1. Slide 1 Challenges of Conducting a Mortality Study in Africa – The Kenyan Experience AFRICAN INSURANCE ORGANISATION 2010 LIFE SEMINAR Lagos, Nigeria 11 November 2010 Presented by: James Olubayi BSc, FIA Alton Rugetho BSc

2. Slide 2 Agenda  Introduction of Study  Review of Data Collection Exercise  Methodology  Graduation of Crude Rates  Individual Life  Group Life  Annuitants  Morbidity (Sickness) Rates  Recommendations

3. Slide 3 Part A Introduction of the Mortality Study

4. Slide 4 Introduction and Background  Project entailed an investigation of mortality and morbidity experience of insured lives in Kenya  Project undertaken in four phases: July 2005 - July 2007:  Phase I - Mortality experience of Individual Assured lives  Phase II - Mortality experience of Group Assured lives  Phase III - Mortality experience of Annuitants  Phase IV - Morbidity (sickness) rates  Completed investigations for all 4 phases and released final reports  Comments and recommendations from peer review actuaries (Quindiem Consulting Actuaries) incorporated in all our final reports  Period of investigation 2001 to 2003 inclusive

5. Slide 5 Part B Review of Data Collection Exercise

6. Slide 6 Review of Data Collection Exercise  Most onerous task of the mortality study and morbidity study  Data collection exercise commenced in July 2005  Data requested:  18 life companies: individual life assured data and group life data  7 companies: annuitants data  10 companies: morbidity data  Each company provided with a copy of the data required and format for the mortality study  Important that all companies participate

7. Slide 7 Review of Data Collection Exercise  Exposure Data Requested  Data requested for all in-force policies as at 31 December 2000, 2001, 2002, 2003 and 2004  Claims Data Requested  Data requested for all death claims notified in the years 2001, 2002, 2003 and 2004  ‘Principle of Correspondence’ critical

8. Slide 8 Review of Data Collection Exercise  Significant delays in the data collection exercise  Main reasons for delays in data collection exercise  Necessary personnel not assigned by insurance companies for the specific purpose of the mortality investigation  Data not readily available or accessible from the different insurance companies  Some companies still hold data in manual registers  Inadequate/ incomplete capture of data records  Inconsistencies in the data provided  Data submitted in tranches  Detailed data checks and validation carried out

9. Slide 9 Review of Data Collection Exercise  A number of significant inconsistencies in data provided by some companies e.g.:  Inconsistent dates of birth from one year to the next  Claims not traceable to exposure data  Duplicate lives  Missing gender  Missing dates of birth and policy issue dates  Inconsistent policy numbers from year to year  Missing policyholder names  Inconsistent data formats from year to year  Errors in data, particularly dates  Matured policies and death claims included in part of the in-force data  Inconsistencies in year on year reconciliation

10. Slide 10 Review of Data Collection Exercise  Concerns on quality of data initially provided  Key objective: utilize as much of the data as possible  Data clean ups undertaken, sought clarifications to resolve queries  Data was partially discarded due to inconsistencies  Approximations and estimations necessary - Not all data required was captured e.g. Date of Birth, Gender etc  Considerable delays experienced  But important to get this step right!  Important lessons for next phases of project

11. Slide 11 Part C Methodology

12. Slide 12 Methodology Crude Mortality Rate at Age x = Number of Deaths aged x Total initial exposed to risk at age x Key – Principle of Correspondence: A life will only be included as part of the exposed to risk at age x if and only if were the life to die immediately, then it would be counted as having died aged x Necessary Approximations:  Age nearest birthday used as age label  Census approach used to determine crude rates

13. Slide 13 Period of Investigation  Period selected is 2001-2003  Balance between reasonable volumes and exposure period  Ensuring data as recent as possible and homogeneity of experience  Other factors  Computerization of records by insurers recent and/or not complete in some cases  Claims experience for 2004 may not be fully developed or complete and hence exclusion of 2004

14. Slide 14 Part D Graduation of Crude Rates

15. Slide 15 Graduation of Crude Rates  Graduation of crude rates necessary in order to  Produce set of smoothly progressing rates (“smoothness”)  Reduce the effect of randomly observed deaths (“goodness of fit”)  However need balance to avoid over or under graduation  Graduation Methodology  Used cubic and cubic spline curve to fit the rates  Graphical method used to fit rates for higher ages  Different statistical tests carried out to assess goodness of fit and smoothness of graduated rates  Compare graduated rates with standard published mortality and morbidity tables commonly in use

16. Slide 16 Phase I: Individual Lives

17. Slide 17 MALES Age Band Exposure (years) No. of Deaths NumberPercentage 16-258,9543.36%19 26-3566,41324.87%115 36-45116,73443.71%407 46-5563,69323.85%304 56-658,7173.26%62 66-751,4310.54%17 76-857040.26%6 86-953360.13%2 96-105650.02%1 Grand Total267,047100%933 Individual Lives Data

18. Slide 18 Individual Lives Data FEMALES Age Band Exposure (years) No. of Deaths NumberPercentage 16-257,3714.89%8 26-3550,14033.26%48 36-4565,86143.69%133 46-5524,83616.48%79 56-652,3511.56%10 66-751610.11%2 76-85170.01%- 86-955-- 96-105--- Grand Total150,742100%280

19. Slide 19 TOTAL Age Band Exposure (years) No. of Deaths NumberPercentage 16-2530,8334.83%37 26-35174,13327.29%488 36-45290,48045.52%1,494 46-55123,56919.36%828 56-6515,4332.42%126 66-752,4750.39%27 76-858160.13%6 86-953570.06%2 96-105650.01%1 Grand Total638,161100%3,009 Individual Lives Data

20. Slide 20 Crude Rates - Males Generally increasing trend of mortality rates

21. Slide 21 Set of Graduated Rates

22. Slide 22 Set of Graduated Rates

23. Slide 23 Set of Graduated Rates

24. Slide 24 Set of Graduated Rates

25. Slide 25 Comparison of Graduated Rates

26. Slide 26 Comparison of Graduated Rates

27. Slide 27 Impact of AIDS  Apparent bulge on the graduated rates at around ages 25-50  Bulge could be as a result of AIDS related deaths  Analysed rates in order to calculate an estimate of AIDS mortality  Used the SA 85-90 (light) table as a base curve to represent non-AIDS mortality  Estimation was done using statistical techniques including curve estimation

28. Slide 28 Impact of AIDS Age Base Curve (Non - AIDS Mortality) AIDS Mortality EstimateTotal Mortality 260.85000.7461.5956 271.05000.4761.5261 281.20000.2801.4803 291.29000.1701.4603 301.31000.1581.4684 311.35000.1571.5066 321.43000.1471.5772 331.54000.1421.6823 341.67000.1531.8229 351.80000.1951.9952 361.95000.2442.1945 372.08000.3362.4158 382.23000.4242.6542

29. Slide 29 Impact of AIDS Age Base Curve (Non - AIDS Mortality) AIDS MORTALITY ESTIMATETotal Mortality 392.36000.5452.9049 402.49000.6733.1631 412.63000.7943.4237 422.71000.9723.6821 432.79001.1433.9332 442.86001.3124.1723 452.92001.4744.3944 462.99001.6054.5946 473.10001.6684.7682 483.20001.7104.9102 493.34001.6765.0157 503.45001.6305.0800

30. Slide 30 Female Mortality Rates Age (years) Female mortality as a proportion of male mortality 16-7070% 70-90(age/100)% 90+90%  Female mortality rates expected to be lower than Males’  Hence important to provide proportions to be used to obtain female rates from male rates  To do this we calculated age related proportions from the crude rates  The following were the derived proportions:

31. Slide 31 Phase II: Group Life

32. Slide 32 Summary of Data MALES Age Band Exposure (Years) No of Deaths NumberPercentage 20-241,5260.68%3 25-2915,6386.94%39 30-3437,18016.49%148 35-3942,58518.89%223 40-4455,54624.64%327 45-4940,80318.10%214 50-5532,12314.25%141 Grand Total225,401100%1,095

33. Slide 33 Summary of Data FEMALES Age Band Exposure (years) No. of Deaths NumberPercentage 20-241,0981.63%1 25-298,54812.71%15 30-3414,60821.72%62 35-3913,56020.16%60 40-4414,83622.06%80 45-4910,14215.08%22 50-554,4716.65%20 Grand Total67,263100%260

34. Slide 34 Male Crude Rates General increasing trend up to age 45 with dip thereafter

35. Slide 35 Set of Graduated Rates

36. Slide 36 Set of Graduated Rates Per 1,000

37. Slide 37 Impact of AIDS  Apparent bulge on the graduated rates at around ages 25- 50  Bulge could be as a result of AIDS related deaths  Analysed rates in order to calculate an estimate of AIDS mortality  Used the SA 85-90 (light) table as a base curve to represent non-AIDS mortality  Estimation was done using statistical techniques including curve estimation

38. Slide 38 Impact of AIDS AgeNon-AIDS MortalityAIDS MortalityTotal Mortality 25 2.077 0.079 2.156 26 2.062 0.367 2.429 27 2.043 0.662 2.704 28 2.019 0.964 2.983 29 1.994 1.271 3.265 30 1.967 1.581 3.547 31 1.940 1.888 3.827 32 1.913 2.189 4.102 33 1.889 2.479 4.368 34 1.868 2.754 4.622 35 1.851 3.011 4.861 36 1.839 3.244 5.083 37 1.834 3.449 5.283

39. Slide 39 Impact of AIDS AgeNon-AIDS MortalityAIDS MortalityTotal Mortality 38 1.837 3.623 5.460 39 1.848 3.761 5.609 40 1.869 3.858 5.728 41 1.902 3.912 5.813 42 1.946 3.916 5.862 43 2.004 3.868 5.872 44 2.076 3.763 5.839 45 2.163 3.599 5.762 46 2.267 3.377 5.644 47 2.389 3.104 5.493 48 2.530 2.783 5.312 49 2.690 2.419 5.109 50 2.872 2.017 4.889

40. Slide 40 Comparison of Graduated Rates

41. Slide 41 Comparison of Graduated Rates

42. Slide 42 Comparison of Graduated Rates

43. Slide 43 Female Mortality Rates Age (years) Female Mortality as a proportion of male mortality 20-5580% 55+(age/100)%  Female mortality rates expected to be lower than Males’  Hence important to provide proportions to be used to obtain female rates from male rates  To do this we calculated age related proportions from the crude rates  The following were the derived proportions:

44. Slide 44 Phase III: Annuitants

45. Slide 45 Summary of Data MALES Age Band Exposure (Years) No of Deaths NumberPercentage 55-59296.518.1%0 60-64349.021.3%4 65-69418.025.5%6 70-74290.017.7%9 75-79148.59.0%1 80-84100.06.1%2 85-8935.52.2%0 90-944.50.3%1 95-99--- Grand Total1,642100%23

46. Slide 46 Summary of Data FEMALES Age Band Exposure (Years) No of Deaths NumberPercentage 55-5961.026.9%- 60-6446.520.5%2 65-6930.513.4%- 70-7425.011.0%- 75-7918.07.9%- 80-847.53.3%- 85-8916.57.3%- 90-9414.06.2%- 95-992.00.9%- 100-1042.00.9%- 105-1104.01.8%- Grand Total227100%2

47. Slide 47 Male Crude Rates

48. Slide 48 Set of Graduated Rates

49. Slide 49 Set of Graduated Rates Per 1,000 AgeGraduated Rates 553.660 564.632 575.432 586.097 596.668 607.182 617.678 628.195 638.771 649.444 6510.255 6611.240 6712.438 6813.889 6915.631 7017.702 7120.140 7222.986 7326.276 AgeGraduated Rates 7430.050 7534.346 7639.203 7744.660 7850.754 7957.526 8065.012 8173.252 8282.284 8392.148 84102.881 85114.522 86127.110 87140.683 88155.280 89170.939 90187.700 91205.600 AgeGraduated Rates 92224.678 93244.973 94266.524 95289.368 96313.546 97339.094 98366.052 99394.458 100424.352 101455.770 102488.753 103523.339 104559.566 105597.472 106637.098 107678.480 108721.658 109766.670

50. Slide 50 Comparison of Graduated Rates

51. Slide 51 Female Mortality Rates Age (years)Female Mortality as a proportion of male mortality 55-10080% 100+100%  Females data provided was scanty  Female mortality rates expected to be lower than Males  Hence important to provide proportions to be used to obtain female rates from male rates  To do this we calculated age related proportions from the crude rates  The following were the derived proportions:

52. Slide 52 Phase IV: Morbidity Study

53. Slide 53 Review of Data Collection  Claims data received did not have an identifier for reason/type of sickness – although we requested  Thus difficult to estimate impact of HIV AIDS  There is need in future to record these as is the only way the impact of HIV AIDS can be studied  Comprehensive data checks and validation carried out  Most data was not provided in the prescribed format hence considerable efforts spent on organising data  There were some gaps in the data provided  Data provided not separable between Group and Individual business  Only 2 companies provide data with distinguishers for Inpatient and Outpatient

54. Slide 54 Review of Data Collection  Traditionally sickness rates are presented in two forms  Rates dependent on period of sickness  Claim inception rates i.e. the likelihood of a claim occurring within a certain exposure period  Data provided only allowed for the claim inception rates to be calculated but not rates dependent on sickness duration

55. Slide 55 Summary of In-Patient Data MALES Age Band Exposure (Years) No of Claims NumberPercentage 20-242,48413.6%404 25-292,05911.3%379 30-343,10317.0%872 35-393,14417.3%1,042 40-442,69414.8%963 45-492,07111.4%734 50-541,4237.8%564 55-598164.5%336 60-643371.8%153 65-70780.4%61 70-74130.1%42 Grand Total18,222100%5,550

56. Slide 56 Summary of In-Patient Data FEMALES Age Band Exposure (Years) No of Claims NumberPercentage 20-242,66816.4%472 25-292,87417.7%425 30-343,27720.2%662 35-392,58215.9%608 40-442,17213.4%397 45-491,3888.5%327 50-548275.1%125 55-593282.0%59 60-641200.7%21 65-70150.1%6 70-74--- Grand Total16,251100%3,102

57. Slide 57 Summary of In-Patient Data Description Exposed To Risk (Years) Number of Claims Average ‘Crude’ Inception Rate Males Inpatient18,2225,550304.577 per mille Females Inpatient16,2513,102190.881 per mille  Average crude rates imply that:  An insured male had a 30.5% chance of falling sick and becoming hospitalized  An insured female had a 19.1% chance of falling sick and becoming hospitalized

58. Slide 58 Summary of Out-Patient Data MALES Age Band Exposure (Years) No of Claims NumberPercentage 20-241,5948.4%1,074 25-291,2826.7%1,838 30-343,14816.5%4,657 35-394,16921.9%6,355 40-443,33117.5%4,964 45-492,58413.6%3,682 50-541,7649.3%2,628 55-599184.8%1,334 60-641840.9%234 65-70590.3%58 70-74130.1%26 Grand Total19,046100%26,850

59. Slide 59 Summary of Out-Patient Data FEMALES Age Band Exposure (Years) No of Claims NumberPercentage 20-241,50813.6%1,003 25-291,83911.3%1,755 30-342,78717.0%3,140 35-392,44117.3%3,066 40-442,06214.8%2,346 45-491,45511.4%1,969 50-547247.8%853 55-591614.5%218 60-64331.8%30 65-7050.4%- 70-74-0.1%- Grand Total13,015100%14,380

60. Slide 60 Summary of Out-Patient Data Description Exposed To Risk (Years) Number of Claims Average ‘Crude’ Inception Rate Males outpatient 19,40626,8501,409.745 per mille Females outpatient 13,01514,3801,104.879 per mille  Average crude rates imply that  An insured male is likely to claim 1.4 times per year  An insured female is likely to claim 1.1 times per year

61. Slide 61 Part E Recommendations

62. Slide 62 Recommendations  Mortality studies should be carried out every 5 years to keep up with demographic changes  Individual lives, group life and annuity rates to be adopted for pricing of insurance products and actuarial valuations of long- term business  Adjustments for the effects of HIV AIDS may be necessary  Individual life rates are “ultimate rates”. However, “select rates’ dependent on policy duration may be derived

63. Slide 63 Recommendations  Morbidity rates could be used as a general guide for pricing Inpatient and Outpatient medical insurance business although calculated crude inception rates have no practical use  Morbidity studies need to be conducted periodically to discern any trends in the rates of sickness  Future morbidity studies need to differentiate between group and individual rates  This possible only if companies keep proper records for each class of business

64. Slide 64 Recommendations  Recommend that companies underwriting medical business to record following data for each policy  Type of policy (inpatient/outpatient)  Whether cover is group or individual)  Period (duration) of sickness for the claimant  Reason/type of sickness e.g. Malaria, Cancer, HIV AIDS etc  There’s need for the maintenance of a central database to reduce delays in data collection for such studies  Further studies be carried out to asses the impact of AIDS on mortality  Insurance companies need to focus greatly on monitoring the standard and quality of the data kept

65. Slide 65 Summary of Key Challenges  Data – Data - Data  Quality  Completes  Computerisation  Manpower / skills  Competition – hence reluctance to provide information  Confidentiality of information  Cost of undertaking the study  Inadequate Actuarial Skills  Support from industry associations / stakeholders  Support from Regulator

66. Slide 66 Thank you for your time