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How to Become an Analytics Ready Insurer Wednesday, March 25, 2015
Featured Presenters
2
Cindy Maike General Manager, Insurance
Hortonworks
Josh Lee Director, Global Industry Marketing
Informatica
Page 3 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
How to Become and Analytics-Ready Insurer
Cindy Maike, General Manager - Insurance
Page 4 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Data never sleeps and…
Source: www.domo.com
“with every status we share, every article we read or every photo we upload
we are creating a digital trail that tells a story…”
Page 5 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Clickstream Capture and analyze website visitors’ data trails and optimize your website
Sensors Discover patterns in data streaming automatically from remote sensors and machines
Server Logs Research logs to diagnose process failures and prevent security breaches
New types of data
Sentiment Understand how your customers feel about your brand and products – right now
Geographic Analyze location-based data to manage operations where they occur
Unstructured Understand patterns in files across millions of web pages, emails, and documents
It is growing exponentially – with new business challenges and potential delays
Page 6 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Hadoop driver: Enabling the data lake SC
ALE
SCOPE
Data Lake Definition • Centralized Architecture
Multiple applications on a shared data set with consistent levels of service
• Any App, Any Data Multiple applications accessing all data affording new insights and opportunities.
• Unlocks ‘Systems of Insight’ Advanced algorithms and applications used to derive new value and optimize existing value.
Drivers: 1. Cost Optimization 2. Advanced Analytic Apps
Goal: • Centralized
Architecture • Data-driven
Business
DATA LAKE
Journey to the Data Lake with Hadoop
Systems of Insight
Page 7 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Business and application silos have caused many insurance carriers to have disparate data and processes; however, a Data Lake enables “all data is searchable” capability
Product Pricing & Underwriting
• Risk/claims experience analysis
• Profit testing • Reinsurance analysis
Risk Analysis • Identification of risk factors • Analysis and development
of risk models • Trend analysis
Campaign • Target selection • Response optimization • Communication tracking • Campaign performance
Profitability Analysis • Margins vs. claims and expense
analysis • Product, segment, customer
profitability
Claims Analysis • Analysis of claims types,
frequencies, amounts claimed and paid
• Fraudulent claims analysis • Analysis of settlement period
Product Management • Product performance analysis • Analysis of competitive products • Market requirements analysis for new
products • Forward premium earning analysis
Segmentation Management
• Segment definition • Segment activity analysis • Segment targets/
achievements analysis • Cross-selling analysis
DATA LAKE
Systems of Insight
Customer Management and Retention
• Response optimization • Communication tracking • Campaign performance • Target selection • Persistency experience analysis • Identification of potential lapses • Competitive analysis
Page 8 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
APPLICATIONS
Analytics-ready Insurers leverage a modern-day data reference architecture blending traditional and new data
HDP Hadoop Cluster
1
Mul1tenant Processing: YARN (Hadoop Opera,ng System)
NoSQL
HBase Accumulo
Stream
Storm
Others
Security (Ranger, Knox, Hive, HDFS, etc...)
Governance Falcon
Script
Pig
SQL
Hive
Java
Cascading
Search
Solr
° ° ° ° ° ° ° ° ° ° °
° ° ° ° ° ° ° ° ° ° ° °
° ° ° ° ° ° ° ° ° ° °
Opera1ons (Ambari, ZooKeeper, Oozie)
Ingest
Sqoop Flume KaJa
DATA REPOS
DATA SOURCES
• Enhance agent productivity • Detect fraud • Launch prevention services • Price using sensor data • Subrogation & litigation • Claims leakage & accuracy • Mileage verification • Payment analytics
Transcriptions
EDW
Underwriting
Claims
Commission& Billing
Product
Finance
Application Documents
Emails CRM Records
Medical Bills Underwriting Notes
Prior Loss & Vendor Repts
Policy Records
Marketing Research Claims Data
Sales Portals Mobile Telematics
Mortality Tables
Clickstream Web Logs
Risk & Claim Models Social Media
In-‐Memory
Spark
Metadata Management HCatalog
° °
° °
° N °
Linear Scale Compute & HDFS Storage
Page 9 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Customers using HDP to meet insurance priorities
Rising Claims Costs (frequency and severity)
Top 3 Challenges facing Insurance Industry Today
Key Business Requirements
Change in Customer Engagement Model
Data Explosion (Complexity of Risk/
Underwriting Information)
n Access to internal and external disparate risk information to make informed underwriting and risk analysis decision (support an underwriting ‘cockpit’ for complex risks)
n Sensor-based insights for pricing (driving habits and usage) n Identification of similar risk characteristics and performance (explore and analyze prior
submissions), text analytics of unstructured submissions n Ability to “tailor personalized prevention based services” vs. traditional product-based
policy offering n Support social/insured ‘supply chain’ network analysis
n Single customer “golden” record n Enable differentiated experience, guidance and recommendations based upon customer
insights n Call center/agent productivity and effectiveness gains through “total view of the
customer” n Support cross-sell opportunities n Web path optimization (identity, state, insight, guide, action)
n Sensor-based insights for claims analytics: product liability, claimant liability (e.g. auto claim: speed at time of accident, proximity, application of brakes)
n Analysis of unstructured claim notes (text analytics) and information n Link analysis across multiple claims n Support enhanced subrogation opportunities n Claim severity model and enhanced loss prevention models
Page 10 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Insurance Business Value Matrix using HDP N
ew T
ypes
of
Ana
lytic
s
New Types of Data
New Types of Data New Analytics Apps
• Sentiment
• Click-stream
• Sensor
• Geographic
• Server Logs
• Unstructured
Existing Data
Exis
ting
Ana
lytic
s
RDBMS
MPP
EDW
• EDW & ETL data & load balancing
• Cost & flexibility • Building new skill
sets • Scale out using
commodity hardware
• Single-View of Customer showing full 360-degree profile and history
• Clickstream analysis for Next Best Action with Customers
• Analyzing submission and claims models against larger historical data sets
HDP
HDP
New Historical View
IT Optimization New Data Influencers
• Collecting Sensor/Telematics for Usage Based Insurance
• Sentiment • Enhanced Loss
Control / Prevention Services
• Needs based coverage vs. traditional coverage
HDP
New Analytics Applications • Text Analytics and Link
Analysis for Claim Anomaly and Fraud Analysis/Detection
• Enhance Risk Analysis with Related Party Network Link Analysis
• Enhanced Claim Severity and Frequency Models using “new” predictive data
HDP
Page 11 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Hadoop for the Enterprise: Implement a Modern Data Architecture with HDP
Customer Momentum
330+ customers (as of Q4 2014)
Hortonworks Data Platform • Completely open multi-tenant platform for any
app & any data. • A centralized architecture of consistent
enterprise services for resource management, security, operations, and governance.
Partner for Customer Success • Open source community leadership focus on
enterprise needs • Unrivaled world class support
• Founded in 2011 • Original 24 architects, developers,
operators of Hadoop from Yahoo! • 600+ Employees • 800+ Ecosystem Partners
Page 12 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
HDP: Any Data, Any Application, Anywhere
Any Application • Deep integration with ecosystem
partners to extend existing investments and skills
• Broadest set of applications through the stable of YARN-Ready applications
Any Data Deploy applications fueled by clickstream, sensor, social, mobile, geo-location, server log, and other new paradigm datasets with existing legacy datasets.
Anywhere Implement HDP naturally across the complete range of deployment options
Clickstream Web & Social
Geoloca1on Internet of Things
Server Logs
Files, emails
ERP CRM SCM
hybrid
commodity appliance cloud
Over 70 Hortonworks Certified YARN Apps
Page 13 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Why Informatica + Hortonworks Features Benefits Visual development environment
Increase productivity 5x, operational efficiency, reuse
200+ high-performance connectors (legacy & new)
Move all types of customer data into HDP faster
100+ pre-built transforms for ETL & data quality
Provide broadest out-of-box transformations on Hortonworks
100+ pre-built parsers for complex data formats
Analyze and integrate all types of data faster
Joint MDA reference architecture
Complementary capabilities to accelerate customer success
100K+ trained Informatica developers
Use existing & readily available skills for big data
Page 14 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Call to Action
• EXPLORE à Learn from your current + New Data • Look outside your industry for additional
leaders
• DISCOVER à New insights with traditional data and “new data” sources”
• Avoid using traditional analysis methods with new data…it is truly different…... • Understand the skills required • Leverage the “right” technology options
• INNOVATE à Launch new innovative products, better serve and attract customers
• Don’t fear “experimentation” • Capitalize on the Opportunity
Page 15 © Hortonworks Inc. 2011 – 2015. All Rights Reserved
Closing thoughts
“Some people see a trend & see threat. Innovators see the same trend & see opportunity.”
Jim Carroll, the world’s leading futurist, trends & innovation expert
Become an Analytics Ready Insurer Josh Lee – Global Director, Insurance Marketing March 2015
Who is Informatica?
17
• 900+ in Financial Services including:
• 25 out of the top 30 P&C, Life Providers in the U.S.
• 35 out of the top 50 global banks
• 85 Insurance Customers
• Leader in #1 growth sector within infrastructure software: Data Integration and Data Quality
• In the Leaders Quadrant on virtually every Gartner Magic Quadrant
• Data Quality
• Data Integration
• Master Data Management
• Data Security
Why Do Analytics in Insurance?
• Grow Revenue • Average insurers must add 13% new policyholders annually
to maintain flat revenue • Combat Fraud
• Insurance fraud tops $40B/year • Fraud drives up premiums by up to $700/year per family
• Develop New Products • By 2030 the “over 65” demographic will be 20% of population
• Reduce Risk • Since 2013, over 50% growth in magnitude 3+ earthquakes
in Oklahoma • …and a whole lot more!
18
Analytics…Good and Bad
19
Unknown – 87% Bob – 6%
Ann – 7%
How does this happen?
When I wanted this!!
Courtesy of Beautiful Data
Where Does My Data Come From?
20
Apps
Files
Custom
Structured
Structured but needs to be integrated
Structure varies or absent, integration
required
Structure indeterminate
Integration Required, formats and storage
constrained
Making the Most of Infrastructure
21
Traditional Data Warehouse
Documents and Emails Social Media, Web Logs
Risk Analytics Claims
Data Quality
Powercenter Big Data Edition
Powercenter Big Data Edition
Mainframes, Apps
• The Reality is… • Everyone has LOTS
of data sources • New and Old data will
be around forever • But…
• New data types and shapes every day
• Data management needs to be reusable
• Data volume is growing
Benefits to Insurers
22
Risk
Return
Current
Desired?
Portfolio Optimization
More Storms, More Data
Bigger, More Diverse Populations Data From Everywhere
A Powerful Analytics Foundation
23
Powercenter Big Data Edition
Integrate, clean and optimize
Discover, shape and leverage
Thank You And
Questions!!
24
Next Steps FREE TRIAL DOWNLOADS
marketplace.informatica.com/bdehortonworks
community.informatica.com/solutions/vibe_data_stream_for_machine_data
More about Informatica & Hortonworks http://hortonworks.com/partner/informatica/
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