From the conference Future Tech in Insurance at Forsikringsakademiet, nov 15 2016. Defining cognitive and how that is relevant for insurance companies.

1. 1
COGNITIVE
INSURANCE
Kim Escherich | @kescherich | @danmark50
IoT Innovation Architect, IBM Watson IoT

2. What happens?
What is cognitive?
What about insurance?
What to do?

4. 4
ECOSYSTEMS

5. 5
Meet Olli

6. Medtronic

7. 7
http://goo.gl/WpukBf

8. Cognitive?

9. Today’s industry
leaders recognize
the gap in their
digital capabilities
Believe they
can’t deliver a
personalized
experience
60%
SOURCE cited in notes
Say the quality,
accuracy or
completeness
of their data is
insufficient
31%
Say they are not
confident in
making spending
and strategic
decisions
53%
expect more
competitors
from outside
their industry
54%
of CxOs

10. A cognitive business has systems that can
enhance digital intelligence exponentially.
REASON
They can reason, grasp
underlying concepts,
form hypotheses, and
infer and extract ideas.
UNDERSTAND
Cognitive systems
understand imagery,
language and other
unstructured data
like humans do.
LEARN
With each data point,
interaction and outcome,
they develop and
sharpen expertise, so
they never stop learning.
INTERACT
With abilities to see,
talk and hear, cognitive
systems interact with
humans in a natural way.

11. An organization that creates knowledge
from data to expand virtually everyone’s
expertise, continually learning and adapting
to outthink the needs of the market
Digital business +
Digital intelligence
Cognitive business
GROW
KNOWLEDGE
FROM DATA
ENHANCE
EXPERTISE
LEARN AND
ADAPT

12. More Accurate
Risk
Assessment for
Underwriting
Reduced
Frequency
and Severity
of Claims
Automated
FNOL Claims
Servicing1
Superior
Customer
Experience,
Satisfaction
and Loyalty
New Product
Offerings
1
First Notice of Loss (FNOL)
Top 5 Benefits of IoT to the Insurance Industry
What we learn from the physical world will transform several industries, including
the Insurance Sector in which IoT will have one of the greatest impacts.

13. Insurance?

14. What is Changing in the Insurance World?
The insurance industry is undergoing a significant transformation.
Historically reactive, it is now needs to become proactive …
ANAL YT I C S
I NFOR MAT I ON
SE NSOR S
D A TA
Source: CenterlineDigital
All equates to a
MAJOR DISRUPTION in the current insurance business model
The Explosion of DataCustomer Engagement Preferences
Diminishing Risk Transition in the Workforce

15. InsurTech will create new eco-systems

16. The most relevant feature of IoT is that multiple use cases can be
enabled by a shared infrastructure
`
Connected industry
Connected car
Connected living and working
Connected cities
Connected health
In-vehicle
voice
Roadside
assistance
Vehicle
platform
Stolen vehicle
recovery
Vehicle
navigation
Vehicle
diagnostics
Lease, rental &
share car
management
Usage-based
insurance
In-vehicle
entertainment
& internet access
In-vehicle
emergency
call system
First responder
connectivity
Telemedicine Clinical
Trials
Clinical remote
monitoring
Connected
medical
environments
Land
agriculture
Fishing Executive
industries
Homeland
security
Emergency services
Road fleet management
Supply chain
Public space
advertising
Manufacturing
& processing
Warehouse
& storage
Boundary
control
Retail goods
monitoring &
payment
Retail &
leisure
specialist
applications
Smart grid
distribution
monitoring
Smart
metering
Building
automation
Micro-
generation
Building
security
Construction
site monitoring
Commercial
appliances
White goodsOffice
equipment
Network
infrastructure
Network
equipment
Handset
& tests
PCs &
laptops
Other consumer
electronics
Household
information
devices
Tracking
appliances
Personal
multimedia
AV sourcesAV displays
Assisted living
Worried well
personal
monitoring
Worried well
remote
monitoring
Environmental
monitoring
Electric vehicle
charging
Road traffic
management
Environment
public safety
Defence
Specialist office
equipment
New energy
sources
Construction
equipment
monitoring

17. To combat these challenges, insurance organizations
need a new mechanism to overcome human and
current systems’ limitations
Human Machine
§ Human brain can consume and process
only a limited amount of information
§ Human beings are subject to physical
and mental fatigue, i.e. are not scalable
§ Human workers and experts can make
mistakes
§ Traditional technology cannot handle
ambiguity
§ Current paradigm of computing is pre-
programmed and rigid; it cannot learn,
reason, or relate
§ Machines do not interact via natural
interfaces
Insurers need a machine that can learn new problem domains,reason
through the hypotheses, resolve ambiguity, evolve towards more accuracy,
and interact in natural ways to engage, discover and decide better

18. Economic Choices
Value Chains
Services & Platforms
Enabling
Infrastructure
IT Infrastructure
Big Data
Integration
Security & Resilience
Cognitive
Computing
The Cognitive Insurer
© 2015 IBM Corporation
Mobile & Social
Customer Value Chains
Omni-Channel
Digital Operations
Machine Learning Algorithms
Natural Language Processing
Cognitive Analytics
Digital
Network
Business
Ecosystems
An integrated cognitive ecosystem
Powering a smarter, more efficient insurer

19. We see cognitive computing as a way to fundamentally transform
how insurance conducts business from end-to-end
Direct-to-consumer cognitive
virtual agents that serve, guide,
& advise on web or mobile
Employee-facing applications
that augment service across the
customer life-cycle
Employee-facing applications
that enhance insurance
operations
TRANSFORMED
ENGAGEMENT
EMPOWERED
ADVISORS
OPTIMIZED
OPERATIONS
© 2015 IBM Corporation 19

20. Auto
Insurance
Equity
Release
Graduation
First Job
First House
Estate
Planning
Moving
Marriage Children
Retirement
University
Life
Insurance
Savings
Health
Insurance
Home
Insurance
Wealth
Management
Wellness
Transforming Digital Customer Engagement
Provide richer engagement across the customer lifecycle with a consistent, informed and natural digital interaction
Review
During and after sale the new
member can be coached on
coverage questionsand
selecting products
Learn
Provide trusted, consistent
expert guidance to members
during life changes anytime,
anyplace
Evaluate
During the year insightful
alerts keep the member
engaged
20© 2015 IBM Corporation

21. 21
Use Case Description Value Proposition
Level of
Integration
Required
Level of
Training
Required
Self-Service Q&A
On-demand access to expert, domain-
specific information on web or mobile-
based platform
Answer simple/procedural questions and
decrease call center demand
Minimal Moderate
Embedded
Watson Virtual
Agent
Engage customers with natural language
dialog and industry specific insights within
a client-proprietary application
Augment existing digital channels with
cognitive guidance to increase digital
sales conversion
Minimal Heavy
Integrated Watson
Virtual Agent
Stand-alone solution that customizes each
customer’s experience with personalized
recommendations
Create a stickier online experience and
scale the agent experience
Heavy Heavy
Cognitive Life
Coach Watson
Virtual Agent
Creating the ultimate experience with
personalized assurance and mentoring
throughout the customer lifecycle
Inculcate a sense of loyalty/assurance
and increase customer retention
Heavy Heavy
Self-Service
Explorer
Dashboard
Discovery and navigation across disparate
sources to address challenges with
accurate, timely data “findability”
Create a more informative online
experience and decrease call center
demand
Moderate Minimal
© 2015 IBM Corporation
Transforming Engagement with Watson
Potential Use Cases to Explore

22. Embedded Watson Virtual Agent
Assisting self-service channels with cognitive process wizard
TRANSFORMED
ENGAGEMENT
Watson instance set in an existing customer
application, allowing for dialog-driven
processes that guides user to transaction
completion
Aid in completion of forms and process-
specific, point-in-time questions that
customers may have during a self-service
interaction
22© 2015 IBM Corporation
Potential Data Sources System Integration
Internal policies, procedures, best practices,
external definitions, industry FAQs
Process wizard

23. 23
Use Case Description Value Proposition
Level of
Integration
Required
Level of
Training
Required
Contact Center
Dashboard
Empower Agents to better respond to
Customer requests and improve call
conversion rate
Shorter, more efficient call times with
less waiting and more helpful answers
increasing satisfaction
Minimal Moderate
Call Log Analyzer
Creating a tool that drives conversion via
enhanced client insight for Agent Advisors
Better understand agent-customer
interactions to improve call conversion
rate
Minimal Moderate
Watson for Life &
Annuities Wealth
Managers
Efficiently explore and understand topics,
news and trends relevant to the customer
needs
Surface information that is relevant,
urgent, and timely to clients & reduce
time spent on review preparation
Minimal Heavy
Watson Crystal+
for Corporate
Insights
Watson will scale the expertise of analysts,
optimize workflow, and increase the scope
of information digested for analysis.
Create a stickier online experience and
scale the agent experience
Heavy Heavy
© 2015 IBM Corporation
Empowering Advisors with Watson
Potential Use Cases to Explore

24. Improve the agent productivity by analyzing
extracted and mined call logs to identify
patterns, quality issues, similar phrases, topics
and trends
Identify common customer issues to prepare
agents for frequent queries, improving training
and overall call center processes
© 2015 IBM Corporation 24
EMPOWERED
ADVISORS
Potential Data Sources System Integration
Enterprise content,Transactionand
application data,call transcripts, email, social
media
CRM, transactional
systems
Watson for Contact Center Support
Analyze and discover new insights to enhance the quality assurance of each interaction

25. 25
Use Case Description Value Proposition
Level of
Integration
Required
Level of
Training
Required
Underwriting
Dashboard
Extraction, collection, aggregation of submission
data, underwriting guidelines from a combination of
internal and external data sources.
Simplify the processing of submission
documents.
Medium Minimal
Underwriting
Advisor
Identify, assess and understand how a risk should be
priced and evaluated.
Optimize underwriting decisions by taking
on more complex risk scenarios.
High Heavy
Underwriting
Research
Aggregate structured and unstructured, internal and
external information to form comprehensive company
profiles
Improve decision making and
opportunities with deeper insights into
disparate companies
Medium Minimal
Claims
Dashboard
Extraction, collection, aggregation of claims and loss
data from a combination of internal and external data
sources.
Simplify the collection, triage and review
of claims cases. Reduce time to perform
quality review
Medium Minimal
Claims Fraud
Advise claims management in identifying SIU/fraud
and litigation risks
Improve risk assessment models by
uncovering patterns and associations
among existing data sources
Low Minimal
Regulatory Policy
Compliance
Explore, search, analyze, and establish correlations
between external regulations, internal company
policies & procedures and controls
Increase visibility into the risk
environments across your enterprise
Medium Medium
© 2015 IBM Corporation
Transforming Operations with Watson
Potential Use Cases to Explore

26. Transform Underwriting
Make existing decisions smarter by incorporating insights from unstructured data
26
Case Underwriter
ReviewApplication
Completeness
Review and Apply
Underwriting Guidance
Recommend
Underwriting Decision
© 2015 IBM Corporation
OPTIMIZED
OPERATIONS
Impact future
underwriting decisions
with continuous learning
and training
Learn
Combine internal,
external, structured and
unstructured data for
deeper insights into
individual risks
Evaluate
Automate the extraction,
and processing of
submission data
Review
Summarize & extract
information from
submission
Enrich submissions
by combining internal
and external data
Evaluate products
for performance and
key metrics
Support decision
making with insights
from precedence
Improve decision
making with
continuous learning
Cognitive Underwriting
Structured
Data
Application
Documents
Historical Data
& UW notes
Social Data Loss History
Inspection
Reports
Example Customer Data
Public Medical
Literature
Watson Health
Data
Wikipedia
DBPedia
Public
Financial Data
Historical
Public
Submissions
Weather
Patterns
Example Watson Data

27. Watson for Claims Fraud
© 2015 IBM Corporation 27
OPTIMIZED
OPERATIONS
Automate the search of different data sources
and historical data for greater insight into
claim losses and insured policy lifecycle
changes
Improve risk assessment models by uncovering
unexpected patterns and associations among
existing data sources
Decrease fraudulent payouts by discovering new insights from mined data
Potential Data Sources System Integration
Claim files, claim guidelines, precedent
claims reports, SIU notes, internal policies,
procedures, best practices,news services
Internal workflows,
claims mgmt system,
internal database(s)

28. Source: Understanding customers and risk Your cognitive future in the insurance industry, IBM Institute for Business Value

29. What to do?

30. The Watson Journey consist of three primary phases
CVA
Use Case
Benefits Case Report
Journey Map
1 Deploy & Manage
Deploy and Expand to
Other Domains
3Configure & Train
Core System
Training
2
StartHere
© 2015 International Business Machines Corporation 30IBM Confidential

31. § Assessment of current business
workflows and identification of
target processes to disrupt with
cognitive solutions
§ Development of final candidate Use
Case(s)
§ Development of User Scenarios /
Personas aligning to Use Case
§ Development of key benefits
hypotheses
§ Data collection to test hypotheses
§ Development of Benefits Case
§ Identification of key Watson
initiatives to support the Client’s
goals for cognitive enablement
§ Development of Client’s Journey
Map for Cognitive Computing
Page | 31 © 2014 International Business Machines Corporation
Three key deliverables drive our teams to define Watson’s initial
capabilities, business value, and overall cognitive journey
Use Cases Cognitive RoadmapBenefits Case
© 2015 International Business Machines Corporation 31IBM Confidential

32. Finally, a Cognitive Roadmap details the client’s journey with
Watson
Key tasks / activities:
§ Outline key initiatives from end user vantage
point.
§ Outline key business milestones supported
by incremental business capabilities
§ Outline the business benefits and metrics
effected over the duration of the
Transformation period
§ Deliver a visual representation of key
initiatives and dependencies, identification
of milestones and benefits improvement
over time, and a detailed plan for execution
Objective: Outline key initiatives required to supportthe transformation journey from the pointof view of the end user(s).
It summarizes the key persona(s),identifies progressive capabilities and highlights sample interactions throughoutthe
transformation.
© 2015 International Business Machines Corporation 32IBM Confidential

33. Kim Escherich
escherich@dk.ibm.com
+45 2880 4733
internetofthings.dk | danmark50.dk
@kescherich | @danmark50
/escherich
/in/escherich
kescherich@gmail.com
Mere information
Se præsentationer og demoer fra World of Watsonher: https://ibmgo.com/wow16
Om Watson: http://www.ibm.com/watson/
WatsonVirtual Agent: https://www.ibm.com/marketplace/cloud/cognitive-customer-engagement/us/en-us
Customer Insights for Insurance: https://www.ibm.com/marketplace/cloud/customer-insight-for-insurance/us/en-us
WatsonIoT: http://www.ibm.com/internet-of-things/
IBM Instutute for Business Value: http://www-935.ibm.com/services/us/gbs/thoughtleadership/
IIBV Cognitive Future Study: https://goo.gl/yTZ50I
IIBV Innovating Insurance Study:https://goo.gl/dCpckR