The current economic environment means that risk assessment is now uppermost in the minds of management. Many lenders are also at a stage in theory model development for the Capital Requirements Directive, which requires the employment of scenario analysis.

The progressive changes in regulation on this topic are illustrated in a series of CEBS and FSA papers which we provide for information here.

Mortgage lenders face a twin challenge in that the in-house data upon which to base credible scenario analysis models are frequently lacking whilst scenario analysis is a relatively new technique, not always available in-house.

Acadametrics are ideally placed to help. Our first loss scenario analysis was built in 1988. Subsequently, Dr Stephen Satchell, at the University of Cambridge, developed and refined our modelling techniques - work which continues today and, as a result of which, Acadametrics has also built a unique historic possessions database, emanating from the 1989-1991 economic recession and the subsequent fallout in the housing market during the 1990s.

Today, our models provide lenders with the ability to assess loss and default outcomes for their whole book down to individual loan level, and to place these results in the context of default at a national level.

Our core Acadametrics Scenario Analysis provides outcomes under four standard or bespoke macroeconomic scenarios. More details are provided here. The results can either stand alone as reference points or be dovetailed with the lender’s own modelling solutions and assumptions. An overhead presentation of our service is provided here.

For lenders requiring calibration of their own models, we also provide an Acadametrics LGD Data service which provides key data from one of our databases (here).

Other prototype solutions include:

• a desktop Mortgage Risk Assessment Model (M-RAM) which provides the same output as our primary Acadametrics Scenario Analysis model, but provides immediate results of especial value for those evaluating loan portfolios with scarce data



• simulation modelling using Monte Carlo techniques



• cash flow modelling to measure mortgage book profitability under different economic scenarios



• Arrears and Possessions Forecasting Model, employing UK macro economic assumptions and CML data