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Petal Uses Machine Learning to Underwrite Credit without Credit Score

After two years of stealth technology development and $3.6 million in venture capital backing, New York City-based Petal has announced a credit card that uses machine learning to underwrite customers instead of traditional credit scores.

Petal, which is targeting 65 million consumers that have struggled to establish credit, uses machine learning to analyze, in real time, a consumer’s full digital financial record.

With this new technology, underserved populations, including millennials, will benefit from safe and affordable credit, with higher limits, lower interest rates, and no fees whatsoever, the company says.

“For new-to-credit consumers, credit is sideways,” says CEO and Co-Founder Jason Gross. “Credit scores are notoriously unreliable and mischaracterize over 65 million Americans, locking them out of the mainstream credit system. These consumers are disproportionately young, immigrant, minority and lower income – and predatory lenders, like payday lenders, have rushed in to fill the gap.”

Petal has partnered with Visa to make its credit card available to consumers. To apply for a Petal Visa credit card, a consumer provides secure read-only access to their bank statements. Petal can verify a consumer’s income, measure monthly expenses and assess a consumer’s ability to afford a credit card.

Petal has no annual, international or late fees and “competitive” introductory interest rates of 17.99 to 24.99 percent. Credit limits range from $500 to $10,000.

Consumers can sign up for an early access waitlist at www.petalcard.com. The company plans to issue cards to beta customers this month and will be announcing its issuing bank partner in “the coming weeks.”

Major financial backers include Brooklyn Bridge Ventures, Afore Capital, Rosecliff Ventures, Guild Capital, Great Oaks Venture Capital, Story Ventures and Silicon Badia.

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