Payments and Big Bangs

I’ve long been surprised by the great respect given to the field of economics.  To be sure, it is an important field of study filled with incredibly smart, engaged people.  But it doesn’t exactly rise to same level of the sciences, which emphasize reproducible results without human interference.  Economics, by contrast, is largely tied to the randomness of human behavior, which gives rise to trenchant observations like this one from John Kenneth Galbraith:  “The only function of economic forecasting is to make astrology look respectable.”

I also have enjoyed this quote about economics I heard years ago – I think from George Will:

“Economics is the study of single instances”. 

This captures the deep thinking that often follows, but infrequently precedes, economic occurrences.

And that brings us to mobile payments.

We live in a time when payment forms are changing.  For those not in the payments industry, it is hard to overstate how seldom the words “change” and “payments” are found together in the same sentence, apart from referring to the return of coins to a shopper.  The payments industry has generally been impervious to innovation, as evidenced by the archaic plastic card, upon which is emblazoned your full name and entire sixteen digit account number for all to see.

Additionally, it is highly regulated. Regulation creates process, process creates predictability, predictability provides confidence to consumers, which in turn stimulates merchant acceptance, which ultimately drives commerce.

Changing a payment system in a developed country like the U.S. can be as complicated as changing physical infrastructures like electrical outlets or gas stations.  So changing payments is hard work indeed, but there is a crack in the mighty fortress of payment stasis which has bankers interested in evolution and disrupters interested in revolution.

It is natural, therefore, for people look for examples in order to make sense of an inherently unpredictable future, and there are two payment innovators that are routinely cited in the industry – one in the U.S., and one in an emerging market.  These two examples are frequently cited in the payments industry, but I believe they unintentionally obfuscate rather than enlighten.

The first, PayPal, has become a household name in the U.S. and around the world.  First, consider the equity inherent in the phrase “household name”.  Although PayPal is without a doubt an incredibly innovative company (with more innovation on the way) the company is a product of highly improbable events which are staggeringly unlikely to reoccur.

Those events include the rise of eBay and a new class of merchants and shoppers that needed a method of conducting small transaction commerce.  Secondly – and this is a big one – the banks didn’t want anything to do with these eBay buyers and sellers, who they viewed as unprofitable and risky, so they didn’t compete with the nascent PayPal until they realized they were ceding the lower end of a high-growth market – something Clayton Christensen has written about.  Third – and I don’t think this should be underestimated – the name “PayPal” became the embodiment of new-age cool (like this), and consumers who had more than enough financial accounts in their lives jumped on the bandwagon, and with the rise of Amazon and other virtual shopping experiences they had an immediate use of their accounts, .

Pretty awesome for Peter Thiel and the PayPal gang.

If we look at Square, which is new payment disrupter with big aspirations, we don’t see the banks taking a laissez-faire attitude.  Both banks and their processing partners are quick to jump into the fray and try to deny Square the oxygen that they provided PayPal a decade ago.  Examples here and here.

The second example of a single instance is M-Pesa.

You can’t talk about mobile payments without looking toward Africa and Asia, where the action really is.  There are few things in payments that fire up both the head and heart like the idea of financial inclusion in developing countries.  Bank branches are hard to find in many population centers, and most of the world’s poor deal in cash, which is complicated and dangerous to maintain and move.

Additionally, apart from micro-lending programs like Grameen, the world’s poor are cut off from small loans.  However, while the world’s poor may lack access to banks, they do have one thing in plentiful supply:  mobile phones.  It is this promise – of turning cash into electronic currency and using the mobile device as a means of storing and transferring wealth – that has everyone from Bill Gates to Bill Clinton enthused, and Kenya’s M-Pesa service, which enables users to store and move funds with their mobile phones, is often held up as an example for how other countries can experience the same success.

Like PayPal however, M-Pesa was the beneficiary of a set of unique events that will likely never occur again.  First, prior to M-Pesa’s launch, Safaricom (M-Pesa’s operator and joint owner with Vodafone) had a de-facto monopoly in the Kenyan market, so when M-Pesa was introduced it immediately avoided one of the biggest problems in money transfer programs:  interoperability.  Getting one network (or bank, or whatever) to agree to a financial transfer program with another network is…um….difficult.  With this in mind, you can see how much easier life was for an M-Pesa user to know that roughly 80% of all other Kenyans had access to the same system.

Secondly, just like PayPal caught the banks napping, so too did M-Pesa catch regulators napping, which reduced the friction associated with establishing and using these new accounts.  Finally, Kenya had unique social issues such as large migrations of workers from villages to big cities, the associated need for money transfers back to the villages, and the unfortunate levels of physical violence that befell travelers with cash.  These events, plus others, made the Kenyan example a single occurrence from which little deep insight can be derived concerning how this will play out in other emerging markets.

Are there insights to be gained from these two examples?  Certainly.  Both represent a treasure of empirical data – user behavior, ecosystem development, etc – that can provide us with some interesting insights.  But you cannot extrapolate a curve with a single data point, or like James Gleick wrote, “Clouds are not spheres.  Mountains are not cones.  Lightning does not travel in a straight line”.

The path forward for mobile payments is unclear, although the payments industry continues to look for models (such as this one) that can help predict what comes next.  I have my opinions, but that’s for another time.

I will, however, pose this question:  what other examples of similar “single instances” can you think of where innovators place too much stock in a one-time event?