The proposed rates were not in the range the CEO expected given the pricing analysis. The CEO has asked the pricing actuary to verify the total projected loss cost excluding potential large storm losses for 2020. In turn, the pricing actuary has asked you to independently calculate the projected costs.

All policies are 12-month policies. The rates will take effect July 1, 2020 and will be in effect for one year. In 2017 there was a large storm resulting in an additional 230 storm-related claims averaging 30,000 each. The company was able to settle 40% of all total claim liabilities relating to those claims within 2017 with the remainder being paid out in 2018. All other claims are completely settled by the end of year 4. The pricing actuary determined trend factors using the least squares method and determined the projected loss cost based on the loss costs for 2018 and 2019 with weightings of 40% and 60% respectively. You are to use the same methodology. The data and underlying model are in the Excel worksheet .

Your response should be formatted as an internal memorandum to the pricing actuary and should include the projected loss costs for 2018 and 2019. Please show your work in an appendix.

 

B D E K L. 1 Part A Data 2 3 Incurred Losses for Reported Claims by Development Year 4 Accident Year 2 3 4 Exposure Units Number of Claims 5 2014 21,146,830 8,312,433 1,662,487 1,681,107 446,876 552,682 6,743 6 2015 20,926,455 7,822,974 2,281,701 1,110,862 453,732 552,375 6,242 7 2016 21,825,318 8,538,857 2,732,434 688,232 558,489 6,255 8 2017 25,818,428 13,105,174 2,868,856 558,505 6,485 6. 2018 23,571,061 9,605,762 553,329 6,087 10 2019 27,002,263 558,871 6,539 11 12 Enter the Lost Cost per Unit to Get the Results of the Regression Analysis 13 14 Accident Year X= Year - 2014 Loss Cost per Unit LN (Loss Cost) avg(x) avg(y) 2.5 #NUM! 2.5 #NUM! y- avg(y) x- avg(x) (x- avg(x))^2 [y - avg(y)] x [x- avg(x)] 15 2014 #NUM! #NUM! -2.5 6.25 #NUM! 16 2015 #NUM! #NUM! -1.5 2.25 #NUM! 17 2016 #NUM! 2.5 #NUM! #NUM! -0.5 0.25 #NUM! 18 2017 3 #NUM! 2.5 #NUM! #NUM! 0.5 0.25 #NUM! 19 2018 4 #NUM! 2.5 #NUM! #NUM! 1.5 2.25 #NUM! 20 2019 5 #NUM! 2.5 #NUM! #NUM! 2.5 6.25 #NUM! 21 22 Fit the line y = mx+b 23 24 b #NUM! 25 #NUM! 26 27 28