Disrupting Insurance with Advanced Analytics The Next Generation Carrier

ConfidentialSaama 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


Speakers

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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 [email protected] @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 [email protected]


• Malcolm Gladwell • The key to good decision making is not just knowledge. It is the

understanding

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Believe the Hype……..

The “Right Now” disruption

Wednesday, May 3, 2023 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

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 UnderwritingEmbracing Big Data


Opportunities to Achieve Data-Driven Business Objectives through a

Modern Data Architecture


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.


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.


TraditionalSolutions Innovation

Traditional EDWFluid Analytics

for Insurance/Hado

op

Which road to take?

Should we wait for core system

replacement first?

Start the advanced analytics

journey along with core system

replacement?


A Radical Shift in Data StrategyA 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.

ConfidentialSaama Technologies, Inc 1

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New Affiliate Data

3rd Party Data

Social Media, UBI,

Clickstream, ...

Guidewire

Analytics Engines

Data Warehouse

Data Lake

Agg

rega

tion, Q

uerie

s, S

ervi

ces,

Bus

ines

s Lo

gic

Dashboards

Scorecards

API Integration

Embedded Analytics

Data Feeds

Ad-hoc Analysis

PrescriptiveModels

PredictiveModels

Report Subscriptions Self-service

Discovery, Self-service

Dat

a R

efin

ery -

Dat

a M

anag

emen

t and

Gov

erna

nce

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


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 1

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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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How it all comes together


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.


Saama Fluid Analytics for Insurance – Conceptual Architecture

Structured Data Unstructured Data

External Data

Hadoop Ecosystem

Data Quality & StandardizationiMAP 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-standardKPIs, implemented in multiple server platforms and mobile devices.

The Hadoop Ecosystem is leveragedfor processing, managing and generating large data sets. For the first time, analysts, underwriters and actuaries will have direct access to thedata in native format in a self-service mode.


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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Summary and Key Resources


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

21Copyright © 2016, Saama Technologies | Confidential

About Saama

5000+Engagemen

ts

900+Employees

50+Global 250

3000+Algorithms

1Purpose

Accelerating Business Outcomes using Data Driven Insights

Disrupting Insurance with Advanced Analytics The Next Generation Carrier

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Transcript of Disrupting Insurance with Advanced Analytics The Next Generation Carrier