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Building the Unbuildable

An interesting concept in architecture is the idea of “unbuildable buildings”. These are designs that when once finished would be able to stand on their own as sustainable structures yet cannot be built as the intermediate steps needed to create them are not technically feasible.

A good example of this may be a building that rests on concrete pillars in a wavy sea. Once built this may be a beautiful and stable structure, but if the intermediate step of pouring concrete into the sea and letting it solidify is not technically possible it cannot be built. Only as technology improves and develops sufficiently, pouring concrete into the sea may become possible, at which point the building can then be built.

Another example could be a colony on Mars – while a fully functioning dome with solar panels and atmosphere control could be a sustainable and self-standing structure, the intermediate steps of setting up a construction site on Mars and shipping workers and materials there is not economically and technically feasible, at least not as of yet.

Suburbia 3.0 – Reserve your spot today

The same concept actually exists in the world of evolution as well. There are theoretical organisms that could possibly exist in our world, yet do not because the intermediate steps needed in their evolution were not possible. Put another way, any species that exist today (e.g. birds) do so because each step in their evolutionary journey (e.g. developing wings) was sustainable. Prior to wings, the ancestors of today’s birds developed wing-like appendages that enabled these bipedal species to leap higher into the air, and thanks to whatever small advantage that gave them, they were sustainable as an intermediate step to developing the full-fledged wings of today. If the intermediate steps had not been sustainable, wings would not exist.  

There is clearly a very interesting parallel here for the startup world. A founder’s end vision for their company may very much be possible, but if the intermediate steps needed to build the company from zero to one are not possible, the founder may never reach their end vision. These intermediate steps may not be possible for a whole host of reasons and include the current state of technology, availability of financial infrastructure, the funding environment, and the applicable legal and moral rules, to name just a few.

For example, if the intermediate step of creating the end vision requires a multiyear journey with heavy losses and lots of big investment along the way, that particular company may not be buildable in a bad funding environment, but could in fact be built in a situation where there are deep pocketed investors willing to fund these losses for many years. Similarly, if the technology or regulatory license needed is impossible to obtain for a small company, until the regulatory environment or technology improves, the company cannot be built.

The big takeaway here is that for a founder to have an end vision that is self-standing and sustainable is not enough. The intermediate steps needed along the way also need to be self-standing in their own right, and the founder has to pay very close attention to what those steps are.

By extension, successful founders are those with a very keen eye for changes in these constraints. Things like infrastructure, regulations, and funding environment are very much dynamic and in constant flux. As laws change, new technologies become available, or central banks decide to pump trillions of dollars into an economy, previous constraints may suddenly be lifted. The best entrepreneurs are the ones ready to pounce quickly when they sense these changes that make their previously unbuildable visions buildable.

To illustrate this point, an interesting example worth taking a deeper look at is the building of a new exchange for residential real estate investment properties. Known as buy-to-let investing in the UK, these are the kinds of properties where landlords buy them to rent them out for a profit.

Currently this is a fairly illiquid market, and rather than being traded on an exchange, it is traded in one to one transactions where buyers and sellers find each other via property listing sites such as Zoopla (which are a big improvement in their own right as in the past one would have had to go to the listings sections in newspapers). Once buyers and sellers find each other (after lots of viewings) and agree on a price (after tense negotiations), it may still take weeks, if not months before the transaction actually closes. When all is said and done, the process will have involved real estate brokers, lawyers, viewings, tons of paperwork, and lots and lots of costs for both sides.

Contrast this with somebody that has invested in a company via the stock market – they can buy and sell their shares instantly because the ownership certificates (shares) are standardized and their trading is regulated by the exchange (e.g. London Stock Exchange). We can think of these standardized certificates as “securities” and the process of taking a non-standardized, clunky asset and turning it into an easily tradable security as “securitization”.

But why should one not be able to “securitize” buy-to-let investing? The end vision is surely feasible with today’s technology: Each property could be owned within a legal structure (a company) with a standardized legal contract.  Then the shares in those companies could be traded on a big exchange that lists thousands of those companies with standardized and regulated ownership structures, and one could browse and filter properties, make an offer online, and trade it with a few clicks. While this process may still not be instantaneous like buying stocks today, the time to transact may nonetheless be cut down from the months and weeks that it takes today to days or perhaps even hours.

One obvious difficulty here is the intermediate step of bringing together the supply and demand (the buyers and sellers of property) under one roof on day one. If there is not enough supply then the demand will not show up, and vice versa. Hence, the entrepreneur that wants to build this new exchange will have to find a way to solve this conundrum by bringing the sellers and buyers onto the platform in incremental yet sustainable steps. If this can be cracked, the pot at the end of the rainbow surely is full of gold: buy-to-let properties represent an asset class of GBP 1.2 trillion in the UK alone and are currently housed in very illiquid structures. Solve the intermediate step, and the end vision is yours for the taking!  

To summarize, having the courage and stamina needed to be an entrepreneur is one thing, but the best founders also need to be the kind of visionaries that see changes as they are about to happen, understand how those changes enable cracking the difficult intermediate steps, and imagine what kinds of future structures all this enables. With that kind of vision, what was once impossible and in the realm of science fiction, becomes reality.

To Lend or Not To Lend

Over the last decade many fintechs have contemplated this very question, with some choosing to lend, some choosing not to, and yet many others ending up in the undiscovered country from whose bourn no traveler returns as a result of doing lending badly.

When dealing with such existential questions, a simple framework can be of great use, so let’s examine one here, with some real-life examples of each instance where it makes sense or not to embark upon a lending journey.

In the simplest of terms, the economic equation from lending can be described as follows:

Π = NPV(Y) – X  where

Π = Profit from lending

NPV = Net Present Value of future cash flows at the firm’s cost of capital

Y = ( [Interest + Fee Income] – [Interest + Fee Expense] – OpExCost – Losses)

Χ = Customer Acquisition Cost (CAC)

So in simple terms, a firm can expect positive economic profits from lending if it is able to charge its customers interest and fees that exceed all its expenses which include cost of funding, operational expenses, losses from credit and fraud exposure, and customer acquisition costs including all marketing expenses.

Now, it is very important to keep in mind that this equation exists in the context of a very competitive market, and in striving to generate a positive profit from lending, a firm will be competing with others that are trying to do the very same thing. Much like the story in which two campers come across a bear outside their tent, the key to survival is being able to run faster than their fellow camper even if one cannot outrun the bear. 

In other words, to embark upon lending successfully one needs to have a competitive advantage in ideally all (being able to outrun the bear), or at the very least one (being able to outrun the other camper) of the key areas outlined in the equation above.

We can now look at some real-life examples from each of the categories.

Traditional players like banks have a clear competitive advantage when it comes to cost of capital given their vast branch networks where they hoover up deposits at close to zero marginal funding cost. A tech enabled fintech may have an advantage when it comes to operational cost given state of the art infrastructure that automates many manual processes. Players like Capital One used vast databases and superior analytics to keep their losses low relative to their interest income, in other words data mining pockets where the risk reward equation was superior. Yet other players may have found superior customer acquisition tools by virtue of a unique partnerships or value propositions to their customers.

Interestingly, while having a competitive advantage in some of these areas is a prerequisite for not being eaten by the proverbial bear, it does not mean that going down the path of lending is the best decision for that particular firm. Playing in just one aspect of the value chain may in fact provide a higher return on equity than lending which is capital intensive.

It is hard to run faster than a bear

Let’s take the prior example of a fintech company that has the infrastructure that enables it to originate and service loans at a lower operational cost compared to anybody else. It may in fact be more profitable for that company to outsource its origination and servicing technology to other players, thus being an infrastructure provider vs an actual lender itself. QED’s portfolio company Amount is a great example of this very case.

Another example would be a company that has a clear advantage in customer acquisition costs. Rather than using this to become a lender, the company could become a loan originator or broker, and originate loans for lots of other lenders. Again, from CreditKarma to Capitalise, there are many examples in the QED portfolio of companies that have adapted this approach.

So, to summarize, founders that are thinking about taking their company down the path of lending first need to ask themselves if they have a competitive advantage in any of the key areas needed for success. If the answer is affirmative, then the next question is to determine if the company is better off selling its unique skills to the broader market, or becoming a lender itself. The answer to this question is to a great extent determined by how tradable those skills are: licensing tech infrastructure, or a loan originator selling leads to a lender is relatively easy. On the other hand for Capital One to transfer the complex analytical framework it has developed over the years is somewhat harder and likewise it is hard for a big banks to “sell” their cheap cost of funding (though they can monetize their advantage in other ways, by for example becoming a wholesale funder of other smaller lenders).

Finally, let’s look at a few examples where it does not make sense to become a lender. One example that we have often seen is when founders mistake having good data scientists as a sufficient condition for being able to create a good risk reward equation (interest income relative to credit losses). While having good data scientists (or statisticians as we used to call them back at Capital One) is undoubtedly a crucial ingredient, it is by no means enough in and of itself. The models and scores that are produced by the data scientists need to be placed in a wholistic business context, where the business analyst takes the model output and determines where to make the right cut offs and tradeoffs. For example, a data scientist with a model can produce an expected fraud probability score for a credit card transaction, but a business analyst needs to determine the optimal threshold where a transaction is declined or approved taking into account the business impact of false positives as well as false negatives. In other words, credit is a culture, not a model. Building the right organizational structure to get it right is not easy.

Another example that comes to mind are companies trying to engage in what could be described as “multiple arbitrage”. The classic example of this is a fintech start up (for example a mortgage broker) that gets allured by the high revenues that lending can provide, and starts lending, hoping that it can attract a tech multiple on its lending revenues. While this may work with some investors initially, if the company does not have a competitive advantage for lending in at least one of the key areas, the bear will catch up with them eventually.

Leave No Business Behind – Capitalise’s Covid Response

More than half a year into the Covid pandemic the grim toll on not just lives but also mental health and our economy continues to build with no end in sight. There will surely be much accounting to be done in terms of which responses were right and which misguided, with many learnings and lessons for the future. Part of this post mortem will surely also include how various business reacted, and what they did to help their respective communities.

In that spirit, Capitalise (which is also a QED investment) constitutes a very interesting case study as the team very much found themselves in the eye of an unexpected but nonetheless perfect storm.

By ways of context, Capitalise works with accountants to give them the tech enabled tools to better serve their small business clients. These tools are varied, but many of them center around helping the small businesses get the funding they need to grow and prosper.

Shortly before the pandemic was yet to hit, Capitalise had embarked on a fundraise as part of its normal fundraising cycle. Given strong traction in the latter half of 2019, the company had decided to push back the fundraise to early 2020. The logic behind this was sound: It would mean using up more of their capital cushion, but nobody had any doubt that they would complete a successful fundraise given the performance metrics they had under their belt.

The fundraise was progressing quite nicely when in February, in the span of a few fateful weeks, it became clear that the virus that had originated on the other side of the planet was now spreading across the globe and would soon be classified as a pandemic. The impact of this on Capitalise was immediate: Small business funding, and by extension Capitalise’s revenue took a big hit, and all the potential investors that had lined up decided to play for time to see how things would shape up.

With revenue falling and the funding round on hold, the team at Capitalise found themselves in a position any founder would dread. Of course, on top of all this came the stress of trying to run a business which was situated in London that was quickly becoming the global epicenter of the pandemic.  

There comes a point in every classic drama where the protagonist has to make a decision that will determine how the story will end and how the finale will unfold. This is commonly referred to as the second act turning point, and typically requires the main character to draw on their values, strengths, and powers in facing the adverse circumstances. The founders and team at Capitalise were now in for such an epic test, and without hesitation chose to focus on how they could give their accountant customers the tools to go out and help the thousands of small businesses that were now facing severe and in many cases existential cash flow issues.

The quick and decisive action by the UK Chancellor Rishi Sunak had already made a tremendous difference with their Bounce Back and CBILS initiatives, but these impactful initiatives came a long way from covering every impacted business. To address this gap, in conjunction with The Corporate Finance Network, Capitalise launched #LeaveNoBusinessBehind drawing from the UN’s similarly named initiative. The movement was supported by the Association of Chartered Certified Accountants (ACCA), AccountingWeb, Accountex, AVN, Clarity & Forgotten LTD. Its objective was to provide accountants resources to support their clients.

As they started working in tandem with the government programs to enable the accountants to deliver much needed lifelines to the small businesses, Capitalise faced the first of many choices it would have to take. To deliver the maximum level of loans to businesses in need would mean Capitalise having to forego its own commission income in many circumstances, and this at a point in time where every pound of revenue mattered immensely. Needless to say, the team decided to do the work needed to process many of these loans for free.

The Capitalise team: Helping accountants deliver for small businesses come rain or shine

In parallel to this, the company also got busy on the product side, and in the span of a few weeks took to market a new product that would enable businesses to litigate  on bad debts, which at this point in time was becoming a crucial priority for many businesses.  

The story is far from over, but after those initial fateful months in March, April, and May Capitalise closed a significant funding round with a mixture of its internal and new external investors, and after the initial hit and sacrifices, delivered record revenues in both June and July.

There are surely many such stories yet to come out, and what we do in the commercially focused startup world pales in comparison to the heroic efforts by the doctors, healthcare workers, delivery staff, all other essential workers that toiled so hard during this period. But in the end, every business matters, and it is the sum total of all these small businesses, whether they be pubs, restaurants, theatres, or retailers that make up the fabric of our modern society. In normal times, these businesses serve us on a daily basis, adding to our quality of life. As the going gets tough, it is important we do all we can to not leave any of these small businesses behind.

This Time It Is Different – Or Is It

Whether history repeats itself, or merely rhymes as Mark Twain suggested, it is surely useful to look to the past in order to find patterns one can recognize in today’s world. One such pattern that has been on the forefront of many people’s mind in the fintech community is whether the valuations of tech companies today represent a situation similar to the dot com bubble of 1999 that ended up bursting in 2000.

In terms of context, some of the ratios and indicators appear alarmingly similar today. The difference between the S&P 500 (which represents a broad index of companies) and the NASDAQ (which is more tech driven) has now reached levels last seen in 1999. Also, the top five companies in NASDAQ now represent 20% of the value of the entire index. Another striking example is that Tesla was at one point worth more than the five biggest global auto makers combined. The list of examples can surely go on, and there are many to give from early stage valuations in the venture capital community (which are very much impacted by the public markets).

There are many solid arguments being made to support this phenomenon of skyrocketing valuations: Interest rates are much lower today than they were in 2000 so there are less alternative places for investors to park their capital, today’s tech companies actually make a lot of money, etc.

The market itself will ultimately provide us all with the answer to this question, but it would be interesting to highlight a few points that hold true from the 1999-2000 period as well as about human nature in general.

Firstly, if (or perhaps when) a crash in tech valuations do happen, it is important to keep in mind that companies with sound fundamentals will still survive, and even thrive. As an example, I remember a conversation with the team at eBay in 2002 who were at that point trying to understand the implications of becoming a bank (they did not become a bank in the end, but did end up buying PayPal). By ways of reference, eBay was one of the most successful tech companies of that era (eBay’s market cap at the time of its IPO in 1998 was $1.9bn, very close to the valuation of Amazon that also reached $2bn in 1998 after its IPO at $438mn in 1997). When asked about what they thought about the dot com crash that had happened less than a couple of years ago, the response from the team at eBay was “what crash?”

Needless to say, companies with less solid fundamentals than eBay fared worse in the crash, and many investors that had piled into various companies without asking too many questions lost a lot (and in some cases all) of their money. This brings us to the point about human nature and an interesting observation about the kinds of questions people ask and which facts they find easy versus difficult to accept.

The best way to illustrate this is perhaps with a story from the Sufi philosopher and folklore legend Nasreddin Hodja. In this story the Hodja asks his neighbor to borrow a kettle, and returns it after some time, but also with a smaller pot inside it. The neighbor who thinks that there has been a mistake returns the smaller pot to the Hodja who assures him that this is no mistake at all, and his kettle has simply “given birth” to a smaller pot during its stay at the Hodja’s house. The puzzled neighbor accepts the smaller pot and walks away. Some months later, the Hodja once again asks his neighbor to borrow the kettle who happily obliges. This time however, the Hodja does not return the kettle, and when the neighbor asks him what has happened, the Hodja simply replies that the kettle has passed away. The neighbor protests in disbelief and tells the Hodja that it is not possible for a kettle to die – to which the Hodja replies “You believed it could give birth, how is it that you cannot believe it can die?”

A 17th century miniature of Nasreddin Hodja

This story illustrates our attitudes as human beings to many a phenomenon, not least of which is perhaps life and death itself. But to stay on our topic of tech valuations, the analogue would probably be that investors are happy to believe a company, say Apple, can go from a valuation of $1 trillion to $2 trillion in something close to a year, but find it much harder to believe that the reverse can just as easily happen. An implication for us in the fintech community is that human beings are not always rational, and the valuations that reflect the behavior of said humans are by extension also not always rational. The best that entrepreneurs can do is to focus on the fundamentals of their business and make sure there is a clear path to sustainability that does not rely on capital markets always behaving in the same manner. In other words, the best immunization against volatile and unpredictable capital markets may well be the vaccination of solid unit economics!   

Embedded Lending

There has been a lot of interesting discussion in the fintech community in the last year around embedded finance. It typically refers to financial products being seamlessly integrated into any non-financial business or service, with a common example cited being how Uber and Lyft integrated payments into their ride-sharing and mobility offerings. Many industry insiders are now predicting that this trend represents the next stage of the evolution of fintech and will spread beyond payments into all of banking and finance.

Based on some of the new business models that have been emerging in the last couple of years, embedded lending represents a particularly interesting subsegment worth highlighting here. Embedded lending is by no means a new phenomenon, and to understand how powerful embedded lending can become in the future, it is worth doing a short recap of the journey thus far.

Early examples of embedded lending include products such as the credit card, which one can think of as a payments product with lending embedded into it. Likewise, Fintech 1.0 companies such as QED investments GreenSky and Klarna are both great examples of how lending can be seamlessly embedded into retail and e-commerce, enabling a very smooth point of sale finance experience for end users.

Today’s embedded lending builds on this rich heritage of financial innovation and uses modern technology to take the product and user experience one step further. These new and innovative companies are characterized by three key features that they have in common.

The first key feature is seamless operational integration. With the APIfication of data, cloud computing, and all other innovations taking place in the info tech and data tech space, financial products can now be integrated with operational processes so seamlessly that much like the invisible man of H.G. Wells’ famous book of the same name, they are very much there but one cannot notice them. This integration is in turn supported by the rich ecosystem that has emerged in financial infrastructure and reg tech, where modular business processes can be used like Lego blocks to build new business structures, all connected to each other with API calls. Needless to say, it took decades of innovation in information technology to get here, from the emergence of C++ and Java as modular coding languages to today’s academic work on how to create abstraction layers from any computer language.

The Invisible Man of H.G. Wells – he’s there but you cannot see him

The second key feature is a realignment of business relationships and incentives to enable better commercial outcomes for all parties involved. Because legacies weigh heavy on institutions (and societies too in many cases!) some of the business and commercial relationships of today are shaped by the technological constraints of the past that no longer exist. There are countless examples of this, but just to pick a random one, consider the signature. In today’s world of Face ID and digital documents, why do I need a wet signature to prove my identity? Or why do I even have to show up in person to prove who I am in the first case? Undoubtedly, the list can go on, but the point here is that the new models that are emerging not only use new technology, but use that new technology to challenge the business logic and conventions of the past, especially where these were driven by constraints that no longer exist.

The third key feature, which is a direct consequence of the two prior ones, is that losses tend to be an order of magnitude lower compared to a legacy lending product. Both because of the closer integration as well as the new alignment of incentives, where in many cases significant credit risk existed, this credit risk starts to approach levels close to zero, instead being replaced by various levels of operational or systemic risk. Alternatively, in some cases an entity’s high credit risk gets replaced by another entity’s significantly lower credit risk. Again, there are countless examples one could give here, but just to consider a fairly common example, one can think of supply chain finance, where a small business is selling products to a large corporation, for example a small supplier selling tomatoes to Tesco. In the legacy world, when the small supplier would go to the bank to request a loan for working capital to fund its tomatoes, it would be charged a high rate of interest because it would be seen as a risky business due to being small and having little capital. But with the right kind of integration and fintech product (such as an invoice finance solution), the risk of the small supplier can be substituted with the risk of the big client (Tesco in this example), so the supplier can now borrow close to the low rates that Tesco can borrow at.

Another interesting example of embedded lending is Wayflyer, which provides e-commerce companies with software to optimize their marketing spend on platforms such as Google and Facebook. Wayflyer’s software is fully integrated with the e-commerce companies, and it helps them allocate their marketing spend online to best capture new customers and grow online sales. However, as a function of doing this, Wayflyer also sees where these e-commerce companies hit pay dirt when for example a new segment of customers that are very hungry for that particular product is uncovered. In this particular case, Wayflyer, which is integrated with the company can seamlessly offer its client extra marketing dollars, which quickly get converted into sales, and then get paid from the proceeds of this incremental sales automatically when the sale happens. From the e-commerce company’s perspective the financing is almost invisible – they just think of Wayflyer as a partner who helps them grow faster by making better marketing decisions and serving as an extra pocket to boost their marketing spend where needed. There are certainly many more examples of this, and some of these businesses are yet to emerge at scale, though they will undoubtedly do so in the not too distant future.  Two particular areas that are very interesting are student finance and property purchases. In the case of the former, Student Finance is working on a model where anybody can go to a vocational training program with no upfront payment, and only pay back the cost of the education when they get a higher paying job as a result of that training. While this is technically a student loan it is very much embedded into the education process itself, and from the perspective of the student they are investing in their intellectual capital and getting a better job in the process – the loan itself is invisible!

The Rise of the Workplace Bank

With the advent of the first industrial revolution in the late 18th century, millions of agricultural workers began a structural shift from agriculture to factories, setting in motion one of the most important events in human history since the domestication of animals and plants. While the overall impact on economic growth and productivity is undebatable, there is more controversy around what the impact was on the living standards of the workers that populated the factory floors, in some cases literally working day and night in very harsh conditions.

Some economic historians such as Robert E. Lucas argue that with the industrial revolution the living standards of the masses began to undergo sustained growth for the first time in history, while other historians argue that yes the growth of the economy’s overall productivity was unprecedented but living standards for the majority of the population did not grow meaningfully until the late 19th and 20th centuries. Some argue even further that living standards for the workers decreased initially, citing the fact that the average height of the population declined during the first industrial revolution as evidence that the nutritional status of workers was actually decreasing.

The perceived safety of having a 9 to 5 job is simply no longer there for a vast majority of workers in the 21st century.

It is actually quite easy to see the parallels to today’s debate about the digital revolution, also referred to as the “third industrial revolution” (the second industrial revolution being the advancements in manufacturing technology that took place in the late 19th century, also referred to as the “technological revolution”).

Just like back then, there is today a very important debate going on about income inequality, living standards, and worker’s rights. And for good reason, too. Widely available statistics tell the story of how more than half of all workers in developed countries are today effectively living what could be best described as “paycheck to paycheck”, without a buffer to meet an unexpected expense as low as GBP 300.   

The dangers of being a delivery person are not limited to traffic: Increasingly financial distress is becoming the bigger peril.

This is clearly a big societal problem and causes great stress and suffering on the working people that toil so hard to make sure our modern economy functions. These are in many cases the nurses, teachers, factory workers, delivery drivers, and countless others that are the glue of the modern economy, yet to an increasing extent they are facing great economic hardships and financial distress.

Finding a solution to this problem will ultimately rest with the politicians that we collectively elect, and one can only hope that our leaders will implement inclusive and progressive solutions as opposed to some of the darker paths that have been trodden tragically in the past. There is however also much that can be done at the level of the companies that employ these workers, and I believe many of the fintech companies of today will have a role to play in helping employers solve this problem.

I refer to this phenomenon as “the emergence of the workplace bank”, and to best illustrate what this means there is a very useful case study from one of the big west coast tech companies. This company contracts with millions of gig economy workers globally and used to pay them on a monthly or fortnightly basis as they completed their work.

Several years ago, it became apparent that these workers wanted to get paid real time as they completed their work (driven by the financial stress referred to above), and the tech company arranged with a fintech start up to help achieve this in what we today refer to as income streaming. It turned out that this was such a critical and strategic area for the tech company that they decided to actually bring all income streaming functionality inhouse. Given that they had the tech and developer resources, this was in fact relatively easy for them, and before long they were paying their contractors on a real time basis.

However transferring money each time the worker completed a task (or in some cases at the end of the shift) had a cost associated with it, and the company realized they could save money if they issued their contractors their own cards. This was welcomed by the workforce, and this new card had great (and quick!) adoption. With the advent of embedded payments and advancement in fintech infrastructure, it was also increasingly easy for the company to do this.

Then something very interesting happened. The contractors increasingly started to close their accounts with their former bank, reverting to live their financial lives fully within this newly issued “employer card”. Once that happened, the next logical steps started falling in place like dominoes. The workers wanted to pay their bills from that card, send money from that card, and pay for their groceries with that card.

And it did not stop there. As we know, these workers were very much living paycheck to paycheck, and they started asking their employer for advances or overdraft facilities on this card as urgent financial needs related to their work or personal lives started cropping up. The employer had now become their bank!

The morale of this case study is manifold, but some things are especially worth pointing out. Firstly, while it is ultimately the government’s responsibility to make sure workers are treated fairly and get to live lives without financial stress, the employers will not be able to avoid having to help their workers deal with the new financial challenges of the 21st century for long. I imagine a big vacuum or gravitational pull that will irresistibly pull employers into being part of the solution, making sure their workers can have access to the new financial tools to help them.

Secondly, as increasingly more and more employers will find themselves in this situation, they may also realize that they do not have the resources of this big west coast technology company to develop and create all these solutions inhouse. Hence, they will look to the rapidly emerging fintech companies of today that are active in the HR-tech space to provide those solutions. Some of these companies such as Wagestream have come at this problem from an income streaming perspective, while others such as Ben have come at it from a benefits perspective, and yet others have come at it from a debt consolidation or credit perspective. In the end, the ultimate driver and impetus here will be the crucial day to day financial needs of the workers, so it is reasonable to expect a big convergence as the workplace bank emerges.

Of Tsunamis and Tech: How Wagestream Responded

Tsunamis are a series of waves caused by a large and sudden displacement of water that is triggered by earthquakes, volcanic eruptions or underwater explosions. Rather than resembling ordinary sea waves that are caused by wind, tsunami waves resemble rapidly rising tides that can reach up to ten meters in height. The series of waves usually hit in periods ranging from minutes to hours, arriving in so called wave-trains. While at first they can appear as a big wave on the horizon, as people living in ocean basins can tell you, they are not to be taking lightly: The 2004 Indian Ocean tsunami was amongst the deadliest natural disasters in human history, with at least 230,000 people killed or missing.  

When I think of the Covid-19 pandemic that erupted in early 2020, I in many ways cannot help to think of a giant tsunami. I remember seeing it rise slowly but surely in the distant east, thinking it was scary but unlikely to have such an impact on our distant shores. But with the unrelenting force of nature it was upon us before long, and all that was left to do was to seek higher ground and respond in the best way one can. Whether the worst of it is now behind us, or whether what we have just been through in the last three months was just the initial installment in a longer series of powerful waves, one thing is clear – our society, in fact the entire world, is continuing to go through a trauma, and as the waves recede there will be much reckoning and rebuilding that will need to be done.

There will surely be a particular reckoning in the area of public healthcare, and whether a majority of Western societies were right in running their healthcare systems with a business minded “Just In Time Inventory” mindset borrowed from globally integrated and cost focused supply chains. These are complex questions, and rather than diving into them here, I’d like to focus on something more upbeat and optimistic, and something that is also much closer to what I do. How did the start-up world respond when the wave started hitting? I’d like to focus in particular on the companies where I serve on the board here in London and the first case study I’d like to bring up is Wagestream, on which I had also done a blog last year.

One of my friends used to say that when under stress and pressure, there is a very strong tendency in people to revert to their comfort zones. He had said this in the context of businesses and their leaders undergoing stress, so for example in a financially and quantitatively focused organization the tendency may be to open up the excel spreadsheet and start sharpening the pencil on costs, whereas a more sales and marketing focused one may be more focused on opening up PowerPoint to draft a new story, etc. Startups are by definition nimble and agile organizations, and hence it is no surprise that when under pressure they would rely on their tech, innovation, and product development skills to respond to the crisis.  

Wagestream’s response was in fact a prime example of such product innovation under pressure. One salient memory that will stay with me forever was the Friday before the lockdown was announced, in Wagestream’s Holborn head office. Life was by no means normal and we all had a sense that something big was happening, and the crowed sidewalks for High Holborn would not remain so for long. The cadence and intensity of bad news was rising sharply, and one could almost touch the fear spreading through all segments of society.

It was under these circumstances that Wagestream announced that they were to host their first ever companywide product innovation competition. Everybody was to be involved and were allocated to a number of smaller teams that would compete to come up with new product ideas with the winning ideas to shape not just the future of the company, but also their response to the Covid crisis. I was asked to join the jury for selecting the winners along with the cofounders, and the competition was on!

I have to say I was incredibly impressed with what the team had produced in a very short time! Every idea was amazing, and all of them had the same laser like focus: How can we use our strengths and positioning as an organization to better help our customers and their employees, many of which were incidentally key workers for the NHS, BUPA, and other organizations. I don’t like spoilers, so I will not give away the winning answers here, but you can check out the results yourself from Wagestream’s web page.

Karl celebrating his two year anniversary at Wagestream, just weeks before the product innovation competition. Photo courtesy of yours truly.

One anecdote that really stands out which I’d like to share was regarding one of the winning ideas that was submitted by Karl, one of the very first employees at Wagestream who had actually just recently celebrated his two year joining anniversary (he was the first one to celebrate this milestone at Wagestream). As we were announcing the winners, we asked Karl how long it would take him to implement it and bring it to life. It should incidentally be noted that the competition had only been announced twenty-four hours ago. His answer was a simple shrug of the shoulder, nonchalantly stating “I’ve already done it”. This is probably one of the most brilliant responses I’ve ever heard, and in that time of crisis it was a much-needed morale boost for the entire team.

There may yet be many more waves that come to hit us, but as David Deutsch says, problems are inevitable, but problems are also solvable. As I continue to work with amazing startups such as Wagestream I cannot help but believe that whatever the world throws at us, we can overcome it together.

Numerical Context on the Proposed Fiscal Stimulus

In my last blog I wrote about the immediate need for helicopter money and coordinated fiscal stimulus from governments around the world. Since then the US administration announced a $850bn stimulus package. I would like to share some numbers to put the figures being proposed by US political leaders into context.

The GDP of the United States was $21.4 trillion in 2019. This means that on average, the US produced a GDP of $1.8 trillion/month in 2019. Obviously, even with all the measures put in place in response to the coronavirus, we are very far from having shutdown the entire economy. But what percent of the economic output has been impacted by the partial shutdown and economic disruption?

To give us an idea, we can actually use the latest economic data shared by China yesterday. According to the National Bureau of Statistics, industrial output in China tumbled by 13.5% in the first two months of the year. As per the Financial Times, the same data also showed that retail sales plummeted 20.5 per cent year on year in January and February, and fixed asset investment fell 24.5 per cent. Services production also declined by 13 per cent in the first two months, and coupled with the industrial production figure, Capital Economics estimates that Chinese GDP contracted by 13 per cent during the first two months of the year. (Source: Financial Times, Chinese economy suffers record blow from coronavirus.)

However, while the data above suggests a 13 per cent drop over two months, it is important to note that China only went into full lockdown on January 23rd. Considering that February is a shorter month, the contraction primarily corresponds to a period of thirty-seven days. Putting this into monthly terms, a reasonable assumption is that China’s economy contracted by 10.5 per cent on a monthly basis during the lockdown period.

Taking this 10.5 per cent number and applying it to the US monthly GDP of 1.8 trillion, we see that the GDP impact of going into shutdown for one full month is about 190 billion dollars, or close to one percentage point of annual GDP each month the shutdown is in place. This sort of math is of course way too simplified, but it helps give a directional understanding, and it seems to imply that by proposing a $850bn stimulus package the current US administration is looking to make up for about three to four months of lost output from slowing down economic activity in response to the coronavirus.

What the numbers do not take into account is follow on disruptions that may be caused as people lose their jobs or companies have to go out of business permanently. It also does not take into account any disruptions from stress building up in the financial system such as the repo or commercial paper markets. Nonetheless, one can only hope that it will inject markets and people with a sense of stability. The delivery mechanisms will also be key, as the stimulus needs to reach the people and businesses that need it most in an expedient manner.

The most important thing to note here however is that the US is far from the only country impacted by the coronavirus. The GDP of the EU is close to $20 trillion, and their economic output have certainly been exposed to the same sorts of unprecedented shocks. Hence, it will be very important that other governments continue to take similar fiscal measures in the coming days, and do so in a coordinated manner.

It Is Time for Helicopter Money

We are living through unprecedented times. Never before has the global economy been this interconnected, and never before have the seven billion plus souls that inhibit this planet changed their collective behavior so suddenly and so dramatically.

The global wave of fear that the COVID-19 virus and the associated media coverage has unleashed has created a tsunami of reactions, with borders closing, factories shutting down, and both the demand and supply side of the economy going into what can best be described as shock.

The health and safety of the world’s citizens should be priority number one, and I would first and foremost like to express my eternal gratitude to the nurses, doctors and medical workers who are working on the frontlines of this pandemic to the point of utter exhaustion, putting their lives at risk on a daily basis to save ours. We are deeply grateful, and words are not enough to express the importance of the work that they do for all of our collective safety.

As for the global political response, I am neither a scientist nor an epidemiologist, so I will not get into the controversial topic of whether the response from the various national governments of the world has been an overreaction or an underreaction.  I would however like to point out that in times of crisis, coordination and solidarity is paramount, as is staying calm and levelheaded. Politicians globally face no easy choices in the coming weeks. It is the job of our leaders to make these incredibly difficult choices, always putting the good of society and the health of all the world’s citizens as the top priority. Sometimes the right choice might not be the most popular one, and it is the job of the leader to make that right choice in light of scientific knowledge and the long-term welfare of society. Open and honest communication that also prioritizes keeping the population as calm as possible will be key.

While nothing can be more important than preserving people’s physical health and wellbeing, I would like to focus here on the economic consequences of what we are going through. I will not go into the numbers here, but the analogy with regards to the global economy that comes to mind is a big airliner that has shut its engines in midflight. We now need to restart the engines and land the plane safely.

The Fed has announced that it has cut its rates to zero percent, so it is fair to say monetary policy is stretched to its maximum. However, while this will undoubtedly help, it will likely not be enough.

Given that the global economy faces an unprecedented challenge, global policy makers now need to focus on unprecedented economic responses. Given that the shock is driven by both the supply side (factories shutting down, supply chains breaking down) and demand side (consumers not spending money and postponing most purchase decisions), governments will have to take swift steps to address both sides.

The term helicopter money is derived from a thought experiment by Milton Friedman

One such step would be what is known as “helicopter money” a term attributed to a thought experiment performed by Milton Friedman, where a helicopter drops money that is directly picked up by the people. One key condition of his thought experiment is that everyone is convinced that this is a unique event that will never be repeated. This thought experiment has since been picked up by economists as an alternative (or supplement) to monetary policy including quantitative easing. Its proponents argue that it can be a very efficient way to increase aggregate demand, especially in what is known as the liquidity trap – or central banks reaching the zero lower bound on interest rates.

The proponents of this tool include Ben Bernanke, who has in the past stated that helicopter money should be on the table as an alternative of last resort.

In practice, there are clearly many ways in which helicopter money can be implemented. The spectrum can range from tax credits to individuals and small businesses (the mildest form) to actually transferring money directly into their bank accounts (basically a sort of temporary Universal Basic Income for the duration of this crisis).

Given the severity of our current crisis, I think policy makers need to immediately start assessing the various delivery mechanisms and preparing an action plan as soon as possible. The best option in today’s circumstances is likely to be one where small businesses and consumers get money put directly into their bank account. While the cost of this will undoubtedly be high (using a simple example, giving forty million people GBP 1,000 per month equates to a cost of forty billion pounds for each month that the policy is in place).

However, if the benefit is to prevent a total breakdown of the economy, the cost may be very worthwhile indeed. The delivery mechanisms will also be key, and alternatives that help small businesses stay solvent also need to be considered. This can take many forms including a forcing mechanism to direct the helicopter money to be spent immediately, or other direct assistance to small businesses, including payroll support where the money in effect gets delivered via business payroll. One big benefit of this would also be to give consumers one less thing to worry about. Everybody is clearly very worried about their physical health and wellbeing, and adding financial worries on top of this only increases the level of stress.

Finally, it is also important to point out that one big benefit of helicopter money is that it would create less inequality and would thus help maintain social stability and cohesion in trying times. Quantitative easing primarily gets delivered via the banking system and tends to flow towards house prices and stock prices, which then tend to leave behind people that cannot afford to own a home or buy stocks.

We need to remember that (God willing) this too shall pass, and once it does, we want to wake up to societies that have made it through these troubling times with their heads held high, in solidarity with their fellow people and neighbors, and without sacrificing the fundamental values on which we have built our civilization.

Your Money Does Not Exist (and Why Your Bank Needs a Babysitter)

In my last blog, I mentioned the slightly disquieting and amusing fact that your money does not exist. People usually have one of two reactions to this statement. If they are an economist or a student of the modern banking system, they say “Yes, so what?” whereas if they are part of the remaining of 99.9% of the population the reaction is usually a mixture of “What have you been smoking?” and general disbelief.

The easiest way to prove the point is to use a simple example, and here it goes. To illustrate that this is not directly related to the digitalization of money which is a separate issue (i.e. paper vs. digital money), let’s consider a bank in an economy that only uses paper banknotes.

In this paper money based economy, imagine Customer #1, who now goes to a bank to deposit her $1,000 in banknotes. The bank happily accepts her money and gives her a little paper ledger that shows an account balance of $1,000 (effectively the bank now owes her $1,000). Our trusting Customer #1 may be thinking of her banknotes living a comfortable existence deep down in a secure bank vault, the equivalent of money heaven.

However, in reality, the bank is much more than a simple safe or a vault for locking up banknotes. The bank needs to make money as well, and to do so, it takes the vast portion (let’s use 90% for illustrative purposes) of Customer #1’s money and lends it out to Customer #2.

Now, Customer #2, who we can imagine to be a bread maker, takes the $900 the bank lent him, and sets out to use his $900 to buy himself a new bread oven for his soon to be opened bakery. Hence, Customer #2 goes to Customer #3 (who happens to be a bread oven maker) and gives him the $900 in exchange for the latest model bread oven.

Customer #3 who sells bread ovens has no interest in putting his money under his pillow either. Hence, he takes his new $900 and goes back to the bank and deposits it. The bank gladly accepts the money and gives Customer #3 another paper ledger that shows his account balance with the $900 on it (so the bank now owes him $900).

Let’s take a little break here and consider how the situation and all the various ledgers look. The bank only has $1,000 in its safe, but Customer #1 has a ledger that tells her the bank owes her $1,000 while Customer #3 has a ledger that tells him the banks owes him $900. If they both were to go to the bank to withdraw all their funds (a total of $1,900) the bank would have to tell them that all the money is not there.

So what gives – where is the money? Of course, the short answer is that the bank has $1,000 in cash, while Customer #2 (the bread baker who took out a loan), owes the bank an additional $900 that he will pay back with the profits from his soon to be opened bakery shop.

Of course it does not stop there. Once Customer #3 (the guy who sold the bread maker the oven) puts his $900 into the bank, the bank once again lends out a big portion (let’s again use 90% as an example). Hence the bank takes $810 and lends it out to Customer #4 who uses the money to buy bricks to build herself a new house, etc.

I’ll spare you the math and the repetitive examples, but when all is said and done, the bank is left with $1,000 in capital (cash in the vault), while the sum total of all the money in the customer’s ledgers is actually $10,000. In other words, Customer #1, Customer #2, Customer #3, etc. all collectively think they have $10,000 of cash in the bank, whereas the bank in reality only has $1,000. Hence, the bank has created $9,000 of “imaginary cash” that does not exist, except as a collective belief. (My math here is only directionally correct, as the real-life computations are complicated by centuries of banking and accounting regulations and customs.)

A bank run from the 1930s

One implication of this this is that banks are vulnerable to “bank runs” that occur when people for whatever reason believe a bank is no longer trustworthy (this kind of panic can occur for any reason but usually involve rumors about the bank’s viability). This creates a self-reinforcing herd behavior where all the customers go to the bank to get their money out simultaneously. As even the healthiest of banks would not actually have all this money as we saw above, long ques form up in front of the bank which make the bank run worse, resulting in a vicious cycle that ends with the bank going bust, and the depositors losing their money.

Times may change, but bank runs don’t

It is for this reason that government support and the associated regulation is crucial for banks. To prevent bank runs (which otherwise would occur quite regularly), the government steps in and informs everybody that they guarantee everybody’s money up to a certain amount (the money still does not exist by the way, but the government has the power to print new money if push came to shove – this of course would create inflation but that is a whole other story). But at least the government guarantee inspires confidence and makes bank runs less likely.

So what is the relevance of all this for entrepreneurs and operators in the fintech space? One big implication, especially for those longing to one day become regulated banks, is to realize that they cannot become one without accepting the protective embrace of their respective governments and bank regulators. And that protective embrace can easily turn into a smoldering bear hug if the regulators think the bank is not being run as it should be. Hence, while becoming a bank may sound tempting, know that it comes with the full weight of history and banking regulation behind it.

After all, everything, even creating imaginary money, comes at a cost.