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Loss Reserving Approaches for Mortgage Guaranty Insurance 2003 CAS Annual Meeting New Orleans Marriott John F. Gibson, FCAS, MAAA Principal PricewaterhouseCoopers, LLP
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1 Outline of Presentation Loss Reserving Distinctives Factors that Influence Ultimate Losses Data to Analyze Contingency Reserves Industry Loss Reserving Approach Problems with Traditional Loss Development Methods Loss Reserving Approaches Current and Future Trends
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2 Loss Reserving Distinctives Claim = Loan that has defaulted as of the statement date Not a reserve for the life of the loan Type and amount of coverage Amounts paid can exceed theoretical coverage
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3 Factors that Influence Ultimate Losses Housing Values Unemployment Interest Rates Claim Settlement Practices
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4 Annual Average 30-Year Fixed Rate
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5 Data to Analyze Analysis by region or state Analysis by type of loan – LTV Analysis by size of loan Analysis by age of loan Analysis of Pool Insurance and other higher risk segments
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6 Contingency Reserves – Need Premiums and losses have mismatched timing Losses realized when loans become delinquent But economic catastrophes can drive 100+% loss ratios for a number of consecutive years Mortgage insurers are monoline
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7 Contingency Reserves - Determination 50% of premium each year is set aside into a contingency reserve and held for 10 years Losses in excess of a 35% loss ratio in a calendar year can be removed on a FIFO basis After 10 years, remaining funds, if any, can be moved to free surplus
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8 Industry Loss Reserving Approach Identification of claims by status – for example: 1.Delinquent 2.Pending Foreclosure 3.Foreclosure 4.Claim Filed Severity Factor – Percentage of exposure to be paid – greater than 100% for filed claim
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9 Industry Loss Reserving Approach IBNR Provision = % of reported Regional analysis Pool business analysis Recent runoff history very favorable
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10 Recent Runoff History (in $ millions) Year Original Loss Reserve Developed Reserves Thru ’02 Developed to Original 19971,152621(46%) 19981,260504(60%) 19991,307530(60%) 20001,337642(52%) 20011,4771,098(26%)
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11 Problems with Traditional Loss Development Methods Leverage effect of economic cycle on number of defaults, cure rates and amounts paid can produce significant volatility Economic cycle operates on a calendar year, not an accident year
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12 Loss Reserving Approach Projection of Ultimate Reported Delinquencies Delinquencies are reported quickly – 85% at 12 months, more that 99% at 24 months Eliminates need for separate IBNR provision
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13 Loss Reserving Approach Delinquency Rate
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14 Loss Reserving Approach Projections of Ultimate Claims Paid - Approaches Project directly – very volatile Project Closed Without Payment (Cured) claims and subtract from ultimate reported Bornhuetter – Ferguson method using a priori ratio of closed with payment (CWP) to loan balances
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15 Loss Reserving Approach Determining Paid Claims by Payment Year Subtract cumulative CWP claims from ultimate CWP claim to derive remaining CWP claims by accident year Using CWP pattern, determine distribution of remaining CWP claim for each accident year to each payment year Sum for each payment year
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16 Loss Reserving Approach Cure Rate
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18 Loss Reserving Approach Determination of Severity Review calendar year severity – has been declining since 1996 Determine selected average loss payment for future calendar years –Trend of prior years –Relate to average coverage amounts –Balance recent favorable results with leveraged effect of economic change
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19 Loss Reserving Approach Average Paid Severity by Calendar Year
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20 Loss Reserving Approach Reserve Estimates Loss reserve by payment year is projected claims to be closed by payment year times projected loss payment by payment year Supplement with traditional loss development methods
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21 Loss Reserving Approach Determination of Reserve Range Based on conservative and optimistic assumptions for defaults, cure rates and severity Reserve range is much wider than most P&C lines of business
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22 Current & Future Trends Impact of the Economic Cycle Refinance Cycle House Price Appreciation Deterioration of Credit Quality
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