The document discusses disruption in the financial services industry from emerging technologies. It notes that the future is already here but unevenly distributed, and that adaptation to change is key to survival. Emerging technologies like the internet of things, artificial intelligence, drones, and driverless cars will disrupt insurance by changing risks and risk assessment. New entrants from technology companies also threaten traditional insurers. The manual and subjective nature of insurance underwriting is inefficient and will be replaced by big data and AI that can automatically analyze vast amounts of information.

1. Disruption in Financial Services
Presenter: Pranav Pasricha, CEO
GAMA ELC Meeting, September 16, 2016

2. “The
future
is
here,
it’s
just
not
very
evenly
distributed”
-­‐
William
Gibson
2

3. Why
talk
of
Disrup1on?
Change
is
the
only
constant
in
life
It's
not
the
strongest
of
species
that
survive,
it's
those
that
are
most
adap1ve
to
change.
Darwin
3

4. Why
talk
of
Disrup1on?
We
do
NOT
offer
a
physical
product,
only
a
technology
enabled
promise
Barriers
to
entry
of
compe11on
and
disrup1on
are
coming
down
quickly
(apart
from
regula1on)
4

5. The
World
As
We
Know
it
is
Changing,
and
FAST
!
• 3D
prin1ng
of
body
parts
:
Forbes
expects
market
to
reach
$4Bn
by
2018
• Pay-­‐per-­‐mile
car
insurance
:
Metromile
partnered
with
Uber
• Messaging
transformed
in
3
years
:
Aiming
to
be
the
Payment
Network
of
the
Future,
ValuaMon
of
Whatsapp
$19Bn
&
Snapchat
$20bn
• Consumer
and
business
robo1cs
:
market
will
be
$1.5
billion
by
2019
• Smart
home
systems
:
forecast
31.4
million
in
North
America
by
2017
• Connected
devices
:
4.3
per
person
on
the
planet
by
2020
• Self-­‐driving
cars
are
now
a
reality
5

6. Non
Tradi1onal
‘Start
ups’
have
toppled
giants
6
Walmart : $220B Amazon : $356B
Comcast $154B, TimeWarner $57B Facebook $362B
Ford & GM $47B Tesla $29B Uber $62.5
Hilton $23B Marriot $17B AirBnB $30B
Market Capitalization / Implied Valuation as of Sept’ 14, 2016

7. 7
US
Insurance
Industry
Premiums
The
Insurance
Industry
Isn’t
In
a
Happy
Place
$0.00
$100.00
$200.00
$300.00
$400.00
$500.00
$600.00
2011
2012
2013
2014
2015
Life
insurance
Annuity
Accident
&
Health
Credit
Life/
A&H
P&C
Data Source : III

8. Imagine
a
world
….
8
• Delivery
drones,
driver
less
cars
and
trucks
avoid
all
human
caused
road
accidents
• IoT
and
Augumented
Reality
devices
drive
down
work
place
accidents
to
near
zero
• Smart
Homes
eliminate
most
accidental
damage
except
true
‘Acts
of
God’
events
• Wearables
&
Gene1cs
make
Life
Underwri1ng
outdated
and
unnecessary
• Ar1ficial
Intelligence
based
Robo
Advisers
are
‘proven’
to
suggest
beger
products
and
manage
porholios
beger
• Commercial
risks
can
be
assessed
and
underwrigen
automa1cally
via
Big
Data
and
Ar1ficial
Intelligence
based
plahorms
• Insurance
for
personal
valuables
is
via
one
click
on
Facebook

9. Insurance
WILL
be
disrupted!
• Internet
of
Things
(IoT)
• Drones,
Autonomous
Cars,
TelemaMcs
• Big
Data
&
ArMficial
Intelligence
• GeneMcs
&
Wellness
• Wearables
1
Smart
Machines
2
New
Paradigms
3
Non
Tradi1onal
Compe11on
• Property/Title
centrally
registered
–
globally
(Blockchain)
• New
Risks
appear,
some
dissapear
• Switch
on/Switch
off
coverage
• Consumer
channels
9
• Social
Insurance
(Crowd
sourced)
• Non-­‐Insurance
entrants
• Re-­‐Insurers

10. 10
And
a
LOT
of
people
are
trying
!

11. • First
GeneraMon
of
Smart
Machines
are
everywhere….
Virtual
Personal
Assistants,
Robots,
Driverless
vehicles,
Process
AutomaMon
Bots,
Chat
Bots,
• Opportunity
to
fundamentally
revisit
what
humans
do
or
NOT
!
• Fundamental
impact
on
the
nature
of
work,
the
workplace,
and
by
consequence
Insurance
Smart
Machines…
11
Machines
and
other
Cogni1ve
Compu1ng
Systems
that
make
decisions,
solve
problems
and
learn
without
human
interven1on

12. Internet
of
Things
12

13. Internet
of
Things
(IoT)
:
Insurance
impact
13

14. Will driverless cars have accidents ?
• Volvo claims to deliver Accident Free driving by 2020
If they do, how do you establish who is at fault
and who is liable ?
Implications go beyond Insurance :
• Taxi and Transport / Logistics Industry
• Automotive manufacturing
• Infotainment
• Mobility services.
Driverless
Car
:
Who
Do
you
Insure
and
for
What
?
14

15. • Non Deterministic, Cognitive analytics, where machines learn from experience and build associations, help develop
technology systems that evolve hypothesis, draw conclusions and codify instincts and experience.
• Parallel information processing, aided through chips custom designed for AI applications, help parallel processing of
vast amounts of data.
• Smarter redefined with the advances in sensor, cloud and machine learning technology, and pushes the boundary of
smarter homes, cars, infrastructure and just about everything.
• Deep learning approaches allow processing of raw data including images, speech and natural language; thus providing
deeper insights.
• Face-reading machines decipher micro facial expressions to build meaningful information on the emotional state of the
user, improving human-computer interaction in areas of e-learning and e-therapy.
• Intelligent automation combines automation with artificial intelligence that allows knowledge workers, from physicians
to investment analysts to plant supervisors, to process, understand and use ballooning volumes of information.
Ar1ficial
Intelligence
:
Learning
without
Teaching
Volume,
Velocity,
Variety
and
Validity
15

16. The
problem
with
Insurance
underwri1ng
16
30
–
60
min
Underwriters
manually
enter
mulMple
queries
to
search
dozens
of
sources
to
begin
the
diligence
process.
OFAC
PEP
RCA
MEDIA
INTERNET
30-­‐60
min
Underwriters
compile
content
associated
with
the
subject
of
invesMgaMon.
Culling
internet
search
results
Misspelled
names
16
min
Underwriters
subjecMvely
select
which
associated
informaMon
to
review,
arMcles
to
read
etc.
SubjecMve
decision-­‐
making
necessarily
results
in
incomplete
reviews
30
min
Underwriters
read
arMcles
and
learn
about
the
subject
of
invesMgaMon,
idenMfying
potenMal
risk
associated
with
the
subject
20
min
Underwriters
designate
certain
informaMon/findings
as
risky
based
on
their
review
and
draw
risk-­‐based
conclusions
about
the
subject
20
min
Underwriters
report
on
their
findings
using
document
templates
and
boilerplate
language
>70% of Underwriting Time
Low
Value
<30% of Underwriting Time
High
Value

17. Enter
As
Ligle
as
Company
Name
17

18. 18

19. …are
star1ng
to
learn
Insurance
and
Wealth
!

20. • Wearables
WILL
transform
health
and
medicine,
fitness,
aging,
educaMon,
gaming
,
finance,
home
and
work
automaMon,
and
many
more
• Wearable
market
predicted
to
exceed
$6
billion
in
2016
and
$30
billion
by
2020
• By
2020,
Smart
Clothing
Shipments
Will
Surpass
10.2
Million
Units
Annually,
While
Body
Sensor
Shipments
Will
Reach
3.1
Million
Units
Annually
Bracelets
Smart
watch
Glasses
Wearables
Hearable
Contact
Lenses
20
Smart
Clothes
Smart
shoes

21. Gadgets
will
monitor
your
health
and
tell
you
more
about
person’s
lifestyle
than
any
medical
exam
Sensory Fitness Socks- sensors
communicate with Bluetooth- powered anklet
all feeding data to your Smartphone
Continuous Glucose Monitoring-
monitors and retrospectively review
patients glucose
Sleep Sensor- tracks your sleep
Smart Shoe Monitor that analyze
running style, distance covered, daily
routes etc
Smart clothing monitors biometric
data on muscle activity, breathing rate,
heart activity zones

22. Google
Contact
Lens
• Google
Contact
Lenses
Focus
helping
paMents
with
diabetes
• PotenMally
become
billion
dollars
digital
healthcare
market
• Measuring
diabeMcs’
blood
sugar
levels
directly
from
tear
fluid
on
the
surface
of
the
eyeball.
• The
system
sends
data
to
a
mobile
device
to
keep
the
individual
informed
22

23. Augumented
Reality
:
Revol1onizing
Work
Place
Safety

24. Augumented
Reality
:
Revol1onizing
Work
Place
Safety

25.
Social
Insurance
The
roots
of
Insurance
• Growth in Peer to Peer social networks
• Sharing Economy
• Increasing Peer to Peer payment networks and Micro payment systems
• Higher trust factor on Social Networks
• Savings of Dis-Intermediation and returning to a Mutual concept
• Potential for immediate gratification
25

26. Social
Insurance
Examples
26
Fellow social insurance start-ups like Friendsurance in Germany or France's Inspeer, are
putting a new spin on modern insurance, in order to introduce a sense of control, trust and
transparency.

27. Old Risk, New Risks
Changing World and Changing Economy
UP DOWN ELIMINATED ?
Car InsuranceVoluntary Group Benefits
Cyber Risk
Terrorism
Pet Insurance
Flood
Insurance of Things ?
Drones ?
Robotic / AI Liability ?
Home ?
Workers Comp ?
27

28. Non Traditional Competition
Waiting to be “Amagled”
28

32. We
make
it
that
simple

33. 33
We
are
Insurance
People
Turned
Techies
Pranav
Pasricha
Chief Executive
Officer
Laila Beane
Head of Marketing &
Consulting
Lakshan De
Silva
Chief Technology
Officer
Bharath
Venkatachari
Chief Operating
Officer
Tony Cid
Head of P&C
Kathy Awanis
Head of Strategy
and Partnerships
Chris
Pinkerton Head
of Life & Annuities
sector
Sriram N
Head of Human
Resources

34. 34
Our Purpose
Xponential Insurance
How
1. Replace traditional paradigms with scientific ones, that can create 10x value
2. Provide a migration path to 10x value with latest technology in cost effective
& low risk/low disruption manner
3. Building a pervasive insurance platform that
a. Harmonizes inside & outside data for better decisions
b. Provides a seamless user experience : Omni Product, Channel & Device
c. Eliminates issues like silos and technology obsolescence

35. The
Real
Fintech
Machine
Age
:
Beger
Decisions
&
Process
Elimina1on
35
Manual
process
Business
Produc1vity
Time
Process
Elimina1on
&
Beger
Outcomes
Process
Automa1on

36. Our
Vision
:
Fundamental
Transforma1on
of
Risk
Assessment
36
• StaNsNcally
Similar
Unique
Risk
Propensity
Looking
Backward
Looking Forward

37. Our
Vision
:
Insurance
Underwri1ng
Manual
Assisted
Supervised
Automated
• 2x
UnderwriNng
ProducNvity
• 2%
Loss
RaNo
↓
• 0.5%
Expense
RaNo
↓
• 5x
UnderwriNng
ProducNvity
• 5%
Loss
RaNo
↓
• 1
–
2%
Expense
RaNo
↓
• 10x
ProducNvity
• 2x
Growth
• 10
–
15%
NCOR
↓

38. Our
Aim
:
10%
-­‐
15%
Improvement
in
NCOR
on
current
baselines
38
5-­‐10%
UW
Profit
Loss
raMo
60
–
70%
10
-­‐
15%
AcquisiMon
Cost
/
Commissions
15%
–
18%
Expense
15
–
25
%
UW
Profit
55
–
60%
Loss
raMo
6%
-­‐
8%
AcquisiMon
/
Commissions
10%
-­‐
12%
Expense
Effectiveness
& Automation :
New Business
Underwriting
Effectiveness
: Renewal
Loss Ratio
and Pricing
Direct online
selling +
effective
marketing
Reduce HR
+ Overheads
NCOR Today
2-­‐3%
3%-­‐4%
5%
-­‐7%
3-­‐4%

40. INTELLECT DISTRIBUTION & SERVICE SUITE
1 Platform, 7 Apps
All Channels, All Products, All Devices - Cloud or On Premise
LEAD
CLOSER
Only
insurance-
specific CRM
NEEDS
ANALYSIS
Engage and
convince
clients,
drive sales
QUOTE AND
ILLUSTRATION
Simplify
and inform
E-APP
Submit
or issue
instantly
PROFILE
MANAGEMENT
360º full
account view
CUSTOMER
SERVICING
Agent and
Customer
self-service
PRODUCT
CONFIGURATOR
Launch new
products in days
DISTRIBUTION
SERVICE
SERVICE

41. Thank
You
41