Upstart 💸 AI-Driven Lending
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Happy to have you on board! Today, we provide you with an easy briefing on an under-hyped and high-growth company:
Upstart 💸
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Please note that this article does not constitute investment advice in any form. This article is not a research report and is not intended to serve as the basis for any investment decision. All investments involve risk and the past performance of a security or financial product does not guarantee future returns. Investors have to conduct their own research before conducting any transaction. There is always the risk of losing parts or all of your money when you invest in securities or other financial products.
Upstart 💸 (NASDAQ:UPST)
🔦 THE INTRO 🔦
Upstart is an online lending marketplace that provides personal loans by applying machine learning to a vast array of non-conventional variables.
It was founded in 2012 by Dave Girouard, former president of Google Enterprise, Paul Gu, a Thiel Fellow and Anna Counselman, a former Google manager.
⚡️ THE ISSUE ⚡️
Upstart quickly found out that there was a mismatch between borrower’s creditworthiness and their access to prime credit.
80% of Americans have never defaulted on any credit product
Only 48% of Americans have access to prime credit
This leads conventional players to refuse credit to “good borrowers”, negatively impacting the borrower but also the lender’s bottom line.
⚙️ HOW IT WORKS ⚙️
The company therefore developed an income and default prediction model that is capable of determining the creditworthiness of prospective borrowers.
As conventional banks, it uses traditional variables (FICO score, income, credit report) to predict creditworthiness
It also uses academic variables (GPA, area of study, colleges) and work history to predict a borrower’s propensity to repay
All in all, it uses over 1,600 data points to score borrowers
🔥 DELIVERING RESULTS 🔥
These consumers benefit from lower interest rates, higher approval rates and a highly automated and digital experience:
Upstart provides 27% more approvals than traditional models
Borrowers benefit from 16% lower rates than traditional models
At the same approval rate, Upstart gets 75% less defaults than large US Banks
At the same loss rate, Upstart gets 173% more approvals
Upstart doesn’t make loans itself, rather it connects consumers to its network of Upstart AI-enabled bank partners.
⚗️ ARTIFICIAL INTELLIGENCE FLYWHEEL ⚗️
Upstart is able to improve its models, cut down its loss ratio and select good borrower more efficiently as the volume its processes increases over time.
It uses more data and better models to undercut competition
Customers get better interest rates, attracting even more customers
With more data, Upstart is able to continuously improve its models
🛍 THE PRODUCT 🛍
Upstart’s loans go from $ 1,000 to $ 50,000 and concern 3 to 5 years loan terms with an APR range of 6.5% to 35.99%.
99% of these loans are funded in 1 business day after signing
Approximately 70% of Upstart-powered loans are instantly approved with no document upload of phone call required
Borrowers can pay their loan back early at no cost
Upstart is focussed on personal loans, it thus offers helps customer with:
Moving loans
Home improvement loans
Medical loans
Credit card consolidation
Debt consolidation
Wedding loans
🍀 EASE OF USE 🍀
Upstart’s tools are delivered in the form of a simple cloud application. This shields borrowers from the underlying complexity of Upstart’s tools.
Upstart’s bank partners can configure many aspects of their lending programs, including factors such as:
Loan duration
Loan amount
Minimum credit score
Maximum debt-to-income ratio
Return target by risk grade
👤 ATTRACTING BORROWERS 👤
Upstart is referring borrowers to partner banks when these visit Upstart’s website. Borrowers can also interact with Upstart’s tools as a white-label product through their bank’s interface.
Directly through the Upstart website
As always, a partner bank will emit the loan as Upstart itself doesn’t provide any loan
The loan can then be retained by the originating bank, sold to Upstart’s network of institutional investors or funded by Upstart’s own balance sheet
In Q3 ’20, around 22% of the loans issued directly through Upstart were retained by the originating bank
Around 76% were purchased by institutional investors (such as PIMCO, Goldman Sachs, Morgan Stanley)
Around 2% were funded by Upstart’s own balance sheet
“but that’s for research and development, so we can test new things.” Dave Girouard by Penny Crosman for American Banker
Through a white-label product on the bank partner’s own website
The bank uses Upstart’s models and algorithms to predict a prospective borrower’s creditworthiness
It then makes the loan on its own through its own interface
📣 MARKETING CONCENTRATION 📣
Most of Upstart’s growth and marketing initiatives are focused on bringing potential borrowers to Upstart. It relies on direct mail, podcast advertising, affiliate marketing and online advertising to boost growth. Noteworthy is their dependence on Credit Karma:
In 2020, 52% of consumers that applied for a loan on Upstart.com learned about and access Upstart.com through the website of a loan aggregator, Credit Karma:
“The percentage of loan originations that were derived from traffic from Credit Karma was 28%, 38%, 38% and 52% in 2017, 2018, 2019 and the nine months ended September 30, 2020, respectively” Upstart S1 Filing
Only 12% of loan originations came from direct mail, down from 36% in 2017
“[…] the percentage of loan originations that were derived from direct mail was 36%, 28%, 23% and 12%, in 2017, 2018, 2019 and the nine months ended September 30, 2020” Upstart S1 Filing
💵 BUSINESS MODEL 💵
Upstart counts 10 bank partners and generates around 98% of its sales with fees paid by these banks. These are charged for:
Referral fees for each loan referred through Upstart
Amounts to $ 400 to $ 500 per loan on origination
Platform fees for each loan originated
Amounts to $ 200 to $ 300 per loan on origination
Loan servicing fees as customers repay their loans
Amounts to 0.5% to 1% per loan
Upstart’s bank partners include Cross River Bank, Customers Bank, FinWise Bank, First Federal Bank of Kansas City, First National Bank of Omaha, KEMBA Financial Credit Union, TCF Bank, Apple Bank for Savings and Ridgewood Savings Bank.
👤 CUSTOMER CONCENTRATION 👤
Of these 10 banks, Cross River Banks generated 65% of Upstart’s total revenue in 2020, down from 81% in 2019. Upstart’s second largest customer generated 15% of Upstart’s sales in 2020.
“for our first four or five years, we just worked with Cross River Bank. We came to a decision point about two years ago: Do you become a bank and pursue a bank charter, or do you decide to be a friend of banks and fan out from Cross River? We chose that second path” Dave Girouard by Penny Crosman for American Banker
Larger banks are not yet working with Upstart as they are figuring out whether they should build the technology in-house.
“The company isn’t yet working with any of the largest banks, as those institutions have to figure out if they want to partner or try to build the technology themselves. But he’s having conversations” by Ari Levy for CNBC
🌐 THE MARKET 🌐
Upstart now controls 5% of the personal loans market, a market that grew by 8% in 2020. The company is further set to benefit from the growth of the digital lending market which is projected to rise by 11.9% a year over the 2020 - 2025 period.
According to TransUnion, there were $ 118B in unsecured loans from April 2019 to March 2020 - growing at 8% year on year
Upstart facilitated the origination of $ 3.5B in unsecured personal loans, accounting for 5% of the total market
According to Mordor Intelligence, the digital lending market is expected to grow at a CAGR of 11.9% over the 2020 - 2025 period
Driven by the proliferation of smartphones, advanced in machine learning and cloud computing
“Also, technologies like Artificial Intelligence, Machine Learning, and Cloud Computing benefit the banks and fintech as they can process huge amounts of information about customers.” Mordor Intelligence
According to the Federal Reserve Bank of St Louis, from April 2019 to March 2020, there were:
$625 billion in U.S. auto loan originations
$363 billion in U.S. credit card originations
$2.5 trillion in U.S. mortgage originations
Upstart’s also ambitions to apply its methodology and models to adjacent markets such as auto, home and credit cards.
“[…] by applying our AI models and technology to adjacent opportunities, we believe we are well-positioned to address the U.S. auto loan, credit card and mortgage markets.” Upstart S1 Filing
This would considerably expand Upstart’s TAM from $ 118B to $ 3.6T.
“In June 2020, we began offering auto loans on our platform, and in September 2020, the first auto loan was originated through the Upstart platform” Upstart S1 Filing
🧞♂️ FOUNDER-LED AND EXPERIENCED MANAGEMENT 🧞♂️
Upstart is a founder-led company as Dave Girouard is CEO, Paul Gu is Product Lead and Anna Counselman is People And Operations Lead. Management has deep experience in technology, consulting and finance.
Co-Founder and Chief Executive Officer of Upstart
Formerly President of Google Enterprise. Before that, he was a Product Manager at Apple and an associate in Booz Allen's Information Technology practice
Graduated from Dartmouth College with an AB in Engineering Sciences and a BE in Computer Engineering. Also holds an MBA from the University of Michigan with High Distinction
Co-founder and Product and Data Science Lead at Upstart
Previously worked in risk analysis at the D.E. Shaw Group and has been recognized as one of Peter Thiel's 20 under 20 Fellows, Forbes 30 under 30, and Silicon Valley Business Journal's 40 under 40
Studied economics and computer science at Yale University
Co-founder and People and Operations Lead at Upstart
Previously led Gmail Consumer Operations at Google and launched the global Enterprise Customer Programs team. Received a White House Champion of Change award and was recognized as one of Silicon Valley Business Journal's 40 under
Graduated Summa Cum Laude from Boston University with a BA in Finance and Entrepreneurship
Chief Financial Officer and responsible for leading financial operations and capital markets efforts at Upstart
Formerly the VP of Advertising Finance at Google, overseeing the global finance organization. Also held various international finance leadership positions in Asia and Europe. Prior to Google, worked at private investment group Artisan Capital, and began his career as a valuation and data specialist at Deloitte Consulting
Has a joint honors degree in Economics and Finance from McGill University in Montreal and an MBA from Stanford University
✋ TAKE A BREATH ✋
So… This is a lot of information. Let’s summarise:
The company developed a model that relies on non-traditional data to predict a borrower’s creditworthiness
It started with the personal loans segment and already serves 5% of the market and it also plans to enter the auto, credit card and mortgage market, unlocking a $ 3.6T market
Upstart is expanding its partner banks’ base in order to reduce customer concentration
However, most of its Upstart.com-generated loans come from one single source, Credit Karma
As for most data-driven players, their flywheel effect is built on increasing the data they can access by increasing their customer base which is done by providing a better (user experience) and cheaper service than competition
💸 FINANCIAL CHECK 💸
Sales grew 44% in first 9 months of 2020 to $ 164m
Spent $ 80m on borrower acquisition, verification and servicing costs
Recorded a contribution profit of $ 63m in first 9 months of 2020 up 151% year over year
Despite a large contraction in lending during the pandemic as its partners paused lending
Operating expenses reach $ 145m up 32% from $ 110m a year earlier
Recorded a profit of $ 4.6m in the first 9 months of 2020 up from a loss of $ 10m a year earlier
⚡️ THE BOTTOM LINE ⚡️
The Good
Upstart is a fast-growing digital lending player that uses machine learning to predict borrowers’ creditworthiness
It is able to provide 27% more approvals than traditional players and 70% of its operations are automated, providing instant approval for borrowers
It started with the personal loans market which grew 8% year over year and plans to enter the auto, credit card and mortgage markets
Upstart doesn’t hold the risks related to lending as it simply refers customers to loan providers
Dealing with customer concentration, Upstart is expanding its partner bank’s base and having conversations with larger banks
Given its total addressable market, management and financial performance, it is reasonably valued at 15 to 17 times its sales
The Bad
The lending market is strongly correlated to the business cycle, negative prospects might reduce borrowers’ propensity to apply for consumer loans as they cut non-essential expenses
A rise in interest rates might negatively influence Upstart’s growth as borrowing would become more expensive for consumers
Over 50% of Upstart’s referrals come from one single source, Credit Karma
Around 80% of Upstart’s revenue is generated from 2 large customers
🚨 THE STAKE 🚨
We have full position in Upstart. Upstart is a fast-growing lending player that is changing the industry by using machine learning and a broader set of variables to assess borrowers’ creditworthiness. Upstart is led by ex-Google managers and directors with strong technology and finance experience. These apply their tech know-how to the slow-moving lending market.
We will increase if Upstart manages to reduce customer concentration, diversify its incoming traffic from Credit Karma and partner with Tier-1 banks
We will cut if customer concentration further increases and if it fails to partner with a Tier-1 bank
Edit (March 22, 2021): We have cleared our stake in Upstart.
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Sources and credits
Investor presentation
Company website
American Banker
Mordor Intelligence
TransUnion
FED
TechCrunch
Crunchbase
Disclaimer
Please note that this article does not constitute investment advice in any form. This article is not a research report and is not intended to serve as the basis for any investment decision. All investments involve risk and the past performance of a security or financial product does not guarantee future returns. Investors have to conduct their own research before conducting any transaction. There is always the risk of losing parts or all of your money when you invest in securities or other financial products.
Disclosures
The author has no business relationship with any company mentioned in this article and the author is not receiving any form of compensation for this article other than contributions from paying subscribers.