Session 162 PD - SOA Survey Committee Update. Moderator: David N. Wylde, FSA, MAAA

Session 162 PD - SOA Survey Committee Update Moderator: David N. Wylde, FSA, MAAA Presenters: Mary Ann Broesch, FSA, MAAA Joel Jones Allen M. Klein, FSA, MAAA Scott Edward Morrow, FSA, FIA, MAAA SOA Antitrust Compliance Guidelines SOA Presentation Disclaimer

2017 SOA Annual Meeting & Exhibit MARY BROESCH, FSA, MAAA Session 162, SOA Survey Committee Update October 18, 2017

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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

Introduction

Improving the New Business Process Continuous desire is for faster, cheaper, better Survey conducted in fall of 2016 Examines changes life insurers recently made, or are thinking of making, to improve the new business process Identifies trends from 2010 to 2016, using prior survey 24 life insurance companies participated Addressed to chief actuaries and chief underwriters Report to be published in fall of 2017 5

Survey Sections The Application Underwriting Requirements Systems and Resources Impact of Past Changes Policy Delivery 6

Demographic Information 19 US and 5 Canadian direct writers of individual fully underwritten life products Participating insurers included: stock (38%), fraternals (21%), mutuals (21%) and other (21%) Responding companies wrote business through more than a dozen distribution channels 62% wrote business through more than one channel 7

The Application

Paper, Electronic and Trial Applications 79% received both paper and electronic applications Within the next 12-24 months, respondents plan to Reduce use of paper and disconnected e-app applications Increase use of web-based e-app applications Career agents most likely to use e-app applications 33% received over 80% of their apps electronically 48% purchased and customized their e-app, while 40% used a home grown e-app About half of respondents accepted trial applications 9

Changes to Underwriting Requirements

Underwriting Requirements Non-Medical NT pro-bnp MVR Paramedical Exam Hemoglobin IR Abbreviated Paramed Lab Score eir Medical Exam Urine HIV Credit Report/Scoring Tele-interview Oral Fluid Predictive Analytics Blood Profile ECG Mature Age Questions Dried Blood Spot ETT Cognitive Testing HbA1C PFT Functional Testing PSA APS Guidelines Prescription Database Q

Frequency of Updates to Underwriting Requirements Reported by Respondents 1-2 years (54%) 3-5 years (29%) 0-6 months (8%) 7-12 months (8%) 12

Top Requirements not changed by respondents, within the last 2 years PSA (88%) MVR (71%) Blood Profile, IR (67%) Hemoglobin, APS Guidelines (63%) HbA1C (58%) 13

Top Requirements not used by respondents, within the last 2 years Credit Report / Scoring (88%) Dried Blood Spot, PFT (83%) Lab Score (75%) Predictive Analytics, Functional Testing (71%) Oral Fluid, eir (63%) 14

Top Requirements with decreased use by respondents, within the last 2 years ECG (54%) Paramedical Exam (50%) Medical Exam, APS Guidelines (33%) Blood Profile (25%) ETT (17%) 15

Top Requirements with increased use by respondents, within the last 2 years Non-medical and NT pro-bnp (42%) Tele-interview (38%) HbA1C, Prescription Database Q (33%) MVR, Predictive Analytics (21%) Abbreviated Paramed (17%) 16

Top Requirements added by respondents, within the last 2 years eir (17%) NT pro-bnp (13%) 17

Reasons prompting changes to requirements, within the last 2 years Protective Value Faster Competitive NT pro-bnp (58%) Non-Medical (50%) Non-Medical (50%) HbA1C (46%) ECG (42%) Paramedical Exam (38%) ECG, Prescription Database Q (42%) Tele-Interview (38%) Medical Exam (29%) Paramedical Exam (38%) ECG (33%) Tele-Interview, NT pro-bnp, APS Guidelines (33%) Abbreviated Paramed, Blood Profile (25%) Blood Profile, ETT, IR (29%) Medical Exam, NT pro-bnp, APS Guidelines (25%) 18

Top Requirements with no change anticipated by respondents, within the next 2 years PSA (88%) MVR (79%) HbA1C, Mature Age Questions (63%) Hemoglobin, APS Guidelines (58%) Cognitive Testing (54%) NT pro-bnp, IR (50%) 19

Top Requirements anticipated to not be used by respondents, in the next 2 years Dried Blood Spot (83%) PFT (75%) ETT (63%) Oral Fluid (58%) Lab Score, Urine HIV, eir, Credit Report/Scoring, Functional Testing (46%) 20

Top Requirements with use anticipated to decrease by respondents, in the next 2 years Paramedical Exam (58%) Blood Profile, ECG (50%) APS Guidelines (38%) Abbreviated Paramed, Medical Exam, IR (25%) Tele-Interview (21%) 21

Top Requirements with use anticipated to increase by respondents, in the next 2 years Non-Medical (46%) Predictive Analytics, Prescription Database Q (42%) Tele-interview (38%) NT pro-bnp (29%) HbA1C, Lab Score, Credit Report/Scoring (25%) 22

Top Requirements anticipated to be added by respondents, in the next 2 years Predictive Analytics (38%) Credit Report/Scoring (25%) 23

Reasons prompting changes to requirements, within the next 2 years Protective Value Faster Competitive Predictive Analytics (58%) Predictive Analytics (50%) Predictive Analytics (58%) Tele-Interview, Credit Report/Scoring (42%) Prescription Database Q (38%) Medical Exam, NT pro-bnp, Lab Score (25%) Non-Medical, Paramedical Exam, Blood Profile, ECG (46%) Non-Medical, Paramedical Exam (50%) Tele-Interview (42%) Blood Profile, ECG (46%) Prescription Database Q (38%) Tele-Interview (42%) HbA1C, eir (21%) Abbreviated Paramed (33%) Abbreviated Paramed (33%) 24

Top Resources Involved in Making Changes to Underwriting Requirements Underwriting (96%) Actuarial (88%) Reinsurers (79%) Medical (58%) Competitive Intelligence (50%) 25

Underwriting Processes and Systems

Who Orders Requirements Who Orders Age and Amount Requirements APS Requirements Underwriting/New Business 79% 100% Producer / Producer s Staff 58% 21% Tele-interview Vendor 21% 13% Other - automated 25% 13% 27

Automated Underwriting System 58% of respondents had an automated underwriting system (AUS) that makes underwriting decisions Of the 42% that did not have an AUS, 40% are planning on moving to an AUS in the near future (1-2 years) Of those with an AUS, or planning to move to an AUS, 56% purchased their AUS with customization, while 33% developed their AUS in-house 28

Top Data Sources Automatically Fed Into Underwriting Rules Engine MIB (80%) e-app (73%) Lab Results (67%) MVR (53%) Prescription History, Tele-interviewing Results (47%) 29

Top Actions or Decisions Made by AUS Approved Preferred/Standard (87%) Refer to Underwriting Partial Assessment (73%) Recommend Underwriting Requirements (60%) Refer to Underwriting No Assessment (53%) 30

Percentage of Applications Approved by AUS 8 7 6 5 4 3 4 7 6 3 # of Respondents 2011 # of Respondents 2016 4 2 1 1 0 1 20% 21 50% 51 75% 31

Prevalence of Tele-Interviewing Yes, Part 2 only (38%) Yes, Parts 1 and 2 (29%) No (33%) 32

Tele-Interviewing Use 50% of respondents made tele-interviewing mandatory for new business within certain parameters, 38% made it optional for their producers, 12% made it mandatory for all business 88% used external vendor, 12% used internal unit 81% have expanded questions with drill down capability, 12% have no drill down capability, 7% have drill down capability & additional functionality 33

Underwriting Resources

Use of Remote Underwriters 79% of respondents reported their companies allowed underwriters to work remotely at least some of the time 46% of respondents reported their companies allowed underwriting managers to work remotely at least some of the time 35

Use of Remote Underwriters For those respondents that allowed underwriters to work remotely The graph shows the percentage of the responding company s staff that actually worked remotely at least some of the time 84% allowed at least some underwriters to work remotely up to 100% of the time, with over half actually doing so 7 6 5 4 3 2 1 0 # of Respondents Linear (# of Respondents ) <50% 50-59% 60-69% 70-79% 80-89% 90-99% 100% 36

ECG Interpretations 54% of respondents noted their underwriters can interpret ECGs, while 46% had no underwriters that can interpret ECGs Of those companies with underwriters who can interpret ECGs: 54% noted that 25% or less of their underwriters can interpret ECGs 54% noted that abnormal ECGs are always referred to the medical department 37

Top Specialty Underwriting Teams Audit (50%) Large Case (38%) Training (29%) Jet Underwriting (25%) Product Line, None (21%) 38

Top Ways New Business is Assigned to Underwriters Face amount (54%) Random (42%) Distribution Channel, Product Line (29%) 58% of respondents use multiple methods to assign cases 39

Impact of Past Changes

Cases Approved Within 30 Days 90-100% (27%) 80-89% (23%) 70-79% (23%) 60-69% (9%) 50-59% (9%) <50% (9%) 41

Top 5 Changes in Underwriting Requirements that Increased Cases Approved Within 30 Days Age and Amount Requirements (2) Underwriting Rules Engine (3) APS ordering or management thereof (1) Electronic Application (5) Underwriting resource management (4) 42

Delivering the Policy

Policy Delivery to Policyowner Mailed to the agent/broker/dealer (88%), or mailed directly to policyowner (50%) Typically, delivery not confirmed (65%), and/or a signed delivery receipt is requested if mailed by agent/broker/dealer (39%) Sent electronically to agent/broker/dealer (25%), or sent electronically to policyowner (21%) Typically, downloaded from a secure website (88%), or sent via encrypted email (38%) 92% of respondents do not use multiple methods to deliver a policy 44

Questions? 45

2017 SOA Annual Meeting & Exhibit JOEL JONES, FLMI, AALU 2016 Older Age Underwriting Practices Survey Report

Agenda Overview Topics covered and pertinent findings Any expected or unexpected results Trends 4

Overview Survey is follow up to similar surveys completed 2001, 2007, 2013 Conducted between July and September 2016 Survey sent to chief actuaries, chief underwriters of direct life carriers in the United States and Canada 29 carriers responded 5

Overview Products and Programs Underwriting Resources Medical and Non-Medical Testing Financial Underwriting Preferred Risk Class Underwriting Reinsurance Assumption Setting Regulatory and Compliance 6

Product and Programs Most common minimum age for Older Age Underwriting Most common Products available at Older Ages Programs available at Older Ages, meaning same products but different ways to market or underwriting approach 7

Underwriting Resources Resources used in underwriting assessment at Older Ages Most common responses 8

Medical and Non-Medical Testing Common Medical and Non-Medical Testing used Definition of Medical versus Non-Medical 9

Financial Underwriting Differences in financial underwriting at Older Ages Differences in requirements Unique financial considerations 10

Preferred Risk Class Underwriting Consideration of Preferred Class at Older Ages Number of Preferred Classes at Older Ages Minimum or Maximums amounts allowed by class at Older Ages 11

Reinsurance Use of Reinsurance at Older Ages Reinsurance Resources Automatic versus Facultative 12

Assumption Setting Mortality Assumptions used at Older Ages Improvements in Mortality Assumptions at Older Ages 13

Regulatory and Compliance Changes in Older Age market Changes in applications at Older Age Market 14

Surprises? Expected Results Unexpected Results 15

Trends Any Trends in Survey Results for Pricing and Mortality Any Trends in Survey Results for Underwriting Any Trend in Survey Results for Requirements 16

Thank You 17

Predictive Analytics and Accelerated Underwriting Survey Results Al Klein October 18, 2017 SOA Annual Meeting Session 162

Agenda Background Results Predictive analytics Accelerated Underwriting Concluding thoughts 2

Background Survey was conducted in June/July of 2016 We initially had fewer responses than we wanted so we called companies we knew had implemented programs and asked them to participate Response to this follow up was good and we believe most 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

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

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

Caveats Original survey is out-of-date as additional companies have implemented new 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 Please find complete survey at: https://www.soa.org/experiencestudies/2017/predictive-analyticsunderwriting/ 6

Predictive Analytics Survey Results

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

Quick Summary of 2015 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 9

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 12 6 6 5 29 Cross selling 10 2 7 9 28 Target market determination 9 8 4 7 28 Up selling 9 3 7 10 29 Customer less likely lapse 7 9 5 8 29 Customer health profile 5 5 11 7 28 Agent selection/hiring 4 6 4 9 23

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 12 9 7 5 33 Deciding on u/w requirements Stretch criteria for selecting u/w class 9 11 8 2 30 5 4 10 13 32 Business decisions 1 2 4 18 25 Table shave 1 1 1 21 24

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 7 6 7 9 29 Targeted conversion 5 2 7 12 26 For term, post-level premium term conservation mgmt. 2 7 8 11 28 Agent monitoring/mgmt. 2 6 11 7 26 In force mgmt. post-lapse 2 5 8 11 26 In force mgmt. Other customer interaction 1 2 4 8 15

Other types of PA programs that have been implemented 1 2 3 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 13

Sources/types of data used to develop PA Models 1 2 3 4 5 Vendor (17) Financial (16) Lifestyle (13) Application (12) Internal experience (12) 14

Individuals/Areas involved in developing PA models 1 2 3 Marketing Internal Actuary, Marketing, Data scientist/statistician Underwriting Internal Actuary, Internal Underwriter, Marketing Post-issue Management Marketing, Data scientist/statistician, Internal Actuary 15

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% 16

Top Obstacles in Developing PA Models 1 2 3 4 5 Data Sources (20) Agent Buy-in (13) Internal User Buy-in (13) Implement -ation (12) Designing/ Building the Model (12) 17

Predictive Analytics 2017 Follow Up Survey Results

2017 Follow Up Survey Industry is moving quickly with PA programs Did a quick survey to determine the changes Focus of survey was on the programs, not the program details, in order to keep survey short 20 of 34 companies responded Some interesting results 19

PA Update Marketing Marketing Programs Program Implemented 2015 Implemented 2015 (20) Changes Updated New Discontinued Other Customer more likely to buy 12 7 1 1 0 0 Cross selling 10 7 1 0 0 0 Target market determination 9 5 2 0 0 0 Up selling 9 6 1 2 0 0 Customer less likely lapse 7 3 0 1 0 0 Customer health profile 5 2 0 1 0 0 Agent selection/hiring 4 4 0 0-1 -1

PA Update Underwriting Underwriting Programs Program Implemented 2015 Implemented 2015 (20) Changes Updated New Discontinued Other U/w risk class 12 5 1 4 0-2 Deciding on u/w requirements Stretch criteria for selecting u/w class 9 3 1 5 0 0 5 0 0 0 0 0 Business decisions 1 0 0 0 0 0 Table shave 1 0 0 0 0 0

PA Update Post-Issue Management Marketing Programs Program Implemented 2015 Implemented 2015 (20) Changes Updated New Discontinued Other In force mgmt. pre-lapse 7 4 0 0 0 0 Targeted conversion 5 4 0 0 0 0 For term, post-level premium term conservation mgmt. 2 2 0 1 0 0 Agent monitoring/mgmt. 2 0 0 0 0 0 In force mgmt. post-lapse In force mgmt. Other customer interaction 2 0 0 0 0 0 1 0 0 1 0 0

Accelerated Underwriting Survey Results

Accelerated Underwriting Accelerated Underwriting (AU) Programs Implemented Working on Not working on but considering Not working on and not considering Total 10 12 1 3 26

Accelerated Underwriting Update Accelerated Underwriting (AU) Programs Implemented 2015 Implemented 2015 (20) Changes Updated New Discontinued Other 10 2 0 3 0 0

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 26

Accelerated Underwriting Decision-making

Data sources used for AU decision-making 1 2 3 4 5 MIB Checking Service (7) MVR (7) Rx History (7) Application (6) Lifestyle & MIB IAI (5 each) 28

Most important data sources for Accelerated Underwriting decision-making 1 2 3 4 Rx History (6) Application (6) MVR (5) MIB Checking Service (4) 29

Data sources used for Risk Class decisionmaking 1 2 3 4 5 MVR (7) Rx History (7) Application (6) MIB Checking Service (6) Financial (5) 30

Most important data sources used for Risk Class decision-making 1 2 3 4 5 Rx History (7) MVR (6) Application (5) MIB Checking Service (5) Personal History Report (4) 31

Individuals/Areas involved in developing Accelerated Underwriting programs 1 Internal Underwriter (all 8) 2 Internal Actuary (7) 3 Internal Marketing (4) 32

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 33

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 34

Biggest challenges encountered in developing AU programs 1 Data sources (4) 2 Justifying cost/benefit analysis (4) 3 Implementation (3) 35

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 to be a PA actuary and to offer creative and constructive solutions. 36

Thank you Al Klein (312) 499-5731, al.klein@milliman.com

Bio Al Klein Al is a principal and consulting actuary with Milliman s Buffalo Grove / Chicago office. He joined the firm in 2009. 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: Society of Actuaries (SOA) representative and 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 Chair of Planning Committee for Joint MWG and Populations Issues Working Group seminar on International Insights on Mortality, Population and the Public Interest 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 Joint American Academy of Actuaries (AAA) / SOA Preferred Mortality Oversight Group Accelerated Underwriting DELPHI study 2015 SOA Valuation Basic Table Development Team Longer Life Foundation Advisory Board Al received a Bachelor of Science degree in Actuarial Science and Finance from the U. of Illinois, Urbana Contact information: (312) 499-5731, al.klein@milliman.com 38

Early Duration Claims Scott E. Morrow, FSA, MAAA, FIA Vice President, Lewis & Ellis October 18, 2017

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

About the Early Duration Claims Survey Specifics of 2017 EDC Survey The last EDC Survey Conducted by the SOA Survey Subcommittee was in December 2009. Current Survey conducted from October 2016 February 2017. Twelve companies responded to the survey. Survey Focused on: Causes of Death Studies within the contestable and early duration period Underwriting Processes Post Issue and Post Claim Underwriting performed Caveats Preliminary results of a Survey Pending approval by the SOA 3

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

Breakdown of Claims Within the Contestable Period % of Claims Paid without Contest Policy Count Aggregate Face Amount 2014 2015 2014 2015 0%-50% 1 2 3 2 50.01%-75% 4 1 3 1 75.01%-90% 2 6 4 6 90.01%-100% 5 3 2 3 Total # of Respondents 12 12 12 12 % of Claims Contested Policy Count Aggregate Face Amount 2014 2015 2014 2015 0%-10% 6 3 3 4 10.01%-25% 3 6 4 5 25.01%-50% 2 3 3 1 50.01%-100% 1 0 2 2 Total # of Respondents 12 12 12 12 5

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

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

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 4 1 5 Legal 3 1 4 Actuarial 2 2 4 Underwriting 2 2 4 Compliance 1 1 2 Medical 1 1 2 Administration/Policy Owner Service 1 0 1 CFO 1 0 1 Sales/Marketing 0 1 1 CEO 0 0 0 COO 0 0 0 CRO 0 0 0 Other 1* 1** 2 Total # of Respondents 5 5 5 8

Claim Study Frequency and Across what Dimensions Studied 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

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

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 3 3 3 Cardiovascular 3 3 3 Other Accidents 3 2 2 Motor Vehicle Accidents 2 2 0 Suicide 2 2 0 Respiratory 1 2 3 Stroke 1 1 2 Alzheimer s 0 0 1 Other 0 0 1* Total # of Respondents 3 3 3 11

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

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

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

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

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

How Collected Form # of Responses Agent collected 10 Paramed 7 Teleinterview 7 Online 1 Total # of Respondents 10 17

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 identify cases of material misrepresentation. 18

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 4 4-6 months post issue 4 7-12 months post issue 4 13-24 months post issue 4 25+ 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

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 1-10% 4 11-50% 3 51-99% 0 100% 3 Total # of Respondents 10 Number of policies rescinded prior to claim during 2014 and 2015 # of Responses 0 0 1-5 6 6-10 2 11+ 2 Total # of Respondents 10 20

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 identify cases of material misrepresentation. 21

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

% of Claims referred to Various Departments Percentage of contestable claims obtain attending physician statements # of Responses 0 1 1-25% 0 26-50% 1 51-75% 0 76-99% 5 100% 4 Total # of Respondents 11 Percentage of contestable claims referred to underwriting or medical department # of Responses 0 0 1-25% 1 26-50% 2 51-75% 0 76-99% 2 100% 6 Total # of Respondents 11 Percentage of contestable claims # of Responses referred to legal department 0 0 1-25% 5 26-50% 2 51-75% 2 76-99% 2 100% 0 Total # of Respondents 11 23

Resources Utilized on 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

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

Contestable Claims by Demographic Mix 26

Contestable Claims by Demographic Mix 27