HONOLULU, HI: Collateral Analytics has launched a new article demonstrating how its CA Credit Risk Model may confirm and quantify the impact of important potential risks associated with appraisals and mortgage lending.
It discusses a number of examples evaluated by CA’s Credit Risk Model which measure the additional credit risk associated with different amounts of potential upward bias in property appraised values. Two of the cases presented highlight the central output measure of model – the credit risk spread (CRS), which is a measure of the annual losses incurred by the lender due to borrower default. The CRS for a loan with a 95 percent LTV and borrower credit score of 660 is estimated to be 82 basis points for the case in which the initial value equals CA’s AVM estimate. The CRS increases to 88 basis points for the same basic loan in which the initial value of the property is 10 percent higher and the AVM remains the same.
The CA Credit Risk model confirms and quantifies this important potential risk of mortgage lending. The article summarizes that a loan with a higher initial value for a given loan amount may look to be less risky than a loan with a lower initial or appraised value for the same loan amount, but such a look may be deceiving if the initial value is inflated or upwardly biased.
“We are excited about CA Credit Risk’s impact in the mortgage industry,” says Michael Sklarz, President and CEO of Collateral Analytics, a leading provider of comprehensive automated valuation solutions and real estate analytic products for large lenders and the financial services industry. “We have the ability to provide AVMs to clients with key summary results of the Credit Risk Model to help them use both the standard AVM results and the credit risk model results to prioritize property valuations most in need of additional review or scrutiny.”
The CA Credit Risk Model combines CA’s industry leading AVM with its proprietary home price forecast and mortgage performance models to predict the expected profitability of a mortgage and offers quantitative measures of the risk and cost of potential borrower default embedded in a residential mortgage.