Following the recent crisis, not yet unwound, tail risk and the need for loan by loan stress testing are top of the agenda, for those responsible for mortgage risk. The Walker Report recommends that “the board risk committee should be attentive to the potential added value from seeking external input to its work”. Acadametrics is uniquely placed to provide both risk departments and board risk committees with the “relevant experience” called for by the Report, given our 20 year focus upon stress and scenario testing and purpose built valuation and stress test models. These are now available for lender downloading and use on the MIAC ACADAMETRICS platform. A pioneering 1988 estimate of £5 billion possible losses for lenders and mortgage indemnity guarantee (MIG) insurers, far exceeding industry expectations, led to our on-going work, following the 1989-1991 housing crisis, and what is believed to be the largest “worst case” default UK database, which drives our stress and scenario testing today. Our “Mortgages in Shock” (MIS) publication is freely available, with descriptions of early 1990’s models, numerous tables (including default data) and an overview text. MIS is important reading for risk departments and committees alike. To world-class university econometrics, provided by Dr Stephen Satchell, The Reader in Financial Econometrics at the University of Cambridge and our advisor for 20 years, we add mortgage lending industry experience – covering 30 years for some of our team. MIAC ACADAMETRICS will enable lenders to forecast arrears and repossessions in the national book and potential losses at loan level under the macroeconomic scenarios of their choice using UKAPF and SST below on the platform.

THE NATIONAL LOAN BOOK - UK ARREARS AND POSSESSIONS

UK Arrears and Possessions Forecasting (UKAPF) employs a Satchell/Wongwachara econometric model to forecast future default at national loan book level, as represented by CML data. The model is being further developed to employ FSA data and to account for the effect of forbearance policies on repossessions, employing Bayesian techniques. UKAPF requires forecasts of unemployment, house prices, interest rates and GDP growth as input. The results are valuable for organisation level understanding of possible future outcomes for the economy and for benchmarking the performance of their own loan books against the UK book, under different macroeconomic scenarios.

LENDER PORTFOLIOS – EXPECTED LOSS AT LOAN BY LOAN LEVEL

Stress and Scenario Testing (SST) – our models have always forecast loan by loan losses, based upon real data, meeting a need for loan level output that is now recognised. Our unique 1989-1995 default database encompasses a range of scenarios, such as “benign”, “average”, “severe” and “worst case”. Thus, we are able to set a lender book, loan by loan, into each scenario and to use the past data to forecast the Probability of Possession and the Loss in the Event of Possession, based upon e.g. client-specified house price and mortgage interest rate scenarios. Our Acadametrics Prices and Transactions (APAT) data are employed with SST for inexpensive revaluation of the portfolio although AVM valuations can be equally employed.

LENDER PORTFOIOS – ARREARS AND CASH FLOW AT LOAN COHORT LEVEL

Predictive Mortgage Analytics (PMA) has particular use for loan books lacking a detailed arrears history and for assessing future losses and cash flow. PMA takes borrower numbers and o/s balances, grouped into buckets by arrears status with a bucket for repossessions and can then run sub-groups, e.g. risk or LTV buckets, selected by the client. Using both client and Acadametrics data, PMA develops transition matrices to project arrears, redemptions and possessions. It can be delivered for desktop use by clients wishing to vary the parameters used.