Tendayi Kapfidze is the chief economist at LendingTree. He oversees the company’s analysis of the U.S. economy with a focus on housing and mortgage market trends. Tendayi utilizes data analysis to be a resource for both consumers and trade media, providing impactful and actionable insights to help consumers make informed financial decisions.
More competition is the theme for 2018 and LendingTree has created a way for loan officers to gauge the aggregate level of price competition in the market in real time. Released weekly, LendingTree's Mortgage Rate Competition Index measures the spread in the APR of the best offers available on LendingTree relative to the least competitive.
Most quoted industry rates are for a hypothetical borrower with prime credit who makes a 20% down payment. Yet, most borrowers do not fit this profile and often experience disappointment when the rate on their loan turns out to be meaningfully higher than what they believed prevailing rates to be. Many loan officers have likely experienced having to explain this discrepancy to borrowers with varying degrees of success.
The appraisal industry is in the midst of huge disruption as automated valuation models and hybrid appraisal products gain favor with regulators and investors. What does the future hold for appraisers and appraisal companies as they adjust to the new realities of automation?
As Millennials grapple with paying off student loans, their opportunity to buy a home gets pushed further and further into the future. That delay has consequences far beyond individual students — the growing student debt crisis impacts every part of the economy.
There has been a conscious and rapid shift to broaden the use of alternative valuation products for origination. Not every decision needs a $500, full-blown 1004 interior appraisal. And in some markets where appraisers are short in number, the turn times can stretch from days to weeks. What these new alternative — some would say disruptive — valuation products do is enable lenders and servicers to better match the product to the risk by harnessing big data and technology.