Earnings by Source

Analysis of earnings for insurance companies

Transcript

1. Earnings by Source John McGarry PhD Kevin Pledge FIA 28 June 2002 Canadian Institute of Actuaries Annual meeting
2. Agenda  Introduction to EBS  EBS and Data Warehousing  Summary of Proposed Method  Formulae Development  Sources of Earnings  Conclusion
3. Introduction to EBS
4. What is EBS?  Used to explain earnings  Reconcile assumptions  Can be based on Statutory or Management Reserves  EBS is a Management Tool
5. Explains Earnings by identifying  Impact of Sales  Variations from Assumptions  earnings implicit in the reserves  variation in rates not amounts
6. Statutory Reserve Basis  Allows impact of statutory reserves on earnings to be explained
7. Management Reserve Basis  Allows sources to aid in managing business  The impact of sales is the profit at issue  The variations can indicate  assumptions need to be changed, or  action may need to be taken (withdrawals, expenses, investments, reinsurance).
8. EBS as a Management Tool  Decision Tool  Profitability of New Business  Impact of Reinsurance  Profitability by Product Line, Demographic or Sales Office  Profit is a collaborative effort  Accessible  Understood across organization  Objectives and Goal Setting
9. Limitations of current approaches  Often analyzed at fund level, with a substantial degree of approximations.  Generally not divisible over time  Approximations may not be understood  Static – prevents analysis by product, sales office or demographic  Different approaches by line of business
10. Compounding Assumptions  Experience in earlier periods impacts perceived results in later periods  Illustrated with simple example  Mortality as expected  Withdrawals 50% of expected for 1st three quarters  Expected values in Q4 based on artificial population
11. Projection at outset vs changing 88,000 90,000 92,000 94,000 96,000 98,000 100,000 102,000 Start Q1 Q2 Q3 Q4 expected actual Understatement of Inforce
12. Actual vs. Expected Mortality 340 350 360 370 380 390 Q1 Q2 Q3 Q4 Actual Expected
13. EBS and Data Warehousing
14. What is a data warehouse? “Complete analytical infrastructure”
15. EBS and Data Warehousing  A data warehouse with policy level reserves and earnings allows:  knowledge discovery with regard to profitability and performance by product, sales office or client segment  can lead to successful management action
16. Data needed For EBS  Policy data, reserves, transactions and expected rates For Analysis of EBS  Product Structure and attributes  Sales structure and attributes  Client attributes Must be unitized to allow alternate aggregations
17. Requirements of an EBS report in a Data Warehouse  Accessible across organization  Explain components  Integrate with other reports  Flexible over time  Analysis by product, sales office, demographic etc
18. Summary of Method
19. General Method  Statutory or “management” reserve bases  Gross or net premium valuation methods  Lines of Business; Life, Disability etc.  No Approximations
20. Monthly Recognition of Sources  Impact of sales recognized in month of issue  Reserves released as at month of exit  Premiums and expenses at start of month, claims at end of month  Monthly sources accumulated using Fund return
21. Monthly Recognition of Sources  Flexible over time  yearly results are easily accumulated from quarterly results.  Simple formula  Reduces compounding and interaction  Contingency sources are based on the immediate impact of the event
22. Monthly Recognition of Sources  Gives immediate impact of Sales  New Business Strain on Statutory  Profit at Issue on Management  Not at a “variable” point in the future.  After the month of issue, policies are included in the “in-force” analysis of variations.
23. Reserves Released on Exit  Projected ending reserves  Survivors and exits  Assumed in derivation  May not equal actual ending reserves  Starting reserves may be used  These may be more easily available  Introduces known approximation
24. Unitized Earnings  Requires investment return and expenses to be unitized for policy level analysis.  Investment return as a rate,  Expenses as a per-policy unit factor
25. Unitized Earnings  Allows analysis at any level:  product, sales office, demographic.  Exp’ d amounts  from valuation system, or if not,  more accurately and easily defined
26. Report Structure  Linear Report  Grid Report
27. Linear Report Normal Profit Issue Profit Issue Margins Release of Margins Experience Variations Interest Premium Expense Mortality Withdrawal Change of Basis Total Earnings
28. Grid Report Statutory Mgmt Margin Sales Impact X X X Variations Interest X X X Premium X X X Expenses X X X Mortality X X X Withdrawal X X X Total Variations X X X Basis Changes X X X Total Earnings X X X
29. Formulae Development
30. Method  Define calculation order  Begin with actual earnings exp’n  Modify 1st var. from “act’l” to “exp’d”  Subtract modified from initial exp’n  Modify 2nd var. from “act’l” to “exp’d”  Subtract modified from prior exp’n  Continue through sources  Final earnings = zero  mgmt earnings on mgmt reserves
31. Order of Sources  Basis Change  Sales Impact  Release of Margins  Interest Variation  Cash Flow Variation  Contingency Variation
32. Sources of Earnings
33. Sales Impact  Issue Profit  Capitalized Future Profits + Cash Flows  Expected profit at issue  Should be at time of issue  Acquisition Expenses, Initial Commission  Issue Margins  Impact of setting up reserves             New Deaths New Issued New Suviviors m S E P V 1
34. Release of Margins (RoM)  Acc’d Starting – Ending Margins  (Act’l) RoM ≠ Expected Earnings  Exp’d Earnings = Exp’d RoM ≠ Act’l RoM unless A = E  “Exp’d Earnings adjusted for act’l experience on margins”  “Actual earnings before variations”  RoM by source/assumption
35. Interest Variation  Act’l interest on Cash-flows + Res. – Exp’d interest on Cash-flows + Res.         Initial Beginners m a a a m i i E P V 0
36. Cash flow Variations  – (Act’l Expenses – Exp’d Expenses) accumulated on Expected Interest  Total exp’d exp’s will change every month.  Reconcile unit expenses, not total         Initial Beginners m m a i E E 1
37. Contingency Variations  Mortality - Life Insurance  – (Actual Strain – Expected Strain)                    Initial Beginners m m Initial Deaths m V S q V S 0 , 1 0 , 1
38. Contingency Variations  Mortality - Disability Insurance  Actual Gain – Expected Gain     Initial Beginners m m Initial Deaths m V q V 0 , 1 0 , 1
39. Contingency Variations  Disablement  Actual Gain – Expected Gain  Gain = Reserve Released – Reserve Set Up           Healthy Beginners m D m H m Healthy ts Disablemen m D m H V V d V V 0 , 1 0 , 1 0 , 1 0 , 1
40. Reconciliation  Reconciliation to both actual earnings and planned earnings
41. Reconciling to Actual Earnings  Sum of Sources = Actual Earnings  No approximations necessary  Known approximations due to data availability  Magnitude can be estimated  Modeling Variation  Also acts as an error- check on the calculation  or an order-check on approximations
42. Reconciling to Planned Earnings  Planned Earnings  Earnings target set by Management usually each year  Based on expense budgets, sales and investment targets, as well as projected policy behavior.
43. Reconciling to Planned Earnings  Reconciliation  First, restate Planned Earnings on Actual Sales over the year.  The difference between Original and Restated Planned Earnings is the impact of sales variations.  Compare Restated Planned Earnings with Normal Profits (Issue Profit + Issue Margin + Release of Margins).
44. Reconciling to Planned Earnings  Issues  Planned Earnings may be carried out in aggregate  Planned Earnings may use different methods
45. Conclusion
46. Conclusion  EBS can be an effective management tool  Continuous approach  No approximations required  Performance can be monitored over the year  Meaningful explanation of results helps decision process
47. Further Information  The Analysis of Insurance Earnings  Formulae  Proofs  www.insightdecision.com
48. Presenters Kevin Pledge kpledge@insightdecision.com (905) 475 3282 x 1 John McGarry jmcgarry@insightdecision.com (905) 475 3282 x 3
49. Thank you for attending