Our records begin with a 1988 forecast of £5 billion losses for lenders and MIG insurers. In 1989, we started work with Dr Stephen Satchell, The Reader in Financial Econometrics at the University of Cambridge, who developed our hazard rate methodology. Using our unique downturn default database which includes default from the 1989-1991 “worst case” housing crisis, we employ hazard rates to calculate PDs. Twenty years later, Dr Satchell continues to lead our risk and index work, enabling us to provide lenders with leading edge models and data support of direct relevance to current regulatory and credit risk requirements. Our models operate across the full range of data levels from individual loans to the whole UK book, as follows:

at UK LOAN BOOK LEVEL

UK Arrears and Possessions Forecasting forecasts future default at national loan book level, as represented by CML data. Results can be used by clients for benchmarking the performance of their own loan books against the UK book, under different macroeconomic scenarios, or by economists modelling the UK economy

at LOAN BY LOAN LEVEL

Stress and Scenario Testing SST enables clients to upload their loan book data onto our secure server and to download results, designed to meet their requirements. Our results typically comprise modelled PDs, using hazard rate methodology, LIEPs (loss in the event of possession) and total expected losses; our revaluations use our THP data or a client-specified index; the model can also use client PDs. Losses are prepared, loan by loan, under any of the key macroeconomic scenario model variables and over timescales, chosen by the client, and employ our extensive downturn default data; optional forced sale values, rental prices and yields; loans may also be ordered by, say, expected loss amount to assist customer/loan management teams, one-off or regularly

at LOAN COHORT LEVEL

Predictive Mortgage Analytics PMA like SST takes loan by loan data which we group within the cohorts (e.g. risk groups) required by the client; to these, we apply the SST procedures (including revaluation using our Transacted House Prices) to calculate a range of input average parameters (or averages may be provided by the client). PMA optionally returns a comprehensive performance appreciation and forecasts arrears, redemptions, possessions and cash flow by quarter for one year and aggregate estimated losses over nine years (or other agreed time period), at cohort level. Our detailed appreciation covers the current book and its potential behaviour over the agreed time period, under agreed future macroeconomic scenarios. PDs can be based upon client, as well as Acadametrics, roll rate data and Acadametrics experience of repossession development patterns. Alternatively, our “worst case” PDs from the 1989-1991 housing crisis, with or without multipliers, can be used. Data will need to be validated and averages by cohort prepared by Acadametrics, but the setting of parameters and the modelling process (including Reverse-stress testing) can be carried out by the client in-house using the PMA model in Excel on a desktop pc.