (Thaler and Levitt would be proud)

Download Tally, complete the signup process, your future self will thank you, and might even make you that avocado toast you’re craving right now.

Originally published at swayvc.com on June 20, 2017.