Black Knight, Inc.’s McDash mortgage and home equity database recently incorporated loan-level performance data for loans on single-family properties in Puerto Rico, the company announced.
The McDash database features mortgage and home equity data on more than 175 million unique loans across the credit spectrum, spanning more than three decades of mortgage performance, according to a company press release. Offering “the fastest turnaround in the market,” the release states, McDash provides data 15 days after month-end. McDash’s data on loans in Puerto Rico will help investors, traders and servicers:
- Perform benchmarking and analysis on loan portfolios
- Build better prepayment, default and economic models
- Help predict loan delinquencies
- Quantify loan-loss behavior
High-quality mortgage performance data is critical to assessing loan portfolio risk on the island, where more than 200,000 homes were damaged by Hurricane Maria. Based on the most recent data, an estimated 84,000 mortgages remain past-due as a result of the storm, according to the release. More than one-third of all mortgages in Puerto Rico are at least one payment in arrears, while 19 percent are 90 or more days past due.
Investors in Government National Mortgage Association (Ginnie Mae) securities may be particularly interested in the new McDash Puerto Rico data, as Ginnie Mae loans make up twice the market share in Puerto Rico as in the U.S. mainland.
“The devastating impact of Hurricane Maria – and to a lesser extent, Irma as well – is still being felt on the ground in Puerto Rico,” said Kevin Coop, group executive and president of Black Knight’s Data and Analytics division. “That impact extends into the mortgage market as well. Expanding our dataset to include mortgage loans in Puerto Rico will help industry professionals assess mortgage credit, prepay and loss performance on the island, even in the best of times. Post-Maria, the need for insight into loans on the island has become that much more urgent, and McDash can help provide the details needed to manage the associated portfolio risk.”