The McDash Flash suite from Black Knight leverages daily, loan-level data to provide market participants with the most current view of the forbearance and mortgage performance landscape
In light of the significant impacts the COVID-19 pandemic is having on the U.S. mortgage market, Black Knight,  has been tracking loan-level forbearance data on a daily basis through its newly introduced McDash Flash data set, and is publicly reporting high-level data points on a weekly basis. According to Black Knight CEO Anthony Jabbour, the recent Federal Housing Finance Agency (FHFA) announcement of a four-month limit on advance obligations for servicers of mortgages backed by Fannie Mae and Freddie Mac provides the industry with some much-needed clarity.
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“Having a four-month end date on the period in which servicers need to advance principal and interest payments on behalf of homeowners in forbearance is extremely helpful to our servicing clients,” said Jabbour. “Still, even knowing that time limit, with today’s number of forbearance plans, servicers are still looking at more than $7 billion dollars in advances over those four months. And the forbearance numbers are climbing steadily, day by day. Clearly, this remains a challenging situation all around.”
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Leveraging Black Knight’s extensive data assets and proprietary analytics, the company has launched a suite of McDash Flash solutions based on daily loan-level mortgage data, with insights delivered in multiple forms to meet specific client needs and budgets. Solutions include the daily Forbearance Tracker that lets market participants review general forbearance trends, model short-term outcomes and plan for reserves as well as the interactive business intelligence (BI) of the McDash Flash Forbearance monitor, where clients can access forbearance-specific information customized for servicer benchmarking. For more granular and actionable insight, customized aggregate data sets are available sorted by investor, vintage, geography and other criteria that allow clients to benchmark their performance against the industry and get metrics on short-term vector forecasts presenting expected future performance.
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