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Machine Learning and LendingClub Data Improve Credit Assessment

Edited by Suzanne Bowen and Rehan Allahwala Ahmed

Lending Club, with over 1.5+ million borrowers since 2007, recently launched the most advanced and predictive credit model ever used on the LendingClub platform. It’s the latest in their history of innovation that benefits both borrowers and investors.

Machine learning and 10 years of LendingClub data work together to help all better assess and price credit risk. Each LendingClub borrower provides unique insight that the company will use in future decisions.

The new credit model helps LendingClub investors with the following:

• This 5th-generation model is 24% better at differentiating the likelihood of a borrower charging off than the 4th-generation model. It is more predictive than a borrower’s FICO score alone. A FICO score is a type of credit score created by the Fair Isaac Corporation. Lenders use borrowers’ FICO scores along with other details on borrowers’ credit reports to assess credit risk and determine whether to extend credit.

• It’s built on a gargantuan amount of proprietary data, incorporates more data points for each borrower, uses best-in-class modeling techniques, and uses dozens of new custom attributes that are predictive in assessing risk.

• LendingClub expects loan volume to shift toward higher quality grades (grades A and B) because some borrowers will qualify for lower interest rates under the new model, and other higher-risk borrowers, who may have received an offer previously, will be screened out. *

• LendingClub continues to see lower delinquency rates across grades and terms in the existing loan portfolio than in the second and third quarters of 2016.

The peer lending company rolls us this new credit model as the latest innovation in their continuous enhancement cycle, and one that helps them continue to provide investors with solid risk-adjusted returns. Want to know more on what makes the model unique.

So, will this mean that fewer higher-risk borrowers will qualify for loans on LendingClub?

Suzanne Bowen, VP and co-founder of Suzahdi, a custom fit cosplay and traditional leather jacket and vest fashion brand, notes of her experience as a LendingClub investor since 2011, “Obviously, it would be nice to give well-meaning, higher-risk borrowers a chance to improve their credit rating by choosing to invest in their notes, but investors lose money when a borrower defaults.”

Find out more about the new and more advanced and predictive credit model of online peer lending opportunities at LendingClub.

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