Motorists insurance company was facing challenges from aging systems, data silos, and an inability to analyze new types of data sources. They partnered with Saama Technologies to implement a hybrid Hadoop and SQL data warehouse ecosystem to consolidate their internal and external data in a scalable and cost-effective manner. This allowed Motorists to gain new insights from claims data, reduce load times by 30% with potential for 70% improvements, and save hundreds of hours on report building. Saama's Fluid Analytics for Insurance solution established a robust data foundation and provided self-service reporting and predictive analytics capabilities. The new environment enabled enterprise-wide data access and advanced analytics to improve business performance.

1. Confidential
Saama Technologies, Inc
Disrupting Insurance with Advanced Analytics –
The Next Generation Carrier
How Motorist leapfrogged into the future of analytics and data
June 28-30, 2016

2. Confidential
Saama Technologies, Inc
Speakers
1
Sanjeev Kumar, Saama
Technologies
As Saama’s Head of Insurance, Sanjeev
Kumar, is responsible for delivering
innovative data analytics solutions for the
insurance industry at Saama. Sanjeev is very
passionate about solving business problems
and eternally believes in process
improvement. He strongly believes that
today’s next generation business intelligence
in the form of advanced analytics will
revolutionize the insurance industry. Sanjeev
is a winner of the Application Innovator award
and a regular speaker at various conferences,
including Business Intelligence.
sanjeev.kumar@saama.com
@saamatechinc
Alan Byers, Motorists
As AVP of Data Analytics, Alan Byers is responsible
for strategic Enterprise Data Management combined
with tactical development of data solutions that
support Analytics and systems integration. Alan is
focused on reducing the company’s time-to-
information from being measured in days, weeks, or
even months down to seconds by using an Agile BI
approach that provides quick delivery of data
services and self-service analytics. He believes that
effective use of data assets by combining wisdom
and advanced analytics methodologies is a key
driver for success in the insurance industry during
the digital age.
alan.byers@motoristsgroup.com

3. Confidential
Saama Technologies, Inc
• Malcolm Gladwell
• The key to good decision making is not just knowledge. It is the understanding
2

4. Believe the Hype……..

5. The “Right Now” disruption
PagMonday, July 11, 2016 Saama Confidential
Weather Patterns
Connected World
Safer Driving Ecosystem
Safety First Eco Friendly, Shared Economy
Autonomous Vehicles
Wearables, More informed,
More connected
Smart / Connected Homes

6. The “Right Now” Disruption
• Peer to Peer, Insurance for miles driven, pay as you
go
• Emerging Business Models
Channel Disruption
• Digital customer experience
• Connected auto, home and self
• The Internet Of “Me”
Digitization
• Traditional model of insurance disrupted
• Innovation by partnering with “technology”
companies. VC funding
Change in Eco
System
• Predictive and automated underwriting and fraud
process.
• Straight through processing for Underwriting
Embracing Big Data

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Saama Technologies, Inc
Opportunities to Achieve
Data-Driven Business
Objectives through a Modern
Data Architecture

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Saama Technologies, Inc
How do we use all this data in the disruptive era?
• To capitalize on the value of big data and leapfrog the competition, leading insurers
are moving towards consolidated data management.
• The introduction of an enterprise data hub built on open-source Apache Hadoop
provides a cost-effective way for insurers to aggregate and store ALL their data, in any
format, in a highly secure environment.
• Users can access rich data sources, blend and analyze data from any source, in any
amount, detect patterns, model risk and gain valuable real-time insights that deliver
results.

9. Confidential
Saama Technologies, Inc
The Situation
In early 2014, Motorists with under $1b in Net Written Premiums and operation in 20+ states
had a few business challenges:
• Aging systems run by an aging workforce
• Reduced customer loyalty + pricing pressures
• Many operational data sources: DB2, VSAM, IMS, SQL, documents, and others
• Needed to analyze new types of data: clickstream, social media, and telematics
• No single version of truth: KPIs were inconsistent, information for decision-making was
unreliable
• Integration of data from new affiliate companies with their own systems and structures
• Needed real-time analysis, that required processing of massive amounts of data faster
• Need of scalable, integrated, secure data in a cost effective way
Motorists wanted to embark on a transformation program to consolidate and modernize
its existing IT systems, which support core Insurance processes – Policy Admin, Claims,
and Billing but was faced with some questions/decisions about its data ecosystem.

10. Confidential
Saama Technologies, Inc
Traditional
Solutions Innovation
Traditional EDW
Fluid Analytics for
Insurance/Hadoop
Which road to take?
Should we wait for
core system
replacement first?
Start the advanced
analytics journey
along with core
system
replacement?

11. Confidential
Saama Technologies, Inc
A Radical Shift in Data Strategy
A Data Warehouse is great for:
– Structured data
– Predictable query patterns
– Combining similarly structured data
But not so great for:
– “Otherly” structured data
– Rapid prototyping with new data sources
– Ad-hoc data blending for analysis
– Complex, multi-stage data analysis
– Very high volumes of data
– Low-latency / real-time data
Motorist made the unique decision to build a hybrid Hadoop – SQL data warehouse ecosystem to collect,
refine, and present high data volumes from a rapidly expanding and unpredictable collection of internal and
external data sources.

12. Confidential
Saama Technologies, Inc
1
1
New Affiliate
Data
3rd
Party Data
Social Media,
UBI,
Clickstream, ...
Guidewire
Analytics Engines
Data Warehouse
Data Lake
Aggregation,Queries,Services,BusinessLogic
Dashboards
Scorecards
API
Integration
Embedded
Analytics
Data Feeds
Ad-hoc
Analysis
Prescriptive
Models
Predictive
Models
Report
Subscriptions Self-service
Discovery,
Self-service
DataRefinery-DataManagementandGovernance
Data Warehouse Ecosystem Features
• Fast data ingest
• Agile data refinery
• Data discovery
• Searchable Information
Catalog
• Rapid solution delivery
• Multi-stage data
governance
• Workload-optimized
architecture
• Distributed architecture
• Data as a Service

13. Confidential
Saama Technologies, Inc
Projects with Saama
• Production infrastructure design and implementation (Incl. Hortonworks)
• Define taxonomy, Hardware specs and design environments, Security
• Personal Lines data warehouse
• MMIC, CIUSA Data in Data Lake
• Saama iMAP data model
• Next steps are to extend the iMAP model and add other affiliates
• Affiliate claims dashboard
• Claim notes enterprise search
• Text mining of Agency Feedback reports
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14. Confidential
Saama Technologies, Inc
Recognized Value
• Faster processing of data – ELT processes running with more parallelism than
prior processes – Load times reduced by 30%, with expected improvements to
70% with more scalability.
• Hundreds of hours saved building agency feedback reports
• New insights into claims handling improvements.
• Information in claims previously undiscoverable now easy to find.
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Saama Technologies, Inc
How it all comes together

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Saama Technologies, Inc
Saama’s Fluid Analytics for Insurance
A solution comprising Saama's Fluid Analytics for Insurance ,a unique offering that
established a strong, robust data foundation utilizing Hortonwork’s Hadoop and provided
the capability for real time streaming and predictive analytics, including self-service reporting
in visualization software using Tableau
Fluid Analytics is a highly-flexible,
high-reuse, rapid iteration process designed to
provide more frequent, more relevant and highly
measurable business outcomes.

17. Confidential
Saama Technologies, Inc
Saama Fluid Analytics for Insurance – Conceptual Architecture
StructuredData UnstructuredData External Data
Hadoop Ecosystem
Data Quality &Standardization
iMAP culls data from
multiple sources,
including: internal
structured data
(policy, claims,
customer, billing,
telematics and call
center); internal
unstructured data
(claims notes,
telematics, log data);
real time geospatial
data; syndicated
data from third
party sources;
enterprise search,
and social media.
The data is
presented in a visual
user interface that is
intuitive, insightful
and actionable.
Charts and
dashboard are
enriched with
industry-standard
KPIs, implemented in
multiple server
platforms and
mobile devices.
The Hadoop
Ecosystem is leveraged
for processing,
managing and
generating large data
sets. For the first time,
analysts, underwriters
and actuaries will have
direct access to the
data in native format
in a self-service mode.

18. Confidential
Saama Technologies, Inc
The Capabilities that this could bring were significant
• Enterprise-wide data model that consolidates actuarial and financial data across multiple line of
businesses.
• Extensible and flexible framework for easier customization across Policy, Billing, Agent and Claims
functional areas.
• Predefined data mapping templates that interface with source systems to mitigate development
efforts and accelerate implementation of a robust data warehouse.
• Data architecture that maintains availability, reliability, scalability and data load strategies to follow
best practices that ease ongoing data maintenance.
• Advanced analytical data components to facilitate Business Intelligence strategy that enables
customers to quickly measure success and improve their performance with highly rated performance
metrics.
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19. Confidential
Saama Technologies, Inc
Summary and Key Resources

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Saama Technologies, Inc
Key Takeaways
• The insurance engagement model is/has changed
• Managing new and existing data and analytical needs is achievable through:
– Industry accelerators of Fluid Analytics for Insurance
– Visualization for business users using capabilities like Tableau
– Manage traditional and new data sources regardless of volume, veracity or
variety through open source capabilities

21. 20Copyright © 2016, Saama Technologies | Confidential
About Saama
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Algorithms
1
Purpose
Accelerating BusinessOutcomes using
Data Driven Insights