Reinsurance Structures, Pro Rata Pricing, When Good Pricing Goes Bad

1. Reinsurance Structures,Pro Rata Pricing, & When Good Pricing Goes Bad August 8, 2007 First A Disclaimer� These views presented are only mine and do not represent the views of Ace Tempest Re or its holding company ACE INA, The Casualty Actuarial Society, or any one else. In spite of that statement I hope that some of my views will become yours An actuary and an underwriter are watching the eleven o'clock news. A story comes on involving a man on a window ledge threatening to jump. The underwriter says, "I'll bet you fifty bucks he doesn't jump." The actuary says, "I'll take the bet." A few minutes later they see that the guy does indeed jump. As the underwriter reaches for his wallet, the actuary says, "Never mind. It's not fair. I saw the six o'clock news." The underwriter responds, "So did I. I just didn't think it would happen twice." First A Disclaimer� These views presented are only mine and do not represent the views of Ace Tempest Re or its holding company ACE INA, The Casualty Actuarial Society, or any one else. In spite of that statement I hope that some of my views will become yours An actuary and an underwriter are watching the eleven o'clock news. A story comes on involving a man on a window ledge threatening to jump. The underwriter says, "I'll bet you fifty bucks he doesn't jump." The actuary says, "I'll take the bet." A few minutes later they see that the guy does indeed jump. As the underwriter reaches for his wallet, the actuary says, "Never mind. It's not fair. I saw the six o'clock news." The underwriter responds, "So did I. I just didn't think it would happen twice."

2. 2 Proportional Reinsurance Structures Straight Quota share- cede a percentage of losses for an identical percentage of premium. If the commission paid is commensurate with insurers costs, there is an alignment of interests. Used to reduce premium writings relative to surplus Generate commission overrides to offset expense and increase profit Surplus Quota Share- A form of proportional reinsurance where the reinsurer assumes pro rata responsibility for only that portion of any risk which exceeds the company�s established retentions. May promote writing larger limits compared to historical experience Promote writing riskier or more volatile business Variable Quota Share � insured cedes different percentages of business depending on the limit � 0% of 5 M limit, 50% of 10 M limit, etc. Essentially, this can be viewed as a variable quota share contract wherein the reinsurer's pro rata share of insurance on individual risks will increase as the amount of insurance increases, given the same reinsurer's retained line, in order that the primary company can limit its net exposure to one line, regardless of the amount of insurance written May promote the writing of larger or more hazardous risks going forward Encourage reducing limits on more profitable business to improve net results Structure � Why do we care about the structure? 1 Yes we need to price it 2 More importantly it gives us a window into the desires of the purchaser. Are they trying to lay off volume, volatility, pure risk layers, new business 3 Allows us to offer alternatives if the structure is not appealing to the Reinsurer. In a straight quota share the loss experience should be identical for the cedent and the Reinsurer. In the other 2 scenarios the loss ratio could be distinctly different. Remember it is the loss experience that is financially equivalent not the overall finances. If the insurer is getting more commission than it is paying out, and it cedes a large proportion of the treaty, it can write at very high loss ratios, and still make money on a net basis. (on next slide) The concern in the latter 2 structures is whether you have the experience to price these structures. Are the losses and premium broken out by line size and is the experience credible enough to use. Are you interested in buying the volatility. Is the lower limit business more profitable?Structure � Why do we care about the structure? 1 Yes we need to price it 2 More importantly it gives us a window into the desires of the purchaser. Are they trying to lay off volume, volatility, pure risk layers, new business 3 Allows us to offer alternatives if the structure is not appealing to the Reinsurer. In a straight quota share the loss experience should be identical for the cedent and the Reinsurer. In the other 2 scenarios the loss ratio could be distinctly different. Remember it is the loss experience that is financially equivalent not the overall finances. If the insurer is getting more commission than it is paying out, and it cedes a large proportion of the treaty, it can write at very high loss ratios, and still make money on a net basis. (on next slide) The concern in the latter 2 structures is whether you have the experience to price these structures. Are the losses and premium broken out by line size and is the experience credible enough to use. Are you interested in buying the volatility. Is the lower limit business more profitable?

3. 3 Commission Override Example

4. 4 Non Proportional Reinsurance Excess of Loss Flat Rated Can be appropriate when there is a standard limit and little variability in insured groups If limits vary, a flat rate may promoted more hazardous writing and large limits Cessions Rated Better when there are a variety of limits or various hazards ceded Facultative Individual risks � usually priced at higher profit margins than treaty business. Obligatory � most similar to a treaty Non-Obligatory Can be used with many types of reinsurance. It means that the insured can pick what risks it wants to keep and cede the rest. Stop Loss A form of reinsurance under which the reinsurer pays some or all of a cedant�s aggregate retained losses in excess of a predetermined dollar amount or in excess of a percentage of premium Often significant adverse selection against reinsurers on these covers as the cedents have a better sense of the ultimate gross loss ratio than the reinsurer Almost always includes a loss ratio cap May have risk transfer issues

5. 5 Basics of Pricing Components Losses Paid/Reported Paid Losses� trend issues Reported Losses � Reserve issues Large Losses Cat Losses Claim Counts Triangulations of Losses Exposure Data Payroll Sales Square Footage Premium Doctors � Base Doctor Equivalents My assumption is that everyone here understands a little bit about reserving or pricing. That developing and trending losses and on leveling premium is a concept that all understand. Therefore my focus will be on problems or concerns one should have when performing theses tasks. What are we trying to do? The bottom line in trying to project out future expected loss costs is to have a credible amount of homogenous data that one can take averages look at trends. or use as a basis for the future projection. Since the past was different than the future, we need to take each component of our experience and adjust them so they are similar to what we expect to write in the future. Paid � Paid losses are great to use since there are no reserve adequacy issues. But the development factors are much higher and the trend factors play a more significant role. The average accident date of the experience period could be 2-3 years older than using reported data. Since , an average book may have a turnover of 40% of their policies in a given year.. Another 2-3 years between the projected accident date and the average experience period can make a significant difference in the connection between the historical policies written and those written in the effective period. Reserves � reserve adequacy is always an issue. There are methodologies to adjust reserves for reserve adequacy changes (Berquest Sherman Fisher Lange). The benefit to the reserves is the opposite of the paids. The development factors are much smaller and you can use much more recent periods in the experience analysis. Claims- These are used much less frequently but can be crucial in interpreting the results or detecting trends. Frequently claim development data is poor so results from this methodology are poor Exposure Data Payroll � excellent data for workers compensations is a homogenous book since it is highly correlated with indemnity losses. The correlation is poor with medical losses since the lowest paying jobs may be the most dangerous. Unfortunately, it is worthless for other lines. Sales � Decent exposure for certain premise and operations but may not accurately reflect exposures. A store with lots of traffic and small sales numbers may have higher loss costs than a store with much more expensive merchandise and less traffic. Square footage � although this is also a rating tool, it does not take into account the type of business. Premium � Why do we use premium. Because the cost of insurance has a more direct correlation with the exposure that any other item. When policy is sold, the debits and credits are supposed to take into account the hazards of the risks that may not be found in the other exposure data. If you are a youthful driver, your rate will be double an adult or if you own a sports car the rate may be double again. Clearly #drivers and or cars is not enough information. The premium charge corrects for this. If we can take that premium and adjust for any of the changes in rates, then we should be able to have each historical year reflects its exposures at the current rates. The problem is that we frequently get bad rate change data which we will discuss later. Doctors � usually used in pricing as a base doctor equivalents. One Ob/GYN is similar to 2 general practitioners, etc. The equivalencies have changed over time. Some legitimately others not.My assumption is that everyone here understands a little bit about reserving or pricing. That developing and trending losses and on leveling premium is a concept that all understand. Therefore my focus will be on problems or concerns one should have when performing theses tasks. What are we trying to do? The bottom line in trying to project out future expected loss costs is to have a credible amount of homogenous data that one can take averages look at trends. or use as a basis for the future projection. Since the past was different than the future, we need to take each component of our experience and adjust them so they are similar to what we expect to write in the future. Paid � Paid losses are great to use since there are no reserve adequacy issues. But the development factors are much higher and the trend factors play a more significant role. The average accident date of the experience period could be 2-3 years older than using reported data. Since , an average book may have a turnover of 40% of their policies in a given year.. Another 2-3 years between the projected accident date and the average experience period can make a significant difference in the connection between the historical policies written and those written in the effective period. Reserves � reserve adequacy is always an issue. There are methodologies to adjust reserves for reserve adequacy changes (Berquest Sherman Fisher Lange). The benefit to the reserves is the opposite of the paids. The development factors are much smaller and you can use much more recent periods in the experience analysis. Claims- These are used much less frequently but can be crucial in interpreting the results or detecting trends. Frequently claim development data is poor so results from this methodology are poor Exposure Data Payroll � excellent data for workers compensations is a homogenous book since it is highly correlated with indemnity losses. The correlation is poor with medical losses since the lowest paying jobs may be the most dangerous. Unfortunately, it is worthless for other lines. Sales � Decent exposure for certain premise and operations but may not accurately reflect exposures. A store with lots of traffic and small sales numbers may have higher loss costs than a store with much more expensive merchandise and less traffic. Square footage � although this is also a rating tool, it does not take into account the type of business. Premium � Why do we use premium. Because the cost of insurance has a more direct correlation with the exposure that any other item. When policy is sold, the debits and credits are supposed to take into account the hazards of the risks that may not be found in the other exposure data. If you are a youthful driver, your rate will be double an adult or if you own a sports car the rate may be double again. Clearly #drivers and or cars is not enough information. The premium charge corrects for this. If we can take that premium and adjust for any of the changes in rates, then we should be able to have each historical year reflects its exposures at the current rates. The problem is that we frequently get bad rate change data which we will discuss later. Doctors � usually used in pricing as a base doctor equivalents. One Ob/GYN is similar to 2 general practitioners, etc. The equivalencies have changed over time. Some legitimately others not.

6. 6 Adjustments Loss Development Trend � Severity/Frequency Premium On Level Adjustments Exposure Adjustments Adjustments for Limits and Attachment/SIR Changes Loading for catastrophe Free cover Load for ECO/XPL Summing claims for basket or aggregate cover Load for Clash Tort Reform adjust trend adjust loss development Is tort reform retroactive? Loss development � few accounts have enough credible data to price with. Either the losses aren�t credible or the amount of years isn�t sufficient to calculate the tail factor. Therefore you can either use industry data or you can try to marry the two sets of data by selecting the account data where it is the most credible and then using tail factors based on industry data. It is important to note that you are implicitly stating that the account has reserves that are consistent with the industry average. Although we are frequently told that the reserves are better than industry, I have never been told that the reserves were worse than average. I can only assume we don�t write that one really bad and incredibly large account. Other thoughts on development � If we are dealing with accident year data � the average effective date is 7/1/. This explicitly assumed even writings throughout the year. In a book that is growing significantly the average accident date is later than 7/1 and an adjustment should be made. If you are dealing with treaty year data the average effective date assumed is 7/1. The average accident date on a 1 year policy is 6 months later which would be 12/31. Once again, if the exposures are growing the average accident is later. Trend � In general, people usually assume a flat frequency trend even if this is not supported by the data. In this case all losses are adjusted by a trend factor from the occurrence date to the average accident date in the current period. There is no reason that you need to use the same trend factor every year although many do. IF there is a frequency trend the trend is applied differently for quota share and excess pricing. In quota share pricing the severity frequency and exposure trend can all be combined into a net trend factor and applied to the losses. So if severity trend =5%, freq -2% and exposure 3% the overall trend is 1.05*.98/1.06 = 0% trend. On an excess basis each claim is trended by the severity trend and then layered. After the claim is layered the adjustment for frequency and exposure is made. To be accurate the exposure trend is usually applied to the premium. I am lumping it all together for illustration purposes. On an excess basis you will find that you overall trend is actually positive since claims will go into the excess layer at a higher rate than the ground up trendLoss development � few accounts have enough credible data to price with. Either the losses aren�t credible or the amount of years isn�t sufficient to calculate the tail factor. Therefore you can either use industry data or you can try to marry the two sets of data by selecting the account data where it is the most credible and then using tail factors based on industry data. It is important to note that you are implicitly stating that the account has reserves that are consistent with the industry average. Although we are frequently told that the reserves are better than industry, I have never been told that the reserves were worse than average. I can only assume we don�t write that one really bad and incredibly large account. Other thoughts on development � If we are dealing with accident year data � the average effective date is 7/1/. This explicitly assumed even writings throughout the year. In a book that is growing significantly the average accident date is later than 7/1 and an adjustment should be made. If you are dealing with treaty year data the average effective date assumed is 7/1. The average accident date on a 1 year policy is 6 months later which would be 12/31. Once again, if the exposures are growing the average accident is later. Trend � In general, people usually assume a flat frequency trend even if this is not supported by the data. In this case all losses are adjusted by a trend factor from the occurrence date to the average accident date in the current period. There is no reason that you need to use the same trend factor every year although many do. IF there is a frequency trend the trend is applied differently for quota share and excess pricing. In quota share pricing the severity frequency and exposure trend can all be combined into a net trend factor and applied to the losses. So if severity trend =5%, freq -2% and exposure 3% the overall trend is 1.05*.98/1.06 = 0% trend. On an excess basis each claim is trended by the severity trend and then layered. After the claim is layered the adjustment for frequency and exposure is made. To be accurate the exposure trend is usually applied to the premium. I am lumping it all together for illustration purposes. On an excess basis you will find that you overall trend is actually positive since claims will go into the excess layer at a higher rate than the ground up trend

7. 7 Loss Development Selection This is an actual triangle of data. I have actually selected some factors but there are definitely other legitimate selections. The problem with this triangle is that you can see there has been significant growth since 1999. In addition. 1999 had a fair amount of development though out its entire history which appeared to me to skew the tail. I tried to credibility weight with NCCI industry factors for the state. If the NCCI factors were countrywide factors I might have given more weight to the submission data. Although I am most concerned about the tail the submission data is probably overstating the development in the last few points. Clearly the volume of losses is small. A brief pick at the premium confirms the lower exposure base. A few brief points � The submission data is PY PY at 15 months is similar to AY at 11 Months. I compared these factors to the NCCI AY data at 12 month evaluations. The first 1 or 2 points may need further adjustment which is another reason to use the submission data. In the tail the difference of 1 months is minimal. I can�t help but emphasize another actuary looking at this data might make different selections.This is an actual triangle of data. I have actually selected some factors but there are definitely other legitimate selections. The problem with this triangle is that you can see there has been significant growth since 1999. In addition. 1999 had a fair amount of development though out its entire history which appeared to me to skew the tail. I tried to credibility weight with NCCI industry factors for the state. If the NCCI factors were countrywide factors I might have given more weight to the submission data. Although I am most concerned about the tail the submission data is probably overstating the development in the last few points. Clearly the volume of losses is small. A brief pick at the premium confirms the lower exposure base. A few brief points � The submission data is PY PY at 15 months is similar to AY at 11 Months. I compared these factors to the NCCI AY data at 12 month evaluations. The first 1 or 2 points may need further adjustment which is another reason to use the submission data. In the tail the difference of 1 months is minimal. I can�t help but emphasize another actuary looking at this data might make different selections.

8. 8 Umbrella Quota Shares use Excess Trend This is a basic example of excess trend. Note that the 5% trend assumption applied to every claim implies an overall trend assumption of 18% for the excess claims. There are a lot of things to consider when discussing claim cost trends. The first is that trends apply equally to all claims. This is probably one of the biggest fallacy�s. There is no reason to assume this is true and plenty of reason to believe it is not. Lets take workers compensation business as an example. The average wc claims is made up of 60% medical and 40% indemnity. The small claims are probably 80% indemnity and 20% medical while the large claims are 20% indemnity and 80% medical. Medical costs are still rising dramatically and are at least double the indemnity. If average claim cost trend is 5%. The smaller claims may be 3-4% with larger claims closer to 8%. This is not always true. Some small claims are pure medical, The bottom line is that large claim trends are different. With respect to frequency trends the numbers are equally as dramatic. There has been significant tort reform in the medical malpractice and workers compensation line in many states. With these reforms are claim frequency reductions of almost 50% over the past several years. The question is what kind of adjustment do you make in pricing. Clearly assuming all the claims are the same and that the 1 million dollar claim is equally as likely to be reduced as the 20 thousand dollar claims is not right. What is driving the frequency decline. It is not safety increase and improvements in the workplace environment or better surgical procedures. It is the change in the compensation system making it more difficult to get money or as much money. This has had a significant impact on the small claims which tend to drift away. However, the person with a serious compensable injury will pursue their cause. In many cases there is little evidence that there is any frequency reduction in large claims. When trending claims you should always add back in any deductible or SIR and then subtract it out after trending. Note that when you do this a small claim can become a large claim very quickly. If you are pricing umbrella with a $1 M attachment a 1000 of 300 dollar claim may just be a place holder for a potential claim. You may not want to assume it is a 1001000 or 1000300 dollar claim. If you trend for 3 years the claims is now a 250,000 dollar claim. If you have 20-30 of those you can quickly show some disastrous loss experience that may not be realistic. Remember to treat SIR and deductibles differently. A deductible erodes the limit while the SIR does not.This is a basic example of excess trend. Note that the 5% trend assumption applied to every claim implies an overall trend assumption of 18% for the excess claims. There are a lot of things to consider when discussing claim cost trends. The first is that trends apply equally to all claims. This is probably one of the biggest fallacy�s. There is no reason to assume this is true and plenty of reason to believe it is not. Lets take workers compensation business as an example. The average wc claims is made up of 60% medical and 40% indemnity. The small claims are probably 80% indemnity and 20% medical while the large claims are 20% indemnity and 80% medical. Medical costs are still rising dramatically and are at least double the indemnity. If average claim cost trend is 5%. The smaller claims may be 3-4% with larger claims closer to 8%. This is not always true. Some small claims are pure medical, The bottom line is that large claim trends are different. With respect to frequency trends the numbers are equally as dramatic. There has been significant tort reform in the medical malpractice and workers compensation line in many states. With these reforms are claim frequency reductions of almost 50% over the past several years. The question is what kind of adjustment do you make in pricing. Clearly assuming all the claims are the same and that the 1 million dollar claim is equally as likely to be reduced as the 20 thousand dollar claims is not right. What is driving the frequency decline. It is not safety increase and improvements in the workplace environment or better surgical procedures. It is the change in the compensation system making it more difficult to get money or as much money. This has had a significant impact on the small claims which tend to drift away. However, the person with a serious compensable injury will pursue their cause. In many cases there is little evidence that there is any frequency reduction in large claims. When trending claims you should always add back in any deductible or SIR and then subtract it out after trending. Note that when you do this a small claim can become a large claim very quickly. If you are pricing umbrella with a $1 M attachment a 1000 of 300 dollar claim may just be a place holder for a potential claim. You may not want to assume it is a 1001000 or 1000300 dollar claim. If you trend for 3 years the claims is now a 250,000 dollar claim. If you have 20-30 of those you can quickly show some disastrous loss experience that may not be realistic. Remember to treat SIR and deductibles differently. A deductible erodes the limit while the SIR does not.

9. 9 Excess Losses Deductibles and Layering This is a simple practical example of trending and layering losses. First lets list the assumptions Loss occurring cover so we are trending to 2007 5 % for 5 year exactly. If we knew the exact loss date we could adjust for the difference in days. If we were projecting to a Risk attaching cover we would add another 6 months of trend The losses have an SIR and the losses are net of the SIR. Therefore a 650,000 loss was really a gross loss of 750,000. The LAE is pro rata to total loss. Therefore if the LAE is 250 for a 650 plus 100 SIR loss, it is 33% load on the loss. LAE can be capped it can be included in loss or capped at limit or as percentage of Loss above SIR. There are numerous assumptions and all of them may not be correct. When the incurred loss excluding SIR is trended. IT is also capped at the limit. Only after it is capped do we apply the LAE percentage to the loss. The final total for the year is then trended by and a development factor for losses excess of 500 K Another final note. The trend for LAE was assumed to be identical to the loss The accident date was assumed to be 7/1 This example assumed SIR. I f a deductible was used you need to adjust the limit since a deductible is different than a limit. If you have losses excess of supported underlying policies, you can put the underlying policies losses in the SIR in this example and mathematically it will all work out.This is a simple practical example of trending and layering losses. First lets list the assumptions Loss occurring cover so we are trending to 2007 5 % for 5 year exactly. If we knew the exact loss date we could adjust for the difference in days. If we were projecting to a Risk attaching cover we would add another 6 months of trend The losses have an SIR and the losses are net of the SIR. Therefore a 650,000 loss was really a gross loss of 750,000. The LAE is pro rata to total loss. Therefore if the LAE is 250 for a 650 plus 100 SIR loss, it is 33% load on the loss. LAE can be capped it can be included in loss or capped at limit or as percentage of Loss above SIR. There are numerous assumptions and all of them may not be correct. When the incurred loss excluding SIR is trended. IT is also capped at the limit. Only after it is capped do we apply the LAE percentage to the loss. The final total for the year is then trended by and a development factor for losses excess of 500 K Another final note. The trend for LAE was assumed to be identical to the loss The accident date was assumed to be 7/1 This example assumed SIR. I f a deductible was used you need to adjust the limit since a deductible is different than a limit. If you have losses excess of supported underlying policies, you can put the underlying policies losses in the SIR in this example and mathematically it will all work out.

10. 10 On Leveling Premium Rate On Level Factors Parallelogram method or Premium at Present Rates Premium/Exposure Trend Yes if exposure base is inflationary insured value Sales revenues No if exposure base is square feet # vehicles # employees # doctors � should consider translating into base doctor equivalents Trend from: Average accident date of experience period to average accident date of prospective period

11. 11 On Leveling Premium Rate Changes should consider changes to base rates, schedule credits and debits, tier rating, LCMs. They should also be adjusted for changes in limits and attachment points on the underlying policies. Parallelogram method uses geometry to calculate on level factors. Premium at Present Rates re-rates all historical policies using prospective rates. Minimum Premiums can have a significant impact on rates. The impact is negative when rates are rising and positive when rates are falling. In a rate environment where rate increases have been significant the last few years the actual on level will be overstated. Rate changes by state. If you have separate rate changes by state you shouldn�t weight them out by premium by year and then aggregate them. The accurate way is to calculate each states on level factor and weight those together by state by year 2 methods typically used matched renewal method � attempting to adjust for premium filed rates method � lcm credit etcRate changes by state. If you have separate rate changes by state you shouldn�t weight them out by premium by year and then aggregate them. The accurate way is to calculate each states on level factor and weight those together by state by year 2 methods typically used matched renewal method � attempting to adjust for premium filed rates method � lcm credit etc

12. 12 Actual Calculation for On Level Factor The on leveling is different for policy attachingThe on leveling is different for policy attaching

13. 13 Shifting Distributions and On Level Factors

14. 14 WC On Level Example

15. 15 Change in Average Premium

16. 16 Losses Occurring with Run-Off Distortion to On � Level Factors if rates are decreasing Price to the contract. If the contract allows the insured to run off the risk. You may want to consider the impact of additional trend on the losses as well as the impact of additional rate decreases on the projected experience period. If rates decrease 15% on 1/1/05 a higher percentage of the business in the experience period is lower rates. It goes from 50% to 66%. Price to the contract. If the contract allows the insured to run off the risk. You may want to consider the impact of additional trend on the losses as well as the impact of additional rate decreases on the projected experience period. If rates decrease 15% on 1/1/05 a higher percentage of the business in the experience period is lower rates. It goes from 50% to 66%.

17. 17 Risks Attaching with Cut-Off Distortion to On � Level if rates are increasing If rates are decreasing and the insured can cut off the treaty you may be left with 50% of the treaty at a lower rate. The rates are the smaller part of the issue. If the treaty is performing well you may find your self cutoff. If performing poorly you will find yourself on risk. If you simulated the value of this option you will reduce the expected profitability of this treaty.If rates are decreasing and the insured can cut off the treaty you may be left with 50% of the treaty at a lower rate. The rates are the smaller part of the issue. If the treaty is performing well you may find your self cutoff. If performing poorly you will find yourself on risk. If you simulated the value of this option you will reduce the expected profitability of this treaty.

18. 18 Premium On Level Adjustments There were several issues with the data provided in this submission. There really are not giving us rate changes. Renewal over expiring premium is just what it says. It may not adjust for exposure changes of any kind. There could be an increase in limits, a shift in business within the client itself. There could also have been huge exposure growth that is not being captured. It also excludes new business. If new business is 40% of the book and the rate increase are half of the 2002 rate increase. The actual realized rate increase is closer to 65% instead of 81%. Why is the submission on level factor so much higher. It is basically a mistake. The rate changes are being calculated for the years that they are already embedded in. Ex 2001 rate are already at the 63% higher rate over 2000. SO the adjustment for 2001 starts in 2002. In addition a modest exposure adjustment was included in the factors but shouldn�t have. If you are using a pure rate change an exposure adjustment for an inflation increase in sales or payroll is appropriate. However, that factor is already included in the renewal over expiring premium and should not be included a second time.There were several issues with the data provided in this submission. There really are not giving us rate changes. Renewal over expiring premium is just what it says. It may not adjust for exposure changes of any kind. There could be an increase in limits, a shift in business within the client itself. There could also have been huge exposure growth that is not being captured. It also excludes new business. If new business is 40% of the book and the rate increase are half of the 2002 rate increase. The actual realized rate increase is closer to 65% instead of 81%. Why is the submission on level factor so much higher. It is basically a mistake. The rate changes are being calculated for the years that they are already embedded in. Ex 2001 rate are already at the 63% higher rate over 2000. SO the adjustment for 2001 starts in 2002. In addition a modest exposure adjustment was included in the factors but shouldn�t have. If you are using a pure rate change an exposure adjustment for an inflation increase in sales or payroll is appropriate. However, that factor is already included in the renewal over expiring premium and should not be included a second time.

19. 19 Limits/Attachments Adjustments When a company�s limits and attachments have shifted, adjustments must be made to the analysis! Trend past historical limits � this will underestimate your costs if the losses were truncated. Only works if the policy limits have adjusted due to inflation. Price lower �fully exposed� layer and use exposure rating relativities to adjust to current layer. This approach is easiest if everything is fully exposed. If there are few losses in the layer, you need to convince yourself that the experience is not credible. Adjust using exposure rating differential based on limits distribution profile in each year Calculate a loss distribution based on current experience and run against new limits Attachments shifting downwards are the easiest to adjust for by subtracting old attachment out after trending and adding new attachment This is the vaguest of all the slides. The material here although conceptually easy can get mathematically tricky. Our first point was to make all the losses seem as if they were occurring under today's conditions. There are a few problems here. If historically limits were 250 K and now they are at 1 M you can�t just decide not to uncap historical losses. A 250 loss historically may have been a 1 M K loss if it weren�t for the cap and $2 M in today's dollars. An SIR of 500 K that drops down to 250 K may be missing losses that may not have even been reported to the company. Interestingly enough, in lines where there has been tort reform there have been lower limits purchased. If for example the exposure loss cost for the fist 5 yrs of an experience period is 30% and the last 5 years is 15% on can adjust the historical experience by .15/.3 before looking at the final results.This is the vaguest of all the slides. The material here although conceptually easy can get mathematically tricky. Our first point was to make all the losses seem as if they were occurring under today's conditions. There are a few problems here. If historically limits were 250 K and now they are at 1 M you can�t just decide not to uncap historical losses. A 250 loss historically may have been a 1 M K loss if it weren�t for the cap and $2 M in today's dollars. An SIR of 500 K that drops down to 250 K may be missing losses that may not have even been reported to the company. Interestingly enough, in lines where there has been tort reform there have been lower limits purchased. If for example the exposure loss cost for the fist 5 yrs of an experience period is 30% and the last 5 years is 15% on can adjust the historical experience by .15/.3 before looking at the final results.

20. 20 Pricing for Contract Provisions Multi-Year Policies- Need to consider the impact on trend and development for multi-year policies Impact on the risk of a deal where your exposure now extends several years. Funding Requirements � this is generally ignored in pricing but shouldn�t be Requirement when rating or surplus drops or reinsurer stops writing new business. Companies that agreed to these provisions found themselves quickly out of business when there rating dropped. Some Surety deals require funding at every 12/31 This usually require and LOC and this cost should be priced into the business Errors & Omissions clauses covering business excluded by the treaty if bound accidentally. Ex Gratia payments � anyone dealing with a large insured may find themselves paying claims just to keep them happy. If the deal is marginal to begin with, this would eliminate some of the expected profit. Some swing rated treaties allow for losses to be deemed $0 and pay only the minimum. It is important to look at the NPV of the deal in all situations and realize that the client will act to maximize that. The end result is that the likely outcomes will be minimum premiums until you are in a loss position.

21. 21 Select Projected Loss Cost Select for Stability? Have there been changes in the writings. Tort Reform Select for Responsiveness? Recent years effected by large development factors Mature years may be over trended or rate changes may be overstated. What if a company renews 60% of the book each year? Somewhere in the middle?

22. 22 Selecting Loss Costs This is a fairly new start up Umbrella book. Only one of the years are even 50% reported. I typically don�t include a year in an analysis until it is at least 25% reported. However, we see the difference in the analysis by including and excluding one year. The last few years look great but there is clearly some poor experience in 2002. Umbrella is typically a volatile line so I would expect some significant variation between years. 2005 is unnaturally good so far with very little reported. I would argue that to include it completely in the waiting ay be too generous. There also seems to be a market cycle which means we have not corrected completely for all the terms and condition changes. If you believe that the losses are trending downwards you would probably select in the high 60�s. I f you think the 2005 is aberration you are probably in the low 70�s. Free Cover � Lets say that you have all of the individual losses and non of these losses would trend higher than 500 K. The indicated ultimate loss ratios are probably too light. I would then suggest pricing the first 500 K ( Which would yield 75% ) and add the amount for 4.5 Mx.5 M.This is a fairly new start up Umbrella book. Only one of the years are even 50% reported. I typically don�t include a year in an analysis until it is at least 25% reported. However, we see the difference in the analysis by including and excluding one year. The last few years look great but there is clearly some poor experience in 2002. Umbrella is typically a volatile line so I would expect some significant variation between years. 2005 is unnaturally good so far with very little reported. I would argue that to include it completely in the waiting ay be too generous. There also seems to be a market cycle which means we have not corrected completely for all the terms and condition changes. If you believe that the losses are trending downwards you would probably select in the high 60�s. I f you think the 2005 is aberration you are probably in the low 70�s. Free Cover � Lets say that you have all of the individual losses and non of these losses would trend higher than 500 K. The indicated ultimate loss ratios are probably too light. I would then suggest pricing the first 500 K ( Which would yield 75% ) and add the amount for 4.5 Mx.5 M.

23. 23 Selecting Ultimate Loss & LAE Costs This is a typical example of what one might see in the analysis. Is this normal random variation. I don� think so. I think there is a market cycle acting behind these numbers.This is a typical example of what one might see in the analysis. Is this normal random variation. I don� think so. I think there is a market cycle acting behind these numbers.

24. 24 Adjusting For Free Cover This is from a workers compensation program. There were very few large losses in the experience period. An attempt was made to credibility weight the exposure and the experience to get to an ultimate gross loss ratio. The 62.5% loss ratio was the same for all losses as it was for losses limited to 500k. This is a classic case of free cover. Additional loss costs were added for the other layers to get to an overall loss ratio of 71%. Now many actuaries can argue over whether 71% is correct. It seems likely that 62.5% is too low and there should be a provision for losses greater than 500 K. Feeling to recognize free cover is a common actuarial mistake. This can occur in both quota share pricing as well as excess pricing. Catastrophe loads ECO/XPL or clash loads. These loads should be added whenever the losses are not in the historical experience or not enough of the losses are in the historical experience. Many things change in the market that make these losses more likely to happen in the future than in the past. In Med Mal market a reduction of available limits increase the likelihood of ECO/XPL and clash losses. Sometime a court ruling will increase the likelihood of ECO/XPL. In Florida, several rulings required the Auto insurer to finish their review in 30 days. This was a distortion of the statute that required the insured to appear within 30 days after filing a pip claim. Once the company failed to meet this burden lawyers got involved and started billing above and beyond the 10 K statutory limit. Some 10 K claims ended up settling out at 40 K. Providing extra limits to clinics that insure doctors not increase the maximum exposure to a single event but also increase the likelihood of a clash loss.This is from a workers compensation program. There were very few large losses in the experience period. An attempt was made to credibility weight the exposure and the experience to get to an ultimate gross loss ratio. The 62.5% loss ratio was the same for all losses as it was for losses limited to 500k. This is a classic case of free cover. Additional loss costs were added for the other layers to get to an overall loss ratio of 71%. Now many actuaries can argue over whether 71% is correct. It seems likely that 62.5% is too low and there should be a provision for losses greater than 500 K. Feeling to recognize free cover is a common actuarial mistake. This can occur in both quota share pricing as well as excess pricing. Catastrophe loads ECO/XPL or clash loads. These loads should be added whenever the losses are not in the historical experience or not enough of the losses are in the historical experience. Many things change in the market that make these losses more likely to happen in the future than in the past. In Med Mal market a reduction of available limits increase the likelihood of ECO/XPL and clash losses. Sometime a court ruling will increase the likelihood of ECO/XPL. In Florida, several rulings required the Auto insurer to finish their review in 30 days. This was a distortion of the statute that required the insured to appear within 30 days after filing a pip claim. Once the company failed to meet this burden lawyers got involved and started billing above and beyond the 10 K statutory limit. Some 10 K claims ended up settling out at 40 K. Providing extra limits to clinics that insure doctors not increase the maximum exposure to a single event but also increase the likelihood of a clash loss.

25. 25 Other Considerations �As If� A term used to restate the treaty statistics for prior years to accord with the current (or proposed) limits, terms and conditions Sometimes also used to show results as if exceptional losses had not occurred. �As If� � short for �As If I only wrote profitable business� Exclude line of business no longer written Does it exclude both losses and premium? Did it also impact the rate changes as well? Exclude these losses since they are excluded from the treaty. There are always exposures not included and there will always be exposures included now but not included in the future. Excludes Underwriter �F� Current insureds only � BEWARE � this is an �as if� in disguise Do you get to exclude future losses from business they will decide to get out of next year? If not, beware of �as if� results.

26. 26 Another �as if� �as If� I wrote the same distribution This is harder to dispute since the basis is well grounded in actuarial science. Take the historical losses and premium and adjust it to the current exposures written. If the book was predominantly GL and now it is predominantly products we should adjust the mix to the current business mix. If the book is predominantly Texas historically and is currently Missouri we should adjust the historical state experience to match the current mix.

27. 27 State Distribution Mix On a prima Facie basis there is nothing wrong with this process. However, there is an implicit assumption used in this analysis that is not shown here and is actually not shown in the analysis that was sent to me. The on level factors for both states are identical. These on level factors were the same ones that were overstated in the earlier exhibit. Even fixing that problem, it is unlikely that the huge rate changes in Texas occurred in �all other� states. If the Texas experience was so much worse that the �all other� states it probably received more of the rate impact. If we are going to readjust for state mix we need to take into account other distortions in the data. The other issue is does it make sense. I think it is highly unrealistic that the loss ratio could be this low. Even though the pricing actuary weighted this with results from an exposure rating, more time should be spent figuring out why these results were so favorable.On a prima Facie basis there is nothing wrong with this process. However, there is an implicit assumption used in this analysis that is not shown here and is actually not shown in the analysis that was sent to me. The on level factors for both states are identical. These on level factors were the same ones that were overstated in the earlier exhibit. Even fixing that problem, it is unlikely that the huge rate changes in Texas occurred in �all other� states. If the Texas experience was so much worse that the �all other� states it probably received more of the rate impact. If we are going to readjust for state mix we need to take into account other distortions in the data. The other issue is does it make sense. I think it is highly unrealistic that the loss ratio could be this low. Even though the pricing actuary weighted this with results from an exposure rating, more time should be spent figuring out why these results were so favorable.

28. 28 Pricing New Business � Start Ups The class of �2001� created several insurance and reinsurance start ups. Many of these companies wanted reinsurance and had no experience. For them the �clean slate� was a plus. What information is available to price start up. Similar treaty business � Can this treaty perform significantly better than established books of similar business? New business is bought with cheaper prices Benchmarking Rate comparisons Overall industry experience Stat Bulletins � NCCI, ISO One Source � Annual Statement Data Broker or Trade Group Studies External or Internal actuarial rate studies Pricing hurdles for start ups. Return requirements � should they be higher? Execution risk Different structure for a start ups � lower cede, loss ratio cap, loss corridors or sliding scale commission What happens when the only business you write in a line are start ups? Time to question the pricing assumptions