Sandbox effect on shadow banking

The Lender’s Challenge: Balancing Non-Prime Risk and Market Opportunity

Not all non-prime borrowers represent a poor credit risk for lenders. By using advanced analytics, smart lenders are finding ways to identify and underwrite many of these households that others cannot.Though consumers seeking credit come from all walks of life, not all appeal to prime lenders. Consider this household profile: A working married couple makes a total of $70,000 per year. Due to some early credit mistakes and medical expenses, each has a credit score below 600 and has been locked out of the prime lending stream. However, they’ve paid their rent, cell phone, and utility bills on time for several years, and always have a few hundred dollars in a joint checking account. Now with a child on the way, they need to make purchases beyond their modest budget.This household is typical of an underserved consumer lending segment: 160 million Americans with no access to prime credit even though many have proven payment records. As of Q3 2017, the personal unsecured loan market transacted $112 billion; 30% of that amount was lent by non-traditional ‘fintechs’, many who cater to non-prime households. It’s a growing market: in 2010, these lenders represented a 3% market share.

We have Moore and sandbox theory finding better matches between deposits and loans.  Market uncertainty driven down via better analytics makes for faster transaction rates, larger market.