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Video / Post | Machine Learning In Fintech/Credit

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October 27, 2015 By Ted OBrien

The Data Science Dude – uses a tree based method in this project named

Customer credit risk analysis using machine learning…

This is a great, quick project explanation – There is a link at the bottom of the page to the full study at GitHub

The purpose of the study is to assess the risk of lending loan to the loan applicant. The data has 20 independent variables that describes the attributes of the loan applicant such as details of bank account, credit history, purpose of loan application, etc, along with bank’s evaluation of the customer having a ‘good’ (low credit risk) or ‘bad’ (high credit risk) as its response. We try to minimize the risk and maximize of profit for the bank. Read More 

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From University of California at Berkeley
Social Data Revolution | Fall 2015

This course is about the use, the importance, and the future of data. It is taught by Andreas Weigend , former chief scientist at Amazon

Here Jonathan Eng & Paul Gu from Upstart discuss how they use machine learning to help younger loan candidates avoid making “short-term optimizations that hurt their long-term potential”

See our open Machine Learning / Data Scientist Positions

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Filed Under: Data Science, Machine learning, What Now? How to get started Tagged With: credit, lending, Machine Learning

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