Fintech’s Quantum Leap
By Roxane Googin, Chief Futurist, Group 11 and Dovi Frances, Founding Partner, Group 11
“Theorizing that one could time travel within his own lifetime, Dr. Sam Beckett stepped into the Quantum Leap accelerator and vanished…
He woke to find himself trapped in the past, facing mirror images that were not his own and driven by an unknown force to change history for the better.
His only guide on this journey is Al, an observer from his own time, who appears in the form of a hologram that only Sam can see and hear. And so Dr. Beckett finds himself leaping from life to life, striving to put right what once went wrong and hoping each time that his next leap will be the leap home.”
Quantum Leap, Opening Narration
Turning up the dial
If the rapid digitization of commerce brought on by COVID has moved us years into our digital future during just a matter of months, it is relevant to ask “where are we now”? While many facets of our new life have grown to seem normal day-to-day, we need to appreciate that in a post-COVID world we will actually be strangers in a strange land, operating in an environment so altered we don’t truly comprehend the change. This disconnect is most evident in equity markets where certain valuations seem to have no upper bound, implying a sudden appreciation of the net present value of their future cash flows. In response to these violent moves, people are putting on their tin-foil hats and yelling “Bubble!” But perhaps, the markets are telling us something.
While excessive liquidity intended to ameliorate the economic impacts of COVID shut-downs on entry-level workers has certainly found its way instead into stocks, it is also reasonable to believe well-placed companies are indeed much more valuable than they were in January because their revenues and competitive position has suddenly strengthened. To explain this, we will review the steps, starting with how the mechanics of raising the “abstraction layer” via automation supercharges productivity. Next we will highlight how this broader automation rush should turbocharge the fintech space specifically in 2021.
While the legacy financial system is clearly entrenched, the unprecedented digitization of all operations in response to COVID is set to finally change how payments are made. When e-commerce was 10% of sales, kludgy legacy payment systems that sort of worked were acceptable. However, when that needle moves to 50% and more, slowing everything down just to facilitate an aging payments infrastructure will become unacceptable. This should become painfully evident in 2021 as we re-open to a new landscape.
The Hidden Automation Explosion
One aspect of the post-COVID landscape people seem to under-appreciate is precisely how deeply digitization will have seeped into all operations. Before COVID hit, automation was a nice-to-have business owners would get around to when they had the time. Everyone knew it was coming, but it could come tomorrow. WIth COVID, automation suddenly became what you do to stay viable. As we moved to a war-like footing all barriers to adoption were dropped like a hot iron as manual processes had to be replaced immediately. This was evident beyond retail, including historically automation-resistant verticals like fulfillment, education, healthcare and payments. Looking forward, what people do not seem to appreciate is that once the pressure of COVID gets lifted from the economy and people try to return to “normal”, this economic landscape will be barely recognizable.
While we are all adjusting to Zoom calls and food delivery at an individual level, the combined impacts of these newly automated processes on a mass scale are sure to be profound by next summer. But operating in our little COVID bubbles, we cannot see this happening. For instance, in education once a critical mass of classes are recorded, what new revenue models could educators leverage to broaden the reach of their intellectual property? In health care, how can recorded sessions and constant symptom recording be used to track disease progression as well as to save doctors’ time? What does the novel data sharing strategy used in COVID vaccine development mean to future drug pipelines? In fulfillment, what will the learnings of this holiday crush mean for future operations? In commerce, what does the rapid expansion of e-commerce mean to access to credit and digital payments as well as to overall business efficiency?
The Automation Chain Reaction
The common ground between these sectors, as well as others that have newly automated such as agriculture and other forms of production, is that automation is not an end in itself, but rather the first step in an economic chain reaction. Importantly, we have just lit the fuse. Once operations are analyzed and made repeatable enough to automate, the next step becomes a new level of orchestration and “abstraction”, along with superior data gathering and optimization.
In computer science, an abstraction layer is the point at which a compute task can be done with an API (Application Programming Interface) call rather than by completing smaller labor-intensive manual programming steps. Economically, once a manual function gets abstracted into an API call, the system gets much more productive as all the cost and uncertainty of performing low-level manual steps suddenly vanishes. At that point, true scaling can begin. What automation does is to essentially retrofit historically variable manual steps into a repeatable equivalent of an API call that can then be scaled via a higher level management platform, erasing all the random noise that tends to jam progress. This parallel between computer science and manual operations is but another example of “software eating the world” as digitization reforms the physical world in its own image.
The Economic Shift: Winners and Losers
This one simple act has significant economic ramifications. Once a function has been simplified and commoditized to the point it can be automatically repeated, it becomes a commodity because individual efforts no longer make any difference as long as the API call works. Instantly, all manual value-add vanishes and that low-level effort becomes completely subject to the dictates of supply and demand. Indeed the whole point of automation is largely to commoditize and standardize those efforts for the sake of larger system efficiency.
Importantly, the value-add that once accrued to those manual steps moves up to the API layer, where the collective productivity improvement becomes evident. Essentially, the devaluation of the lower-level steps accrues to the vendor getting more done for less by making the API call. This is why software platforms become so valuable while the value attributed to manual business processes supporting them keeps falling. In this world, the overall economy gets more efficient as manual waste is reduced while platform owners like Amazon do better than their third party sellers and Uber does better than their drivers. It collectively hurts small businesses and / or drives income inequality in the name of overall productivity gains. COVID has accelerated this trend.
By automating business processes like their hair is on fire, businesses are collectively devaluing equipment and labor beneath a new and higher abstraction layer across the economy while simultaneously turbocharging productivity. Because this is happening everywhere and all at once at an unprecedented rate, the economic impact over the next few years will be quite significant, and if history is any guide, quite mis-understood by economists and our Federal Reserve. The true impact of this aggregate move should only become broadly apparent after we quit focusing on COVID and try to return to a “normal” life that no longer exists. This is what our markets are telling us.
The Data Imperative
But wait; there is more! Along with owning APIs and controlling downstream inputs, the API owner also gets to collect data. As we focus on COVID remediation, data collection is silently growing at an alarming pace, everywhere you look. The owner of this data gets almost supernatural powers of prediction and coordination. While even the small business that automates collects significant data in the process to the betterment of their bottom line, the eye in the sky that watches all those newly automated businesses from their platform perch gets exponentially more benefit. Data becomes so valuable, it becomes profitable in the long term to give away the core commoditized services just to collect that data. This is in a sense the business model of Google and Facebook.
The FinTech Imperative
As we all madly automate, one aspect that permeates business still holds us back. That is payments and credit, a very critical last-mile piece of the puzzle. Our financial system is largely out of the 1800s, with patches that have dragged it forward at least until 2008. But it remains a rigid, slow, data-starved and expensive impediment to conducting business as transaction costs are high, money flows are slow and credit remains scarce. As the rest of business processes automate, these weaknesses should become glaring. In a world where savings are so excessive that $17T of bonds have negative yields, it is inexcusable that up to 50% of domestic small businesses lack access to credit and that 14M Americans lack even a bank account. It is inexcusable that in a world where 50% of Americans live paycheck-to-paycheck they have to pay a 2.5% transaction fee for online purchases. Credit cards were cool in the 1960s when they first appeared, but these fees are inexcusable in a world where everything else moves at both the low cost and high speed of API calls.
In short, post COVID, financial services will need to operate at internet speed and scale, just like everything else. What we need are low transaction costs, instant transfers and smart credit availability suited to the dynamic capabilities of the borrower. Accessing these services needs to be as fast, simple and secure as the rest of the digital transactions they intermediate. In short, finance needs to move to the 21st century, and soon. Importantly, it will take a broader revolution of the order we envision to truly up-end this entrenched model.
The FinTech Cambrian Explosion
If banks and credit card companies are not adjusting to an online world, fintech vendors are filling the void. The airwaves are getting saturated with offers of friendly financial services delivered over your phone. PayPal offers free payments via Venmo with the help of Plaid, while also inching into credit with their own credit card and free multi-payment service. Affirm and Sunbit also offer instant credit at the digital and physical points of sale, respectively. Both Stripe and Plaid reduce banks to the dreaded API call. Square offers Square Card and Square Cash. Robinhood traders are moving stocks. Everyone wants to be the next Ant Financial. Even Bitcoin is experiencing a resurgence as an inflation hedge and a sure-fire way to deliver cheap transactions at global scale. Square CEO Jack Dorsey calls it “The currency of the internet.” . Slowly but surely, the barbarians are gathering at the banks’ gates. Money will move and credit will be offered a thousand new ways. As we step through the looking glass into an automated digital world, the legacy manual banking and credit system is getting left behind.
The True versus Fake Revolution
However, these restlessly gathering forces are peering through the fog to a currently unknown future. Like the six blind men and the elephant, they are grasping onto part of the problem as if it were the whole. The current strategy is often to replicate or extend part of the existing banking structure, but ultimately many replicate and amplify the core structure of the legacy system under a pretty new face. They use the old system as an API call while extending the reach of that system literally, through cell phones instead of branches, as well as logically, by offering new features. But at the end of the day, the result is a better version of the same product; payments and credit. Because it is recognizable, it has not truly replaced the old system to better fit a radically new present.
The Fintech Disruption
True disruption appears not as a better version of a legacy product, but as an unrecognizable offering that obliterates the old value proposition. Frequently, the output of the old system gets offered for free as just one of many inputs to the new, higher order system. This is what higher abstraction layers do. In this case we expect transactions to be immediate and free, while credit becomes a feature not a product. Instead of faster-cheaper transactions and credit, the product will operate at a higher abstraction layer using both payments and credit invisibly as part of a larger solution of managing for larger business outcomes. Instead of just getting you a loan that may turn into a problem, they will help you save, budget and retire. This new layer is what grows a TAM as it becomes a self-referential system that actually modifies its environment. In this case fintech can improve the creditworthiness of the user rather than just extending them occasional (and expensive) credit they may not be able to handle, unlocking previously stranded resources and growing the entire economy.
And yes, the data this system collects will pay for giving those transactions away instead of charging 2.5%. But in addition to offering services for free, the data these systems collect through use gives them x-ray vision into creditworthiness unimaginable in today’s manual environment. They can also intervene to improve credit worthiness by changing behavior for the better, either with a carrot via nudging or gaming cues, or through a known stick via their outright ability to take a slice of cash flows. It is this magnitude of letting go entirely of a successful existing business model that makes disruptive change so counterintuitive and difficult.
Higher Level Goals
An example of this type of disruptor is Shopify. Shopify is shaping up to be a huge new fintech winner. In their quest to “make commerce better for everybody” they stand to commoditize both payments and credit as we know them as those products become tools in a larger toolbox of running a store rather than ends in themselves. Note how their goal is not to “make credit cheaper”, but rather to “make commerce better”, using both higher-level software and the data they collect. Importantly, this higher level goal enables them to attract the needed critical mass of both users and data, fueling a flywheel of growth.
Importantly, this strategy gives Shopify two critical advantages in extending credit. One, is they improve the creditworthiness of their user-base by helping them manage their business better. Two, they know everything that their customers are doing in real time, to the point they can do aggregate and individual trend analysis to predict the success of future operations with great accuracy. Compared to this, banks are flying blind as they only have a few forms, faxes and individual hunches to work from. The collective impact can be transformative.
Group 11 Investments
Group11 has focused on fintech platforms since 2014, and now their time has come. The portfolio contains several clear platforms, as well as some growing extensions. The platforms include; Tipalti, TripActions, HomeLight, Papaya Global and Lili Bank. Extensions include; Next Insurance, Sunbit and EquityBee.
Tipalti works at such a high abstraction layer that their very name literally means “I handled it.” Accounts payable and remittance has historically been a back-office rat’s nest of manual processes, made more difficult by a lack of payments standards. By forming API-level agreements with most conceivable payment systems and giving businesses a birds-eye view of the entire process, Tipalti becomes a classic abstraction layer. From there, businesses can measure the efficacy of their payments cycle. This agility has suddenly become necessary in a largely automated world.
TripActions has done the same to travel. They have automated the painful and aggravating manual steps we all just accepted as part of booking and expensing a trip. By reducing those steps to API calls and presenting a data-filled front end to users’ phones, TripActions has brought travel into the 21st century. Rather than booking flights and hotels, TripActions simplifies travel.
HomeLight works to do the same for home buying. While home buying platforms have historically focused on improving one aspect of home buying, the overall process remains difficult. Just seeing random listings or paying lower commission does not mean a seller gets the best overall price, or the buyer finds the house they really wanted. Even finding an acceptable sale does not mean the needed cash is available. Indeed, buying a house is a multi-variable puzzle that needs to be optimized at a higher level. This is exactly what sets HomeLight apart.
Lili Banking similarly simplifies life for gig economy workers, a group that should grow even more quickly in a post-COVID world as legacy enterprises struggle to adjust. More than a source of affordable credit, Lili becomes a “pocket MBA” by helping independent contractors manage all aspects of their business, Like Shopify, Lili addresses a larger question than “how do I manage cash flows” but rather addresses “how do I intelligently automate my entire back office so I can focus on my work.” Importantly, independent businesses, now matter how small, need all the automation of larger businesses in order to thrive. This is essentially what Lili offers.
Somewhere between a platform and an extension, Next Insurance both extends traditional insurance offerings via a cell phone interface, and aggregates low level options into a higher abstraction package. While the act of buying insurance remains recognizable, the process is vastly improved because they seamlessly aggregate a myriad of maddening options into one optimized and affordable offering. Importantly, the insurance industry is vulnerable for the same legacy reasons banks are vulnerable; they are expensive, slow and data-poor. In this environment, Next becomes a very important partner.
While extending credit into four easy payments at the point of sale is the new fad, Sunbit goes further. They help ensure the buyer can afford the transaction. Just getting instant credit can get many buyers into trouble. The Sunbit platform screens buyers for their ability to pay and has known enforcement capabilities via access to their debit card account. In this way, Sunbit moves beyond a mindless front-end that can become a trap, to actually helping critical transactions get completed end-to-end, again by altering the credit cycle — allowing over 100 million Americans access to credit for non-discretionary expenses.
A Virtual Economy Reinvention
As we emerge from COVID, we should expect much more than any return to “normal”. That world is gone. Instead, as business activity heats up in the spring we foresee a surprising lurch into a highly automated future where business becomes frictionless and intelligent. While everyone madly automated to survive COVID, what they really did was to set the seeds for a new and shockingly productive economy overall.
But one fly in the ointment remains our antiquated banking system. The problem is that the high transaction costs and poor credit offerings from this legacy system are becoming not only more glaringly evident as the rest of the system streamlines, but literally an increasingly unacceptable final impediment to progress. Financial services are supposed to grease the gears of business, not throw sand into them. To improve this situation we need to automate both the credit and payments process by commoditizing the steps then automating their sequence under the guise of a larger platform.
Into this gap is jumping a Cambrian Explosion of fintech companies, ranging from new front-ends to existing products, to platforms that strive to solve higher level problems. True disruption accrues to the historically unrecognizable higher level products. In the process, legacy products become commodity features rather than ends in themselves. The next generation fintech winners will solve problems like how to run a business or how to retire in 20 years. With low level task automation and superior data collection, historic imponderables become realistic solutions to the betterment of everyone.
