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aEverything You Ever Wanted to Know About Reinsurance and Retention
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AgencyONE – 2013 Underwriter Workshop and Producer ConferenceWilliam E. Moore, Chief Underwriter, Managing Director, Swiss ReCarlo Fusco, Chief Underwriter, MetLife
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How are we alike?How do we differ?What do reinsurers do other than
say no?
Broker/Direct Writer/Reinsurer
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More businessGood mortalityHappy clientsSound relationshipsProduct innovationUnderwriting toolsProtection gap – middle marketManuals, guidelines and medical research
What Do Reinsurers Think About?
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1960 1976 1984 1992 1998 2004 201040%
45%
50%
55%
60%
65%
70%
75%
80%
85%
90%83% 83%
81%78% 76% 78%
70%
Percentage of US households holding life insurance
TotalIndividualGroup
Life Insurance Ownership is at a 50-year Low
Source: LIMRA
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1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%
Market Ups & Downs
Cession Rate
Year
Percentage
Declining Cession Rates for Reinsurers
Reinsurance Market: cessions and share
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"If the only tool you have is a hammer, you tend to see every problem as a nail."
- Abraham Maslow, 'Maslow's Hammer'
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"It is not the job of the underwriter to make an uncompetitive product competitive."
Mortality Expectations
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What do they need?What will they buy?Can we build it as partners?
The End Consumer – "Our collective client"
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More term plans? NoLifecycle products? YesElderly specific products
– Life/critical illness/LTCMutuality of interestElderly preferred criteriaDo young people want a "death benefit?"
Or "income replacement?"
Product Innovation
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Overview of Predictive Models Insurance laboratory models
– All use traditional insurance exam and lab test results to create a score, by repackaging traditional UW data into a "black box."
Personal health risk models
– Use individual detailed health and risk factor data to assess disease risk and life expectancy.
Financial services models
– Use personal data for market segmentation (income based), and therefore, potentially, propensity to buy. Models exist for identity verification and cross-selling in P&C markets (using a company's internal data).
Non-traditional mortality risk assessment models
– Use public records, marketing data, consumer data sources, and proprietary identity confirmation algorithms to link disparate data items to assess health and lifestyle.
– So far, limited industry pilots, promising, but inconclusive results
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Accelerated underwritingAffinity groupsAnti-selectionWork site and payroll deduct
– Pre tax payment of life insurance premiums?
The Great Middle Market/The Protection Gap
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RetentionAutomatic poolsFacultativeReinsurersRetrocessionaires
Facultative Obligatory
Capacity in the Market
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Rules vs. guidelinesGuess work vs. researchReinsurers vs. direct writers
Underwriting Manuals
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Changing Medical Conditions
Obesity
HIV Infection
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Meta-analysis JAMA 2013
Overweight (BMI >25 but <30)
– Reduced mortality as compared to "normal" weight
"Grade 1" obesity (BMI > 30 but <35)
– Mortality hazard no different from "normal" weight( 6' 0" 250# = BMI 35)
Obesity and Mortality – 2013
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aTrends in Annual Rates of Death due to the 9 Leading Causes among Persons 25−44 Years Old, United States, 1987−2009
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aNumbers
50,000,000 'Hits' since debut Feb 2004 to December 2012
7,581,057 'Hits' in the last 12 months
> 10,000 Keywords in Life Guide's Index
> 4,000 Registered, Active Life Guide users
> 2,400 Sections in the new Life Guide
> 2,000 Total sections updated since 2004 (11 updates)
> 1,700 Number of archived historical pages
> 180 Insurers accessing Life Guide (US, Canada, and Caribbean)
> 100 Sections updated in September 2012
85 Estimated percentage use in the industry
20 Risk calculators in Life Guide
1 Life Guide's rank in industry surveys
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NA Life Guide by the Numbers
As of December 2012
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aMost popular "hits"
Build and blood pressure
Diabetes
Liver Enzymes
Renal function
Mood disorders
Sleep apnea
CAD
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Life Guide Top 20 Impairment Hits
12 months, 9/2011- 8/2012
Thank youa
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Legal notice
©2013 Swiss Re. All rights reserved. You are not permitted to create any modifications or derivatives of this presentation or to use it for commercial or other public purposes without the prior written permission of Swiss Re.
Although all the information used was taken from reliable sources, Swiss Re does not accept any responsibility for the accuracy or comprehensiveness of the details given. All liability for the accuracy and completeness thereof or for any damage resulting from the use of the information contained in this presentation is expressly excluded. Under no circumstances shall Swiss Re or its Group companies be liable for any financial and/or consequential loss relating to this presentation.
