RMBS – Prepayment and Default Projection Model

RMBS – Prepayment and Default Projection Model

Context:

  • Automation and process improvement of a model that is used to project Prepayment and default behaviours of different product types at various weighted average loan age.

 

Approach:

  • Collect RMBS unpaid balance and loan status information over the life of the loan from 1010data or suitable databases
  • Divide the entire data into various tranches based on age, product type, fico rating, Prepayment penalties.
  • Analyze the behaviors of each tranche
  • Create prepayment and default curves for each product type at WALA (weighted average loan age)
  • Make necessary adjustment to the curves and incorporate recent prepayment or default pattern. For example give higher weight to the deal originated after 2006 or so, mainly because the prepayment or default behaviour has totally changed over last few years.

Result:

  • Identifying the expected behaviors of prepayment and default curves in immediate future
  • Vital input to cash flow projection, amortization and servicing liability calculation models.