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{"sheet":"Instructions","index":0,"n_rows":32,"n_cols":1,"rows_kept":32}
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[]
[]
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["Instructions"]
[]
["1.) Find a quiet place and allow yourself the full four hour exam period to practice. Treat this just as you would the real exam."]
[]
["2.) Use the Navigator worksheet to see a brief description of each question, its point value and navigate between questions in your preferred order."]
[]
["3.) Answer each question either to the side or below the grey question area."]
[]
["4.) Use cell B1 on each question worksheet to mark whether you finished the question or not. You should use this feature to"]
["       reflect your confidence in your answer. This way you'll know if you're on the money or your guesses were lucky."]
[]
["5.) Grade each question harshly. It's better to put in extra reviewing time now than find the examiners aren't as generous as you hoped."]
["       Use increments of 0.25 when scoring; pay attention to the language used in the question and the point value. An \"identify\" question"]
["       is likely 0.25 per item while an \"explain\" or \"briefly justify\" gets 0.25 for the item and another 0.25 for the justification."]
[]
["6.) Enter your estimated score for each sub-part of a question in the box beneath the sub-part point value. They look like:"]
[]
["7.) Use the Point Grid to see your score and a breakdown of where you scored well and where you didn't."]
[]
["8.) Find the top five questions where you lost the most points. These are the topics you need to review the most intensely in the"]
["      next day or so."]
[]
["9.) On the BattleActs site → Custom Battles → BattleCards - Prior Exams → Select this exam and mark the cards you got right and wrong."]
["      This allows your Battle Readiness Quotient (BRQ) to track your strengths and weaknesses."]
[]
["10.) Use the Reset Exam button on the Point Grid worksheet to clear all of your work ready for a new attempt at this exam later."]
["slay the beast"]

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["Practice Exam 1 – Exam 8"]
[null,"Total Point Value","Sub-Part of Question",{"$nulls":8},"Your Score","Sub-Part of Question"]
["Question",null,"(a)","(b)","(c)","(d)","(e)","(f)","(g)","Status",null,"Question","(a)","(b)","(c)","(d)","(e)","(f)","(g)"]
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[2,{"$f":"SUM(C9:I9)","v":{"v":2,"d":"2.00"}},{"v":2,"d":"2.00"},{"$nulls":6},{"$f":"INDIRECT(\"'\"&A9&\"'!B1\")","v":"Incomplete"},null,{"$f":"A9","v":2},"","","","","","",""]
[3,{"v":2,"d":"2.00"},{"v":2,"d":"2.00"},{"$nulls":6},"Incomplete",null,3,"","","","","","",""]
[4,{"v":1.5,"d":"1.50"},{"v":1.5,"d":"1.50"},{"$nulls":6},"Incomplete",null,4,"","","","","","",""]
[5,{"v":1.5,"d":"1.50"},{"v":1.5,"d":"1.50"},{"$nulls":6},"Incomplete",null,5,"","","","","","",""]
[6,2.75,{"v":1.5,"d":"1.50"},0.25,{"v":1,"d":"1.00"},{"$nulls":4},"Incomplete",null,6,"","","","","","",""]
[7,{"v":3,"d":"3.00"},{"v":2.5,"d":"2.50"},{"v":0.5,"d":"0.50"},{"$nulls":5},"Incomplete",null,7,"","","","","","",""]
[8,{"v":3.5,"d":"3.50"},{"v":1.5,"d":"1.50"},{"v":2,"d":"2.00"},{"$nulls":5},"Incomplete",null,8,"","","","","","",""]
[9,{"v":4,"d":"4.00"},{"v":4,"d":"4.00"},{"$nulls":6},"Incomplete",null,9,"","","","","","",""]
[10,1.75,{"v":0.5,"d":"0.50"},0.25,0.25,0.75,{"$nulls":3},"Incomplete",null,10,"","","","","","",""]
[11,2.75,{"v":0.5,"d":"0.50"},{"v":0.5,"d":"0.50"},{"v":0.5,"d":"0.50"},{"v":0.5,"d":"0.50"},0.75,null,null,"Incomplete",null,11,{"$f":"_xlfn.IFNA(IF(ISBLANK(INDEX(INDIRECT(\"'\"&$L18&\"'!$A:$A\"),MATCH(M$7,INDIRECT(\"'\"&$L18&\"'!$A:$A\"),0)+2)),\"\",INDEX(INDIRECT(\"'\"&$L18&\"'!$A:$A\"),MATCH(M$7,INDIRECT(\"'\"&$L18&\"'!$A:$A\"),0)+2)),\"\")","v":""},"","","","","",""]
[12,{"v":3,"d":"3.00"},{"v":1,"d":"1.00"},{"v":1,"d":"1.00"},{"v":1,"d":"1.00"},{"$nulls":4},"Incomplete",null,12,"","","","","","",""]
[13,{"v":2,"d":"2.00"},{"v":0.5,"d":"0.50"},{"v":0.5,"d":"0.50"},{"v":0.5,"d":"0.50"},{"v":0.5,"d":"0.50"},{"$nulls":3},"Incomplete",null,13,"","","","","","",""]
[14,{"v":2,"d":"2.00"},{"v":2,"d":"2.00"},{"$nulls":6},"Incomplete",null,14,"","","","","","",""]
[15,{"v":4,"d":"4.00"},{"v":2,"d":"2.00"},{"v":2,"d":"2.00"},{"$nulls":5},"Incomplete",null,15,"","","","","","",""]
[16,{"v":4,"d":"4.00"},{"v":2,"d":"2.00"},{"v":2,"d":"2.00"},{"$nulls":5},"Incomplete",null,16,"","","","","","",""]
[17,{"v":1.5,"d":"1.50"},{"v":1.5,"d":"1.50"},{"$nulls":6},"Incomplete",null,17,"","","","","","",""]
[18,{"v":3,"d":"3.00"},{"v":2.5,"d":"2.50"},{"v":0.5,"d":"0.50"},{"$nulls":5},"Incomplete",null,18,"","","","","","",""]
[19,{"v":2.5,"d":"2.50"},{"v":1.5,"d":"1.50"},{"v":1,"d":"1.00"},{"$nulls":5},"Incomplete",null,19,"","","","","","",""]
[20,{"v":2.5,"d":"2.50"},{"v":0.5,"d":"0.50"},{"v":0.5,"d":"0.50"},0.75,0.75,{"$nulls":3},"Incomplete",null,20,"","","","","","",""]
[21,2.25,{"v":1,"d":"1.00"},{"v":1,"d":"1.00"},0.25,{"$nulls":4},"Incomplete",null,21,"","","","","","",""]
[22,1.75,0.75,{"v":0.5,"d":"0.50"},{"v":0.5,"d":"0.50"},{"$nulls":4},"Incomplete",null,22,"","","","","","",""]
[23,{"v":2,"d":"2.00"},{"v":0.5,"d":"0.50"},{"v":1,"d":"1.00"},{"v":0.5,"d":"0.50"},{"$nulls":4},{"$f":"INDIRECT(\"'\"&A30&\"'!B1\")","v":"Incomplete"},null,{"$f":"A30","v":23},"","","","","","",""]
[]
["Total",{"$f":"SUM(B8:B30)","v":58.75},{"$nulls":9},"TOTAL",{"$f":"IF(SUM(IF(M8:S30=\"\",0,1))=0,\"\",SUM(M8:S30))","v":""},null,"Percentage:",{"$f":"IF(M32=\"\",\"\",M32/B32)","v":""}]
[]
[{"$nulls":11},"Passing Score:",{"$f":"MROUND(72%*B32,0.25)","v":42.25}]

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[]
[]
[]
[]
[]
["Navigator – Select a question to go to it"]
[]
["Question #",{"$nulls":6},"Status"]
["Q1 -- Bailey & Simon -- Relative Credibility -- 3.50 points",{"$nulls":6},{"$f":"'Point Grid'!J8","v":"Incomplete"}]
["Q2 -- GLM -- Estimate probability using GLM output -- 2.00 points",{"$nulls":6},{"$f":"'Point Grid'!J9","v":"Incomplete"}]
["Q3 -- GLM -- Number of Parameters within a GLM -- 2.00 points",{"$nulls":6},{"$f":"'Point Grid'!J10","v":"Incomplete"}]
["Q4 -- Mahler -- Criteria for Credibility -- 1.50 points",{"$nulls":6},{"$f":"'Point Grid'!J11","v":"Incomplete"}]
["Q5 -- Couret & Venter -- Determine best approach using SSE -- 1.50 points",{"$nulls":6},{"$f":"'Point Grid'!J12","v":"Incomplete"}]
["Q6 -- GLM -- Adding variables to a GLM or GLMM -- 2.75 points",{"$nulls":6},{"$f":"'Point Grid'!J13","v":"Incomplete"}]
["Q7 -- Fisher -- Rating Plan Equity -- 3.00 points",{"$nulls":6},{"$f":"'Point Grid'!J14","v":"Incomplete"}]
["Q8 -- Bahnemann -- Excess Layer Inflation -- 3.50 points",{"$nulls":6},{"$f":"'Point Grid'!J15","v":"Incomplete"}]
["Q9 -- ISO -- Calculate experience modification factor -- 4.00 points",{"$nulls":6},{"$f":"'Point Grid'!J16","v":"Incomplete"}]
["Q10 -- Fisher -- Split Modification Formula -- 1.75 points",{"$nulls":6},{"$f":"'Point Grid'!J17","v":"Incomplete"}]
["Q11 -- ISO -- Schedule Rating -- 2.75 points",{"$nulls":6},{"$f":"'Point Grid'!J18","v":"Incomplete"}]
["Q12 -- Fisher -- Credibility Functions -- 3.00 points",{"$nulls":6},{"$f":"'Point Grid'!J19","v":"Incomplete"}]
["Q13 -- Fisher -- Balanced Rating Plan -- 2.00 points",{"$nulls":6},{"$f":"'Point Grid'!J20","v":"Incomplete"}]
["Q14 -- Fisher -- Large Dollar Deductible Premium -- 2.00 points",{"$nulls":6},{"$f":"'Point Grid'!J21","v":"Incomplete"}]
["Q15 -- Fisher -- Table M and Large Dollar Deductible Premium -- 4.00 points",{"$nulls":6},{"$f":"'Point Grid'!J22","v":"Incomplete"}]
["Q16 -- Fisher -- Retrospective Premium and Savings -- 4.00 points",{"$nulls":6},{"$f":"'Point Grid'!J23","v":"Incomplete"}]
["Q17 -- Bahnemann -- Risk-adjusted ILFs -- 1.50 points",{"$nulls":6},{"$f":"'Point Grid'!J24","v":"Incomplete"}]
["Q18 -- NCCI Experience Rating-- Calculate experience mod -- 3.00 points",{"$nulls":6},{"$f":"'Point Grid'!J25","v":"Incomplete"}]
["Q19 -- Bahnemann -- Pricing with Straight Deductibles -- 2.50 points",{"$nulls":6},{"$f":"'Point Grid'!J26","v":"Incomplete"}]
["Q20 -- NCCI Circular -- Policy Excess Ratio and Expected Claims -- 2.50 points",{"$nulls":6},{"$f":"'Point Grid'!J27","v":"Incomplete"}]
["Q21 -- Bahnemann -- Mean Excess Claim Size -- 2.25 points",{"$nulls":6},{"$f":"'Point Grid'!J28","v":"Incomplete"}]
["Q22 -- GLM -- Model Refinement -- 1.75 points",{"$nulls":6},{"$f":"'Point Grid'!J29","v":"Incomplete"}]
["Q23 -- Holmes -- Lasso Credibility Coefficients -- 2.00 points",{"$nulls":6},{"$f":"'Point Grid'!J30","v":"Incomplete"}]

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[1,"Incomplete",{"$nulls":5},"Navigator",null,"Solution"]
[{"$nulls":8},"a.)"]
["Points","The following information can be used to calculate the credibility assigned to the"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('1'!A1,'Point Grid'!A:A,0))","v":3.5},"experience of a single private passenger car."]
[]
[null,"Group","Last Accident","Earned Car Years","Premium at Present B Rates","Number of Claims"]
[null,"A","3+",{"v":671000,"d":"671,000"},{"v":600000000,"d":"600,000,000"},{"v":60000,"d":"60,000"}]
[null,"X",2,{"v":553000,"d":"553,000"},{"v":225000000,"d":"225,000,000"},{"v":25000,"d":"25,000"}]
[null,"Y",1,{"v":120000,"d":"120,000"},{"v":93000000,"d":"93,000,000"},{"v":21000,"d":"21,000"}]
[null,"B",0,"M",{"v":50000000,"d":"50,000,000"},{"v":18000,"d":"18,000"}]
[null,"Total",null,{"$f":"TEXT(SUM(D7:D9),\"0,000\")&\" + M\"","v":"1,344,000 + M"},{"$f":"SUM(E7:E10)","v":{"v":968000000,"d":"968,000,000"}},{"$f":"SUM(F7:F10)","v":{"v":124000,"d":"124,000"}}]
[]
[null,"You may assume the following:"]
[null,"   • High frequency territories are also high average premium territories."]
[null,"   • Territory differentials are proper."]
[null,"   • The total claim frequency for the entire class does not change from year to year."]
[]
["(a)","Calculate M, the earned car years for Group B, given that the credibility for an insured that has"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A18,'Point Grid'!$C$7:$I$7,0))","v":2.5},"had no claim-free years is equal to 0.167."]
[]
[]
["(b)","Calculate the credibility for the group of risks that have been claim free for two or more years."]
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[2,"Incomplete",{"$nulls":5},"Navigator",null,"Solution"]
[{"$nulls":8},"a.)"]
["Points","You are given the following output from a GLM to estimate the probability of a claim:"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('2'!A1,'Point Grid'!A:A,0))","v":2},"• The actuary selected a Binomial distribution."]
[null,"• The actuary selected the logit link function."]
[]
[null,"Parameter","β"]
[null,"Intercept",-1.485]
[]
[null,"Vehicle Body"]
[null,"Coupe",-0.881]
[null,"Roadster",-1.047]
[null,"Sedan",-1.175]
[null,"Station Wagon",-1.083]
[null,"Truck",-1.118]
[null,"Utility",{"v":-1.33,"d":"-1.330"}]
[]
[null,"Driver Gender"]
[null,"Male",-0.025]
[]
[null,"Driver Age"]
[null,"ln(age)",-0.05]
[]
[null,"Territory"]
[null,"B",0.094]
[null,"C",0.037]
[null,"D",-0.101]
[]
["(a)","Calculate the estimated probability of a claim for:"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A29,'Point Grid'!$C$7:$I$7,0))","v":2},"   • Driver Gender: Female"]
[null,"   • Driver Age: 25"]
[null,"   • Vehicle Body: Sedan"]
[null,"   • Territory: D"]

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[3,"Incomplete",{"$nulls":5},"Navigator",null,"Solution"]
[{"$nulls":8},"a.)"]
["Points","You are given a GLM which models liability claim size using the following explanatory variables:"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('3'!A1,'Point Grid'!A:A,0))","v":2}]
[null,"• Vehicle price, which is a continuous variable model with a third order polynomial."]
[null,"• Average driver age, which is a continuous variable modeled with a first order polynomial."]
[null,"• Number of drivers, which is a categorical variable with four levels."]
[null,"• Gender, which is a categorical variable with two levels."]
[null,"• There is only one interaction in the model, which is between gender and average driver age."]
[]
["(a)","Determine the maximum number of β parameters in this model."]
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[4,"Incomplete",{"$nulls":4},"Navigator",null,"Solution"]
[{"$nulls":7},"a.)"]
["Points","Three experience rating plans have been developed and you are trying to evaluate"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('4'!A1,'Point Grid'!A:A,0))","v":1.5},"which is optimal.  Each rating plan has been tested on four different risks."]
[]
[null,"The following tables summarize the indicated modifications and the resulting errors."]
[]
[null,"Plan 1"]
[null,"Risk #","Predicted Modification Factor","Error"]
[null,1,1.2,{"v":0.5,"d":"50%"}]
[null,2,1.2,{"v":0.45,"d":"45%"}]
[null,3,0.7,{"v":0.2,"d":"20%"}]
[null,4,0.7,{"v":0.3,"d":"30%"}]
[]
[null,"Plan 2"]
[null,"Risk #","Predicted Modification Factor","Error"]
[null,5,1.2,{"v":0.08,"d":"8%"}]
[null,6,1.2,{"v":-0.08,"d":"-8%"}]
[null,7,0.6,{"v":-0.22,"d":"-22%"}]
[null,8,0.6,{"v":0.22,"d":"22%"}]
[]
[null,"Plan 3"]
[null,"Risk #","Predicted Modification Factor","Error"]
[null,9,1.4,{"v":0.03,"d":"3%"}]
[null,10,1.3,{"v":0.01,"d":"1%"}]
[null,11,0.75,{"v":-0.02,"d":"-2%"}]
[null,12,0.65,{"v":-0.05,"d":"-5%"}]
[]
["(a)","Which is the preferred plan based on the Meyers/Dorweiler criterion?"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A29,'Point Grid'!$C$7:$I$7,0))","v":1.5},"Which is the preferred plan based on the mean squared error criterion?"]
[null,"Explain your answer to each part above."]

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[5,"Incomplete",{"$nulls":4},"Navigator",null,"Solution"]
[{"$nulls":7},"a.)"]
["Points","A multi-dimensional credibility technique has been developed to predict claim frequencies"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('5'!A1,'Point Grid'!A:A,0))","v":1.5},"for permanent total (PT) claims."]
[null,"   • Seven years of data were collected."]
[null,"   • The technique produced a raw predicted relativity based on the oldest five years."]
[null,"   • The most recent two years were used as the holdout sample."]
[null,"   • The sample means are normalized within a hazard group."]
[]
[null,"Quintile","Holdout Sample Relativity","Prediction Based on Raw","Prediction Based on Credibility Procedure"]
[null,1,0.55,0.4,0.45]
[null,2,0.9,0.6,0.7]
[null,3,1.1,1.05,1.15]
[null,4,1.25,1.5,1.3]
[null,5,1.5,2.5,1.9]
[]
["(a)","Using the sum of squared error, demonstrate whether the multi-dimensional credibility "]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A17,'Point Grid'!$C$7:$I$7,0))","v":1.5},"technique produces an improved estimate over the estimates produced using the raw relativities"]
[null,"and the total hazard group relativities."]

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[6,"Incomplete",{"$nulls":6},"Navigator",null,"Solution"]
[{"$nulls":9},"a.)"]
["Points","You are testing the addition of a new categorical variable into an existing GLM, and are"]
[null,"given the following information:"]
[]
[null,"• A is the change in AIC and B is the change in BIC after adding the new variable."]
[null,"• B > A + 100"]
[]
[null,{"v":5000,"d":"5,000"},"Number of observations in the model"]
[]
["(a)","Calculate the minimum possible number of levels in the new categorical variable."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A11,'Point Grid'!$C$7:$I$7,0))","v":1.5}]
[]
[]
[null,"Suppose instead the new categorical is added as a random effect, turning the GLM into a"]
[null,"GLMM."]
["(b)","Identify the minimum possible number of parameters added to the model when the new"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A17,'Point Grid'!$C$7:$I$7,0))","v":0.25},"categorical variable is introduced."]
[]
[]
[null,"A colleague suggests the GLM approach is better than the GLMM approach because the"]
[null,"GLM coefficients are greater in magnitude than those produced by the GLMM for the"]
[null,"new categorical variable. "]
[]
["(c)","Briefly describe an issue presented by the GLM approach and explain how the "]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A25,'Point Grid'!$C$7:$I$7,0))","v":1},"GLMM approach is an improvement."]

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[7,"Incomplete",{"$nulls":5},"Navigator",null,"Solution"]
[{"$nulls":8},"a.)"]
["Points","The following information was taken from two different experience rating plans:"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('7'!A1,'Point Grid'!A:A,0))","v":3}]
[null,null,"Experience Modification",null,"Experience Data"]
[null,"Insured","Plan A","Plan B","Manual Premium","Losses"]
[null,1,0.8,1.03,{"v":75000,"d":"75,000"},{"v":60000,"d":"60,000"}]
[null,2,0.85,0.69,{"v":75000,"d":"75,000"},{"v":58000,"d":"58,000"}]
[null,3,{"v":0.9,"d":"0.90"},0.75,{"v":75000,"d":"75,000"},{"v":61000,"d":"61,000"}]
[null,4,0.91,0.89,{"v":125000,"d":"125,000"},{"v":104000,"d":"104,000"}]
[null,5,0.96,0.87,{"v":125000,"d":"125,000"},{"v":116000,"d":"116,000"}]
[]
["(a)","Demonstrate whether Plan A or Plan B appears to be more equitable."]
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[]
[]
["(b)","Demonstrate whether Plan A or Plan B gives too much credit for good experience."]
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{"$rows_empty":13}
[{"$nulls":8},"b.)"]

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[{"$nulls":5},"a.)"]
["Points","A portfolio of insurance policies currently has the size of loss distribution shown below:"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('8'!A1,'Point Grid'!A:A,0))","v":3.5},"Occurrence Limit","Probability that a Claim is less than the Occurrence Limit","Expected Limited Severity for the Occurrence Limit"]
[null,{"v":100000,"d":"100,000"},{"v":0.673,"d":"67.3%"},{"v":48000,"d":"$48,000"}]
[null,{"v":125000,"d":"125,000"},{"v":0.689,"d":"68.9%"},{"v":59000,"d":"$59,000"}]
[null,{"v":150000,"d":"150,000"},{"v":0.712,"d":"71.2%"},{"v":63500,"d":"$63,500"}]
[null,{"v":175000,"d":"175,000"},{"v":0.712,"d":"71.2%"},{"v":68000,"d":"$68,000"}]
[null,{"v":200000,"d":"200,000"},{"v":0.818,"d":"81.8%"},{"v":73500,"d":"$73,500"}]
[null,{"v":225000,"d":"225,000"},{"v":0.819,"d":"81.9%"},{"v":90500,"d":"$90,500"}]
[null,{"v":250000,"d":"250,000"},{"v":0.864,"d":"86.4%"},{"v":120000,"d":"$120,000"}]
[null,{"v":300000,"d":"300,000"},{"v":0.884,"d":"88.4%"},{"v":123000,"d":"$123,000"}]
[null,{"v":400000,"d":"400,000"},{"v":0.895,"d":"89.5%"},{"v":124000,"d":"$124,000"}]
[null,{"v":500000,"d":"500,000"},{"v":0.903,"d":"90.3%"},{"v":130500,"d":"$130,500"}]
[null,{"v":750000,"d":"750,000"},{"v":0.903,"d":"90.3%"},{"v":135000,"d":"$135,000"}]
[null,{"v":800000,"d":"800,000"},{"v":0.93,"d":"93.0%"},{"v":140500,"d":"$140,500"}]
[null,{"v":900000,"d":"900,000"},{"v":0.957,"d":"95.7%"},{"v":153000,"d":"$153,000"}]
[null,{"v":1000000,"d":"1,000,000"},{"v":0.972,"d":"97.2%"},{"v":159500,"d":"$159,500"}]
[null,{"v":1250000,"d":"1,250,000"},{"v":0.974,"d":"97.4%"},{"v":178000,"d":"$178,000"}]
[null,{"v":1500000,"d":"1,500,000"},{"v":0.979,"d":"97.9%"},{"v":186000,"d":"$186,000"}]
[]
[null,{"v":250000,"d":"$250,000"},"\"Large Loss\" threshold for the insurer today"]
[null,50,"It's estimated the portfolio policies will generate this many "]
[null,null,"\"large losses\" during the next two years."]
[]
[null,"The actuary estimates the following:"]
[null,{"v":0.118,"d":"11.8%"},"Annual claim severity inflationary trend"]
[null,{"v":0.2,"d":"20%"},"Expected annual exposure growth"]
[]
["(a)","Calculate the expected number of claims that exceed the large loss threshold in two years time."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A30,'Point Grid'!$C$7:$I$7,0))","v":1.5}]
[]
[]
["(b)","Calculate the expected losses for this portfolio in the layer $1,000,000 excess of $250,000 after "]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A34,'Point Grid'!$C$7:$I$7,0))","v":2},"two years."]

{"sheet":"9","index":11,"n_rows":54,"n_cols":11,"rows_kept":54,"merged":[[0,7,0,8]]}
[9,"Incomplete",{"$nulls":5},"Navigator",null,null,"Solution"]
[{"$nulls":9},"a.)"]
["Points","Consider the following loss experience as of June 30, 2021 under a claims-made commercial general"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('9'!A1,'Point Grid'!A:A,0))","v":4},"liability policy:"]
[]
[null,"Policy Year","Claim Number","Basic Limit Indemnity","ALAE"]
[null,2016,1,{"v":25000,"d":"$25,000"},{"v":1000,"d":"$1,000"}]
[null,2017,2,{"v":8500,"d":"$8,500"},{"v":0,"d":"$0"}]
[null,2018,3,{"v":100000,"d":"$100,000"},{"v":55000,"d":"$55,000"}]
[null,2018,4,{"v":55000,"d":"$55,000"},{"v":5000,"d":"$5,000"}]
[null,2020,5,{"v":0,"d":"$0"},{"v":150000,"d":"$150,000"}]
[null,2020,6,{"v":32000,"d":"$32,000"},{"v":800,"d":"$800"}]
[]
[null,"The policy being rated has the following characteristics:"]
[null,"   • The policy always runs from January 1st through December 31st each year."]
[null,"   • The company has been with the same insurer in a claims-made program for over 15 years."]
[null,"   • The company's annual basic limit premium is:"]
[null,{"v":100000,"d":"$100,000"},"Premises/Operations"]
[null,{"v":25000,"d":"$25,000"},"Products/Completed Operations"]
[null,{"v":0.68,"d":"68%"},"Expected Loss Ratio"]
[]
["(a)","Calculate the experience modification factor for the policy effective between January 1 and "]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A22,'Point Grid'!$C$7:$I$7,0))","v":4},"December 31, 2022."]
[]
[null,"You may use the following information below:"]
[null,null,"Occurrence","Claims-Made Year in Program (YIP)"]
[null,"Subline","Policy","Mature","Fourth","Third","Second","First"]
[null,"Prem/Ops",{"v":1,"d":"1.00"},1.05,1.14,{"v":1.2,"d":"1.20"},1.32,1.62]
[null,"Products",{"v":1,"d":"1.00"},1.24,1.51,1.59,2.03,2.39]
[null,"Table 13.B"]
[]
[null,null,"Occurrence","Claims-Made Year in Program (YIP)"]
[null,"Subline","Policy","Mature","Fourth","Third","Second","First"]
[null,"Prem/Ops",{"v":1,"d":"1.00"},0.94,0.84,0.78,0.67,0.47]
[null,"Products",{"v":1,"d":"1.00"},0.72,0.49,0.43,0.35,0.22]
[null,"Table 13.C"]
[]
[null,"Experience ",null,"Factors for"]
[null,"Period Year","Subline","Rule 5.B","Rule 5.C"]
[null,"Latest","Prem/Ops",0.916,0.949]
[null,null,"Products",0.882,0.914]
[null,"2nd Latest","Prem/Ops",0.876,0.919]
[null,null,"Products",0.828,0.869]
[null,"3rd Latest","Prem/Ops",0.839,0.887]
[null,null,"Products",0.777,0.821]
[null,"Table 14"]
[]
[null,"CSLC","Credibility","EER","MSL"]
[null,"194,380 - 203,002",0.36,0.911,{"v":147550,"d":"147,550"}]
[null,"203,003 - 211,901",0.37,0.914,{"v":150450,"d":"150,450"}]
[null,"211,902 - 221,089",0.38,0.917,{"v":153400,"d":"153,400"}]
[null,"221,090 - 230,581",0.39,{"v":0.92,"d":"0.920"},{"v":156450,"d":"156,450"}]
[null,"230,582 - 240,392",{"v":0.4,"d":"0.40"},0.923,{"v":159600,"d":"159,600"}]
[null,"Table 16"]

{"sheet":"10","index":12,"n_rows":19,"n_cols":8,"rows_kept":19}
[10,"Incomplete",{"$nulls":3},"Navigator",null,"Solution"]
[{"$nulls":6},"a.)"]
["Points","Answer the following in the context of the NCCI experience rating formula."]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('10'!A1,'Point Grid'!A:A,0))","v":1.75}]
[]
["(a)","Explain why splitting the formula into primary and excess components is"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A6,'Point Grid'!$C$7:$I$7,0))","v":0.5},"preferable for Workers' Compensation risks."]
[]
[]
["(b)","Briefly describe the function of the primary component of the formula."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A10,'Point Grid'!$C$7:$I$7,0))","v":0.25}]
[]
[]
["(c)","Briefly describe why the excess component is capped."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A14,'Point Grid'!$C$7:$I$7,0))","v":0.25}]
[]
[]
["(d)","Discuss how using full credibility conflicts with one goal of experience rating."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A18,'Point Grid'!$C$7:$I$7,0))","v":0.75}]

{"sheet":"11","index":13,"n_rows":30,"n_cols":9,"rows_kept":30}
[11,"Incomplete",{"$nulls":4},"Navigator",null,"Solution"]
[{"$nulls":7},"a.)"]
["Points"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('11'!A1,'Point Grid'!A:A,0))","v":2.75},"ABC Incorporated is a theme park operator who is purchasing a Commercial General Liability "]
[null,"policy with an effective date of January 1, 2022. Assume ABC Incorporated is eligible for both "]
[null,"experience and schedule rating, and each scenario listed below is independent."]
[]
[null,"For each scenario identify whether a debit or credit should apply to the schedule rating,"]
[null,"suggest an appropriate figure and state the maximum possible debit or credit that could"]
[null,"be applied."]
[]
["(a)","In 2017, ABC Incorporated implemented a mandatory one-month training program for all"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A12,'Point Grid'!$C$7:$I$7,0))","v":0.5},"new hires that teaches equipment maintenance, safety programs, and first aid."]
[]
[]
["(b)","In 2021, ABC Incorporated added a full-time, on-site doctor in each of its locations and trained"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A16,'Point Grid'!$C$7:$I$7,0))","v":0.5},"all employees in emergency first aid."]
[]
[]
["(c)","Due to an increase in visitors in 2021, ABC Incorporated reduced ride downtimes and hired"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A20,'Point Grid'!$C$7:$I$7,0))","v":0.5},"inexperienced employees to staff its locations. ABC Incorpated usually only hires employees"]
[null,"with at least three years of experience."]
[]
["(d)","ABC Incorporated began replacing all equipment over 5-years old in each of its locations"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A24,'Point Grid'!$C$7:$I$7,0))","v":0.5},"in the second quarter of 2021. The upgrades will be completed by Q1 2022."]
[]
[]
["(e)","In order to accommodate more visitors in 2022, ABC Incorporated has increased the maximum "]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A28,'Point Grid'!$C$7:$I$7,0))","v":0.75},"capacity of its indoor rides across all locations without making any physical changes. "]
[null,"No changes are made to outdoor rides."]

{"sheet":"12","index":14,"n_rows":20,"n_cols":9,"rows_kept":20}
[12,"Incomplete",{"$nulls":4},"Navigator",null,"Solution"]
[{"$nulls":7},"a.)"]
["Points"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('12'!A1,'Point Grid'!A:A,0))","v":3}]
[]
["(a)","Using words, identify the three criteria that define an effective credibility function "]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A6,'Point Grid'!$C$7:$I$7,0))","v":1},"for experience rating."]
[]
[]
["(b)","Using equations, describe the three criteria from part (a), making sure to "]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A10,'Point Grid'!$C$7:$I$7,0))","v":1},"define all notation used."]
[]
[]
["(c)","For each of the three criteria, briefly explain whether or not the following credibility function "]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A14,'Point Grid'!$C$7:$I$7,0))","v":1},"satisfies the criterion."]
[null,null,"Expected Losses Between","Credibility"]
[null,null,"$0 to $5,000",{"v":0,"d":"0%"}]
[null,null,"$5,001 to $10,000",{"v":0.35,"d":"35%"}]
[null,null,"$10,001 to $25,000",{"v":0.8,"d":"80%"}]
[null,null,"$25,001 or more",{"v":1,"d":"100%"}]

{"sheet":"13","index":15,"n_rows":28,"n_cols":9,"rows_kept":28}
[13,"Incomplete",{"$nulls":4},"Navigator",null,"Solution"]
[{"$nulls":7},"a.)"]
["Points","The following information applies to a balanced retrospectively rated policy:"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('13'!A1,'Point Grid'!A:A,0))","v":2}]
[null,{"v":26000,"d":"$26,000"},"Standard Premium"]
[null,{"v":24000,"d":"$24,000"},"Guaranteed Cost Premium"]
[null,{"v":20000,"d":"$20,000"},"Provision for Losses and Expenses excluding Taxes"]
[null,{"v":15000,"d":"$15,000"},"Expected Losses"]
[null,1.15,"Loss Conversion Factor"]
[null,0.06,"Charge for Maximum"]
[null,0.57,"Savings for Maximum"]
[null,0.685,"Charge for Minimum"]
[null,0.019,"Savings for Minimum"]
[]
["(a)","Determine the tax multiplier."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A15,'Point Grid'!$C$7:$I$7,0))","v":0.5}]
[]
[]
["(b)","Determine the minimum premium ratio as a percentage of standard premium."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A19,'Point Grid'!$C$7:$I$7,0))","v":0.5}]
[]
[]
["(c)","Calculate the converted insurance charge in dollars."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A23,'Point Grid'!$C$7:$I$7,0))","v":0.5}]
[]
[]
["(d)","Determine the loss ratio at minimum."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A27,'Point Grid'!$C$7:$I$7,0))","v":0.5}]

{"sheet":"14","index":16,"n_rows":11,"n_cols":7,"rows_kept":11}
[14,"Incomplete",null,null,"Navigator",null,"Solution"]
[{"$nulls":5},"a.)"]
["Points","Using the information below, calculate the premium for a $50,000 deductible policy."]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('14'!A1,'Point Grid'!A:A,0))","v":2}]
[null,{"v":314200,"d":"$314,200"},"Standard Premium"]
["(a)",{"v":0.65,"d":"65%"},"Expected Loss ratio"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A6,'Point Grid'!$C$7:$I$7,0))","v":2},{"v":0.1,"d":"10%"},"ALAE as a percentage of loss"]
[null,{"v":0.175,"d":"18%"},"Commission as a percentage of premium"]
[null,{"v":0.08,"d":"8%"},"Other variable expenses"]
[null,{"v":22000,"d":"$22,000"},"Fixed expenses"]
[null,0.32,"Loss Elimination Ratio at a $50,000 deductible"]

{"sheet":"15","index":17,"n_rows":29,"n_cols":9,"rows_kept":29,"merged":[[17,2,17,3],[18,2,18,3],[19,2,19,3],[20,2,20,3],[21,2,21,3]]}
[15,"Incomplete",{"$nulls":4},"Navigator",null,"Solution"]
[{"$nulls":7},"a.)"]
["Points","An insurer writes five identical workers compensation risks for one year and observes "]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('15'!A1,'Point Grid'!A:A,0))","v":4},"the following:"]
[]
[null,{"v":1250000,"d":"$1,250,000"},"Standard Premium for each risk"]
[null,{"v":0.06,"d":"6%"},"General Overhead Expense as a Percent of Standard Premium"]
[null,{"v":0.045,"d":"4.50%"},"Credit Risk Charge as a Percent of Standard Premium"]
[null,{"v":0.11,"d":"11%"},"Expected ULAE as a Percent of Loss and ALAE"]
[null,{"v":0.04,"d":"4%"},"Loss Based Assessment as a Percent of Loss and ALAE"]
[null,{"v":0.1,"d":"10%"},"Excess Ratio for a $250,000 Deductible (% of Loss and ALAE)"]
[null,{"v":0.08,"d":"8%"},"Acquisition Expenses as a Percent of Standard Premium"]
[null,{"v":0.03,"d":"3%"},"Premium Tax as a Percent of Standard Premium"]
[null,{"v":0.05,"d":"5%"},"Profit Load as a Percent of Net Premium"]
[]
[null,"Actual losses for each risk are as follows:"]
[null,"Risk #","Actual Loss & ALAE"]
[null,1,{"v":400000,"d":"$400,000"}]
[null,2,{"v":800000,"d":"$800,000"}]
[null,3,{"v":1000000,"d":"$1,000,000"}]
[null,4,{"v":1200000,"d":"$1,200,000"}]
[null,5,{"v":1600000,"d":"$1,600,000"}]
[]
["(a)","Construct a Table M for this book of business by displaying the insurance charges and savings"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A24,'Point Grid'!$C$7:$I$7,0))","v":2},"for entry ratios from 0.00 to 1.60 in increments of 0.20."]
[]
[]
["(b)","For any risk above, estimate the prospective premium for a large dollar deductible (LDD) policy with"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A28,'Point Grid'!$C$7:$I$7,0))","v":2},"a per-occurrence deductible of $250,000 and an annual aggregate deductible of $1,260,000."]

{"sheet":"16","index":18,"n_rows":20,"n_cols":9,"rows_kept":20}
[16,"Incomplete",{"$nulls":4},"Navigator",null,"Solution"]
[{"$nulls":7},"a.)"]
["Points","The following information applies to a company's retrospectively rated Workers'"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('16'!A1,'Point Grid'!A:A,0))","v":4},"Compensation policy:"]
[null,"   • Its losses are expected to be uniformly distributed on [0, 1,000,000]."]
[]
[null,{"v":750000,"d":"$750,000"},"Losses at maximum premium"]
[null,{"v":225000,"d":"$225,000"},"Losses at minimum premium"]
[null,1.15,"Loss conversion factor"]
[null,{"v":130000,"d":"$130,000"},"Basic Premium"]
[null,{"v":0.05,"d":"5%"},"Tax Rate"]
[]
["(a)","Calculate the expected retrospective premium for this Workers' Compensation policy."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A13,'Point Grid'!$C$7:$I$7,0))","v":2}]
[]
[]
["(b)","The company is considering whether to implement a fraud detection device."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A17,'Point Grid'!$C$7:$I$7,0))","v":2},"This addition would result in a shift in the loss distribution to a uniform distribution"]
[null,"between [0, 800,000]."]
[null,"Assuming no other plan parameters change, calculate the resulting premium savings."]

{"sheet":"17","index":19,"n_rows":16,"n_cols":9,"rows_kept":16}
[17,"Incomplete",{"$nulls":4},"Navigator",null,"Solution"]
[{"$nulls":7},"a.)"]
["Points","Given the following information about an insurer's book of business:"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('17'!A1,'Point Grid'!A:A,0))","v":1.5}]
[null,{"v":10000,"d":"$10,000"},"Basic limit",null,"Claim Size","Probability"]
[null,{"v":250000,"d":"$250,000"},"Policy limit",null,{"v":250,"d":"$250"},0.1768]
[null,{"v":500,"d":"$500"},"Average ALAE",null,{"v":2500,"d":"$2,500"},0.5709]
[null,{"v":0.02,"d":"2.0%"},"ULAE",null,{"v":15000,"d":"$15,000"},0.1565]
[null,{"v":4,"d":"4.0"},"Expected Claim Count",null,{"v":75000,"d":"$75,000"},0.0958]
[null,{"v":0.15,"d":"15.0%"},"ISO k-value"]
[]
[null,"• Claim counts are assumed to follow a Poisson distribution."]
[null,"• The insurer follows the ISO approach to load their ILFs for risk."]
[]
["(a)","Calculate the ILF at the policy limit with and without including the risk load."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A15,'Point Grid'!$C$7:$I$7,0))","v":1.5}]

{"sheet":"18","index":20,"n_rows":47,"n_cols":10,"rows_kept":47,"merged":[[0,6,0,7]]}
[18,"Incomplete",{"$nulls":4},"Navigator",null,null,"Solution"]
[{"$nulls":8},"a.)"]
["Points","An insured is subject to experience rating under the National Council on Compensation Insurance "]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('18'!A1,'Point Grid'!A:A,0))","v":3},"(NCCI) Experience Rating Plan Manual for Workers Compensation and Employers Liability Insurance."]
[]
[null,"The following information about the insured is given:"]
[null,{"v":4000000,"d":"$4,000,000"},"Payroll for the experience period"]
[null,"AL","State"]
[null,4279,"Class"]
[null,{"v":5000,"d":"$5,000"},"Primary/Excess split point"]
[null,{"v":167000,"d":"$167,000"},"State per Claim Accident Limitation"]
[null,{"v":334000,"d":"$334,000"},"State Multiple Claim Accident Limitation"]
[null,{"v":6.7,"d":"6.70"},"G value"]
[]
[null,"The following claims apply to the experience period."]
[null,"Excluding Medical Only Losses",null,null,"Medical Only Losses"]
[null,"Claim #","Indemnity",null,"Claim #","Indemnity"]
[null,1,{"v":2000,"d":"$2,000"},null,7,{"v":500,"d":"$500"}]
[null,2,{"v":2500,"d":"$2,500"},null,8,{"v":1750,"d":"$1,750"}]
[null,3,{"v":4000,"d":"$4,000"},null,9,{"v":3000,"d":"$3,000"}]
[null,4,{"v":5000,"d":"$5,000"},null,10,{"v":25000,"d":"$25,000"}]
[null,5,{"v":25000,"d":"$25,000"}]
[null,"6*",{"v":350000,"d":"$350,000"}]
[null,"* Only one person was injured in claim 6."]
[]
[null,"You may use the following tables to answer the question below."]
[null,"Class Code","ELR","D Ratio"]
[null,4263,1.01,0.22]
[null,4273,0.94,0.21]
[null,4279,1.17,{"v":0.2,"d":"0.20"}]
[]
[null,"Expected Losses","Weighting Value",null,"Expected Losses","Ballast Value"]
[null,"31,844 to 47,399",{"v":0.1,"d":"0.10"},null,"0 to 36,038",{"v":16750,"d":"16,750"}]
[null,"47,400 to 61,236",0.11,null,"36,039 to 62,025",{"v":20100,"d":"20,100"}]
[null,"61,237 to 74,710",0.12,null,"62,026 to 91,884",{"v":23450,"d":"23,450"}]
[]
["(a)","Calculate the experience modification for this insured."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A37,'Point Grid'!$C$7:$I$7,0))","v":2.5}]
[]
[]
["(b)","Select all true statements below:"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A41,'Point Grid'!$C$7:$I$7,0))","v":0.5}]
[null,"i.) The state per-accident and multiple claim accident limits do not apply to disease losses."]
[null,"ii.) Policy level disease losses are capped at 3*(State per-claim accident limit) + 120% Expected Loss."]
[null,"iii.) Primary disease losses are capped at 2x the primary/excess split point."]
[null,"iv.) Primary disease losses are capped at 2x primary/excess split point + 40% Expected Primary Loss."]
[null,"v.) Disease losses do not include losses due to occupational exposures such as exposure to asbestos."]

{"sheet":"19","index":21,"n_rows":30,"n_cols":11,"rows_kept":30}
[19,"Incomplete",{"$nulls":6},"Navigator",null,"Solution"]
[{"$nulls":9},"a.)"]
["Points"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('19'!A1,'Point Grid'!A:A,0))","v":2.5},"Given the following information about an insurer's book of business which "]
[null,"utilizes straight deductibles:"]
[]
[null,0.0003,"Ground-up claim frequency"]
[null,{"v":100000,"d":"100,000"},"Basic policy limit"]
[null,{"v":12310,"d":"12,310"},"Basic limit expected loss"]
[null,150,"ALAE"]
[null,{"v":0.12,"d":"12.0%"},"ULAE"]
[]
[null,{"v":250000,"d":"$250,000"},"Policy limit"]
[null,{"v":1000,"d":"$1,000"},"Policy Deductible"]
[null,{"v":4684.152990107914,"d":"$4,684"},"Policy Premium"]
[]
[null,"Deductible","E[X; d]","FX(d)",null,"Limit","ILF"]
[null,0,0,0,null,{"v":100000,"d":"100,000"},{"v":0.6666666666666666,"d":"0.667"}]
[null,{"v":1000,"d":"1,000"},659,0.4847,null,{"v":250000,"d":"250,000"},{"v":1,"d":"1.000"}]
[null,{"v":2000,"d":"2,000"},{"v":1111,"d":"1,111"},0.5989,null,{"v":500000,"d":"500,000"},{"v":1.1666666666666667,"d":"1.167"}]
[null,{"v":3000,"d":"3,000"},{"v":1478,"d":"1,478"},0.6625,null,{"v":1000000,"d":"1,000,000"},{"v":1.2666666666666666,"d":"1.267"}]
[null,{"v":5000,"d":"5,000"},{"v":2071,"d":"2,071"},0.7364]
[null,{"v":10000,"d":"10,000"},{"v":3144,"d":"3,144"},0.8215]
[]
["(a)","Calculate the loss elimination ratio, modified frequency, severity and pure premium "]
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[]
[]
["(b)","Calculate the premium for a policy with a $1,000,000 limit and $2,000 deductible."]
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{"sheet":"20","index":22,"n_rows":37,"n_cols":12,"rows_kept":37,"merged":[[0,8,0,9]]}
[20,"Incomplete",{"$nulls":6},"Navigator",null,null,"Solution"]
[{"$nulls":10},"a.)"]
["Points","Given the following information about a retrospectively rated Workers' Compensation policy which is"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('20'!A1,'Point Grid'!A:A,0))","v":2.5},"also subject to experience rating."]
[]
[null,0.95,"Experience Modification Factor",{"$nulls":4},"Table of Policy Excess Ratio Ranges"]
[null,{"v":0.66,"d":"66%"},"Expected Unlimited Loss Ratio",{"$nulls":4},"Sub-table","Excess Ratio Range"]
[{"$nulls":7},7,"0.146 - 0.181"]
[null,null,"Hazard","Manual","Excess Ratio ","Avg. Cost",null,8,"0.182 - 0.221"]
[null,"State","Group","Premium","at Loss Limit","per Case",null,9,"0.222 - 0.269"]
[null,"X","A",{"v":70000,"d":"70,000"},0.72,{"v":25000,"d":"25,000"},null,10,"0.270 - 0.316"]
[null,"Y","B",{"v":120000,"d":"120,000"},0.05,{"v":17000,"d":"17,000"},null,11,"0.317 - 0.358"]
[null,"Z","C",{"v":135000,"d":"135,000"},0.59,{"v":20000,"d":"20,000"},null,12,"0.359 - 0.420"]
[{"$nulls":7},13,"0.421 - 0.484"]
[]
["(a)","Calculate the policy excess ratio and associated sub-table to use when rating this policy under the"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A16,'Point Grid'!$C$7:$I$7,0))","v":0.5},"NCCI Retrospective rating plan."]
[]
[]
["(b)","Calculate the total number of expected claims for this policy."]
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[]
[]
["(c)","Organize the following according to whether or not they are part of the policy's basic premium."]
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[]
[]
[null,"Included in Basic Premium",null,null,"Not Part of Basic Premium"]
{"$rows_empty":7}
["(d)","Identify two advantages and one disadvantage of using the table of aggregate loss factors over the"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A36,'Point Grid'!$C$7:$I$7,0))","v":0.75},"previous table of net insurance charges."]

{"sheet":"21","index":23,"n_rows":24,"n_cols":10,"rows_kept":24}
[21,"Incomplete",{"$nulls":5},"Navigator",null,"Solution"]
[{"$nulls":8},"a.)"]
["Points","An actuary wishes to fit a claim size distribution to a sample of 1,000 claims."]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('21'!A1,'Point Grid'!A:A,0))","v":2.25}]
[null,null,"Size Group","# Claims","Total Loss","Severity"]
[null,null,"0 – 100",99,{"v":5000,"d":"5,000"},{"$f":"E6/D6","v":{"v":50.505050505050505,"d":"51"}}]
[null,null,"101 – 500",293,{"v":84000,"d":"84,000"},{"$f":"E7/D7","v":{"v":286.68941979522185,"d":"287"}}]
[null,null,"501 – 1,000",221,{"v":162000,"d":"162,000"},{"v":733.0316742081448,"d":"733"}]
[null,null,"1,001 – 2,000",213,{"v":305000,"d":"305,000"},{"v":1431.924882629108,"d":"1,432"}]
[null,null,"2,001 – 4,000",127,{"v":354000,"d":"354,000"},{"v":2787.4015748031497,"d":"2,787"}]
[null,null,"4,001 – 5,000",20,{"v":91000,"d":"91,000"},{"v":4550,"d":"4,550"}]
[null,null,"5,001 – 10,000",27,{"v":193000,"d":"193,000"},{"v":7148.148148148148,"d":"7,148"}]
[null,null,"Total",{"$f":"SUM(D6:D12)","v":{"v":1000,"d":"1,000"}},{"$f":"SUM(E6:E12)","v":{"v":1194000,"d":"1,194,000"}},{"$f":"E13/D13","v":{"v":1194,"d":"1,194"}}]
[]
["(a)","Calculate the empirical mean excess claim size distribution and identify the distribution."]
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[]
[]
["(b)","Using the distribution identified in part a.) above, calculate the empirical parameters"]
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[]
[]
["(c)","Identify a condition on the claim data set in order for the above analysis to produce"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$28,MATCH($A$1,'Point Grid'!$A$8:$A$28,0),MATCH(A23,'Point Grid'!$C$7:$I$7,0))","v":0.25},"an accurate distribution."]

{"sheet":"22","index":24,"n_rows":40,"n_cols":9,"rows_kept":40,"merged":[[0,5,0,6]]}
[22,"Incomplete",{"$nulls":3},"Navigator",null,null,"Solution"]
[{"$nulls":7},"b.)"]
["Points","An actuary is about to peer review a GLM. They are refreshing their memory on some model"]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('22'!A1,'Point Grid'!A:A,0))","v":1.75},"refinement techniques."]
[]
[]
["(a)","Match the following descriptions to the correct techniques."]
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[null,"Cook's distance"]
[]
[]
[null,"Cross validation"]
[]
[]
[null,"Bootstrapping"]
{"$rows_empty":12}
["(b)","Identify a weakness of graphically analyzing deviance residuals and briefly describe how to"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$29,MATCH($A$1,'Point Grid'!$A$8:$A$29,0),MATCH(A28,'Point Grid'!$C$7:$I$7,0))","v":0.5},"overcome it."]
[]
[]
["(c)","Identify all true statements below:"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$29,MATCH($A$1,'Point Grid'!$A$8:$A$29,0),MATCH(A32,'Point Grid'!$C$7:$I$7,0))","v":0.5}]
[null," i.) Deviance residuals should have no predictable pattern."]
[null,"ii.) The shape of the deviance residuals should match the choice of GLM distribution."]
[null,"iii.) Deviance residuals should be normally distributed with constant variance."]
[null,"iv.) When plotting deviance residuals, significant deviations from normality"]
[null,"imply the model fit is good."]
[null,"v.) Both ends of a q-q plot for deviance residuals lie above the line of equality. This means the"]
[null,"chosen GLM distribution was too skewed to the right."]

{"sheet":"23","index":25,"n_rows":24,"n_cols":10,"rows_kept":24,"merged":[[0,6,0,7]]}
[23,"Incomplete",{"$nulls":4},"Navigator",null,null,"Solution"]
[]
["Points","An actuary has built a GLM for a countrywide rating plan. "]
[{"$f":"INDEX('Point Grid'!B:B,MATCH('23'!A1,'Point Grid'!A:A,0))","v":2},"They are using a lasso credibility model with a log-link function to produce"]
[null,"a rating plan for one of their mid-size states."]
[null,"The actuary uses the relativities from the countrywide GLM as the offsets."]
[]
["(a)","Using the information below, construct the table of rating factors for"]
[{"$f":"INDEX('Point Grid'!$C$8:$I$30,MATCH($A$1,'Point Grid'!$A$8:$A$30,0),MATCH(A8,'Point Grid'!$C$7:$I$7,0))","v":0.5},"the VehicleType rating variable for the mid-size state."]
[]
[{"$nulls":3},"GLM",null,"βj","Mid-Size"]
[null,"VehicleType",null,"Relativity",null,"Coefficients","Exposures"]
[null,"Sedan",null,{"v":1,"d":"1.000"},null,{"v":0,"d":"0.0000"},{"v":250000,"d":"250,000"}]
[null,"Van",null,0.691,null,0.2187,{"v":15000,"d":"15,000"}]
[null,"SUV",null,1.187,null,-0.0631,{"v":140000,"d":"140,000"}]
[null,"Luxury SUV",null,1.285,null,0.0192,{"v":53000,"d":"53,000"}]
[null,"Convertible",null,1.065,null,{"v":0,"d":"0.0000"},500]
[]
["(b)","Identify which vehicle types have full credibility on their complement."]
[{"$f":"INDEX('Point Grid'!$C$8:$I$30,MATCH($A$1,'Point Grid'!$A$8:$A$30,0),MATCH(A19,'Point Grid'!$C$7:$I$7,0))","v":1},"Briefly explain why."]
[]
[]
["(c)","Briefly explain why the VehicleType relativity for Convertibles found in "]
[{"$f":"INDEX('Point Grid'!$C$8:$I$30,MATCH($A$1,'Point Grid'!$A$8:$A$30,0),MATCH(A23,'Point Grid'!$C$7:$I$7,0))","v":0.5},"part a.) above may be incorrect."]