Lakshan De Silva, CTO of Intellect SEEC presented a talk at the SMA Summit, 2017. Download his presentation here to understand how Big Data and advanced analytics are moving the needle for insurance. With transformative changes in technology, he says insurance will become personal, proactive and disintermediated.

1. www.intellectseec.com
Innova'on in Ac'on: Big Data & Advanced
Analy'cs
September 18, 2017 1

2. Recent Progress in Technology is only ge;ng Faster
Late 90s Early 2000 Early 2010 Today 2017
Y2K Era
Legacy
Moderniza>on
Internet
SOA Based
Progressive
Moderniza>on
& Portals
Cloud &
Mobile
Digital, Cloud
Apps
& Mobility
Big Data &
Machine
Learning
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3. As an industry, Insurance is s'll stuck in the past & ge;ng further behind
Digi>ze a “Paper” process –
policy centric, get enough
to rate, quote and issues
Enough to know someone like
you “homogenous large
pools”
Ra>ng models are based
on backward,
predominantly internal
and structured sources
Insurance
Mercy of the
intermediary and
the dreaded forms
Disintermediated,
digital and ask less,
know more and
“converse”
Tech fueled industries
Do whatever it takes to
know the customer
con>nuously and
relentlessly
Know you in>mately
“pool of one”
Externally focused, using
unstructured data
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4. We Saw Some Big Systemic Industry Problems
INSURANCE TODAY
Reac>ve . Impersonal . Intermediated
INSURANCE TOMORROW
Proac>ve . Personal . Disintermediated 10x CHANGE
ON LOW-VALUE
TASKS
STRUCTURED DATA
NOT ENOUGH TO ANALYZE
AND ASSESS RISKS
INSURERS KNOW
VERY LITTLE ABOUT
THEIR INSURED
COST TO ONLY TOUCH
A CUSTOMER
1-2 TIMES
70% ||||| 30-40%
?
4

5. S Class 1980
S Class 2016
Tesla 2016
“Cars with Computers”
• Looks contemporary
• Built on new technology
• BUT gets outdated every 7 years
• Expensive to run and maintain
• Electric & par>ally autonomous
• No engine, no maintenance,
no down>me, no emissions,
no noise,
• Minimal deprecia>on
• Always updated automa>cally
Fully autonomous vehicles
“Computers with Wheels?”
• Electric + mostly autonomous
• Low cost to no cost vehicles
• Vehicles interac>ng with each other
• Planning and Logis>cs networks redefined
Exponen'al
Linear
Approach to solving – 10% (Linear) or 10x (Exponen'al)
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6. Would your Underwri'ng Decision or Rate change if …..
¤ Directors/Officers had fraudulent or criminal history?
¤ Business was ge_ng into serious li>ga>on under another name?
¤ Customers were giving bad reviews about product or service quality?
¤ Employees were complaining of harassment or unsafe work environment ?
¤ A trucking company was o`en carrying dangerous cargo?
¤ A restaurant was actually a bar with adult entertainment and history of ‘incidents’ ?
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7. and…..
¤ What if we could get them instantly?
¤ What if you could do it without human interven>on?
¤ What if you could just do this like asking Alexa/Siri i.e.
a conversa>on?
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8. We are only just star'ng
Imagine it being the 1M pixel Camera but we are doubling every year
2014
Product Imagined –
Our “moonshot”
2015
Batch Machine Learning
Structured/Unstructured
Text
Report Based
2017
Real Time Machine Learning
Structured/Unstructured
Text + Images
Report Based
2018
Real Time Machine Learning
Structured/Unstructured
Text + Images + Video
Conversa>onal
LINEAR GROWTH
XPONENTIAL GROWTH
WHEN?
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9. Ten years from now,
when we look back at how
this era of Big Data evolved...
We will be stunned at how uninformed
we used to be when we made decisions
- Billy Bosworth, DataStax CEO (2015)
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