Chief Data Officer Forum, Insurance September 15, 2016 How Insurers are Leveraging Modern Technology for Improved Customer Experiences This document discusses how insurers can use modern technologies like cloud services, machine learning, and robotic process automation to improve customer experiences. It provides examples of how insurers have used technologies like Captricity's automation platform to extract data from documents, automate processes, and gain insights from customer data to reduce costs, speed up processes, and unlock new opportunities. The document highlights the challenges insurers face in leveraging historical paper records and improving analytics capabilities.

1. Chief Data Officer Forum, Insurance
September 15, 2016
How Insurers are Leveraging
Modern Technology for
Improved Customer Experiences

2. Today’s Agenda
• A little about the Client Experience
• Who We Are
• Modern Technology For Insurance
• Customer Use Cases and Examples

4. • Paper continues to be an ideal way to collect customer information
• Historical data is often only available on paper (or images of paper)
• How do we quickly and accurately capture this data in a way that …
• Maximixes operational efficiency
• Ensures high data quality
• Eliminates redundancy / cost of rework
• Remains flexible and scales elastically based on the business needs
• Avoids disruption of established workflows and existing IT investments
Paper is an “Operational Constant” in Insurance
Source: Accenture Automa.on Technology Series, 2016

5. 74% say it is a critical or high priority
#1
Source: Forrester Research Business Technographics Global Priorities & Journey Survey, 2015
95% of Agency owners …
… say they are focused on improving the
customer experience over the next year
priority of insurance
carriers is “Addressing Rising
Customer Expectations”
… about sharing their personal information
in digital channels
53%
of online American consumers
are “concerned” or
“very concerned” …
…but they refuse to use them
42%
of online consumers are aware of
online forms offered by their
insurance carriers …
… but “going paperless” is not always the best answer.
Insurance Carriers and Agents are Trying to Improve the Customer Experience…

6. The Customer’s Expectations for their Experience…

7. The Reality of the Customer’s Experience:

8. Our Mission
To democratize
data access
for organizations
that serve
everyone

9. GovernmentHealthInsurance & FinancialServices
10 of the Top20 U.S. Insurers
Captricity Customers
Non-Profit

11. Software-as-a-Service Powered by Machine Learning
Multi-Channel Capture Digital Enrichment Actionable Data

12. Captricity’s Automation Platform Delivers 99.9% Accuracy and …
Same-Day Turnaround Time;
Time-to-Value <30 days
Cost Savings of 50% - 70%+;
Return on Investment <3-8 months
Enterprise-Grade Security;
100% HIPAA Compliant
Infinite, Elastic Platform Scalability

13. Advanced Capture
Cloud Services & Crowdsourcing
Artificial Intelligence
Robotics Process Automation
Alternative Data, Big Data & Analytics
What are “Modern Technologies”?

14. o Transformation: Operational vs. Capital cost, on-demand &
scalable, eliminating maintenance and upgrade cycles
o Examples: Salesforce.com, Gmail, Captricity, DropIn
o What we’re seeing: reduced costs, new models
Cloud Services, SaaS, Crowdsourcing…and Insurance
o Transformation: less physical mail, faster processes
o Examples: pictures via mobile apps, smart forms, handwriting capture
o What we’re seeing: improvements in the customer experience
Advanced Capture…and Insurance

15. SaaS solutions do not require upgrades to …
• Existing IT infrastructure
• Business operations
• The way day-to-day transactional
data is processed
Accenture named Captricity as a“SaaS
provider on the leading edge.”
Forrester recognizes Captricity as an
“Advanced Capture” solution and say that
“ Capture As A Service (CaaS) Will Replace
Batch Capture Systems”
Software-as-a-Service (SaaS) and Advanced Capture
vs. Traditional Capture Solutions
Source: Accenture Automa.on Technology Series, 2016
“Capture is one of the most
complex, labor intensive and
challenging aspects of the
document delivery pipeline.”
- Accenture 2016

16. o Transformation: solving historically difficult problems
o Examples: self-driving cars, reading handwriting
o What we’re seeing: AI & ML can solve traditionally very hard
problems
Artificial Intelligence…and Insurance
o Transformation: Automation of repetitive and rudimentary tasks
o Examples: Looking up policy information, entering address changes
o What we’re seeing: there’s low hanging fruit, don’t overcomplicate
Robotics Process Automation…and Insurance

17. Crowd-Guided Deep Learning
DEEP LEARNING CROWD VALIDATION

18. What is Robotic Process Automation (RPA)?
RPA

19. o Data can be big because of Volume,Variety or Velocity
o Analytics requires data and can be very focused or very broad
o Disruption: Automation of decision making (underwriting),
approaching new demographics and offering new products
o Examples: AllLife (South Africa) & Diabetes, Fast Track Underwriting
o What we’re seeing: Know the desired business outcomes first
Alternative Data, Big Data, Analytics…and Insurance

20. Process Analytics in 6 Simple Steps
Identify
Workflow
Define
Requirements
Execute
POC
Analyze
Data
Develop
Value Assessment
Present
Business Case
Customer selects
a workflow
Customer provides batch
of sample forms (1k+)
Both parties determine
critical data fields
Both parties define
success metrics vs. ’as-is’
Sample forms run
through Captricity’s
crowd-guided
digitization platform
Captricity’s data science
team performs analysis
of sample data
• Form design
• NIGO ID & remediation
• Fraud Detection
• Data validation
• Data enrichment
• Intelligent delivery
Customer & Captricity
partner to build a value
assessment using
findings from data
analysis
Customer & Captricity
conduct workshop to
deliver the business case
to LOB leadership teams

21. Anatomy of a Process Analytics Project
Identify
Workflow
Customer selects
a workflow to use as a
starting point to build
a clear business case
around
Build Requirements
Customer provides batch
of sample forms (1K+)
Both parties determine
critical data fields
Both parties define success
metrics vs. ‘as-is’
Run POC
Sample forms run
through Captricity’s
crowd-guided
digitization platform
Analyze Data
Captricity’s data science
team performs analysis of
sample data
• Form design
• NIGO ID & remediation
• Data validation
• Data enrichment
• Intelligent delivery
Define Value
Customer & Captricity
partner to build a value
assessment using
findings from data
analysis
Deliver Business
Case
Customer & Captricity
conduct workshop to
deliver the business case
to LOB leadership teams
(1-2 WEEKS)

22. Customer Stories.

23. Familiar forms and workflows:
• Applications/Enrollment Forms (new business)
• Change forms
• Claims forms
• Electronic payment authorizations
• Contract change requests
• Collateral forms
• Withdrawal forms
• Death certificates
• Operational use cases involve using Captricity
day-to-day, eliminating manual entry.
• Analytics use cases involve using Captricity on
archived/historic documents to unlock missing or
unavailable data.
Use Cases : Operations & Analytics

24. Information Types
Systems & Tools
Process
Example: Typical New Business Process
Imaging
Manual
Indexing
NIGO / IGO
Underwriting
Scanners
Doc Prep
Document
Repository
New Business
System
Policy Admin
System
Data Entry

25. Information Types
Systems & Tools
Process
New Business Process With Captricity
Business Result:
Imaging
NIGO / IGO
Underwriting
Scanners
Doc Prep
Document
Repository
New Business
System
Policy Admin
System
Captricity
Capture
Transform
Deliver

26. CHALLENGE:
Software unable to capture handwriting from direct mail lead
generation program; team of data entry clerks not scalable
SOLUTION: A fully-automated data capture solution
• Auto-Sort amongst 100+ versions for different promotions
• Improve accuracy to 99.5% (vs ~94% + 3rd party validation)
• Reduced process time to hours (vs days)
• ~50% cost of status quo
• Custom data output for easy integration with legacy systems
Operational Efficiency:
Automating Business Reply Card Processing

27. CHALLENGE:
No easy access to “cause of death” data from death certificates,
which are submitted along with death claims but typically filed
away without further analysis
(100’s of potential templates to identify, sort and capture)
SOLUTION:
Enabled big-data analytics for underwriting innovation and to,
specifically, improve fraud detection capabilities leveraging
patterns found in historical customer data
Analytics Enablement:
Extracting Data from 1M+ Death Claims

28. LA Death Certificate LA Death Certificate
Only Possible With Advanced Capture and Machine Learning Technology
New York Life now has access to over 20 million new data points
after digitizing ten years of legacy death certificates

29. CHALLENGE:
Need to provide analytics and actuarial teams with self-serve access
to customer data generated by new life applications and paramed
forms (lab reports).
SOLUTION:
Enabled analytics teams across the organization to run advanced
analytics which will inform the business of potential improvements to
shorten the underwriting process and improve the overall new
customer experience.
Analytics Enablement:
Fast-Track Underwriting

30. CHALLENGE:
Volume outpacing throughput capacity. Errors in manual processing
causing rework. Slow turnaround time = poor customer experience.
Analytics team lacked access to critical customer data
SOLUTION:
Utilize cloud native SaaS business model that scales with business
need. Replace manual outsourced operations. Reduce turnaround
time in half. Unlock actionable data for fraud protection
Operational Efficiency:
Automating Claims & Service Form Processing
Top 5 U.S. P&C Insurer

31. Thank You.
For more information:
Visit:
www.captricity.com
www.captricity.org
Email:
brianc@captricity.com
Call:
(415) 237-FORM (3676)