This is Upstart

Our mission is to enable effortless credit based on true risk.

Why? Because credit really matters. Money is a fundamental ingredient of life, and unless you’re one of the few percent of Americans with significant wealth, the price of borrowing affects you every day. Throughout history, affordable credit has been central to unlocking mobility and opportunity.

Founded by ex-Googlers,

Upstart is a leading artificial intelligence (AI) lending platform designed to improve access to affordable credit while reducing the risk and costs of lending for our bank partners. By leveraging Upstart's AI platform, Upstart-powered banks can offer higher approval rates and experience lower loss rates*, while simultaneously delivering the exceptional digital-first lending experience their customers demand.

$13.6B

originated

**

71%

of loans fully automated

**^

* In an internal study, Upstart replicated three bank models using their respective underwriting policies and evaluated their hypothetical loss rates and approval rates using Upstart’s applicant base in late 2017. Such result represents the average rate of improvement exhibited by Upstart’s platform against each of the three respective bank models.

** As of 6/30/2021. Fully Automated metric is calculated on a quarterly basis.

^ Fully automated loans are defined as loans originated end-to-end (from initial rate request to final funding) with no human involvement.

Lending is centuries old,

but has changed little in recent decades.

Traditional lenders use simple FICO-based models to decide who is approved for credit and at what interest rate. While simple and intuitive, these “scorecard” methods are limited in their ability to quantify risk.

Four in five Americans

have never defaulted on a credit product, yet less than half have access to prime credit.* The implication is eye-opening. With a smarter credit model, lenders could approve almost twice as many borrowers, with fewer defaults.

* According to an Upstart retrospective study completed in December 2019.

AI is upending existing industries

and creating new ones. Whether self-driving cars, home assistants, or language translation, software that learns and improves on its own has moved from research labs to the mainstream in just a few years.

Upstart is one of the first

to apply AI to the multi-trillion dollar credit industry. Upstart goes beyond the FICO score, using non-conventional variables at scale to provide superior loan performance and improve consumers' access to credit.

The system improves constantly,

learning and optimizing in response to daily loan-level repayment and delinquency data.

Upstart's model is significantly more accurate than traditional lending models;

allowing us to approve more applicants at lower loss rates.

Approval numbers compare the 2020 loan approval rate by the Upstart model and a hypothetical traditional credit decision model. The APR calculation compares the two models based on the average APR offered to borrowers up to the same approval rate. The hypothetical traditional model used in Upstart’s analyses was developed in connection with the CFPB No Action Letter access-to-credit testing program, is trained on Upstart platform data, uses logistic regression and considers traditional application and credit file variables.

Upstart model vs. traditional bank models

In an internal study, Upstart replicated three bank models using their respective underwriting policies and evaluated their hypothetical loss rates and approval rates using Upstart’s applicant base in late 2017. Such result represents the average rate of improvement exhibited by Upstart’s platform against each of the three respective bank models.

Realized Loss Rates vs. Rating Agency Model

Rating agencies have an assessment of default for each platform. Upstart has performed better than rating agency expectations.

In an internal study, Upstart compared the actual realized loss rates of Upstart loans securitized in eight securitization transactions between June 2017 and February 2020 and the loss rate predictions for those loans obtained from KBRA Surveillance Reports published by Kroll Bond Rating Agency in October 2020. As compared to Kroll’s loss predictions, actual realized losses were approximately 32% to 54% lower, with an average deviation across all eight securitization transactions of 7%. As compared to our internal forecasts, actual realized losses ranged from approximately 70% higher (for the earliest securitization transaction) to approximately 46% lower (for the most recent securitization transaction), with an average absolute deviation across all of eight securitization transactions of approximately 13%.

Upstart’s AI models allow us to rewire the verification process

approving a majority of loans nearly instantly.

Fully automated loans are defined as loans originated end-to-end (from initial rate request to final funding) with no human involvement.

AI has the opportunity to improve most types of lending globally

over the next decade. While Upstart is focused today on the US consumer market, similar techniques can be applied to all credit markets.

Upstart has worked with regulators since inception to ensure it operates safely within the law.

AI-based lending expands access to affordable credit by constantly finding new ways to identify qualified borrowers. Yet an AI based model must avoid unlawful disparate impact or statistical bias, that would be harmful to disadvantaged groups.


Upstart has demonstrated that our platform doesn’t introduce bias to the credit decision process and has developed reporting procedures to ensure future versions of the model will continue to be fair. In September 2017, Upstart became the first company to receive a No Action Letter from the Consumer Financial Protection Bureau (CFPB).* The purpose of such letters is to reduce potential regulatory uncertainty for innovative products that may offer significant consumer benefit. On November 30, 2020, at the expiration of our first no-action letter, we received a new no-action letter from the CFPB, which has a 3 year term.

Meet our leadership team

Dave Girouard

Co-Founder & CEO

Paul Gu

Co-Founder | Product & Data Science

Anna M. Counselman

Co-Founder | People & Operations

Alison Nicoll

General Counsel

Sanjay Datta

CFO

Jeff Keltner

Business Development

Sagar Mehta

Engineering

Annie Delgado

Compliance

Michael Lock

Bank Partnerships

Chantal Rapport

Growth

Pavi Ramamurthy

Chief Information Security Officer

Meet our board of directors

Jeff Huber

Kerry Cooper

Sukhinder Singh Cassidy

Hilliard C. Terry, III

Mary Hentges

Ciaran O’Kelly

Dave Girouard

Paul Gu

Careers at Upstart

Join us as we bring a combination of modern data science and relentless effort to improve the lives of borrowers.

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