Types of Equity Release Products



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Equity Release Assumption Setting Gina Craske Colin Wilson Types of Equity Release Products Reverse Mortgage/Home Income Provider lends home owner cash which must be repaid with rolled up interest on death or move to long term care, cash may be taken all up front or in stages Reversions Provider buys a share/all of the home owner s property, who lives in the property rent free until they die or move to long term care. The price paid reflects the time till the provider expects to get their share of the house. Can be sold with back to back annuities. Shared Appreciation Home owner gives up the right to some of the capital gain on the property in return for paying reduced or no interest on that part of the borrowings. Reverse Mortgages Loan Types Fixed / variable Lump sum / income / redraws Low maximum LTV s Age dependent: No Negative Equity Guarantees Repayment on death or move to care is not higher than the value of the property value. Housing Maintenance Regular valuations Other Obligations Insurance, Rates, Prior approval for renovations 1

Risks to the provider (reverse mortgages) House price inflation (can be exasperated by longevity) Movements in interest rates Higher mortality/move to long term care than expected Reputational risk Individual house price volatility Lack of data Lapses/remortgages and the correlation with interest rates Elements in the basis HPI rates Interest Rates Mortality Move to long term care Other lapses/surrenders Expenses Setting HPI Assumptions 2

Data Issues Problems of index construction Transactions / standardised Limited data Single 30 year history for regional data Insufficient granularity For equity release, may need assumption for individual house volatility, not index Lack of (prospective) model consensus Climate change? Population growth? Halifax Indices 1000 H alifax House P rice Indices (All houses, All buyers, S easonally adjusted) NORTH NORTH W EST YORKS. & HUMB. E. MIDLANDS W. MIDLANDS EAST ANGLIA SOUTH W EST GR. LONDON SOUTH EAST WALES Price Index (log scale) SCOTLAND UK N. IRELAND 100 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Q1 Quarterly Log Changes NORTH YORKS. & HUMB. NORTH WEST E. MIDLDS W. MIDLDS EAST ANGLIA SOUTH WEST SOUTH EAST GR. LONDON WALES SCOT. N. IRELAND UK Mean 0.019 0.020 0.019 0.020 0.019 0.019 0.019 0.019 0.021 0.019 0.016 0.020 0.019 S.d. 0.030 0.029 0.027 0.033 0.033 0.034 0.033 0.029 0.029 0.033 0.024 0.035 0.023 Ann'd mean 0.075 0.078 0.075 0.078 0.078 0.077 0.077 0.076 0.083 0.076 0.063 0.079 0.077 Ann'd s.d. 0.060 0.058 0.054 0.065 0.067 0.069 0.065 0.059 0.057 0.066 0.049 0.069 0.045 Autocorrel 0.64 0.76 0.66 0.67 0.59 0.75 0.74 0.71 0.75 0.53 0.04 0.14 0.83 s for quarterly log price changes 10 0.072 0.057 0.058 0.052 0.055 0.053 0.056 0.053 0.057 0.058 0.048 0.061 0.048 50 0.013 0.015 0.013 0.014 0.013 0.019 0.017 0.021 0.026 0.016 0.015 0.016 0.017 90 0.011 0.008 0.006 0.010 0.010 0.020 0.017 0.017 0.024 0.015 0.009 0.016 0.007 Regression of quarterly log price changes on national index β 0.791 1.056 0.859 1.319 1.302 1.139 1.264 1.021 0.916 1.125 0.468 0.047 1.000 α 0.004 0.001 0.002 0.006 0.006 0.003 0.005 0.001 0.003 0.002 0.007 0.019 0.000 σ 0.024 0.017 0.019 0.013 0.016 0.023 0.016 0.018 0.020 0.021 0.022 0.035 0.000 3

Correlations of Quarterly Changes YORKS. & NORTH E. W. EAST SOUTH SOUTH NORTH HUMB. WEST MIDLDS MIDLDS ANGLIA WEST EAST GR. LON WALES SCOT. N. IRE YORKS. & HUMB. 0.78 NORTH WEST 0.78 0.84 E. MIDLANDS 0.47 0.74 0.65 W. MIDLANDS 0.45 0.75 0.59 0.85 EAST ANGLIA 0.17 0.38 0.25 0.67 0.71 SOUTH WEST 0.24 0.54 0.42 0.84 0.85 0.86 SOUTH EAST 0.19 0.37 0.25 0.71 0.65 0.85 0.86 GR. LONDON 0.13 0.31 0.25 0.59 0.54 0.74 0.76 0.85 WALES 0.69 0.77 0.68 0.70 0.74 0.50 0.59 0.47 0.36 SCOTLAND 0.53 0.58 0.48 0.37 0.38 0.05 0.16 0.12 0.10 0.37 N. IRELAND 0.05 0.04 0.08 0.01 0.05 0.04 0.00 0.06 0.10 0.14 0.01 UK 0.60 0.82 0.73 0.91 0.89 0.75 0.87 0.79 0.72 0.78 0.44 0.03 (Overlapping) 5 Year Log Changes NORTH YORKS. & HUMB. NORTH WEST E. MIDLDS W. MIDLDS EAST ANGLIA SOUTH WEST SOUTH EAST GR. LONDON WALES SCOT. N. IRELAND UK Mean 0.345 0.354 0.345 0.371 0.383 0.355 0.374 0.357 0.385 0.358 0.260 0.332 0.355 S.d. 0.311 0.332 0.313 0.341 0.327 0.388 0.364 0.354 0.376 0.316 0.184 0.139 0.291 Ann'd mean 0.069 0.071 0.069 0.074 0.077 0.071 0.075 0.071 0.077 0.072 0.052 0.066 0.071 Ann'd s.d. 0.139 0.149 0.140 0.152 0.146 0.173 0.163 0.158 0.168 0.141 0.082 0.062 0.130 s for log price changes 10 0.822 0.768 0.739 0.776 0.772 0.794 0.773 0.716 0.742 0.787 0.482 0.478 0.693 50 0.305 0.337 0.346 0.370 0.377 0.412 0.472 0.479 0.499 0.338 0.264 0.342 0.362 90 0.038 0.039 0.066 0.124 0.085 0.161 0.176 0.168 0.204 0.065 0.054 0.168 0.091 Positive autocorrelation leads to higher annualised standard deviations Model Output Random Walk 1 5 10 20 20Y %Growth Average 1.05 1.29 1.69 3.17 0.059 1 1.36 2.35 3.96 13.29 0.138 5 1.27 1.95 2.99 7.35 0.105 25 1.13 1.49 2.04 3.77 0.069 50 1.04 1.25 1.57 2.45 0.046 75 0.96 1.04 1.21 1.61 0.024 95 0.86 0.80 0.83 0.94 0.003 99 0.80 0.67 0.63 0.61 0.024 4

Model Output Mean Reversion 1 5 10 20 20Y %Growth Average 1.05 1.30 1.72 3.21 0.060 1 1.37 2.16 3.60 12.00 0.132 5 1.27 1.87 2.81 7.02 0.102 25 1.13 1.48 2.01 3.76 0.068 50 1.05 1.27 1.62 2.58 0.048 75 0.97 1.09 1.31 1.87 0.032 95 0.86 0.86 0.95 1.18 0.008 99 0.80 0.75 0.77 0.87 0.007 Questionnaire Questionnaire results Just under 30 providers were contacted Around 15 responses Only 4 respondents filled the questionnaire in Others either commercially sensitive don t do any modelling 5

Mortality/LTC Mortality tables varied (PPM, PMA, PML, IML) Mortality all 100% Improvements mainly 100% mc, 1 used 92 basis Little use of selection Large variation in LTC (2% mortality to 50%) All LTC assumptions age dependent Lapses around 1%2% where used 1 company considered correlation with interest rates None used own data, some use of working paper and rating tables Methodology Decrements deterministic 1 company used stochastic interest rates 2 companies modelled HPI deterministically and 2 stochastically (1 closed form) 2 companies hedged out the interest rate 1 company uses the assets to back annuities Example Sensitivities 6

Case Assumptions Male, age 65, House Value 250k, LTV 23% ( 57.5k) Mortality: PXA92, CMI MC Move to LTC: 0%, 10%, 20%, 30%, 40% by duration Lapses, expenses: zero margin: 1.11% Interest Rates, HPI: stochastic, calibrated to current economic conditions at 30 June 2006 5,000 scenarios Sensitivities Applied Mortality: base rates +/30% HPI: 120% HPI volatility (12% to 14.4%) LTV 40% + HPI 20% Lapse rates: introduce interest sensitive lapse rates: Results Distribution 8% 7% 6% 5% 4% 3% 2% 1% 0% 47,000 39,700 32,400 25,100 17,800 10,500 3,200 4,100 11,400 18,700 26,000 33,300 40,600 47,900 55,200 62,500 69,800 77,100 84,400 91,700 99,000 7

Mortality Sensitivity 80,000 Mortality +30% Mortality 30% 40,000 20,000 20,000 40,000 Increase HPI Volatility HPI Losses 80,000 HPI Volatility (+20%) 40,000 20,000 20,000 40,000 Increase HPI Volatility 80,000 HPI Volatility (+20%) 40,000 20,000 20,000 40,000 8

Increase HPI Volatility HPI Losses 100,000 HPI Volatility (+20%) 80,000 40,000 20,000 20,000 40,000 = 40%LTV, HPI 20% 125,000 105,000 HPI Volatility (+20%) 85,000 65,000 45,000 25,000 5,000 15,000 35,000 55,000 75,000 Interest Sensitive Lapse Rates 14% Interest Sensitive Lapse Rates 12% 10% 8% 6% 4% 2% 0% 47,000 43,350 39,700 36,050 32,400 28,750 25,100 21,450 17,800 14,150 10,500 6,850 3,200 450 4,100 7,750 11,400 15,050 18,700 22,350 26,000 29,650 33,300 36,950 40,600 44,250 47,900 51,550 55,200 58,850 62,500 66,150 69,800 73,450 77,100 80,750 84,400 88,050 91,700 95,350 99,000 9

Results Impact of Swap 12% 10% 8% 6% 4% 2% 0% 45,000 41,250 37,500 33,750 30,000 26,250 22,500 18,750 15,000 11,250 7,500 3,750 3,750 7,500 11,250 15,000 18,750 22,500 26,250 30,000 33,750 37,500 41,250 45,000 48,750 52,500 56,250 63,750 67,500 71,250 75,000 78,750 Impact of HPI Sensitivity assuming Swap 80,000 + Swap + Swap + HPI Volatility (+20%) 40,000 20,000 20,000 40,000 = 40%LTV, HPI 20% (with swap) 125,000 105,000 + Swap + Swap + HPI Volatility (+20%) 85,000 65,000 45,000 25,000 5,000 15,000 35,000 55,000 75,000 10

= 40%LTV, HPI 20% (with swap, no HPI losses) 125,000 105,000 (no HPI loss) + Swap (no HPI loss) 85,000 65,000 45,000 25,000 5,000 15,000 35,000 55,000 75,000 Other Issues Accounting treatment of the asset Real world or market consistent Dividend yields Lack of market for pricing options Prevention of poor persistency and protection of profits Conclusions Hedging interest rate risk is effective but reduced by offs being different to expected Consider how to model HPI/interest rate correlation Sensitive to lapses/surrenders but no data, penalties key HPI really kicks in with higher LTV and when interest rates are hedged 11