Collateral Valuation Case Study: Mid-Sized Commercial Bank’s Mortgage Unit Leverages MAP AVM for Periodic Updating of Its Held-for-Investment Mortgage Portfolio Collateral Values

Client’s Challenge

  • The consumer risk management group determined that as the bank’s mortgage whole loan portfolio had grown, its ability to conduct periodic updated valuations of collateral underlying those mortgages was limited.
  • The bank had expanded its mortgage lending activities beyond its historic footprint and so it wanted to understand how changes in collateral value would translate into current LTVs that in turn would influence delinquency and default performance of the portfolio over time.

Our Solution

  • The bank sought a solution that met the following requirements; could efficiently and accurately assess property values in the portfolio; was lowcost; and could integrate easily with existing portfolio management capabilities.
  • The MarketAssessed Price (MAP) AVM was determined to be the right solution for the risk management team’s problem since it is one of the most accurate AVMs on the market and has extensive coverage among AVMs used today.
  • MAP was tested by the risk management team on a representative sample of the bank’s mortgage portfolio and found to be easytouse and satisfied the requirements stipulated by the bank.
  • MAP was deployed by the bank into its regular portfolio management process and returns estimates of current estimated values that are used in calculating current LTVs.

Outcome

  • Every quarter, the bank creates its MarktoModel CLTV Report which describes changes in the distribution of its $10 billion mortgage loan portfolio’s estimated current LTVs using the MAP automated valuation model.
  • The bank has further evolved its process for updating portfolio collateral valuation by leveraging the FBA house price forecasting model to project CLTVs in the portfolio over time and under different economic scenarios,further enhancing their ability to understand the impact of market movements on credit risk migration.