Session 60 PD, SOA Survey Committee Update. Moderator: David N. Wylde, FSA, MAAA

Transcription

1 Session 60 PD, SOA Survey Committee Update Moderator: David N. Wylde, FSA, MAAA Presenters: Constance E. Dewar, FSA, MAAA Allen M. Klein, FSA, MAAA Scott Edward Morrow, FSA, FIA, MAAA SOA Antitrust Disclaimer SOA Presentation Disclaimer

2 2018 SOA Life & Annuity Symposium CONNIE DEWAR, FSA, FCIA 2016 Older Age Underwriting Practices Survey Report May 8, 2018

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4 Presentation Disclaimer Presentations are intended for educational purposes only and do not replace independent professional judgment. Statements of fact and opinions expressed are those of the participants individually and, unless expressly stated to the contrary, are not the opinion or position of the Society of Actuaries, its cosponsors or its committees. The Society of Actuaries does not endorse or approve, and assumes no responsibility for, the content, accuracy or completeness of the information presented. Attendees should note that the sessions are audio-recorded and may be published in various media, including print, audio and video formats without further notice. 3

5 Overview Gather feedback on underwriting guidelines, requirements, assumptions and practices utilized in the assessment older age applicants Survey sent to chief actuaries, chief underwriters of direct life insurers in the United States and Canada 29 responses Similar surveys were conducted in 2001, 2007,

6 Categories Products and Programs Underwriting Resources General, Medical and Non-Medical Testing Financial Underwriting Preferred Risk Class Underwriting Reinsurance Assumption Setting Regulatory and Compliance 5

7 Product and Programs Definition of older age Programs available at older ages 6

8 Underwriting Resources Resources used in underwriting assessment at older ages 7

9 General, Medical and Non-Medical Testing Criteria used Changing technology 8

10 Financial Underwriting Financial underwriting at older ages Differences in requirements between older and younger ages Verification tools 9

11 Preferred Risk Class Underwriting Preferred at older ages Number of preferred classes Minimum or maximum amounts 10

12 Reinsurance Use of reinsurance at older ages Reinsurance resources Automatic versus facultative 11

13 Assumption Setting Sources of information Mortality table used Mortality improvement Select period 12

14 Regulatory and Compliance Information requested or testing requirements 13

15 Thank You 14

16

17 Predictive Analytics and Accelerated Underwriting Survey Results Al Klein May 8, 2018 SOA Life and Annuity Symposium Session 60

18 Agenda Background Results Predictive analytics Accelerated Underwriting Follow-up Survey Results Concluding thoughts 2

19 Background Original survey was conducted in June/July of 2016 Initial response was low so we contacted companies we knew had implemented programs and asked them to participate Response to this was good and we believe many of the companies that had a program when we conducted the survey participated Responses were received from both direct companies and reinsurers who helped implement programs 3

20 Background (cont d) Goal was to learn about company practices on three timely issues: Predictive analytics Accelerated underwriting The use of tools such as a predictive model to waive requirements such as fluids and a paramedical exam on a fully underwritten product for qualifying applicants without charging a higher premium Enhanced underwriting Insufficient response The use of supplemental information (e.g., criminal history, credit rating, prescription histories) and a predictive model to refine the underwriting process for a simplified issue product Avoided questions on proprietary information to maximize participation 4

21 Background (cont d) Started both sections of the survey with a large question to establish what was: Implemented Being worked on Not worked on or considered Focus of all subsequent questions was on the programs implemented by the respondents 5

22 Background (cont d) Because of the continued growth of these programs, we conducted a follow-up survey in July/August 2017 to see what had changed among these companies Results of the follow-up survey will also be discussed 6

23 Members of Subcommittee Al Klein, FSA, MAAA, Chair Roland Fawthrop, FSA, MAAA Gord Gibbins, FSA, FCIA Randy Makin, FSA Did not participate in Follow Up Survey Bill Tilford, FALU, CLU, FLMI, Fellow (ALUCA) David Wylde, FSA, MAAA, CLU, ChFC 7

24 Caveats Original survey did not include all of the companies with these programs However, I believe the information is still good and useful for both those with programs and those considering new programs I will be covering results at high level so please refer to survey reports for more details 8

25 Predictive Analytics Survey Results

26 Predictive Analytics Implementation Choices Implemented Plan to implement within 1 year Working on and Plan to implement within 1-2 years Plan to implement longer than 2 years Not sure if will implement Considering it Not currently working on but Considered it and/or worked on it but decided not to do it Not considering it

27 Quick Summary of 2016 PA Results 34 companies responded to the survey 26 of these companies implemented one or more PA programs 117 PA programs were implemented Two companies implemented the most PA programs (12 each), others implemented 1-10 programs 11

28 Predictive Analytics Marketing Marketing Programs Program Implemented Working on Not working on but considering Not working on and not considering Total Customer more likely to buy Cross selling Target market determination Up selling Customer less likely lapse Customer health profile Agent selection/hiring

29 Predictive Analytics Underwriting Underwriting Programs Program Implemented Working on Not working on but considering Not working on and not considering Total U/w risk class Deciding on u/w requirements Stretch criteria for selecting u/w class Business decisions Table shave

30 Predictive Analytics Post-Issue Mgmt Post-Issue Management Programs Program Implemented Working on Not working on but considering Not working on and not considering Total In force mgmt. pre-lapse Targeted conversion For term, post-level premium term conservation mgmt Agent monitoring/mgmt In force mgmt. post-lapse In force mgmt. Other customer interaction

31 Other types of PA programs that have been implemented Marketing (4) Attract new reinsurance business, Prospecting models, Identifying prospects, UL vs. Term Prospecting Underwriting (2) implemented another type of underwriting PA program, Working on something Post-issue Management (8) Implemented another, working on other, or considering another type of post-issue management program (6), Ongoing claim study, Considering for business considerations 15

32 Sources/types of data used to develop PA Models Vendor (17) Financial (16) Lifestyle (13) Application (12) Internal experience (12) 16

33 Individuals/Areas involved in developing PA models Marketing Internal Actuary, Marketing, Data scientist/statistician Underwriting Internal Actuary, Internal Underwriter, Marketing Post-issue Management Marketing, Data scientist/statistician, Internal Actuary 17

34 Other Interesting findings Most PA programs were implemented within the last few years, but some PA marketing programs were implemented earlier Most PA programs were implemented as a pilot and many of the underwriting and post-issue management programs remain as a pilot Most PA programs impacted only 0-10% of the overall business and none impacted more than 75% 18

35 Top Obstacles in Developing PA Models Data Sources (20) Agent Buy-in (13) Internal User Buy-in (13) Implement -ation (12) Designing/ Building the Model (12) 19

36 Predictive Analytics 2017 Follow Up Survey Results

37 2017 Follow Up Survey Asked about changes to the programs Provided original responses to better enable respondents to answer the follow up survey 20 of 34 companies responded 21

38 PA Update Marketing Marketing Programs Program Implemented 2016 Implemented 2016 (20) Changes Updated New Discontinued Customer more likely to buy Cross selling Target market determination Up selling Customer less likely lapse Customer health profile Agent selection/hiring

39 PA Update Underwriting Underwriting Programs Program Implemented 2016 Implemented 2016 (20) Changes Updated New Discontinued U/w risk class Deciding on u/w requirements Stretch criteria for selecting u/w class Business decisions Table shave

40 PA Update Post-Issue Management Marketing Programs Program Implemented 2016 Implemented 2016 (20) Changes Updated New Discontinued In force mgmt. pre-lapse Targeted conversion For term, post-level premium term conservation mgmt Agent monitoring/mgmt In force mgmt. post-lapse In force mgmt. Other customer interaction

41 PA Update What happened to programs within one year of implementation in 2016? Type of Program Number of programs within 1-year of implementation in 2016 Implemented Status as of 2017 Still within 1 year Decided not to proceed Marketing Underwriting Post-issue Management

42 Accelerated Underwriting Survey Results

43 Accelerated Underwriting Accelerated Underwriting (AU) Programs Implemented Working on Not working on but considering Not working on and not considering Total

44 Accelerated Underwriting Follow up Survey Results Accelerated Underwriting (AU) Programs Implemented 2016 Implemented 2016 (20) Changes Updated New Discontinued

45 Accelerated Underwriting Program Limits Maximum issue age ranged from 35 to 85 and most common was 60 Maximum face amounts ranged from $100K to $3M, with most common $1M 29

46 Accelerated Underwriting Decision-making

47 Data sources used for AU decision-making MIB Checking Service (7) MVR (7) Rx History (7) Application (6) Lifestyle & MIB IAI (5 each) 31

48 Most important data sources for Accelerated Underwriting decision-making Rx History (6) Application (6) MVR (5) MIB Checking Service (4) 32

49 Data sources used for Risk Class decision-making MVR (7) Rx History (7) Application (6) MIB Checking Service (6) Financial (5) 33

50 Most important data sources used for Risk Class decision-making Rx History (7) MVR (6) Application (5) MIB Checking Service (5) Personal History Report (4) 34

51 Individuals/Areas involved in developing Accelerated Underwriting programs 1 Internal Underwriter (all 8) 2 Internal Actuary (7) 3 Internal Marketing (4) 35

52 Other Interesting findings 5 of 9 accelerated underwriting programs were implemented as a pilot program and one remains as a pilot program 4 of 9 companies randomly check some applicants to test their assumptions and/or model 4 of 8 use predictive analytics in the decision-making process for AU programs 36

53 Other Interesting findings (cont d) 7 of 8 indicated time to issue decreased 6 of 8 indicated they were not sure if mortality changed since implementation of the AU program 7 of 8 plan to expand their AU programs 4 of 8 indicated that their reinsurers participated in the AU program 37

54 Biggest challenges encountered in developing AU programs 1 Data sources (4) 2 Justifying cost/benefit analysis (4) 3 Implementation (3) 38

55 Concluding thoughts Both PA and AU programs are growing at a rapid pace and I expect that to continue over the next several years. I also expect to see new methodologies and hybrid approaches emerge over this same time period. I believe this is a great time PD actuaries to get involved and help develop innovative solutions to these emerging programs. 39

56 Links to the surveys Original survey: Follow up survey: ience-studies/2018/predictiveanalytics-accelerated-follow-up/ 40

57 Thank you Al Klein (312) ,

58 Bio Al Klein Al is a principal and consulting actuary with Milliman s Buffalo Grove / Chicago office. He joined the firm in Al s primary responsibilities include industry experience studies and helping clients with mortality, longevity, and underwriting related issues. Al s expertise on mortality and underwriting includes traditional products, simplified issue, final expense, older age, and preferred. Prior to joining Milliman, Al worked for a large stock life insurance company where he was responsible for experience studies across all lines of business. He has also worked for other life insurance companies, a reinsurer and consultant, where he has been responsible for strategic planning, product development and traditional reinsurance. Al is a frequent speaker and currently involved with a number of industry activities, including: Co-Vice Chair for the Mortality Working Group (MWG) of the International Actuarial Association MWG Chair of projects on: Underwriting Around the World, Future Drivers of Mortality, Older Age Mortality Member of MWG project on e-cigarettes SOA Longevity Advisory Group Chair of SOA Underwriting Issues and Innovation Seminar Planning Committee SOA Mortality and Underwriting Survey Committee, Chair of survey on Predictive Analytics and Accelerated and Enhanced Underwriting SOA Project Oversight Groups: US Population Mortality, 1900 Birth Year Cohort, Human Mortality Database Project Accelerated Underwriting DELPHI study 2015 SOA Valuation Basic Table Development Team Longer Life Foundation Advisory Board Al was named a SOA Outstanding Volunteer in 2017 Al received a Bachelor of Science degree in Actuarial Science and Finance from the U. of Illinois, Urbana Contact information: (312) , al.klein@milliman.com 42

59 Early Duration Claims Scott E. Morrow, FSA, MAAA, FIA Vice President, Lewis & Ellis May 8, 2018

60 Scott Morrow, FSA, Chair Mary Bahna-Nolan, FSA Suzanne Chapa, FSA Mark Dion, FALU Shawn James, AALU Members of the Survey Subcommittee SOA Staff: Korrel Rosenberg 2

61 About the Early Duration Claims Survey Specifics of 2017 EDC Survey The last EDC Survey Conducted by the SOA Survey Subcommittee was in December Current Survey conducted from October 2016 February Twelve companies responded to the survey. Survey Focused on: Causes of Death Studies within the contestable and early duration periods Underwriting Processes Post Issue and Post Claim Underwriting performed 3

62 Section 1 Scope and Data This Section focused on claims reported and a breakdown of those claims within the contestable period It also focused on the respondents claims committee (if available) and the types of cases that would potentially be referred to the claims committee 4

63 Breakdown of Claims Within the Contestable Period % of Claims Paid without Contest Policy Count Aggregate Face Amount %-50% %-75% %-90% %-100% Total # of Respondents % of Claims Contested Policy Count Aggregate Face Amount %-10% %-25% %-50% %-100% Total # of Respondents

64 Breakdown of Amount Ultimately Paid for those contested 7 of the 12 respondents paid out the full face amount over 50% of the time 4 of the 12 respondents paid out the minimum required by the contract over 50% of the time 6

65 Factors Affecting Claims Investigation Practices Factors Affecting Claims Investigation Practices # of Responses Cause of Death 11 Duration from Underwriting 6 Geographic Location at Death (local country or foreign risk) 6 Face Amount 1 Policy Status (e.g., Limited Pay, Paid Up) 1 Reinsured status 1 Underwriting Method (Fully, SI) 1 Age at Death 0 Age at Issue 0 Distribution Channel 0 Producer/Producer group 0 Other* 1 Total # of Respondents 12 7

66 Face Limitation and Claims Committee All 12 respondents stated their company had no Maximum Face Amount below which their company would not contest 7 of the 12 respondents stated their company did not have a claims committee Disciplines # of Responses Regularly As Required Total Claims Legal Actuarial Underwriting Compliance Medical Administration/Policy Owner Service CFO Sales/Marketing CEO COO CRO Other 1* 1** 2 Total # of Respondents

67 Claim Study Frequency and Claim Study Dimensions Claim Study Frequency # of Responses At Least Annually 6 Every 2 Years 0 At Least Once Every 5 Years 0 As Needed 2 Do Not Study 4 Total # of Respondents 12 Claims Experience Study Dimensions Study by Duration Do Not Study by Duration Duration from Underwriting 6 5 Age at Issue 5 5 Age at Death 4 4 Cause of Death 4 6 Face Amount 4 5 Product 4 5 Risk Class 4 5 Gender 2 5 Distribution Channel 1 5 Market Segment 1 5 Producer/Producer group 1 6 Underwriting Method 1 4 Underwriter 0 5 Other* 0 3 Total # of Respondents 11 9

68 Section 2 Causes of Death This Section focused on the various causes of death in the contestable and early duration periods and the experience studies performed during those periods 10

69 Cause of Death Study 4 of the 12 respondents performed studies for cause of death focusing on either the contestable or early duration period Cardiovascular and Cancer combined resulted in over 39% of all contestable claims, over 54% of all early duration claims and over 38% of all claims. None of the other causes of death was over 10% for any of the respondents for the contestable, early duration and all claims periods. Causes of Death Contestable Early Duration All Claims Cancer Cardiovascular Other Accidents Motor Vehicle Accidents Suicide Respiratory Stroke Alzheimer s Other 0 0 1* Total # of Respondents

70 Departments Reviewing the Studies 2 respondents performed studies on an annual basis, while the other 2 performed the studies more frequently Department Reviewing the Studies: Department # of Responses Actuarial 4 Board of Directors 0 Claims Committee 0 Medical Directors 2 Senior Management (CEO, CFO, CRO) 0 Underwriting 2 Total # of Respondents 4 12

71 Section 3 Underwriting Practices This Section focused on the aspects of the respondents underwriting processes that may identify potential early death claims resulting from accidental death, suicide or homicide. 13

72 Application Questions Topics to Identify Accidental, # of Responses Suicide or Homicide Risk Alcohol Abuse 11 Aviation 11 Avocations 11 Depression 11 Driving 11 Foreign Travel 11 Illicit Drug Use 11 Occupation 11 Criminal Activity 10 Alcohol Use 9 Dementia/Alzheimer s 8 Military 8 Bankruptcy 7 Total # of Respondents 11 Future Plans # of Responses Foreign Travel 11 Aviation 10 Avocations 9 Total # of Respondents 11 14

73 Tests and Data used or Under Consideration for Use in Underwriting Process Examination # of Responses Blood Pressure 10 BMI/Build 10 EKG 10 Pulse 10 ADL/IADL 5 Cognitive Tests 4 Functional Tests 4 Treadmill EKG 4 Total # of Respondents 10 Urine # of Responses Cocaine 10 Glucose 10 Protein 9 Microalbumin 8 Other Drugs of Abuse 3 Total # of Respondents 10 Blood # of Responses Albumin 10 HbA1c 10 HDL 10 LFTs 10 PSA 10 Triglycerides 9 Globulin 7 NT-proBNP 7 egfr 5 CDT 4 Blood Alcohol 1 Total # of Respondents 10 15

74 Tests and Data used or Under Consideration for Use in Underwriting Process Application Questions # of Responses Aviation 10 Avocation or sports 10 Criminal activity 10 Driving record 10 Foreign residence and/or travel 10 Doctors seen/recent hospitalization 9 Family history heart disease 9 Income or net worth 9 Family history cancer 8 Medications 8 Tests or procedures not yet completed 8 Actively at work 7 Bankruptcy records 6 Planned doctors visits 5 Total # of Respondents 10 Third Party Information # of Responses MIB 10 Prescription histories 9 MVR 8 Income or net worth 6 Bankruptcy records 5 Criminal activity 5 Identity verification 5 Credit history 4 Lab score or similar 3 Tax records 2 Other external data sources 1 Total # of Respondents 10 16

75 Method of Collection Form # of Responses Agent collected 10 Paramed 7 Teleinterview 7 Online 1 Total # of Respondents 10 17

76 Section 4 Post Issue Underwriting (Prior to Claim) This section of the survey looks at underwriting practices after the initial underwriting and policy issue before a claim has occurred. The purpose of post-issue underwriting may include quality control, assessment of routine underwriting practices, fraud prevention or identification of cases of material misrepresentation. 18

77 Routine Post-Issue Underwriting Prior to Claim Program to perform routine postissue # of Responses underwriting Yes 6 No 5 Total # of Respondents 11 Routine post issue underwriting # of Responses time-frame 1-3 months post issue months post issue months post issue months post issue months post issue 1 Total # of Respondents 6 Routine post issue underwriting type # of Responses MIB Plan F follow-up 4 Order prescription history profile 1 Other third party data search 1 Rerun MIB checking service and/or Insurance Activity Index (IAI) 1 Order APS 0 Other - Audit of cases to determine if guidelines followed 1 Total # of Respondents 6 19

78 Policies Referred to Underwriting for Review Estimation of the percentage of contestable period # of Responses policies referred to underwriting or the medical department 0% % % % 0 100% 3 Total # of Respondents 10 Number of policies rescinded prior to claim during 2014 and 2015 # of Responses Total # of Respondents 10 20

79 Section 5 Post Claim Underwriting This section of the survey looks at underwriting practices after the initial underwriting and policy issue and after a claim has occurred. The purpose of post claim underwriting may include quality control, assessment of routine underwriting practices, fraud prevention or identification of cases of material misrepresentation. 21

80 Practices performed on contestable claims Re-run MIB checking service and/or IAI on contestable claims # of Responses Yes 4 No 7 Total # of Respondents 11 Run a pharmacy record check on contestable claims # of Responses Yes 9 No 2 Total # of Respondents 11 22

81 % of Claims referred to Various Departments Percentage of contestable claims obtain attending physician statements # of Responses % % % % 5 100% 4 Total # of Respondents 11 Percentage of contestable claims referred to underwriting or medical department # of Responses % % % % 2 100% 6 Total # of Respondents 11 Percentage of contestable claims # of Responses referred to legal department % % % % 2 100% 0 Total # of Respondents 11 23

82 Resources Utilized in Contestable Claims and Cases Suspected of Fraud Dedicated resources, an individual or a unit, # of Responses focused only on contestable claims Yes 4 No 7 Total # of Respondents 11 Company resources involved in cases # of Responses suspected of fraud Underwriting 11 Legal 10 Claims Committee 6 CSI Unit 5 Sales/Marketing 5 Law Enforcement 4 Executive Committee 3 Actuarial 2 Other 4 Total # of Respondents 11 24

83 Section 6 Miscellaneous Questions This section of the survey contained a further breakdown of contestable claims by age, gender and face 25

84 Contestable Claims by Demographic Mix 26

85 Contestable Claims by Demographic Mix 27

86 Thank You Scott E. Morrow, FSA, MAAA, FIA