New Big Data Underwriting Models introduced by Zestcash

by Hongde H
The article I read for this week is about a new big data underwriting models that is introduced by ZestCash. The model helps analyze credit risk in an better accuracy that would allow the company to extend credit to 25 percent and increase repayment from customers by 20 percent.

According to what I read, ZestCash underwrites by combining Google-style machine learning techniques and data analysis, and traditional credit scoring. As a result, the company can offer credit to people who would be mistakenly turned away.

How it works?

First of all, the model starts by targeting thousands of variables / data, then it computes related ones and transform the best into most useful form that will be combined into meta-variable which describes a borrower in a specific aspects; For example, customer behaviors such as fraud, short-term and long-term credit risk, or the amount of money a borrower will likely repay.  The meta-variables are later on allocated into different models and will be run through a different method and finally generates factors that contribute to a final decision.

I chose this article because  it is related to what we are lectured last week. besides, the models will help reduce credit flaws and help granting loans to people who really need money in a safer and better way.

Source:  Rao, Leena (April, 26 2012)     “ZestCash Debuts New Big Data Underwriting Models To Determine Consumer Credit Risk”

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3 thoughts on “New Big Data Underwriting Models introduced by Zestcash

  • October 7, 2012 at 9:23 pm

    I thought this article is very interesting because I didn’t know how big a role data plays in the underwriting process. Of the many mortgage lenders that I’ve worked with, many still rely on manual human underwriting and credit risk analysis. Although I think using such automated tools can help with the process, I’m not sure if it should be used as the main determining factor. I think the best thing about ZestCash’s system is that it is able to run up to 10 different underwriting models at the same time.

  • October 7, 2012 at 11:48 pm

    Nice post. ZestCash, founded in 2006, had a winning idea, in principle. It made loans to borrowers with poor credit scores by using complex data analysis to better determine their credit quality. The co-founder of ZestCash, Douglas Merrill said “Our mission was to use big data to save the under-banked billions of dollars in high fees. We think that will work better if we get our technology into the hands of established providers.” I think the model provides a better system.

  • October 9, 2012 at 12:17 pm

    According to the press release on July 1st 2012, ZestCash becomes ZestFinance to extend their big data analytic driven underwriting technology to other lenders (B2B) to help them better understand credit risk in their own businesses and better determine their borrowers creditworthiness, while keep offering loans nationwide (B2C) through working with

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