Fintech

Quick S-1 Teardown: nCino

[July 14, 2020 IPO update – stock popped + 195% first day of trading, see end of post for details on IPO]

The upcoming nCino IPO is an interesting story, and a good reminder that strong cloud/SaaS companies can be built outside of the usual Silicon Valley or NYC venture path (even with VCs on board)

(As a side note: we often do those S-1 summaries internally to keep tabs on the software IPO market, so my colleague Avery Klemmer and I figured we’d “open source” this one in case it might be interesting to others – thoughts and comments welcome. Our firm FirstMark is not an investor in nCino)

HIGH LEVEL THOUGHTS & LESSONS:

nCino is a refreshing example of a successful software company that’s built a little bit outside of what’s currently in favor in venture capital circles:

Vertical software: Many VCs these days tend to prefer broad horizontal opportunities, with a concern that vertical software ultimately has a limited TAM, even a large one – but nCino is 100% focused on the banking market
Service heavy, no bottoms up GTM: nCino sells its products through AEs , with long sales cycles, and significant implementation services are involved
Platform dependency? Being built on top of someone else’s platform is often a concern for investors. nCino is built on top of Salesforce (like Veeva). They’ve seemingly safeproofed this relationship by reselling Salesforce products in their deals, and raising money from Salesforce, wnich is a large investor.
Not a Silicon Valley or NYC story: Launched in 2012 by executives of North Carolina-based Live Oak Bank as a spin-off venture. Still based in Wilmington, North Carolina
It’s a spinoff from a bank: the company was originally founded as a majority-owned subsidiary of Live Oak Bancshares, a bank holding company. It then raised $9m in seed funding in 2013 from a variety of individuals including John Mack of Morgan Stanley and Chip Mahan, the Chairman of Live Oak Bank. So nCino didn’t have the structure that most VCs like to see, where the founding team has high ownership and the first money in comes from institutional investors. This history as a spin-off is probably the reason why the CEO of the company owned only 1.6% at IPO time, although we don’t know this for sure).

The Path to a $2.7B Unicorn: In Conversation with Zach Perret, CEO, Plaid

“We are, by far, the earliest company here”. This how Zach Perret, CEO of Plaid, started his talk at his first appearance at Data Driven NYC, back in February 2013. “We are basically three guys, coding 24 hours a day, and building developer tools…”.

Fast forward to today: the company was valued at $2.7B (“allegedly”, says Zach) in its most recent $250M round; Plaid has integrated with 15,000 banks in the U.S. and Canada and 4,000 fintech applications. One in four people in the U.S. have linked an account using Plaid. And they have just acquired New York based competitor Quovo for $200M (“reportedly” as well).

Not bad for a self-described “data plumbing” company. As today’s consumers expect to live fully digital financial lives, with their phone at the core, Plaid provides the financial infrastructure that enables developers in fintech companies to build great applications, and have consumers connect those to their bank accounts – basically Plaid is the connective tissue between the app and the bank, and takes care of moving all the data back and forth in the background.

It was a lot of fun having Zach back at the event 6 years later. Here’s the video of our fireside chat, and my notes are below the fold.

Data, AI & Hedge Funds: In Conversation with Matt Ober, Chief Data Scientist at Third Point

The hedge fund world has been evolving dramatically over the last few years.

Just like in other industries, software, data and AI/ML have been playing an increasingly important, and disruptive, role. Many hedge funds have been scrambling to embrace this evolution – not just to gain an edge, but also to avoid becoming extinct.

Certainly, quantitative hedge funds have been making heavy use of software and data for a while now. The “quant” funds rely upon algorithmic or systematic strategies for their trades – meaning that they generally employ automated trading rules rather than discretionary (human) ones, and they will trade tens or hundreds of assets simultaneously.

But another big part of the industry, the “fundamental” hedge funds, had been operating very differently. Those funds will perform a bottoms up analysis on individual securities to value them in the marketplace and assess whether they are “undervalued” and “overvalued” assets. They’ll often have a much more concentrated portfolio.

In part because the entire hedge fund industry has been performing generally poorly recently (years of performance trailing the stock market), there’s been mounting pressure on hedge funds to evolve rapidly, particularly fundamental ones.

A couple of years ago, Third Point made a big splash when they hired Matt Ober, who was 32 at the time, to become their Chief Data Scientist. Dan Loeb, the billionaire founder of Third Point, was a prime example of a fund manager who had reached tremendous success through a fundamental approach. His efforts to hire Matt away from his previous employer and make him Third Point’s head quant was widely viewed as a sign of the times. Continue reading “Data, AI & Hedge Funds: In Conversation with Matt Ober, Chief Data Scientist at Third Point”

Ledger and the Fundamental Need for a Security Infrastructure in Crypto

2017 was an extraordinary and crazy year in the world of cryptocurrencies. Prices skyrocketed (Bitcoin: +1,400%; Litecoin: +5,400%, Ethereum: +8,700%; Ripple +35,000%). ICOs raised over $3 billion. Crypto hedge funds emerged all over the map and a handful of blockchain startups reached unicorn-level valuations.

Almost inevitably, the price of individual cryptocurrencies will experience substantial volatility in 2018, and the first few days of January already look like a rollercoaster. Prices may very well crash altogether. In more ways than one, the space feels reminiscent of the dot-com days of the late 1990s, whether it is stories of newly minted bitcoin millionaires, the undeniable speculation rampant throughout the market, or the emergence of many weird things. While growing and expanding, the actual use cases of the blockchain still trail behind.

Taking a step back from the immediate frothiness, however, it seems that the crypto world has hit the point of no return, vaulting from a fringe movement into the mainstream collective consciousness, with strong interest both from the public and Wall Street. The blockchain has cemented its position as a new paradigm, which will only grow in importance, offering new solutions to the world, and new opportunities to entrepreneurs.

Continue reading “Ledger and the Fundamental Need for a Security Infrastructure in Crypto”

The New Gold Rush? Wall Street Wants your Data

A few months ago, Foursquare achieved an impressive feat by predicting, ahead of official company results, that Chipotle’s Q1 2016 sales would be down nearly 30%. Because it captures geo-location data from both check-ins and visits through its apps, Foursquare was able to extrapolate foot-traffic stats that turned out to be very accurate predictors of financial performance.

That a social media company could be building a data asset of immense value to Wall Street is part of an accelerating trend known as “alternative data”. As just about everything in our lives is getting sensed and captured by technology, financial services firms have been turning their attention to startups, with the hope of mining their data to extract the type of gold nuggets that will enable them to beat the market.

Could working with Wall Street be a business model for you?

The opportunity is open to a wide range of startups. Many tech companies these days generate an interesting “data exhaust” as a by-product of their core activity. If your company offers a payment solution, you may have interesting data on what people buy. A mobile app may accumulate geo-location data on where people shop or how often they go to the movies. A connected health device may know who gets sick when and where. A commerce company may have data on trends and consumer preferences. A SaaS provider may know what corporations purchase, or how many employees they hire, in which region. And so on and so forth.

At the same time, this is a tricky topic, with a lot of misunderstandings. The hedge fund world is very different from the startup world, and a lot gets lost in translation. Rumors about hedge funds paying “millions” for data sets abound, which has created a distorted perception of the size of the financial opportunity. A fair number of startups I speak with do incorporate idea of selling data to Wall Street into their business plan and VC pitches, but how that would work exactly remains generally very fuzzy.

If you’re one of the many startups sitting on a growing data asset and trying to figure out whether you can make money selling it to Wall Street, this post is for you: a deep dive to provide context, clarify concepts and offer some practical tips.

Continue reading “The New Gold Rush? Wall Street Wants your Data”

Lending Club IPO: Nice Guys Don’t Finish Last, and Other Lessons

The superb Lending Club success story is what the startup world is all about: a software-based reinvention of massive and inefficient industry; a product that puts consumers first and delivers undeniable benefits ; and an entrepreneurial mega-hit that brings incredible riches and returns to its founder and investors.

In some ways, Lending Club is a classic Silicon Valley story; in some other ways, it is pretty atypical. As a friend of Renaud Laplanche’s for over 20 years, I have had a chance to witness from up close some parts of his journey with Lending Club. It is full of interesting lessons for entrepreneurs and the tech industry in general:

Continue reading “Lending Club IPO: Nice Guys Don’t Finish Last, and Other Lessons”

Can the Bloomberg Terminal be “Toppled”?

In the eye of some entrepreneurs and venture capitalists, the Bloomberg terminal is a bit of an anomaly, perhaps even an anachronism. In the era of free information on the Internet and open source Big Data tools, here’s a business that makes billions every year charging its users to access data that it generally obtains from third parties, as well as the tools to analyze it. You’ll hear the occasional jab at its interface as reminiscent of the 1980s. And at a time of accelerating “unbundling” across many industries, including financial services, the Bloomberg terminal is the ultimate “bundling” play: one product, one price, which means that that the average user uses only a small percentage of the terminal’s 30,000+ functions. Yet, 320,000 people around the world pay about $20,000 a year to use it.

Continue reading “Can the Bloomberg Terminal be “Toppled”?”