Ford Credit in the US is developing plans to implement machine learning credit approval models to broaden its lending base.
The move came after a study by the captive lender and ZestFinance, which measured the effectiveness of machine learning to better predict risk in auto financing and potentially expand auto financing for millennials and other Americans with limited credit histories.
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Ford Credit chairman and chief executive officer Joy Falotico said: “For this study, we worked with ZestFinance to harness the capability of machine learning to analyse more data and to analyse our data differently. The study showed improved predictive power, which holds promise for more approvals, enhanced customer experiences and even stronger business performance, including lower credit losses.”
According to the company, the machine learning study compared results from a Ford Credit scoring model with a machine learning model developed by ZestFinance using its underwriting platform to do deeper analysis of applicant data. They found it could reduce future credit losses while potentially improving approval rates for qualified consumers, while maintaining its consistent underwriting standards.
A total of 26m Americans have no credit record, according to the U.S. Consumer Financial Protection Bureau
This group includes a large number of millennials, a generational group which made up 29% of all US car sales in 2016, a figure expected to grow to 40% by 2020. This group often struggle to get finance due to a lack of credit history.
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By GlobalDataZestFinance founder, and chief executive officer Douglas Merrill, said: “Machine learning-based underwriting will be a game-changer for lenders, opening entirely new revenue streams. Millennials offer the perfect example.
“They are typically a good credit risk and are expected to command $1.4tr in spending by 2020, but many lack the financial history needed to pass a traditional credit check.”
“Applying better math and more data to traditional underwriting illuminates the true credit risk and helps forward-looking companies like Ford Credit continue to grow their businesses while predictably managing their risk.”
ZestFinance is now offering the Zest Automated Machine Learning (ZAML) Platform, which it developed specifically for credit underwriting. ZAML uses complex algorithms to analyse thousands of data points to provide a richer, more accurate understanding of all potential borrowers, delivered in an easy-to-use web interface.
The ZAML Platform consists of three components: data collection and assimilation, machine learning modelling tools, and transparency tools that enable companies to explain credit decisions.
