Business Case for Connected Insurance Ecosystem...technology. And as the proliferation of connected cars, and cities, gains momentum this segment that is a big contributor to the written

WhitepaperBusiness Case for Connected

Insurance Ecosystem

Author:

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Synopsis

Analysis and Background

Driving Change

Opportunity and Application of using Sensors

Conclusion

About the Authors

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Contents

SynopsisInsurance as an industry has been impacted by consumer behavior like what is being witnessed in Banking

and Retail industries. The NAIC (National Association of Insurance Commissioners) data on written premium

indicates that there is a slowdown in insurance premium collections. The pattern clearly suggests shifts in

buying behaviors on the personal and commercial insurance side fueled by easier access to data and how

goods and services are consumed by people all over the world. Changing population trends have also

impacted some of this with a visible slowdown in population growth. While the traditional sources of historic

data have long been relied on for product design and go to market strategies, access to data via sensors in

different areas of the insurance life cycle have opened a new avenue for product design shifting the

attention from pure risk transfer to elements of risk mitigation and risk prevention. For the newer insurance

entrants that do not carry the legacy of old transactional systems, a connected ecosystem presents a bigger

opportunity. Riding this wave of technology proliferation traditional insurance carriers have started also

exploring IoT connected sensors as packaged offerings outside of the typical telematics product bundles,

exploring opportunities in property, specialty areas and workers comp.

The data collected as part of this new wave of products being rolled out will set the stage for new product

categories that are priced competitively and can change pricing dynamically in response to market situations

triggered by usage or natural events. In addition to pricing, the process of underwriting and claims

notification are also going to be areas getting impacted by the entry of sensors. These devices could

potentially be connected to the backend systems of insurance carriers feeding real time data, this could be

information that in today’s world is typically updated after the fact or by human operators. The business use

cases are evolving and in the next few years’ carriers and insurance tech companies are poised to shape the

future of an ecosystem of connected devices that will make the selection, pricing and underwriting of risk

change in ways we are only beginning to learn.

The ecosystem of connected devices will provide insights to predict a future that most insurance carriers did

not have the infrastructure to foresee a few decades ago. Today, sensors present an opportunity to manage

and prevent risks in an ecosystem, giving it a whole new dimension.

In this white paper, we discuss how IoT-connected devices in a Connected Insurance Ecosystem, can be

leveraged for risk analysis. We will also highlight how data from different sources can be used for analysis and

decision making, with insights based on current information vs historic experience.

1

L&T Infotech Proprietary 03 / 15

Business Case forConnected Insurance Ecosystem

Analysis and BackgroundThe industry’s approach to ‘risk’ has been relatively unchanged since the very beginning. Simplistically put,

the model has leveraged the concept of risk transfer, coupled with the application of math of probability on

historical data sets. At the heart of any insurance product, the fundamental model has stood the test of time,

and this has worked in the absence of devices that can provide real-time data, in an infrastructure hosted

outside the insurance provider’s network.

Times have changed and technology has evolved to the point where we have the infrastructure, and the

means to capture data pertaining to usage, movement and various other external factors that are pertinent

to the entire risk that an insurer maybe covering. From time immemorial outside of flight, Man’s strongest

desire has been to be able to predict the future. The entire insurance industry has thrived on historic data,

and the ability to calculate the probability of an event occurring based on the historic experience. An

ecosystem with connected sensors, presents a situation where predicting the future is possible with eyes,

ears and insights into the risk covered by the insurance carrier.

IoT-connected devices for the purposes of this white paper fall under the following broad categories.

2


DataCollection

DataAnalysis

DecisionPoints

RiskManagement

Water Pressure,Leakage,Quality

HVAC -Humidity,Ventilation, Air QualitY

Electric Meters, Supply,Fluctuations inVoltage

Accelerometers,gyroscopic

Fire Sprinklers Systems,Alarms

Location Monitoringsensors for

Sensor data

Demographic Info

Historic Experience

Third party info

Custom view byRisk Class

Trend Analysis

Calculated Metrics

Risk AssessmentAlgorithms

Roles based Persona’s

Scoring Frameworks

Recommendations

On going Updates

Outcome BasedRisk Assessment

Competitive productpricing

Predictive analysis

Claims Monitoring

Reporting Thresholds

Product performancemonitoring

01

02

03

04

05

06


( GPS enabled withVideo & Audio Capability)


We foresee the evolution of a connected ecosystem under these six broad categories of devices, which will

fuel data analysis of sensor data with a flavor of demographic info, historical experience and third- party data.

This data can be consumed by complex algorithms forecasting trends and providing insights at the most

granular level of Risk classes. This can happen under a coverage or sub coverage as defined in marketable

products sold by an insurance carrier.

This paradigm shift will be visible in a more responsive risk assessment model, where the calculation metrics

and the risk assessment algorithms will help experts assess and price insurance products. They can use

scoring frameworks in a manner, where the pricing updates can be done in an ongoing manner based on

the sensor data that is collected.

The results of this change in decision points will be witnessed with outcome-based risk assessment and

added benefits of competitive pricing and predictive analytics, that would be closer to the actual experience.

In cases where risk prevention is not a possible outcome, the sensors could serve as recording tools for event

data or real-time product monitoring validating assumptions used for product pricing or definition.

In a study from the National Insurance Crimes Bureau, the average cost of water damage claims was $6965,

with the maximum being as high as $ 26,285 for a single itinerary in a claim for the calendar year of 2015.

However, the count of claims was 1.3 Million for the same period. This translates to roughly 9 Billion plus of

water damage losses alone. Even a 5 to 10 % change in this number, would leave a significant impact. If you

go with a rough estimate of $2000 per incident the investment in sensors would pay for itself, and still

provide additional savings if amortized over a 3 to 5 year period.

Water Damage Counts in 2014 & 2015

January February March April May June July August September October NovemberDecember

0

50,000

100,000

150,000

200,000

250,000

204

,581

1,4

0,4

22

1,32

,753

1,0

9,79

6

1,0

9,79

699

,412

1,12

,269

1,11

,34

5

1,4

0,4

22

1,11

,593

1,13

,04

51,

30,7

61

1,18

,711

1,0

9,59

5

1,25

,793

1,0

7,78

5

1,0

3,73

41,

02,

582

1,17

,868

88,2

23

81,6

94 1,0

3,4

85

91,9

86

90,8

84



The Average cost of a repair caused by avoidable circumstances or human negligence pays for the cost of sensor instillations. Water

Damage Facts: Insurance Industry Research from Market Intelligence Reports published by National Insurance Crimes Bureau

Market leaders are poised to drive this change fueled by one, some or all these reasons:

3

Economic Drivers

Historically, investment earnings were an easy fallback for insurance carriers, and the prospect of a growing

client base to fuel future income was the ray of hope in the midst of catastrophic losses. All this worked just

fine in the 80s-90s, but times are changing and investment incomes are not as lucrative and regulations are

dampening any possibilities to realize massive investment growth.

Average cost of Water Damage

Water Heater…

Frozen Pipe Related Failures

Bathroom Fixtures

Washing Machine Failure (Unoccupied Homes)

Appliance leaks (Overall)

Faulty Plumbing

Flooded House (9-10 inches of water)

Flooded House (18 inches of water)

Water Heater (Valve Failures)

Washing Machine Failures (Occupied Homes)

Water Heater (Supply Line Failures)

Flooded House (1-4 inches of water)

$0 $10,000 $20,000 $30,000

$3,642

$4,218

$4,959

$5,825

$7,800

$8,189

$10,799

$12,308

$13,467

$17,250

$18,930

$26,285


4,34,058


The Graph shows how the gap between income and expenses is shrinking, and the only opportunity that

may soon be left is to manage losses stemming from claims. In a market that is relatively flat from a growth

view point and diminishing returns on investment incomes, IoT connected devices present an opportunity of

risk prevention, mitigation and monitoring that never existed a decade ago.

Narrowing Gap between the Net Written Premium vs

Loss and operating overheads.

All data points in (000)’Source NAIC


Premium Collection Data by Business Line

Fire

All Other

550,000

525,000

Warranty

Accident and Health

Financial Guaranty*

Mortgage Guaranty

Workers Compensation

Products liability

Other liability

Medical Professional Liability

Inland Marine

Allied Lines

Commercial Multiple Peril

Farmowners Multiple Peril

Homeowners Multiple Peril

Commercial Auto Physical

Commercial Auto Liability

Private Passenger Auto Physical

Private Passenger Auto Liability

0 20,000,000

44,81,818

34,99,096

95,22,172

1,97,62,300

2,59,08,051

3,92,43,363

2,29,42,083

60,000,000 100,000,000 120,000,000

1,83,65,040

21,48,313

50,50,236

15,89,280

5,63,84,554

5,90,49,127

1,23,82,455

39,89,126

8,73,15,954

72,55,720

7,84,07,380

11,75,25,193

All data points in (000)’ Source NAIC

500,000

475,000

425,000

450,000

400,0002016 2015 2014 2013 2012 2011 2010 2009 2008 2007

4,97,933

476,974

457,906

442,785

453,521

Net Premiums Earned Net Premiums Written Net Loss + Loss Expenses + Underwriting Expenses

430,556

4,76,739

4,76,739

4,40,094

4,71,459

4,31,708

4,71,346

5,03,435

4,83,489

432,662

450,464

533,165

515,837

4,57,115


This Graph highlights the Lines of business we have identified based on written premium data, that presents

a great opportunity for the application of IoT-connected devices to monitor, prevent or mitigate risk.

• Sensors can be used for incentivizing new business targeting more technology savvy customer group in

the Private auto group, which represents over 190 Billion in Written Premiums

• The Written premium by Line of business for the calendar year of 2015

• This represents the list of key lines of business, where risk management services can help in increasing the

profitability

• The maturity of these lines of business with reference to carrier collected data and third-party data, makes

these lines candidates for having a pilot to deploy sensors

• Data collected from the sensors can be leveraged for better pricing

The next 5 years are bound to see the influx of self-driving autonomous cars. How this will impact the

Personal auto segment that represents over 190 Billion dollars of written premium remains to be seen.

The commercial fleet and Commercial auto segments have already started seeing impacts of disruptive

technology. And as the proliferation of connected cars, and cities, gains momentum this segment that is a

big contributor to the written premium will see a tectonic shift from Risk transfer, to smarter risk control


Applicability of Sensors to Business Line based on Risk Exposure

Private Passenger Auto Liability 117.5

78.4

23

7

3

87

12

19

Private Passenger Auto Physical

Commercial Auto Liability

Commercial Auto Physical

Farm owners Multiple Peril

Homeowners Multiple Peril

Fire

Inland Marine

56Workers Compensation

Line Of BusinessWritten

Premiumin bn Appx. 2015

WaterPressure/

Leakage/ Quality

HVAC-Humidity,Ventilation,Air quality

ElectricMeters Supply

Fluctuations in Voltage

Accelero-meter

gyroscopic

Fire Sprinkler Systems,

Alarms

Location Monitoring

sensors for Equipment

Weak to Strong


Demographic Drivers

The most interesting data points are on Net premium data collected State wise. Close to 39% of all collection

are from the top 5 states. This clearly indicates that in order to validate any hypothesis, the sensor data from

a few states can be used to validate product pricing definition and associated benefits of a sensor roll out,

before making any attempts of a country wide roll out.

Texas 4,82,21,695New York 4,24,94,444

20,000,000

New

Jers

ey

40,000,000

60,000,000

80,000,000

New

Mex

ico

New

Yor

kN

orth

Car

olin

aN

orth

Dak

ota

Ohi

oO

klah

oma

Ore

gon

Penn

sylv

ania

Rhod

e Is

land

Sout

h C

arol

ina

Sout

h D

akot

aTe

nnes

see

Texa

sU

tah

Verm

ont

Virg

inia

Was

hing

ton

Wes

t Virg

ina

Wisc

onsin


initiatives fueled by insurers and auto makers alike and the lines of separation will continue to disappear. As

auto makers like Tesla see market opportunity in insurance with their smart cars, the remainder of the auto

industry will also take queue.

0

20,00,000

40,00,000

60,00,000

80,00,000

100,00,000

120,00,000

140,00,000

160,00,000

180,00,000

200,00,000

Source: Automakers & ANDC YTD is for first 4 months of 2017

169,

58,5

63

174,

10,3

20

17,1

77,4

45

16,8

48,

180

54,

61,8

82

175,

39,0

52

174,

70,6

59

165,

31,0

70

155,

82,13

6

144,

92,3

98

127,

78,8

85

115,

89,8

44

104,

31,5

10

132,

45,7

18

161,

54,0

54

165,

60,9

89

169,

97,2

03

169,

13,3

51

166,

75,6

48


California, 67,423,426

Florida, 44,143,145

illinois, 23,732,508

20,000,000

Illini

os

Indi

an

40,000,000

60,000,000

80,000,000

20,000,000

Low

a

Kans

as

Kent

ucky

Loui

siana

Mai

ne

Mar

ylan

dM

assa

chus

etts

Mic

higa

nM

inne

sota

Miss

isipp

iM

issou

riM

onta

naN

ebra

ska

Nev

ada

New

Ham

pshi

re

40,000,000


Workforce Trends

The workforce is seeing some radical shifts with middle and senior management seeing a visible shift of

decision makers under the age of 40. This will also have an impact on the technology roadmap that some

insurance companies will embark on. The personal affinity and technology adoption mindset of the decision

makers will be translated into professional buying decisions and adoption of IoT sensors.

All data points in (000)’

20 to 24

Data from Bureau of Labor Statstic

Data for 59,438,000 jobs pertaining to

Management, professional, and related occupations

from the overall employed population of

151,436,000 for the year 2016

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000

16 to 19

25 to 34

35 to 44

45 to 54

55 to 64

> 65

Age

Data for overall employed population of

151,436,000 for the year 2016

396

3,118

13,561 13,926 13,818

10,689

3,931

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

16 to 19years

20 to 24years

25 to 34years

35 to 44years

45 to 54years

55 to 64years

65 yearsand over

Data from Bureau of Labor Statstic

All data points in (000)’

8,916

25,524

32,720

31,562

33,72214,027

4,965


Consumer Trends

Last mile consumers are poised to be dominated by a subset of younger customers, whose buying choices

and technology adoption are radically skewed towards a more digital experience.


Pastoral Pride 4.98

Cultural Connections 5.22

Golden Year Guardians 8.02

Aspirational Fusion 2.95

Economic Challenges 4.13

Significant Singles 4.84

Families in Motion 2.97

Singles and Starters 10.96

Power Elite 5.34

Booming with Confidence 6.61

Thriving Boomers 6.11

Family Union

Autumn Years

5.16

6.25

Blue Sky Boomers 6.58

Categories % mix

Flourishing Families 4.52

Suburban Style 4.85

Promising Families 3.36

Young, City Solos 3.18

Middle-class Melting Pot 3.97

Another application of sensor technology put to use, is in areas where backup sunk pumps kick into action

on the alert of minor flooding incidents detected by sensors installed on the floor of basements. While claims

are bound to happen, the introduction of sensors can reduce or even prevent an incident from occurring in

certain instances.

In the Workers Compensation area, sensors offer the possibilities of tracking the movement of staff and

movable assets and sending alerts to staff on the proximity to heavy machinery or high fatality prone zones.


Traces of this shift are apparent in some of the disruption seen in the retail sector. Amazon’s cashier less

grocery shopping model or the driverless cars of the future are all an indication of shifting demographic

patterns. A younger customer base will also have similar expectations from the insurance buying and

servicing journey. Connected devices fill this void and better align to a digital experience for the entire

insurance value chain. The Data from Experian in the table below Segments the US Customer Base with the

top 39 % of buying consumers being under the age of 40.

Declining cost of Sensors & energy storing devices:

The declining cost of sensors and batteries getting more efficient, will fuel adoption of sensors as some of

the hindrances for entry of sensors in risk monitoring and prevention are overcome.

Usage data:

It could be an onboard sensor or a monitoring video cam with motion detection, the possibility of a risk event

is tied to usage. Even in the event where a claim event is triggered for reasons outside of equipment usage,

the device can be used for capturing event data used to derive Subrogation revenue from the party at fault.

Market leaders are poised to drive this change fueled by one, some or all these reasons:

4

Pricing differentiator:

The data collected, can be used to better price risk in order to make the insurance product more competitive.

Regional insights, demographic data on usage patterns and movement of people, with reference to assets

covered under different types of insurance coverage can provide additional insight to pricing.

Risk Prevention:

The data collected providing insights into preventing or reducing the risk events from occurring, present the

biggest possibility for IoT sensor usage in insurance. Water damage losses is one of the key areas for using

sensors. Industry research has captured some very thought provoking data points. For instance, a recent

study from the National insurance Crimes Bureau, points to data suggesting that a significant percentage of

water damage losses could be prevented or reduced by introduction of water pressure sensing devices

designed to switch off water mains in the event of sudden water pressure changes, due to frozen water pipes.


L&T Infotech Proprietary 13/ 15

Fatal occupational injuries Goods producing (NAIC code GP1AAA)

0 500 1000 1500 2000

Private Residence

Farm

Mine and Quarry

Industrial Place and Premises

Place for Recreation and Sport

Street and Highway

Public Building

Residential Institution

Fatal occupational injuries by selected worker characteristics and selected industry, All US, all ownerships,

2015 for, Goods producing (NAIC code GP1AAA) as a sample set:

• 59% of all fatal occupational incidents occurred on location where IoT monitoring devices could be used

• The IoT devices could assist to predict hazardous conditions

• Data capture associated with the claims incident is also a possible use case

Data collected from Bureau of Labor Statistics (BLS)

Fatal occupational all ownerships Goods producing (NAIC code GP1AAA)

Street and highway 39%

Place for recreation and sport 2%

Industrial place & premises 24%

Public building 12%

Farm 9%

Mine & auarry 1%

Private residence 12%

Residential Institution 12%


16

528

1676

73

1034

33

393

514

L&T Infotech Proprietary 14/ 15


With the shift in goods and services, there is a possibility that personal and commercial auto segments will

change drastically due safer and smarter vehicles on the road, and carriers will be forced to revisit pricing and

new emerging product segments in response to this. Connected homes and commercial establishments

also present the same shift in trends requiring Insurance carriers to bundle their product offerings with

sensor bundles that could pre-empt an incident.

Another major influence to the proliferation of connected devices is going to be driven by the retail segment,

where there is a silent revolution in progress with smart Televisions, and home appliances that will eventually

impact the insurance ecosystem as well. All this will be connected with overarching analytic platforms and

computing capabilities that are defying Moore’s law, with the pace at which technology is driving progress

in the area of Big data and Analytics.

The future of insurance is going to be defined by connected devices that will provide data in short cycles

over an infrastructure channel that will help carriers price products more dynamically and responsively to

customers and market needs. Despite all the progress we make on the technology front, incidents are bound

to happen and risk will still be present.

The only difference will be that the census and historic loss experience data will be replaced by data coming

as a regular feed from connected devices, and the algorithms to predict the probability of events will get

smarter as an outcome.

The dawn of smart cities, homes, cars, workplaces & living spaces are the only natural progression.

Insurance-as-a-service will need to catch up with the ecosystem it is created to cater to. The data collected

from industry sources and our hypothesis from it, points in this direction. The carriers that approach this

opportunity with the openness to change and adapt with the ecosystem that they service, will thrive in the

decades to come. A classic example of this can been seen in the entertainment industry, where names like

Blockbuster bear witness to the wrath of not keeping pace with the ecosystem that they serviced. As

technology moved from physical devices to streaming entertainment over the internet, blockbusters

inability to keep pace with these changes took its toll on the existence of the firm, and made way for

streaming service like Netflix to quickly change the way entertainment was delivered over a digital medium.

Similar changes can be expected in how connected devices will impact the insurance industry; and there is

a possibility of seeing the lines between Insurance companies and technology firms blur. The insurance

carriers that recognize these changes and react in a timely manner, will reap the benefits of this technology

wave set to change the industry.

Conclusion5

15/ 15

About the author(s)6

Christopher Fernandes is Director Solutions in Insurance in LTI. He is an Insurance

Solutions Leader, with a focus on Big Data Analytics, Robotic Process Automation

and Packaged Solutions delivery. Focusing on key clients serviced by LTI, with an

added responsibility to articulate Go-to-Market strategy for new offerings in the

P&C and Life Domain in the US. He has also worked in insurance companies

managing business operations as part of start up operations and subsequently

moved to technology consulting helping insurance & health care companies

improve process controls and innovate business operations.

Rodney David is in Consulting Practice in LTI. He has over 2 years of experience in

Account Management Support & Proposal Bid Management. He has a good

understanding of the key industry trends and key issues impacting the Insurance

industry in North America. He is also involved in Insurance solutions designing. He

holds a Master's degree in Business Administration and Bachelor’s degree in

Management Studies.

Sanghamitra Paul is a Senior Business Analyst (Insurance) in Consulting Practice in

LTI. She has experience working with leading, US-based insurance companies. Her

expertise includes Data Analysis, Client handling and establishing relationships with

critical business stakeholders in the project, and acting as a liaison between

Business and Technology. She has an engineering (IT) degree and is working in both

P&C and Life Insurance, taking care of Functional and Technical aspects in

Requirement gathering and Designing solutions.


[email protected]

LTI (NSE: LTI, BSE: 540005) is a global technology consul�ng and digital solu�ons Company helping more than 350 clients succeed in a converging world. With opera�ons in 30 count�es, we go the extra mile for our clients and accelerate their digital transforma�on with LTI’s Mosaic platform enabling their mobile, social, analy�cs, IoT and cloud journeys. Founded in 1997 as a subsidiary of Larsen & Toubro Limited, our unique he�tage gives us un�valed real-world exper�se to solve the most complex challenges of enterp�ses across all indust�es. Each day, our team of more than 28,000 LTItes enable our clients to improve the effec�veness of their business and technology opera�ons, and deliver value to their customers, employees and shareholders. Find more at www.Ln�nfotech.com or follow us at @LTI_Global

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Business Case for Connected Insurance Ecosystem...technology. And as the proliferation of connected cars, and cities, gains momentum this segment that is a big contributor to the written