Session 71 PD, Underwriting Techniques. Moderator: Donna Christine Megregian, FSA, MAAA. Presenters: Alan J. Hobbs, FSA, LLIF, MAAA Carmela Tedesco

Transcription

1 Session 71 PD, Underwriting Techniques Moderator: Donna Christine Megregian, FSA, MAAA Presenters: Alan J. Hobbs, FSA, LLIF, MAAA Carmela Tedesco

2 Underwriting Techniques - Session 71 Society of Actuaries Life and Annuity Symposium May 4-5, 2015 Alan J. Hobbs RGA Reinsurance Company J

3 Underwriting Goals Accurately assess risk profile Uncover existence and severity of impairments and other factors impacting life expectancy Make decisions as quickly as possible Minimize underwriting costs 2

4 Underwriting Techniques 1. Change the way underwriting data is viewed 2. Change the way underwriting data is obtained 3. Change how the underwriting data is reviewed 4. Change the underwriting data 5. Change the applicant pool before obtaining the underwriting data 6. Change the use of underwriting data as it changes 3

5 1. Change the way underwriting data is viewed 4

6 Motor Vehicle Records (MVR) The Way It Has It Has Been Has been used for decades in life insurance underwriting Characteristics Low cost Readily accessible General philosophy and approach pretty much unchanged for years and years Scored by points Flat extra premiums assigned to cover additional risk Some decline in use over the years 5

7 MVR Current Use Source. Motor Vehicle Records and All Cause Mortality 6

8 2012 Mortality Study of MVR Records Study completed jointly by LexisNexis and RGA Over 7 million applicants Approximately 73,000 deaths 7

9 2012 Mortality Study of MVR Records Key Observations Significant all-cause mortality differentials are observed between applicants with clean or modest motor vehicle records and those with major motor vehicle violations The extra mortality risk presented by individuals with adverse motor vehicle histories is probably better represented by a mortality multiple (i.e., table rating) rather than a flat extra mortality load. MVRs likely provide positive protective value across a wide spectrum of ages at relatively low face amounts 8

10 MVR- Mortality Differentials 9

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12 MVR - Properly Categorizing Violations Major violations include the following types of infractions: Alcohol or substance related infractions Speeding in excess of 30 mph above the speed limit Suspended, withdrawn, revoked, surrendered or cancelled drivers license Failure to provide proof of financial responsibility Failure to appear in court Reckless or negligent driving 11

13 MVR Protective Value 12

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15 MVR Mortality by Severity and Age 14

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17 MVR Comparing Extra Mortality vs Flat Extra Premiums Extra Mortality - Assumptions % Extra for Major Violations 170% Mortality Table Valuation Basic Select and Ultimate (VBT) Male nonsmoker 10 years, 6% interest, 6% lapse rates 16

18 Motor Vehicle Records A New Paradigm? Use more often because of protective value Rate for the codes that are actually indicative of extra mortality Charge applicants % increases in premium, not flat extra premiums 17

19 2. Change the way underwriting data is obtained 18

20 Obtaining of Lab Data The Way It Has Been Agent makes the sale Paramed Comes to applicant s home and obtains vial of fluid Mails the vial to Kansas City Lab runs tests on fluid and provide results after several days to insurance company Works well with current distribution which sells to higher income market May not work so well as companies develop direct-toconsumer for selling to the mid market 19

21 Obtaining of Lab Data Where 20

22 Walgreens Nation's largest drugstore chain 8,200 drugstores in all 50 states believes its pharmacists and nurse practitioners can help fill the gap in primary care, expand health and wellness and lower overall health care costs vision be the first choice in health and daily living for everyone in America, and beyond Source: Walgreens Outlines Growth Opportunities and Strategy at 2014 Annual Shareholders Meeting 21

23 Walgreens - Healthcare Clinic Options 7 days a week and weeknights, too. Services Prevention and Wellness Vaccines Physicals & Wellness Visits Health Screenings & Testing Treatments Illness, Aches & Pains Minor Injuries Skin Conditions Monitoring & Management Ongoing Health Conditions Medications & Treatments 22

24 CVS - MinuteClinic 800 clinics nationwide as of 2014 Expects to Add 150 more in next year Have 1,500 clinics by 2017 Services Similar to Walgreens Healthcare Clinic Source: Washington Post 4/4/

25 Obtaining of Lab Data How Quickly Force Diagnostics FDA-approved rapid diagnostic tests Administered at the point-of-presence Identify Underlying disease states Presence of Drugs of Abuse Source: 24

26 Obtaining of Lab Data How Much Fluid Theranos one tiny drop changes everything Our mission is to make actionable information accessible to everyone at the time it matters. Laboratory can precisely analyze tiny samples Blood, urine, fluids, and more Done quickly, easily, and accurately Source: 25

27 Obtaining of Lab Data Bringing It All Together? Theranos Wellness Centers At Walgreens in Arizona and California Source: 26

28 Obtaining of Lab Data A New Paradigm? Obtained in new ways/locations Analyzed using new tools Analyzed more quickly 27

29 3. Change how the underwriting data is reviewed 28

30 Reviewing Underwriting Data - The Way It Has Been Human underwriters Obtains paper copies/pdf s of underwriting information from all the sources Leading edge sometimes still defined as using imaging in the underwriting process Use years of experience to Spot areas of concern or Correlate data obtained from multiple sources Similar process followed On most every life insurance application As the amount of data has increased 29

31 As of 2015 Life insurance industry Underwriting data Most all underwriting data is available in data form More underwriting data available - Types, amount, Underwriters Average age of underwriters increasing yearly Limited number of underwriters being trained Industry Searching for new markets, distribution, Society Technology explosion Instant results and answers in most every area of our lives 30

32 Automated Underwriting Components to Deal with These Issues Some of the benefits Decrease underwriting time Reduce underwriting cost Ensure consistency of underwriting Reducing the workload of underwriters Enter new channel/market 31

33 Source: Underwriting engines: the new strategic imperative in life and disability business by Select X and by Hank George Inc

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35 Source: Automated Life Underwriting survey; Society of Actuaries

36 Reviewing Underwriting Data - The New Paradigm? Human underwriters and automated underwriting partnering All underwriting data Received electronically Reviewed electronically Much data Evaluated by technology alone Human underwriters only review Applications that for which a human brain is needed to process Relevant underwriting data 35

37 Reviewing Underwriting Data - The New Paradigm? Question Is the decision to embrace automated underwriting a choice To be leading edge? Or To remain relevant? 36

38 4. Change the underwriting data 37

39 The Underwriting Data - The Way It Has It Has Been The data Application Questions MIB MVR Labs APS Somewhat recently Rx 38

40 TransUnion / RGA Mortality Study Credit based solutions for Life Insurance Scott Rushing FSA, MAAA Vice President and Actuary, Global R&D RGA Reinsurance Glenn Hofmann Ph.D., MBA Senior Vice President, Analytic Services TransUnion SOA 2014 Life & Annuity Symposium Atlanta, GA May 19, 2014

41 Introduction Introduction / Motivation TransUnion / RGA joint research to better understand the predictive nature of credit data for life insurance TransUnion built the Life Mortality Index (predictive model based on credit data) TransUnion shared the mortality index and about 85 other credit and demographic variables with RGA for a more traditional actuarial analysis Motivation for the Study Deeper understanding of credit data and the many credit scores available Desire to work with partners having data Insurance solutions for underinsured using data-driven analytics General R&D Predictive & Protective Value Studies to benefit the industry Rx MIB MVR Protective Term Tail Studies 40

42 TransUnion is a trusted partner for businesses and consumers around the globe Insurance Leading provider of credit and many other data types to the Insurance industry for over 20 years All of the top 10 P&C Insurance carriers are customers of TransUnion Full data/analytics product suite, e.g. Generic and Customized Insurance Scores, Vehicle History Score, A-Plus Risk Alerts, Risk Verification Platform (fraud solution) Comprehensive offering for Life Insurance Financial Services Insights and services to manage risk and grow profitability Eighteen of the top twenty U.S. banks and all major card issuers P&C Companies Healthcare Systems and solutions for the provider (hospitals) and payer (health insurers) markets Entered market in 2004 countries Consumer Other Industries Consumer credit reports and scores Identity monitoring and fraud prevention businesses Tenant screening services for property management firms and landlords Mortgage, auto, and employment screening Collections prioritization and recovery solutions for 15 of the top 20 collections companies 41

43 Federal Statute Credit Regulations and Insurance Adoption Fair Credit Reporting Act (FCRA) Section 604 specifies permissible purposes for use of consumer reports to a person which it has reason to believe intends to use the information in connection with the underwriting of insurance involving the consumer Thus, consumer reports may be available to be used in connection with the underwriting of life insurance underwriting. State Laws and Regulation NCOIL Model Act ~ 50% of states adopt Model Act for P&C: Sensible restrictions on credit variables Most other states propose own rules for credit use in rating/underwriting 3 states (CA, MA, HI) do not allow credit P&C Insurers 99% of insurers use credit in connection with underwriting Life Insurers Early adopters are using in connection with underwriting Used in direct marketing by several life insurers 42

44 Modeling Methodology - Modeling Process Data: Sample depersonalized dataset from the credit-active population in 1998 (90% of adult U.S. population). Non-overlapping samples from 4 quarterly credit archives (3/26/98, 6/26/98, 9/26/98, 12/26/98) to avoid seasonality. Exclusions: People with Age <20 and >=70, Missing/invalid SSNs, People w/o credit history Mortality Definition: Policyholders who died during the 12-year observation period (98-10). Merged deaths from Social Security Master Death File from October, 2011 using SSN Most credit features Variable Selection Modeling TransUnion Mortality Index Started with ~800 variables, all indicating features of credit history Variables with highest predictive power for mortality Low correlation among variables Stable variables (over time) Non-gameable variables Binary Logistic Regression Age at Issue, Implied Gender and Region used as control variables Score card development in multivariate context 0 (low risk) to 100 (high risk) Single number to express mortality risk on continuous scale Used for subsequent AE analyses 43

45 Study Background Analysis Methodology Studied a random sample of nearly 18 million individuals from the 1998 credit archives. TransUnion Mortality Index was calculated for each individual. RGA built a 12-year mortality study ( ) on the 18 million lives. Study resulted in 194 million exposure years and 1.1 million deaths (using the Social Security Master Death File from October, 2011) Gender Variable: Derived based on the individual s name (one gender required > 90% of the time). Those names with < 90% (unknown gender) were excluded. Expected Basis: Started with historical US Population mortality tables (by gender & attained age, includes improvement) Adjusted the Expected for: Gender mixing in the data Missing SSMDF deaths by age and calendar year 44

46 Overall Results Exposure distribution is nearly uniform across the index Smooth increasing AE curve Results 300% Overall Mortality 20 AE (Adjusted Population) 250% 200% 150% 100% 50% 0% Exposure Count in Millions TU Mortality Index 45

47 The Underwriting Data - The New Paradigm? The data Application Questions MIB MVR Labs APS Somewhat recently Rx New data such as Transunion TrueRisk Life 46

48 5. Change the applicant pool before obtaining the underwriting data 47

49 Underwriting The Way It Has It Has Been Underwriters review all applications sent to the carrier Applicants chosen entirely by distribution Any target marketing is done based on likelihood to buy 48

50 An Actuarial/Underwriting Question #1 Assume 10 applicants All same age, gender All rated in the same underwriting class Expected mortality for the class $1.45/1000 Question What is the expected mortality of each individual applicant? 49

51 Expected Mortality/1000 Average for Each Expected Applicant Applicant Mortality

52 An Actuarial/Underwriting Question #2 Question: What happens if applicant 10 never applies? 51

53 Expected Expected Mortality/1000 Average Mortality/1000 Average for Each Expected for Each Expected Applicant Applicant Mortality Applicant Mortality

54 Question: What happens if applicant 10 never applies? Answer: Expected mortality for the group is 1.40/1000 Potential Choices: Decrease the charge for all to 1.40/1000 OR Increase your margin on every applicant by 0.05/

55 Overall Results Exposure distribution is nearly uniform across the index Smooth increasing AE curve Results 300% Overall Mortality 20 AE (Adjusted Population) 250% 200% 150% 100% 50% 0% Exposure Count in Millions TU Mortality Index 54

56 Potential Applications Target Marketing Can be used to assist in the market segmentation process Among other things, focus on the best risks for new customers or upsell / cross-sell campaigns Conversion near the end of the level-term period Assist in the selection of policies for conversion near end of term Offer favorable conversion terms to less risky policy holders Simplified issue programs Use in conjunction with other real-time data (violations, Rx, MIB) Additional segmentation in full underwriting Lapse prediction and related underwriting actions (premium, face, payment terms, etc.)

57 Underwriting The New Paradigm? Carriers, whenever possible, work to influence the pool of applicants before each person submits application data 56

58 6. Change the use of underwriting data as it changes 57

59 Attending Physician Statements (APS) The Way It Has Been Has been used for decades in life insurance underwriting Characteristics Loved The Gold Standard Hated Obtaining - Time Consuming Reviewing - Time Consuming Cost Expensive Results Declining as an age/amount requirement New tools/techniques frequently include discussion about how to reduce APS usage 58

60 Electronic Health Records (EHR) In 2004, President W. Bush 10-year EHR adoption plan. Created Office of the National Coordinator (ONC) for Health Information Technology (HIT): Oversee development of policies and standards Responsible for development and adoption of a national health IT infrastructure Certification of standards and technology required for exchange. Goal: All Americans have an EHR by

61 Adoption Rates 60

62 Electronic Health Records (EHR) In 2009, President Obama American Recovery and Reinvestment Act of 2009 (ARRA); enacted to promote the meaningful use of electronic health records (EHRs) and related technologies. Health Information Technology for Economic and Clinical Health Act (HITECH): Subsection that provides funding to promote adoption of Health Information Technology (HIT). Key points: Not just EHR adoption, but the meaningful use. ARRA/HITECH requires EHR to be certified. Incentives followed by penalties penalties for providers who do not 61 successfully demonstrate meaningful use

63 EHRs: Good News / Bad News Good news: More Data Lifetime medical history Multiple sources Discrete data Records on demand Bad news: More Data Volume of data (1,000 s of pages) Disparate formats, hybrid records New standards, vocabularies, etc. Access, sharing, matching 62

64 Solving the Many Challenges Large number of companies and lots of money committed Example: IBM Announces Deals With Apple, Johnson And Johnson, And Medtronic In Bid To Transform Health Care (4/13/2015) IBM Some 2,000 employees in a new Watson-inmedicine business unit. Two acquisitions Explorys Phytel 63

65 Solving the Many Challenges Apple: Integrate Watson-based apps into its HealthKit and ResearchKit tool systems Johnson and Johnson Use Watson to create a personal concierge service Medtronic Use Watson to create an internet of things around its medical gadgets, collecting data both for patients personal use 64

66 Attending Physician Statements (APS)/ Electronic Health Records The New Paradigm? Continue/begin to be used in life insurance underwriting Characteristics Loved - The Gold Standard Loved Obtaining - Immediate Reviewing Immediate using electronic tools Cost Much less expensive than a 2015 APS? Results Increasing use as an age/amount requirement May enable direct-to-consumer sales to be offered at near fully underwritten prices 65

67 Underwriting Techniques 1. Change the way underwriting data is viewed 2. Change the way underwriting data is obtained 3. Change how the underwriting data is reviewed 4. Change the underwriting data 5. Change the applicant pool before obtaining the underwriting data 6. Change the use of underwriting data as it changes 66

68 Underwriting Techniques - The New Paradigm? Question Is the decision to embrace one or more new underwriting techniques a choice To be leading edge? Or To remain relevant? 67

69 Underwriting Techniques May 5, 2015 Presented by: Carmela Tedesco VP Underwriting & Claims

70 TALKING POINTS. Not this PeopleSoft Pension Administration 9.1 PeopleBook 2

71 TALKING POINTS.. 3

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73 WHY ARE CUSTOMERS NOT BUYING? Complexity Other Financial Priorities Cost Other Demands on Attention TRUST Unpleasantness Misconceptions *Aubrey Cohen Life Insurance March

74 WHAT NEEDS TO CHANGE? Better Marketing/Awareness Products Cost Simplicity & Speed TRUST 6

75 BETTER MARKETING / AWARENESS Target Market Who needs it? 7

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84 PRODUCTS It has to be an easy product! Get them through the door! Upsell later! (Wisdom comes with age) 16

85 COST We want to eliminate the misconceptions of $$$ 17

86 DISTRIBUTION 18

87 SIMPLICITY & SPEED 19

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89 VITALITY EXPLAINED VITALITY 101 GET STARTED Vitality works in three easy steps 3 STEPS TO CLICK ON A SECTION TO FIND OUT MORE

90 VITALITY EXPLAINED VITALITY 101 GET STARTED Vitality works in three easy steps 1. UNDERSTANDING YOUR HEALTH Find out just how healthy you are. The Member Zone has all the tools you need to do this. Login to the Member Zone to access the quick, free online Health Review to get you started. This will give you your Vitality Age and highlight areas that you can improve. MEMBER ZONE Your online one-stop-shop to accessing all that Vitality has to offer. Your login details are sent with your policy welcome pack.

91 VITALITY EXPLAINED VITALITY 101 GET STARTED Vitality works in three easy steps 2. GETTING HEALTHIER Once you ve pinpointed the areas that you d like to improve, Vitality gives you many ways to get active with our partner companies. We give you points when you do healthy things. These count towards your Vitality Status. You start at Bronze and work your way up through Silver, Gold and Platinum. WHERE VITALITY CAN HELP Running Monitoring exercise Stop smoking Relaxing spa breaks Points needed for a single policy It s easy to reach Silver status

92 VITALITY EXPLAINED VITALITY 101 GET STARTED Vitality works in three easy steps IT S EASY TO BUILD YOUR VITALITY STATUS In fact you could reach Silver status in just a week by taking part in the following activities: Online Health Review FREE 2. GETTING HEALTHIER Non-smokers declaration Once you ve pinpointed the areas that you d like and test to improve, Vitality gives you many ways to get active with it s partner companies. As part of the Vitality Healthcheck Vitality Healthcheck We give you points when you do healthy things. These count towards your Vitality 15 with status. roadtohealth You start at Bronze and work your way up through Silver, Gold and Platinum. * Score in the healthy range for 4 of the key measurements 100 POINTS 300 WHERE POINTS VITALITY CAN HELP Running Monitoring exercise Stop smoking Relaxing spa breaks 480 POINTS* This is where everyone starts

93 VITALITY EXPLAINED VITALITY 101 GET STARTED Vitality works in three easy steps 3. MOTIVATING REWARDS Healthy living can be expensive, so we give you access to discounts and rewards on healthy things to make it easier. You could also save on your plan premiums. The higher your Vitality Status, the better the rewards available. CLICK HERE TO FIND OUT MORE ABOUT THE DISCOUNTS AND REWARDS AVAILABLE.

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96 WHAT ELSE? Risk Assessment 28

97 WHAT ELSE? TRUST 29

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99 WHAT ELSE? Not the fastest decision but the RIGHT decision! 31

100 RE-THINK Simple Product Target Market Cost 32

101 RE-TOOL Simplicity Speed 33

102 RE-STORE TRUST Incentivize Behavior & Give Back Tell a Good Story 34

103 LIFE INSURANCE Re-Think + Re-Tool + Re-Store 35

104 CUSTOMER EXPERIENCE Reward Me Serve MY Needs Make it Easy Be Consistent Give me VALUE Be Transparent 36

105 Q & A Let s Chat! 37

106 CONTACT US! Office: Website: Phone: Fax: 105 King Street East, Toronto, ON, M5C 1G LOGiQ 3 LOGiQ 3 Corp LOGiQ 3 38