Yesterday Bad. Today Good!

Please don’t laugh at me. I’m about to share an embarrassing secret and would like to do so without the fear of judgment or ridicule. Want to know my secret?

I have a long and sad history of trying to solve problems with the wrong technology.

And guess what happened each and every time? I failed just about as badly as is humanly possible. Crash and burn doesn’t even begin to describe these disasters.

For instance, let’s go back to 1995 when I was working on the Account Management team at Capital One. My mission in life at that time was to dream up products, services and programs that would improve the profitability of our existing credit card portfolio. I worked on everything from Credit Limit Increase programs to Collections strategies and overall did a decent job.

One day I had a killer idea: What if we built functionality that allowed customers to pay their recurring bills using their credit cards? Utility bills, rent, lawn services, etc. We’d pay them all. We’d make their Capital One credit card more useful which would theoretically drive up utilization, improve satisfaction and drive down attrition. I smelled profit!

This was a time before the internet was a real thing to most people. It was a time before online account servicing existed in any form or fashion. It was a time before moving money was easy. And this is precisely why I thought it was a good idea. Nobody was doing it so we should!

So what did I do? I cobbled together a hacked together version of the service with the help of one of my co-workers (thanks Kathy!). Here’s how it worked:

Customers would register their bills by calling a number and interacting with an interactive voice response unit (an IVR). They had an option to enter a new biller as well as an option to edit or delete an old biller. They could set a bill up as a recurring payment for a fixed amount on a fixed schedule or store the biller’s name and address and their account number in the system and then each month call in and enter the desired payment amount.

Once the customer was set up, every time a bill approached its due date we’d manually print an envelope and stuff it with a buck slip with the relevant payment information and a physical check for the payment amount. To ensure the bills were paid on time, we’d mail our checks 3-5 days in advance of the bill’s due date depending on when the weekend fell. Simple!

And since we didn’t know how much people would be willing to pay for the service or what the effect would be on important drivers like utilization and attrition, we decided to test a variety of price points from $1 a bill to free.

Guess what happened? It was a colossal disaster on every dimension.

First, customers were very price sensitive with the only real response coming from the “free” test cells. This didn’t kill the program outright but it was discouraging.

Second, the initial setup of a recurring bill using a phone as an input device didn’t work. Numbers weren’t difficult to enter using the phone but biller names and addresses were. So we basically ended up using the IVR as a recording device and then had someone manually transcribe the information into our system. Guess what our error rate was? Guess how many times we had to call customers back to clarify the billing information? Guess how many customer complaints we had?

Third, there was no easy way to inform a customer that a bill had been processed. Guess how many customers cared about this? Guess how many called to check on the status of their bills?

The result: We created an operationally intensive service that customers weren’t willing to pay for. To make matters worse, our complaint volume spiked (which is never a good thing). And to add insult to injury, we significantly increased the attrition rate among customers that tried the service.

Kathy and I tried to fix the program for a few months but eventually dug a big hole and buried it.

Fast forward to today and the majority of US consumers use one or more electronic bill payment services and many consumers are more than willing to pay a fee to have a bill paid using their credit card (i.e. – taxes). What changed? Technology.

We now have the right input devices (keyboards and smart phones) and the right interfaces (web portals and apps) and the right back-end infrastructure (electronic movement of money). This combination works brilliantly while the 1995 version of the service failed. Technology made the difference.

And this theme is precisely why I’m so excited about our recent investment in Current. For those of you not familiar with the company, Current offers a debit card for teenagers that’s nested under a parent’s core checking account. The product is chock full of functionality that includes various buckets to store money (spend, save and give), monitoring and controls around spending, and features that allow parents to administer allowance and track chores. It really is a fantastic product and if you have teenage kids you should check it out (www.current.com).

Would it surprise you to know that a platform was created by Visa to address this need almost two decades ago (Visa Buxx) and it’s barely used today? Would it surprise you to know that Current’s version of the same product is literally flying off the shelves?

How’s this for product/market fit: Current sat down with a room of parents and a full 75% ended up purchasing the product afterwards.  And as for the teenage children of these same parents, 100% of them wanted the card!

The difference?  Technology.

The problem has been around for decades but the right technological solution only emerged recently. Smart phones plus e-commerce is a recipe for success while desktop plus physical retailers makes for a clunky solution. Guess the average age that a teenager gets their first smart phone? Around 12. Guess where they like to spend money? Online.

Compare this to two decades ago and it’s a completely different story. Where was the majority of money spent? Physical retail stores. This meant that money was only useful in the context of mobility. Until semi-independence came with a driver’s license (at the age of 16 or 17), kids relied on their parents to unlock the value of money. Allowance only mattered in the context of “when can you take me to the mall” so being a few days late didn’t matter much. And while it was inconvenient, if parents didn’t have cash in their wallets they could swing by an ATM on the way to carting their kids to the mall. The system was clunky but it worked.

The right technological solution applied to the right problem at the right time is a thing of beauty and can ultimately be the catalyst for creating a very large company. Will Current onboard a few hundred thousand customers? No doubt. Will they onboard a million customers? It’s definitely possible. At the very least it will be a fun one to be part of. Let the accounts continue to fly off the shelf!

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Money2020, Building Businesses and Why I Love American Ninja Warrior

I don’t think this is a very profound insight, but having been around the business building block for two and a half decades I can truly say that building a wildly successful business is difficult.  Building a so-so business is equally difficult.  And what’s sad is that building an unsuccessful one might be even more difficult than building a successful one.  An entrepreneur can have a great idea that solves a persistent, obvious and painful problem, but the number of things that have to line up perfectly for a truly great business to be built is actually quite daunting (see this oldie but goodie for more on the topic: The Tyranny Of 0.8 To The 5th).

I bring this up because we’re right around the corner from Banking’s largest conference of the year – Money2020.  In attendance will be over 11,000 people from 4,500 companies, many of which are start-ups trying to find their place in the big bad financial services ecosystem.  While most of the start-ups will ultimately fail, I can’t help but relish in the obvious and infectious energy that’s generated by the entrepreneurs at these companies.  They have no political filters clouding their ideas.  They have no higher-ups waiting around to smash their ideas.  They don’t care about sacred cows and they don’t care if hundred-year-old brands are shattered.

What they care about is solving problems and doing things better than those that came before them.

But while each Founder believes that he or she is destined to succeed, the statistics would suggest otherwise.  They’re most likely going to fail or stall somewhere on the way to greatness.  Sad, but true.

So as an Investor, where do I fit in?  The simple (but incorrect) answer would be that my firm (QED Investors) provides capital to various startups trying to disrupt the incumbents in pursuit of better business models.  The reality is that there are plenty of sources of capital out there and ours is relatively shallow in comparison to the giant funds that are putting hundreds of millions if not billions of dollars to work in the Banking ecosystem.

The reality is that we exist to help Founders climb Mount Midoriyama.

I assume I’ve probably confused most of you, but just humor me and all will be revealed.  Mount Midoriyama is a fantastically large steel structure at the end of the world’s most difficult (and constantly changing) obstacle course.  The obstacle course originated in Japan under the name Sasuke, and over a thirty-four season run, only four competitors have completed the course (one did it twice!).  Of course, the US had to create its own version of the show, and so was born America Ninja Warrior.  The popularity of the show has been growing since it first aired in 2009 (with over 70,000 applicants in the last season alone) and thus far in American Ninja Warrior history, Isaac Caldiero and Geoff Britten are the only two Americans who have completed the course.  In summary —- it’s a nearly (but not) impossible task to climb Mount Midoriyama.

Bar none, America Ninja Warrior is my favorite show on television.  The contestants train year-round for what could sadly be seconds on the course.  A great year for a contestant might be conquering the obstacle that they fell on the previous year.  Or it might be making it farther than they did in the past.  Or it might be to just go out and “represent”.  Success means different things to different Warriors.

From all this a Ninja Warrior community has emerged, and what’s fascinating is that they exist to help each other get better and to help each other succeed.  They don’t see themselves in competition with each other, but rather they’re all in competition with Mount Midoriyama.  Dedicated Warriors sacrifice just about everything in their lives to train for a course that will almost certainly get the better of them.  Each individual knows that he or she is expected to fail but the best of them believe success is possible.

So this is where I feel like our firm fits.  If we can give a little piece of advice that gives a Founder a better chance at success, we’re helping him tackle Mount Midoriyama.  If we can help a Founder structure her product a bit better or think through a tricky either/or decision, we’re helping her tackle Mount Midoriyama.  And if we have the privilege of watching one of our Founders make it to the top of Mount Midoriyama, we can relish in the little things we did to help along the way, but more importantly know that it gives us and the Founders of the future a reason to believe ultimate success is possible.

See you all at Money2020!

(And now time for a shameless plug which has nothing to do with my “day job”.  My children’s book “The Festive Frolics of Panda and Owl” is available at Amazon and major book stores everywhere – www.goo.gl/sguDcr.  Feel free to support my labor of love….)

Know What Race You’re Running

A year in the life of an Entrepreneur often feels like being on an eternal roller-coaster.  Five hundred twenty-five thousand six hundred minutes (no I’m not channeling a song from “Rent”).  And every one of them a chance for the up feeling that comes with good news or the depression and panic that inevitably accompanies bad news.

A year ago most of the next-gen fintech lending businesses found themselves in the midst of a down cycle and it felt horrible.  The cycle started in early 2016 with a pullback from loan purchasers due to increasing losses and reduced unlevered returns. Not long afterwards the industry had to deal with the Lending Club “Event” that sent waves of panic throughout the ecosystem.  A few months later we started to see some of the smaller platforms shut their doors and the larger platforms tighten their credit criteria and reduce burn through RIFs.  Earlier this year the major platforms started to grow again and we now find ourselves in an environment where every recent securitization seems to be oversubscribed and well received by the investor community.  What a crazy year!

So, I thought it would be worth a follow-up piece to the posts that I wrote when the industry was in its downturn.  In Thriving, Surviving or Dying I laid out four critical questions that lending originators had to answer in order to thrive.  In What Happens When The Cash Runs Out I laid out the importance of “Climbing the Relevance Curve”.  And in I Once Was Lost… I made some obvious statements about what lending was all about.

Be your own judge about whether the points made a year ago are still relevant today.  I personally think they are, but I happen to be a bit biased.  But having lived through the past year, I feel that there are a few additional points worth sharing now and in future posts that will hopefully add a bit of richness to the view of “success and failure” in the lending ecosystem.

With this in mind, I thought it would be worth adding a new concept to the mix that I call “Know What Race You’re Running.”  Put simply: There are business models that are designed to favor a single break-out winner and there are business models that are designed to do quite well alongside a broad ecosystem of players.  A flaw I’m seeing quite often is that some Entrepreneurs don’t know what model they’re pursuing and therefore they don’t design or run their business correctly.  To make this tangible, it’s worth digging into the differences between “Type 1” and “Type 2” models.

Type 1 business models are designed around “being the best” for a given customer segment.  By having the best product/service for a given customer segment, Type 1 businesses aim to attract, service, retain and X-sell customers on the strength of their offering and brand positioning.  Many want to create “THE destination” for customers in their segment.  They want to make sure that awareness within their target segment is strong and that they lock up marketing and distribution channels that cater specifically to their prospects.

Type 2 business models are designed to “show me the money” by having both attractive horizontal and vertical economics.  Horizontal economics are the annuity oriented cash flows (unit economics) and vertical economics are the in-period cash flows (P&L economics).  These business models are designed around efficiency and healthy margins and ultimately around bottom line cash production.

The reason why it’s important to know what type of business you’re building is that the best strategic and tactical moves around what it takes to “be the best” vs “show me the money” are different.

A few things to internalize about each model:

Type 1 – Being The Best

  • A simple definition of “best”: You need to believe that if a typical consumer in your target segment were faced with perfect information that they’d pick your product every time.
  • Almost by definition there can only be one “best” business for a given customer so it takes being obsessive around product, brand, service, the competitive landscape etc. to remain on top
  • To carve out this position, a business usually has to provide a great deal of value to their customers which can put pressure on margins and make significant scale a necessity
  • War can break out if multiple well-resourced and nimble businesses try to own the distinction of being the “best”. In these cases, value tends to migrate back to the customer, the market becomes fragmented, and nobody achieves scale or generates attractive economics.
  • Falling farther and farther behind is a likely outcome when an under-resourced player chases a well-resourced player and they both want to “be the best”.
  • The majority of enterprise value creation will fall into the hands of the break-out winner and almost every investment into other entities in the space will prove to be “mediocre at best”.

Type 2 – Show Me The Money

  • The truth is that there’s typically room in most industries for multiple well-run players to thrive
  • The best operators of Type 2 businesses obsess over the fact that every dollar invested in growth needs to achieve a hurdle rate return and every dollar invested in a non-growth initiative is a dollar that eats into the company’s operating margin
  • Designing the company’s infrastructure such that it can earn money at low levels of scale is critical to building a cash machine (most overlooked design principle!)
  • Being the biggest or the best isn’t as critical as being really good, extremely efficient and scaling in a disciplined manner
  • Operations of Type 2 businesses typically believe that serving your current customers well and offering a slightly more complete product each year is a winning formula

So why does this matter?  It matters because certain ecosystems aren’t conducive to supporting a “best” business.  But, most Investors want to invest in and Entrepreneurs have therefore built business plans around “Being The Best”.  Too many Entrepreneurs design their businesses to give every dollar of margin back to the customer through pricing and functionality and justify it by thinking they’re in a Type 1 race.  Rock meet hill.  Cash meet toilet.

And the opposite situation is also frustrating.  Chasing a break-out winner in a Type 1 race is a near impossible task.  Type 1 races are awesome if you can win them but when you don’t you have some really unhappy investors and a really broke company to show for it.  I can point to a few businesses that lost ground every year to the dominant player and had to close shop (or are about to).  Punching yourself in the face would be more pleasant.  Rock meet hill.  Cash meet toilet.

With this in mind, the best advice I can give is “Know what race you’re running” and act accordingly!

Kind of Blue

Forgive me (my few but loyal readers) for I have been busy.  It’s been 3 months since my last post which is the longest period of inactivity since I started blogging a few years back.  The excuses are many but in the grand scheme of things not important.  What matters is that it’s time to get back on the wagon and write!

But before I jump into my “thought du jour”, I did want to point out some fun things that have happened since my last post.

First, QED and QED’s companies were well represented at this year’s LendIt Conference.  Both Zopa and ApplePie Capital won awards — Zopa for Top Consumer Lending Platform and ApplePie Capital for Emerging Small Business Lending Platform.  And the QED team must have said or done something right because we won the Top Fintech Equity Investor award.  Silly judges!

Second and also at the LendIt Conference, QED put forth a new conceptual framework that seems to be gathering a little steam.  We’ve creatively called it the “QED Matrix” and you can see Nigel’s presentation and learn more about it at www.qedmatrix.com.

Third, my wife’s business (www.nestiny.com) is about to cross 100,000 registered members.  I’m ultra-proud of her and am thrilled to have an entrepreneur in the family.  But, as great as this accomplishment is, our “claim to fame” moment came a month or so ago when photos from our wedding were picked up by the press and went viral due to the presence of a “unicorn”.  Glamour, The Knot, People, House Beautiful, Yahoo, etc.  We blew up the internet for a few minutes and it was fun to watch.  Just google “Frank and Jody’s Unicorn Wedding” if you want to see some pics.

Now back to our regularly scheduled programming…

If startups were a style of music, it’s very clear to me that they most closely represent Jazz.  Building a business requires a master plan, but most entrepreneurs will tell you that what happens day-to-day has an element of improvisation and spontaneity that’s a reaction to what they’re experiencing in the moment.  Decisions are typically made with incredible speed and adjustments are made equally fast.  An entrepreneur needs to be hyper-alert to signals and feedback coming from all directions and as a result their plans and teams need to be fluid and malleable.

A byproduct of improvisation is that it isn’t flawless.  In fact, “mistakes” are made with regularity.  To quote the immortal Miles Davis:

“When you hit a wrong note, it’s the next note that you play that determines if it’s good or bad.”

Resolution is what matters.  Dissonance moving to consonance.  Drama and agitation builds when resolution is delayed.  Calmness and tranquility result from resolution.

The analogy applies perfectly to many aspects of business building so I won’t spend any more time hammering the metaphor home.  Instead, I’ll share a real world example that hopefully you’ll find interesting.

About a week ago we brought a very early stage company in to present to the QED team.  It was a company that I had been actively following and doing my best to help for the better part of a year.  They had made amazing progress over this period of time growing their early client base, shipping code and building out critical functionality.

And, the meeting with the Partnership went well…..mostly.  The Founder was convincing in his articulation of the problem and pain points his business was tackling.  The addressable TAM was compelling.  The unit economics resembled those of a great SaaS business.  The “fit” with the QED team was obvious.  But, to put it bluntly, the long-term P&L forecast that was presented described a crappy business.  Dissonance became tangible.

One of the QED Partners pointed this out and offered to help re-forecast the business.  In fact, multiple QED team members offered to help frame various pieces of the puzzle.  And what did the Founder do?

Thing 1: He recognized and admitted that he hit a wrong note.  Zero ego.  Zero defensiveness.

Thing 2: He offered an explanation for the disconnect but more as an apology than as an excuse.

Thing 3: He embraced our feedback, re-worked the model with his team, and quickly set up follow-up meetings with various members of the QED team to drill into the revised model/make additional revisions.

And while the new model is still a work-in-progress, I can definitely say that dissonance has changed to consonance.  What’s even more important is that it gave us a chance to see how the Founder problem-solved his way out of what could have been a sticky situation.  By hitting a wrong note and resolving the disconnect quickly, the Founder became more liked by the team rather than less liked for the error.  It’s what’s so great about jazz.  Dissonance to Resolution to Consonance.

What’s My Favorite Color?

Apologies for being so delinquent in posting but it’s been a busy start to the year.  In addition to working on time intensive projects with a few of our portfolio companies, QED formalized a very exciting relationship with Fifth Third Bancorp.  You might or might not have read about it (Fifth Third Bancorp Partners With QED Investors), but hopefully it explains why I’ve been a little light on the content recently.  More on this relationship soon.  With this said, back to the Blog!

Every once in a while I feel like I’m experiencing what I think of as “Advisory Deja Vu” (ADV).  It’s when I’ve had the same thematic conversation on multiple occasions over a short window of time but with different founders.  And more than once it’s become a theme for a Blog post, this being the case in point.  So, to convey my current ADV theme, I thought it would be best to start with a simple story.

A behavioral psychologist, a data scientist and a five year old walk into a bar.  All three belly up to the bar and order drinks (and in case you’re wondering, the five year old ordered milk – don’t hate on me!).  After a few minutes of complete silence, the bartender addresses the group.

“I can tell that you’re bored and can use a bit of a challenge to liven things up.  Do you see that woman sitting over there?  Free drinks for a year to whoever tells me her favorite color.”

The challenge is accepted and they agree to meet back in an hour to reveal their guesses.

When they return, the behavioral psychologist answers first.  “I spent the last hour analyzing her every movement and studying her attire and jewelry.  She must like muted colors because of her subtle shade of lipstick and very minimal use of makeup.  Her outfit is comprised of shades of black and gray as is her handbag.  But, lots of women like to wear black and gray so this doesn’t tell me much. What’s interesting is that she went to the bathroom half-an-hour ago and came out wearing a maroon colored hair clip.  It stands out nicely against her black outfit and her confidence increased once it was in place so it must be a color she really adores.  As a result, I can definitively say that her favorite color is Maroon.”

The bartender responds: “Sorry.  That’s not right.  The woman is my wife and I bought her that hair clip a year ago.  She wears it to humor me but I don’t think she likes it very much.”

The data scientist goes next.  “I spent the last hour hacking into her computer and analyzing all her purchase behavior on Amazon and her searches on the web.  I loaded all the data into a machine learning optimizer and using a random forest algorithm determined that her favorite color is Green.”

The bartender responds: “Sorry.  We share a computer so the data you analyzed isn’t quite right.  What’s funny is that you figured out MY favorite color, not hers!”

The five year old goes next: “Blue.”

The bartender responds: “That’s right.  How did you know?”

The five year old: “You’re a silly goose.  All I did was go up to her and ask.”

Why tell this simple story?  A recent string of conversations I’ve had with Founders have all centered around something not being quite right with a business with the Founder trying to diagnose the cause using complex data analysis or econometric trends or “theories”.  I’ve found myself giving the same advice over and over and a few Founders have actually taken my advice and started to report back pretty interesting findings.  The advice?

“Your customers know more about themselves than you do and are more than happy to share their thoughts if you ask.”

This is a simple but profound truth that I find is often neglected by Founders and Executives at small and big companies alike.  If you want to know why customers aren’t buying the high end version of your product — ask them.  If you want to know why customers aren’t making payments on your loans — ask them.   If you want to know why customers use your product once and never come back — ask them.

Don’t get me wrong — data is fantastic and very helpful in many contexts.  I love data and what it can teach a business.  I’m a big fan of tools like Full Story and Google Analytics.  But, when trying to understand why your prospects and customers are behaving a certain way I’d suggest you find a way to talk to them and listen to their answers.  Trust me: Ask and they will tell — Listen and you’ll learn.

A long time ago in a galaxy far, far away….

While I don’t like to admit it, I think I’ve finally become “that grumpy old guy”.  To be clear, I’m still in my 40s and am generally upbeat.  But, I’ve finally ticked all the major boxes that would qualify me as a curmudgeon.

Box #1: In my early 30s I called the cops on a neighbor who was racing his motorcycle at 3am.  I felt like a heel but wanted some sleep.

Box #2: About 5 years ago, sitting on a plane I (nicely) told a mother that she needed to control her child.  In my defense, the child was about 3 years old and kept putting his drooly hands on my laptop, my shoulders, my hair, etc.  Not cool.

Box #3: I’ve started to play the “remember when” game all the time.  Remember when everyone wasn’t pausing for selfies every 3 seconds?  Remember when new college grads understood that they had to work their way up the ladder and didn’t complain about it?  Remember when you drank some orange juice when you felt sick instead of “researching your symptoms” on WebMD and convincing yourself that you’re about to die?

And I’m definitely becoming an elder statesman in the FinTech world because in my work interactions I’ve also started to play the “remember when” game.  In fact, just this week I had multiple conversations with various 20+ year veterans in the space about how the most recent generation of FinTech companies should review the lessons learned from last generation’s innovators.   And of these lessons, we all agreed that they should pay special attention to what’s been learned on the topic of “growth”.

To put it simply, there are usually three phases of growth and each has its own characteristics and cadence.

Phase 1: Test, learn and burn

Phase 2: Revenue your way into scale

Phase 3: Cost your way into a healthy business

In Phase 1, every iota of energy needs to be focused on figuring out product/market fit and if the unit economics of the product make sense.   It’s about maniacally executing a well designed learning agenda.  It’s about interpreting early market/test results.  It’s about figuring out which levers matter and how hard they should be pulled.

Phase 1 is also about burning cash.  There’s no way around it because at this stage the business by definition has very few customers and revenue can’t overcome the fixed costs of supporting the product.  While every dollar matters for all the obvious reasons, the goal should be to maximize learnings rather than minimize burn.  Test, learn and burn.

In Phase 2, a business should be focused on scaling aggressively in order to build market relevance and overcome fixed costs.  But, aggressive scaling doesn’t mean mashing the accelerator with no constraints.  Decisions should be made based on the learnings from Phase 1 and not be speculative in nature.  In the formative days of Capital One we used to talk about how this phase of a product’s life felt like cheating because we learned enough in Phase I to know what the results were going to be in advance of spending our marketing dollars.  Cha-Ching!

Phase 2 is also about building out the capabilities of the team and operational processes such that the results are repeatable.  Selling widgets starts with making consistent widgets to sell, and this is a piece of the growth story that’s routinely being overlooked by today’s hyper-growth lending start-ups.  My observation is that many lending companies that I’ve diligenced over the years grew or are growing faster than they should.  It’s not uncommon for a hyper-growth lending company to tap pockets of customer demand at the margin, and it’s precisely these marginal customers that have less robust economics and more volatility associated with them.  Increasing repeatability and reducing volatility is almost always more important than an extra 10%, 20% or even 50% growth rate.  Volatile revenue is garbage and nine times out of ten will destroy value and create distracting fire drills.  Do the work and analyze what the last 10% or 20% is actually contributing.  It’s not an easy exercise but ALWAYS worth the time and effort.  Revenue your way into scale is a good mantra to espouse but only if the revenue is stable and robust revenue.

The transition from Phase 2 to Phase 3 is really interesting because it usually comes as a wake-up call vs. a choice.  Most successful businesses grow at a 45 degree angle straight up until the day that they suddenly hit a wall.  WHAM!  Sometimes the wall is a direct result of a shock to the industry or the economy.  Sometimes the wall shows itself after an internal breakdown in processes or controls.  And sometimes the wall is erected by the competitive landscape and appears as a slowdown in the growth rate of the business.  Welcome to Phase 3!

The Phase 3 playbook is usually quite obvious but not without pain and suffering.  The leverage in this Phase typically comes from refinement vs. trail blazing.  It comes from ripping costs out of the system and jettisoning marginal projects, tests and even people.  It comes from renegotiating contracts and focusing on cost-efficient-widget-making.  Costing your way into a healthy business is almost always an inevitable stop on the way to greatness, so when it arrives embrace it, deal with it, and move past it.  I wrote a few posts  earlier in the year that lightly touch on this topic: Thriving, Surviving or Dying and What Happens When The Cash Runs Out.

So how does this tie to my earlier comments about being in “remember when” mode?  It ties to my comments because I find myself sharing stories (both good and bad) and lessons from the past with less experienced operators.  I find myself remembering back to a time when being great meant growing top line at 20-40% a year with 20%+ ROEs for 10 years in a row.  I remember when hyper-growth was punished and consistency was rewarded.  I remember when the resilience and quality of revenue mattered more than raw growth numbers.

Don’t get me wrong, early stage lending companies need to grow at 2-3X a year in order to achieve relevance and overcome fixed costs.  But, my lamentation is around the growth advice that some investors are giving to entrepreneurs and that many entrepreneurs are glomming onto.  Grow, grow, grow!  More is better!

In many cases there doesn’t seem to be an appetite for discussing the right growth rate if it’s sub-100%.  In many cases unit economics take a back seat to top line revenue growth and vertical economics.  And in many cases the hard work around attacking costs is replaced with a view that “we can grow our way into our cost structure”.

My advice is simple.  Learn first.  Grow when you’re ready.  Become operationally excellent.  Embrace the inevitability of a wall.  Build a great business by attacking costs and improving the bottom line.  Rinse and repeat.  And don’t let anyone fool you into thinking that building a lending business is a land grab (as justification for their growth advice).  We live in a consumerist society so the opportunity to lend money will be there tomorrow if it’s there today.  Patience you must have my young Padawan.  Patience.

Belts and Suspenders

First, apologies to those dedicated fellow fintech junkies that actually read what I write.  I’ve been very delinquent in posting recently but it’s been a busy time personally and professionally.  Hopefully I’ll be able to post more regularly going forward….hopefully!

With this said, having just returned from the Money2020 conference I thought I’d share a few thoughts on a topic that I was asked about by quite a few people.  It’s not lost on the broad community of investors and entrepreneurs in the lending space that most of the “next-gen” lenders have built and optimized their risk models during a fairly benign economic period.  Everyone seems to be worried about how well these models will perform in a downturn and how one can protect against a sudden and massive deterioration in a portfolio’s performance.

The key to answering these questions lies in the meta-question: “How resilient is your borrower base”.  And measuring resilience is really about understanding “How many things have to go wrong” at the customer level.

At its core, a lender’s job is relatively straightforward.  A loan officer makes loans to “healthy” customers who they believe are willing and able to pay back the loans.  But the unfortunate truth is that some borrowers in every portfolio default on their loans.  The “why” is pretty clear:   Borrower’s circumstances change over time and these changes matter.

Foundationally, a healthy borrower has the following traits:

  • A relatively stable source of income that supports one’s obligations/lifestyle
  • Enough savings to weather a temporary disruption to one’s income
  • Enough savings or free cash flow that can handle the introduction of additional unforeseen expenses
  • A willingness to pay one’s debtors when the money is available
  • The ability to quickly find a new source of income after a disruption
  • The ability and willingness to turn collateral into cash to pay one’s obligations

So the breakdown of a healthy customer can be traced to a fundamental change in their circumstances.

  • Temporary reduction of income (job loss, reduced commission, etc)
  • Permanent reduction of income (major change in health, retirement, etc)
  • Increased cost of living (increased borrowing, new child, etc)
  • Unforeseen major expenses (car repair, medical bill, etc)
  • Reduction in financial safety net (increased spending, reduction in new savings, etc)
  • Reduction in willingness to pay (strategic default, attitudinal change, etc)

Statistically based underwriting models perform better than loan officers because models are able to predict the natural change in circumstances at the customer and portfolio levels.  A model doesn’t classify a customer as “good” or “bad” but rather that they have a certain probability of paying back a loan.

But both human and statistical based underwriting models/policies suffer from the same phenomenon – tomorrow isn’t guaranteed to look like today.  And while models are able to project an ambient deterioration in a portfolio’s performance, they aren’t fundamentally able to project what will happen in a future they’ve never seen before.

The natural reaction from investors and entrepreneurs who haven’t managed loan portfolios through cycles is to be terrified of what’s to come.  Investors want to naturally stop investing in companies that originate loans.  Less experienced entrepreneurs don’t know how to build resilient underwriting models and convince investors that all is “OK”.

My advice is simple:

Make sure your models give significant weight to the major drivers of risk (ability to pay, willingness to pay, stability of income, etc).  Just exposing a model to hundreds of potential variables isn’t good enough.  Credit officers have to make sure their models appropriately weights each and every potential driver.  And if a model doesn’t want to use an important variable or driver, a credit officers’ job is to force it into the models or policies.

Why?  If an important goal is to create a resilient portfolio, to do this a lender needs to make sure many things can go wrong within the customer base before defaults exceed expectations.  For example, it’s critical to avoid lending to customers who are on edge from a capacity standpoint because minor changes in their circumstances will push them from solvency to insolvency.  DTI might not show up in the underwriting models because our economy has been great for the past handful of years, but I can definitively say from experience that DTI won’t matter until it’s the only thing that matters.  Models don’t understand this.  Good credit officers do.

Another example: Make sure customers with less stable professions have enough savings to weather a temporary disruption to their incomes.  There’s great data at the Bureau of Labor Statistics regarding unemployment rates by profession.  If you’re not studying these statistics and internalizing their impact on the stability of your customer base’s income stream you’re missing out on a great source of information.  Reg B (fair lending) has to be considered when designing approve/decline/pricing policies but once again I can definitively say that this data can be used to improve the resilience of a portfolio of loans.

Belts and Suspenders.  Just make sure you’re not building a business where a single shock to the system causes issues at the customer level.  Trust me — you’ll sleep better as will your investors and customers!