Machine Learning –
Transforming Small Business Lending from the Inside Out
When considering loans, whether personal or small business, borrowers and banks alike most often think credit scores. Further, when reviewing small business borrowers for loans, lenders typically consider criteria like how long the business has operated, its payment history, its debt service coverage ratio, and its owner’s personal credit.
But do these criteria, especially a small business owner’s personal credit score, truly reflect that business’ ability to repay a loan? What if the business owner maxed out personal credit cards to get the business off-the-ground? What if a 10-year-old sole-proprietor just reorganized the business into an LLC? What variables really determine small business credit risk?
The answer could lie in a tool many banks already use: machine learning. Offering more than data for activities like customer service and marketing, machine learning can also improve a bank’s traditional credit model – especially for small business lending – and complement a banker’s lending experience and expertise.
In his most recent Forbes article, Mirador CEO and Co-Founder Trevor Dryer shares Mirador’s experience with machine learning and how it’s transforming banking – particularly small business lending – from the inside out. Read it now.
Dryer is an advocate for small business lending and fintech. As a contributing member of Forbes Finance Council, he offers perspective on improving access to capital, small business lending considerations and trending topics in the banking industry. Be sure to follow his contributor page.