Webinar : L&H Insurance in the 21st Century: Navigating Antimicrobial Resistance, Climate Change, Mental Health, and Technological Advancements

1. L&H Insurance in the 21st Century:
Navigating Antimicrobial Resistance,
Climate Change, Mental Health, and
Technological Advancements

2. Disclaimer
Presentations are intended for educational purposes only and do not replace independent
professional judgment. Statements of facts and opinions expressed are those of the
participants individually and, unless expressly stated otherwise, are neither the opinion nor
position of The Digital Insurer. The Digital Insurer do not endorse or approve, and assume
no responsibility for, the content, accuracy or completeness of the information presented.
Delivering Digital Together 2

3. Host
Delivering Digital Together 3
Hugh Terry
Founder, The Digital Insurer

4. Today’s Agenda
120
Minutes
Delivering Digital Together
4
Welcome
Antimicrobial resistance – a global health threat
Impact of climate change on L&H insurance
Breaking the stigma: Exploring mental health trends in the insurance
industry
The Digital Insurer – Updates
Close
Beyond ChatGPT: The Impact of Artificial Intelligence (AI) and Machine
Learning on Clinical and Insurance Medicine

5. Housekeeping
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Delivering Digital Together
5

6. Today’s Moderators
Dr Detloff Rump
Director,
Head of Underwriting L&H
at Peak Re
Prof. Tobias Schiergens
Medical Officer,
CUO L&H Reinsurance
at Swiss Re
Delivering Digital Together 6

7. September 2023
Antimicrobial Resistance
– A global health threat
Prof. Stephan Harbarth
Director of the Infection Control Division & WHO
Collaborating Center at Geneva University Hospitals,
Switzerland

8. Antibiotic resistance: global public health concern

10. What are clinical implications of antimicrobial resistance?
• Treatment failure due to wrong choice
–Increased morbidity and mortality
• Use of more toxic, more expensive and less
efficacious therapeutic alternatives
• Added burden of nosocomial infections
• Risk of explosive outbreaks

11. Main Conclusions:
- Antibiotic resistance significantly impacts on illness burden in the community.
- Patients with laboratory-confirmed antibiotic-resistant urinary and
respiratory-tract infections are more likely to experience delays in clinical
recovery after treatment with antibiotics.

12. • C. H. (71) first woman elected lieutenant governor in South
Dakota.
• She had suffered a spinal fracture and 3 broken ribs Oct. 8 while
sailing the Adriatic Sea.
• She underwent surgery in Zagreb, Croatia on Oct. 10, then was
hospitalized Oct. 19 during a stop in Switzerland on her way
back to the US.
• She suffered pneumonia, a bacterial blood infection, and a
series of strokes, which claimed her life in Lausanne,
Switzerland on October 25, 2007.
Deadly MRSA Infection

13. Six surgeries
Lost leg
Six weeks in
hospital
Died
Three
months off
work
Two months
in hospital
Fecal
transplan
t
Deaf

14. Acinetobacter Outbreak, Lausanne
• Index patient
– Severe burn injuries, transfer from Bali (Oct
2002)
– Multi-R Acinetobacter at admission
• Outbreak
– Spread to 2 patients
– 6 months later: 6 new cases
– Closure of the burn unit
• Environnement
– Widespread contamination: 16/161 (10%)
positive swabs
Patients Environnement
► Environmental cleaning & disinfection
► Complete replacement of all disposable material
Zanetti G et al. Infect Control Hosp Epidemiol 2007; 28: 723-25

15. Economic burden of MDROs
• Increased direct costs of providing care to
patients infected with multidrug-resistant
organisms (MDRO);
• Indirect costs to patients, caregivers, &
diminished quality of life;
• Infrastructure and productivity costs of
surveillance, screening and isolation;
• Antibiotic treatment costs for therapy or
empiric coverage of MDRO

17. 17
Assessing the Global Economic and Poverty
Effects of Antimicrobial Resistance. © World
Bank
Macro-costing of drug-resistant infections
• Direct costs
Increased healthcare costs
• Indirect costs
Work absenteeism, reduced
productivity, reduced livestock
production & trade
Up to 4% decrease in GDP

18. 18
Assessing the Global Economic and Poverty
Effects of Antimicrobial Resistance. © World
Bank
Macro-costing of drug-resistant infections
• Direct costs
Increased healthcare costs
• Indirect costs
Work absenteeism, reduced
productivity, reduced livestock
production & trade
Up to 4% decrease in GDP
April, 2022
www.spglobal.com

21. Estimates of the global
AMR burden

22. “ Data are insufficient to determine full
extent of public health burden associated
with antibacterial resistance.”
US General Accounting Office, 1999
Report to U.S. Congress
“ The estimates of the burden caused by
bacterial resistance depend heavily on
unknown parameters.”
Public health burden of drug resistance
C.E. Phelps, Med Care 1989; 27: 194-203

23. Tackling drug-resistant infections globally (O’Neill report) - Mai 2016

24. De Kraker N, Stewardson A, Harbarth S. PLoS Med 2016; 13: e1002184

25. Situation in 2050
• 10.000.000 people dying due to antibiotic resistance?
• Methodological challenges & flaws of these projections:
– To predict total number of infections
– To predict the proportion of resistance
– To predict the attributable mortality
• Lack of robust data ➔ note of caution:
“broad brush estimates, not certain forecasts”
De Kraker N, Stewardson A, Harbarth S. PLoS Med 2016; 13: e1002184

26. Methodological challenges --
Why is it so difficult to estimate
the attributable mortality of AMR-
related infection?

27. Risk factors for negative clinical outcomes due to AMR

28. PROBLEM 1: Severity of ilness
• High crude mortality in patients with infections caused by
multidrug-resistant bacteria
• Carriers of multiresistant bacteria who die in the hospital
may die either…
– with simple asymptomatic carriage of resistant bacteria
– with infection by resistant bacteria
or
– because of infection by resistant bacteria (primary cause of death)

29. PROBLEM 2: Pathogen specific impact on outcomes
Lambert Lancet ID 2011

30. PROBLEM 3: Appropriateness of AB therapy
Basetti Int J Antimicrob Agents 2020

31. Multicenter study (TIMBER)
Population
Patients with bloodstream infection (BSI) caused by S. aureus or
Enterobacteriaceae
Main exposure of interest
Methicillin resistance or third-generation cephalosporin resistance
Main comparison group
Patients with infections by susceptible strains
Main outcomes
Excess length of stay (LoS) and in-hospital mortality
Stewardson A, …., Harbarth S. EuroSurveillance 2016; 21: 33
= Extended-spectrum
betalactamase-producing
Enterobacteriaceae (ESBL-E)
(e.g. E.coli, Klebsiella spp)

32. Methods
• Design:
– Multicentre retrospective cohort study
– 10 European hospitals
• Population:
– All acute inpatient admissions
– January 2010 – December 2011
• Data collection:
– Demographic, clinical, microbiologic & administrative data were extracted electronically
– One investigator from each site trained in standardized data collection during a workshop
Stewardson A, …., Harbarth S. EuroSurveillance 2016; 21: 33

33. Statistical methods
• Cox proportional hazards analysis
– Compute hazards of inpatient mortality
– Multivariable models
• Baseline covariates: for age, sex, elective versus emergent admission,
previous hospitalisation, 17 comorbidities
• Time-varying covariates: bloodstream infection, ICU admission or surgery
• Multistate modeling
– Compute excess hospital LoS (days) attributable to each type of BSI
– Accounting for competing risks (discharge vs death)
Stewardson A, …., Harbarth S. EuroSurveillance 2016; 21: 33

34. 36
S. aureus analysis
Group N
Incidence proportion
(events/100 admissions)
Total length of stay
Median (IQR)
Mortality
Count (%)
MRSA BSI 163
0.03 31 (16–45) 36 (22.1%)
MSSA BSI 885 0.15 23 (13–39) 149 (16.8%)
Non-infected 604797 - 4 (2–7) 10161 (1.7%)
Group n
Incidence proportion
(events/100 admissions)
Total length of stay
Median (IQR)
3GCR-E BSI 360
0.06 26 (12.75–45)
3GCS-E BSI 2100
0.35 14 (7–28)
Non-infected 603972 - 4 (2–7)
Enterobacteriaceae analysis
Outcomes (unadjusted)
Stewardson A, …., Harbarth S. EuroSurveillance 2016; 21: 33

35. In-hospital mortality
Adjusted proportional hazards analysis
37
Interpretation: Risk of death after bloodstream infection (BSI)
Adjusted for age, sex, emergent/elective admission, comorbidities, nights hospitalised in previous 12 months,
plus ICU-admission and surgical procedures as time-dependent covariates
Stewardson A, …., Harbarth S. EuroSurveillance 2016; 21: 33

36. Excess length-of-stay
Multistate model
38
Stewardson A, …., Harbarth S. EuroSurveillance 2016; 21: 33

40. Global burden of antimicrobial resistance
Lancet 2022:
• Global study
• 23 bacteria considered
• Combination of data and modeling
➔ 1.3 million attributable deaths (vs S)
• 16 deaths/100,000
➔ 5 million associated deaths (vs Uninf)
• 64 deaths/100,000
Naghavi et al. Lancet 2022
AMR burden Europe
6/100,000 inhabitants
AMR burden USA
11/100,000 inhabitants

41. Global burden of antimicrobial resistance
E. coli, S. aureus, K. pneumoniae
Lower respiratory tract infections
Bloodstream infections
Naghavi et al. Lancet 2022

42. Global Burden of Disease
Causes of death
Global AMR burden
5 million associated deaths
Rank THREE
Global AMR burden
1.3 million attributable deaths
Rank TWELVE
Rank Cause of death Deaths
1 Ischemic heart disease 9 137 791
2 Stroke 6 552 725
3 Chronic obstructive pulmonary disease 3 280 636
4 Lower respiratory infections 2 493 200
5 Tracheal, bronchus, and lung cancer 2 042 640
6 Neonatal disorders 1 882 438
7 Alzheimer's disease and other dementias 1 623 276
8 Diabetes mellitus 1 551 170
9 Diarrheal diseases 1 534 443
10 Cirrhosis and other chronic liver diseases 1 472 012
11 Chronic kidney disease 1 427 232
12 Road injuries 1 198 289
13 Tuberculosis 1 179 766
14 Hypertensive heart disease 1 156 733
15 Colon and rectum cancer 1 085 797
16 Stomach cancer 957 185
17 HIV/AIDS 863 837
18 Self-harm 759 028
COVID
9.5-15 million deaths
Rank ONE

43. Caveats: Global burden of AMR estimates
•Sparse data (LMIC, community, attributable
mortality per age/gender/infection/country)
•Many assumptions
•Focus on mortality, other long-term sequelae
were not considered
46

44. Is AMR a global problem?
• COVID-19 ranks higher, but AMR ranks THIRD after ischemic heart disease and
stroke and is an ongoing pandemic
• Antibiotic overuse/misuse most important contributor to AMR
– Aggravated by COVID-19 in certain patient groups
• Carbapenem-R A. baumannii, P. aeruginosa, and Enterobacteriaceae most critical
pathogens, considering resistance, clinical burden, treatability and clinical pipeline
• Largest burden: ESBL-Enterobacteriaceae (EU+global), MRSA (USA+global)
– Bloodstream infections and lower respiratory tract infections
– Sub-Saharan Africa

45. Is AMR a global problem (2)?
• Large economic impact, especially considering direct and
indirect costs, possibly equal to climate change
• Solutions: hygiene, vaccines, improved hospital infection
control, antibiotic stewardship, new antibiotics ....
➔ Preventing antimicrobial resistance is desirable by patients,
society and your industry !

46. Thanks for your attention !

47. September 2023
Q & A
Prof. Stephan Harbarth
Director of the Infection Control Division & WHO
Collaborating Center at Geneva University Hospitals

48. September 2023
The risk of a lifetime:
Climate Change Impact on
Life & Health
Dr Prachi Patkee
Life & Health R&D Analyst – Swiss Re

49. September 2023
Key risk drivers of
long-term mortality
and morbidity
Source: The risk of a lifetime 18
Examples of adverse health
outcomes:
• Heat stress induced
cardiovascular events
• Increased allergy incidence
• Air pollution - pulmonary stress,
exacerbation of respiratory
conditions, cancer
Disproportionate impact:
• Clinically vulnerable with
comorbidities
• Elderly
• Disabled people
• Socioeconomically
disadvantaged groups

50. September 2023
Global population excess mortality under different RCP scenarios
ranges from no impact to a modest impact of 1.5-5.25% under the more extreme scenarios
Source: The risk of a lifetime 18

51. September 2023 18
Projected global
increase of extreme
heat days under a
high emissions
scenario
Compared to the historical
scenario from 1986-2005,
under a presumed high
emissions climate (RCP 8.5),
by 2080-2099, vast swathes
of the globe are expected to
experience significantly
greater days of extreme
heat (>35 degrees Celsius)
Source: Climate Impact Lab –
reproduced by Swiss Re Institute

52. September 2023
Extreme heat and the wet-bulb
effect: the greater the humidity, the
greater the risk to life
55
• NASA Jet Propulsion Laboratory: highest wet-bulb
temperature humans can tolerate is 35°C (at 100%
humidity) for 6 hrs
• Once this threshold has been exceeded, “no amount of
sweating or other adaptive behaviour is enough to lower
your body to a safe temperature.”
• Even a very healthy, young individual with unlimited
drinking water and shade is at risk under these conditions
Source: Swiss Re Institute – The risk of a lifetime
Manulife & Swiss Re | March 2023

53. September 2023
Cold deaths out number heat-related deaths at present, but not for long
56
• Over the course of this century deaths from extreme cold are expected to sharply decline, as
heat-related mortality creeps up.
• In regions with strong seasonal temperature variations and cold winters, these variations may
become less pronounced if winters become milder.
Cold-related
deaths
Heat-related
deaths
Flood/storm/lightning-
related deaths
Deaths
per
million,
resident
population
Crude death rates for weather-related mortality, by age: United States, 2006–2010 (CDC)
Source: Swiss Re Institute – The risk of a lifetime

54. September 2023 18
Worldwide air
pollution mortality
distribution
The largest air pollution
impacts are in developing
countries. Under an ideal RCP
4.5 or lower scenario, air
pollution is expected to
improve and reduced deaths
in high-income countries
Source: Hannah Ritchie and Max Roser
(2019) - "Outdoor Air Pollution".
Published online at OurWorldInData.org.

55. September 2023 18
Air pollution deaths
as a proportion of
total mortality in
the USA in 2023
Total deaths predicted for 2023
• Tobacco: 16%
• Dietary risks: 16%
• High blood pressure: 15%
• Low physical activity: 3%
• Air pollution 2%
Source: GBD Foresight VizHub - GBD
Foresight Visualization (healthdata.org)
Tobacco
Dietary risks
High BP
High BMI
High fasting
blood glucose
High…
Alcohol &
drug use
Impaired kidney…
Low physical
activity
Occupational
risks Air pollution
UNITED STATES, ALL GENDERS, AGE-
STANDARDIZED, 2023 % OF TOTAL DEATHS

56. September 2023
Vector-borne diseases: the threat
of the unknown and pandemics
remain
59
• Vector-borne diseases continue to migrate
and emerge relatively
• Approximately 60-75% of human infectious
diseases originate from other species
(zoonotic)
• Climates frequently change is putting pressure
on natural habitats of species - zoonotic
events on the rise
• Illnesses can spread significantly through
globalisation and travel
• The COVID-19 pandemic has shown how the
healthcare systems of even the most
advanced countries can be crippled under the
pressure of an acute, shock event
Manulife & Swiss Re | March 2023

57. September 2023
Global spread of new and significant emerging disease outbreaks since
1998
60
Source: Public Health England – reproduced by Swiss Re Institute

58. September 2023 61
Secondary impacts of climate
change
Migration
• 216 million + people potentially displaced due to climate
change and natural disasters by 2050
• Potential for the spread of tropical diseases
Food security & nutrition
• Extreme weather (droughts, floods, desertification)
impact on agriculture
• Lower yield affecting nutritional supply chains
• Fisheries unable to compensate due to rising sea
temperatures and ocean acidification
Water scarcity
• As temperatures rise, the number of regions affected by
water stress (drinking, sanitation, public health) will
increase
• The UN - global demand for fresh water will exceed
supply by 40% in 11 major cities by 2030
Source: Public Health England – reproduced by Swiss Re Institute

59. September 2023
• Individuals can reduce
personal exposure to air
pollution and heat-related risks
–there is much risk
interdependence
• Insured segments will be
impacted but are typically
more resilient due to:
i. decreased climate exposure
ii. reduced health sensitivities
iii. greater adaptive capability
Simple, yet effective
mitigation strategies
62

60. September 2023
Latest Swiss Re L&H research publications
63
Expertise Publications
The risk of a lifetime: mapping the impact
of climate change on life and health risks
Download the publication

61. Thank you!
Dr Prachi A. Patkee
Contact us
Life and Health R&D Analyst
Prachi_Patkee@swissre.com
©2023 Swiss Re. All rights reserved. You may use
this presentation for private or internal purposes but
note that any copyright or other proprietary notices
must not be removed. You are not permitted to
create any modifications or derivative works of this
presentation, or to use it for commercial or other
public purposes, without the prior written permission
of Swiss Re.
The information and opinions contained in the
presentation are provided as at the date of the
presentation and may change. Although the
information used was taken from reliable sources,
Swiss Re does not accept any responsibility for its
accuracy or comprehensiveness or its updating. All
liability for the accuracy and completeness of the
information or for any damage or loss resulting from
its use is expressly excluded.

62. September 2023
Q & A
Dr Prachi Patkee
Life & Health R&D Analyst – Swiss Re

63. 2023
Hugh Terry
Updates from TDI
Learning Opportunities in the World of
Digital Insurance
Founder,
The Digital Insurer

64. Introducing TDI
The platform for exploring, learning and delivering digital across the insurance world
“TDI is like a lighthouse for me.
Standing firm through life’s ups and
downs, and providing guidance and
insight as my career, and our industry
evolves.
Its team of industry specialists offer
authentic insights, a sense of
community, and a helping hand for all,
as we journey together into the digital
insurance world.”
Helping individuals & companies across the industry
explore, learn and deliver digital, for the benefit of
insurance professionals, their employers, the broader
industry, insurance customers and society as a whole.
OUR PURPOSE
WHAT OUR MEMBERS SAY
67
HOW WE DO IT
OUR BUSINESS MODEL
TDI Academy - modern certified learning programmes
Digital Transformation Services – Corporate Membership & tailored support for Co’s
Knowledge & Resources – free for all members across the industry
Run by a team of industry specialists.
From the industry, for the industry. Since 2012.
Delivering Digital Together

66. Connect has global, specialist and
country communities
Delivering Digital Together

67. TDI Connect – Join online now
More than
8,000
members on
TDI Connect
https://tdiconnect.the-digital-insurer.com
Delivering Digital Together

68. …and download the app for the best
experience
More than
3000
members on
TDI Connect
Delivering Digital Together

69. Placeholder - TDI Update
There are 3 critical people centric problems
holding back digital transformation efforts
Companies see
the gap
And employees
feel it too
1. Increase Digital Skills
% of companies reporting sustained
strong or breakthrough performance
2.Create a Digital Culture 3. Address the Pace of Change
Change is rapid and organisations must
keep up – learning needs to shift from once
and done to life-long
Source: World Economic Forum - With lifelong learning, you too can join the digital workplace
Source Salesforce- 2022 Global Digital Skills Index
Source: Boston Consulting Group - It is not a digital transformation without a digital culture Source: Chiefmartech.com – Bending Martech’s Law
TDI is uniquely designed to address these 3 problems all
in one go

71. TDI Corporate Membership
Operating at the intersection of structured
and unstructured learning, TDI’s
customised Corporate Membership
packages help Insurers / Reinsurers
structure and execute
their digital transformation programmes
more effectively.
Delivering Digital Together 74

72. Get to know TDI better
I’d like to start a conversation with TDI on
- TDI Academy
- Corporate membership
- Something else!
- No thanks – all good for now
Delivering Digital Together 75

73. TDI Updates
Working together to accelerate the digital transformation of insurance
Global Awards Finals
7th December 2023
(Global Award only)
Regional Awards
Asia Pacific
Award Finals: 29th June 2023
Europe, Middle East and Africa
Award Finals: 14th September 2023
The Americas
Award Finals: 9th November 2023
We are looking for most innovative insurance projects and the
most innovative InsurTechs in three different regions. The
regional winners will qualify for the global finals in their
category.
Global Awards
The winners of the regional innovation awards will be
competing for the global award in their category. In addition,
we have a gobal only award, the Insurer Transformation
Award.
Global winner
of the Insurer
Innovation
Awards
Insurer
Transformation
Awards
Visit the TDI Awards
page to see all the
regional finalists
Sign up for the Global
Awards (7th Dec – 6 PM SGT
/ 5 AM EST / 12 AM CET)
The World’s Digital Insurance Awards
2 Rounds to go!

75. 2023
Hugh Terry
Updates from TDI
Learning Opportunities in the World of
Digital Insurance
Founder,
The Digital Insurer

76. Breaking the Stigma:
Exploring Mental Health Trends
in the Insurance Industry
Dr. Laura Laprell
Medical Consultant, Medical Research and
Development at Munich Re 19.09.2023 80

77. Example for Germany:
Between 11.1 and 17.7 million
people
The cumulative probability of suffering
from at least one of the mental
disorders studied by age 50:
46,4%
(USA)
73,9%
(Zurich)
Lifetime prevalence of selected mental
illnesses
Source: OBSAN BULLETIN 5/2017; Angst et al., 2016; Moffitt et al., 2010; Kessler et al., 2005 19.09.2023 81

78. The cumulative probability of
suffering from at least one of the
mental disorders studied by age 50:
A spotlight on German insurance data
Underwriting data
• from brokers
• from digital application tools
Claims data
• from biometric portfolio analysis of
the German disability insurance
market
• from digital claims tools (CLARA and
CLARA plus)
• Analysis based on statutory health
insurance data
• Scientific publications & other publicly
available data sources
MIRApply
Biometric
Portfolio
Data
CLARA
(plus)
Vers.Diag
Scientific
Publications
Statutory
Insurance
Data
19.09.2023 82

79. Increasing information about mental
health problems in life insurance
applications
Frequency of mental illnesses in insurance
applications
Source: Vers.Diagnose applicant data, Munich Re internal evaluation
2020 2021 2022
Year
% Applications with information on mental health problems
8
9
10
11
19.09.2023 83

80. Application data show a trend towards
less severe mental disorders
The full range of mental health conditions is
represented in insurance applications
Sources: Vers.Diagnose applicant data, Munich Re internal evaluation (2019 – 2022)
https://attitudeblog.org/2017/11/10/zahlen-und-fakten-psychische-erkrankungen/
Mental
Diagnoses
22%
Two
10%
Three
13%
Four +
55%
One
Multiple mental diagnoses often co-occur
19.09.2023 84
Mental disorders reported in application data

81. Typical comorbidities of mental disorders – a Munich Re study of long-term sick leave
Mental disorders often co-occur with a broad range of
comorbidities
• Additional mental diagnoses
• Back pain
• Neurological Disorders
• Cardiovascular Diseases
• Abuse
• ….
Source: Sick-leave study @ Munich Re (submitted for publication) 19.09.2023 85

82. 0%
5%
10%
15%
20%
15 25 35 45 55
Education level
High: n = 10406
Mean: n = 19934
Low: n = 2791
Undetermined: n = 795
Especially young people
(pupils, students) with still low
or indeterminate educational
status have a higher percentage
of mental health problems.
An essential target
group for occupational disability
insurance
Age
19.09.2023 86
Applicants with mental health problems occur in all
age and educational groups
Source: Vers.Diagnose applicant data, Munich Re internal evaluation
Dependencies between age and socioeconomic status
%
Applications
with
mental
illness
(relative)

83. Specific somatic diseases and
risk factors increase the
probability of developing a mental
health condition
▪ Factors investigated
▪ Somatic (Back pain, migraine, tinnitus,
palpitations, CFS, irritable bowel
syndrome, hyperventilation, etc.).
▪ Risk factors (bullying, stress, sleep
disorders, concentration problems)
▪ Objectifiable factors: Days off work,
doctor's visits
19.09.2023 87
Predictive Underwriting? – Risks for Mental Health
0
2
4
6
8
0 1 2 3 4 5 6
Functional
disorders
Risk factors Frequency of
doctor visits/year
1-20 21-42 43-90 > 90 5-8 > 9
Days off work
Source: Prediction study @ Munich Re (submitted for publication)
A Munich Re study: Which factors have an association with a later
diagnosis of depression/anxiety disorder (aORs )?1
1 Adjusted for all other risk factors and functional diseases, AU, age, gender, profession

84. ▪ Stable prevalences in
epidemiological studies
▪ 12-month prevalence of mental
disorders was in D (18-65 years)
(Life) problems today are more often interpreted and treated psychologically.
31,1%
(1999)
29,9%
(2012)
&
0
2 000
4 000
6 000
8 000
10 000
12 000
14 000
16 000
18 000
20 000
1980 1990 2000 2010 2020
0
1
2
3
4
5
2010 2012 2014 2016 2018 2020
Number of suicides in Germany
(1980-2020)
Sickness rate of members of DAK Health
(%)
19.09.2023 88
Are we becoming more (mentally) ill?
Sources: DeSTATIS, Federal Statistical Office; AU data of DAK Health 2010-2021

85. Mental health is the most frequent
disability benefit trigger
Cause of claim – mental health as
a disability trigger stable
0,00
0,05
0,10
0,15
0,20
0,25
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Non-Mental Mental
%
19.09.2023 89
Mental health as a disability trigger stable
Source: Biometric Portfolio Analysis (Munich Re)
DI Probability of occurrence for the portfolio (2010-2019)

86. Mental health disability claims
occur at a younger age (appr. 2
years)
Comparison of age, duration, and reactivation in
mental health vs. other disability claims
Mental health disability claims last
shorter than other causes of
claims (especially for younger age
groups)
19.09.2023 90
Claimants with Mental Health Diseases vs. Other
Causes
Source: Biometric Portfolio Analysis (Munich Re)

87. Observation Solution Consequence
MHC:
Adaptation of the
Risk assessment
guidelines
Social
Change
Destigmatisation
Psychologisation
Rising
Number of
applicants
with mental
illness
New business potential
Social
Responsibility of
Insurers
(Treat your customer fairly)
Reputation protection and
Protection from regulation
19.09.2023 91
Why inclusion of people with mental health problems?

88. Q & A
Dr. Laura Laprell
Medical Consultant, Medical Research and
Development at Munich Re 19.09.2023 92

89. Beyond ChatGPT:
The Impact of Artificial
Intelligence (AI) and Machine
Learning on Clinical and
Insurance Medicine
Dr Daniel Zimmerman
SVP, Chief Science Advisor at the
Reinsurance Group of America
19.09.2023 93
Prof. Eric Raymond
CMO Inclusive UW and Medical
Expertise at SCOR

90. Agenda
• Introductions
• The Clinical Medicine Perspective – Prof. Raymond
• The Insurance Medicine Perspective – Dr. Zimmerman
• Q and A

91. Prof. Eric RAYMOND at eraymond@scor.com
• MD Board certified in medical oncology
• PhD in molecular biology
• Professor in Medicine at Paris Sorbonne University
and University of Lausanne
• Head and Chairman of Medical oncology at Paris
Saint-Joseph Hospital
• Chief medical Officer of Inclusive UW and Medical
Expertise at SCOR since 2016
• More than 250 peer-reviewed publications in medical
and scientific journals

92. • B.S. in molecular biology and medical
microbiology
• Board-certified in Internal Medicine,
Pediatrics, and Insurance Medicine
• 10-years experience in primary care
clinical practice
• 17-years experience in insurance
medicine
• Joined RGA in October 2014
• Based in Chesterfield, Missouri, USA
• Managing Director of the Longer Life
Foundation (www.longerlife.org)
Dr. Daniel Zimmerman
Dr. Daniel Zimmerman
dzimmerman@rgare.com
linkedin.com/in/daniel-zimmerman-md

93. The Clinical Medicine Perspective
Professor Raymond

94. History

95. Today

96. Ten
Applications of
AI in Heath
Care

97. Why do we need to develop AI ?
• The world population increases i.e. needs of large scale/easily accessible healthcare
services increase in parallel
• Increasing number of birth
• Increasing longevity / decreasing mortality
• Health care providers cannot embrace the non-linear increase of information i.e.
the added value of standard medical knowledge is challenged
• General practitioners versus hyper-specialized physicians
• Liability / responsibility for healthcare providers to provide the ‘best of possible’ care
• The number of healthcare providers is decreasing dramatically
• Lack of attractivity / lost of vocations
• The big quit
• The complexity of Healthcare organizations / hospitals shall adapt to multiple
dimensions (technical, organizational, juridical, economical, human resources, …)

98. Digital Twin Hospital for Complex Health Care Organizations

99. Automation in imaging
reading
Current medical applications in radiology and pathology

100. Robotic
Surgery

101. Metaverse
Avatars
Digital Twin
Florence stop smoking avatar
Patient avatar

102. AI-Based Decision in Personalized Medicine

103. The Insurance Medicine Perspective
Dr. Zimmerman

104. Used with permission, Neil Parkin, RGA South Africa

105. Phase 1: Automated underwriting
• Automation via software systems of traditional underwriting
guidelines to improve efficiency and consistency
Phase 2: Data-driven, accelerated underwriting
• Automated or manually implemented underwriting guidelines and use of
predictive models to determine eligibility for acceleration (no exam/lab)
and improve risk segmentation
Phase 3a: Alternative underwriting, manual
• Early exploration and use of alternative medical data (EMR, patient
portal, clinical lab hx) as substitutes for the exam/lab
• Utilized predominantly on a manual basis
Phase 3b: Alternative underwriting, automated evolution
• Maturation of alternative underwriting data usage underpinned by
new protective value methods and DHD scoring for use in
automation
Phase 4: Precision underwriting
• Advancement of incremental AI to achieve a more granular view of
risk and lessen reliance on underwriting rules
Phase 5: Personalized underwriting
• Dynamic determination of requirements enabling an optimized and
right-fit underwriting journey for the consumer while maintaining
desired mortality
Phase 6: Continuous underwriting
• Dynamic underwriting adjustment based on longitudinal monitoring
of customer behavior (wellness, activity, engagement, etc.)
Future of Underwriting
109
Used with permission, Dr. Dave Rengachary, US Mortality Markets/RGA

106. Human + AI solutions
Underwriting
Insurance
core systems
integration
Intelligent email
Intelligent
ingestion
Data enrichment
Triage: Appetite UW Portal
Comparative
analytics
Submission Enrichment Assessment UW Portal
Extraction
2
1 3
4
5
6
7
UW quality
improvement
2–6 loss ratio points
Speed & effort to quote
reduction
20–40%
Retention improvement
2–3 points
Cycle time
reduction
20–50%
Value
at stake
Broker Email
Email received with
documents/package
and automatically
routed using AI
capabilities
Email Extraction
Information is extracted
from the documents
received via email by
leveraging AI capabilities
Data from client data
systems and 3rd party
data sources are
integrated to supplement
submission
Data Submission
New
submission
Old
submission
Automated appetite
checks occurs to assess
and flag submission if
necessary
New submissions are
compared to
past submissions by
leveraging historical
trends and risk
analytics
Rules
engine
Appetite
check results
Triage: Propensity
ML is leveraged to
compute win
propensity scores
from submission
data to inform
decision
ML
model
ML model
output
UWs access comprehensive
view of submission data to
support review and decisioning
within UW Portal
Submission data UW
portal
8
Connection with core
system enables
automatic policy
document generation
and management of
the signing process
Data Insurer core
systems
Copyright @ 2023 Accenture. Used with permission. All rights reserved.

107. ChatGPT-3: case example

108. ChatGPT-3 vs. ChatGPT-4
GPT-3: 38/50 correct answers*
• Performed well on questions
related to anatomy, physiology,
insurance practices.
• Unable to answer cross-discipline
questions
• Avocations and co-morbidity
assessment proved difficult
GPT-4: 47/50 correct answers*
• Stronger privacy guardrails
• More accurate, detailed, and
concise answers
• Tightened or eliminated
redundancies
• Correctly answered the hemophilia
question on the prior slide
*50 underwriting-related questions – article by Jeff Heaton, RGA
https://www.rgare.com/knowledge-center/article/gpt-4-upgrade-improves-results-expands-application-potential

109. Copyright @ 2023 Accenture. Used with permission. All rights reserved.

113. 1.
Ensure
leadership
champions AI
as a strategic
priority across
the
organization.
2.
Invest heavily
in talent to get
more from your
AI investments.
3.
Industrialize AI
tools and
teams to create
an
“AI Core.”
4.
Use AI
responsibly
from the start!
5.
Plan long- and
short-term
investments
There’s no finish line
with AI.
5 success factors
Copyright @ 2023 Accenture. Used with permission. All rights reserved.

114. Q & A
19.09.2023 118
Prof. Eric Raymond
CMO Inclusive UW and Medical
Expertise at SCOR
Dr Daniel Zimmerman
SVP, Chief Science Advisor at the
Reinsurance Group of America

115. Closing Remarks
Dr Detloff Rump
Director,
Head of Underwriting L&H
at Peak Re
Prof. Tobias Schiergens
Medical Officer,
CUO L&H Reinsurance
at Swiss Re
Delivering Digital Together 119

116. Contact Details
Hugh Terry hugh.terry@the-digital-insurer.com
Detloff Rump detloff@peak-re.com
Tobias Schiergens tobias_schiergens@swissre.com
Prachi Patkee prachi_patkee@swissre.com
Stephan Harbarth Stephan.Harbarth@hcuge.ch
Laura Laprell LLaprell@munichre.com
Daniel Zimmerman dzimmerman@rgare.com
Eric Raymond eraymond@scor.com
SP Delivering Digital Together

117. L&H Insurance in the 21st Century:
Navigating Antimicrobial Resistance,
Climate Change, Mental Health, and
Technological Advancements
Thank you for your time and attention today!