Abstract
In order to minimize losses, mortgage servicers must identify and prioritize those troubled loans that pose the greatest risk to their portfolios. Drawing upon the rich stores of loan-level data residing in their servicing platforms, servicers can better identify their highest-risk loans though the use of predictive models and analytics. By segmenting their portfolios according to expected loss measures, mortgage servicers can more effectively target their limited resources where they have the potential to have the most risk mitigation impact. Predictive modeling allows servicers to project the impact a wide variety of corrective measures may have on the probability and severity of loss and choose their mitigation strategies accordingly. By developing servicer-defined or investor-defined goals and constraints, predictive modeling also enables servicers to structure optimized loan modifications. <b>TOPICS:</b>MBS and residential mortgage loans, CMBS and commercial mortgage loans
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
