using a data lake at the core of a life assurance business
TRANSCRIPT
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Using a Data Lake at the core of a Life Assurance business
Hadoop World SummitApril 13th 2016
Rajdeep Mukherjee & Chris Murphy
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Zurich is a global insurance company founded in 1872 ,Head Quartered in Zurich Switzerland.
Zurich business is organized into three core business segments: General Insurance, Global Life and Farmers.
Zurich’s customers include – Individuals.– small businesses.– mid-sized and large companies, including
multinational corporations.in more than 170 countries.
Zurich Insurance – Introduction
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Insurance Industry – Key trends
The key trends impacting the business
– Digital Trends : Consumers are looking for simplicity , transparency and speed in their transaction with business . Relentless march of online and mobile technologies is continuing to fuel this change . A Digital transformation needs easy and quick access to data as a foundation.
– Technological : IOT and sensors presenting new opportunities and challenges at the same time and advent of Big data techs is allowing companies to process unstructured data to gain insights in conjunction with the structured data.
– Risks: Emerging risks due to new technology ,human interaction , habits needs advanced analytical models to predict losses.
– Regulatory : The effect of global regulations such as SOX , GLB and solvency II are driving insurers to ramp up Enterprise data management
Insurance
Digital Trends
Analytics Emerging Risks
Regulations
All Trends have Data in Common!
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State of Data Management
Fragmented Landscape. Rigid data design fails to Incorporate local business requirements Very long Change cycles.
OPERATIONS
oPERATION
LOB
Adhoc
Corporate
CRM PolicyMgmt
ClaimMgmt
ERP
ODS LoB Marts Spread sheets EDW
External Data
Business Users
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What Capabilities are required to Keep up with the Trends
Capability to store all data(Internal, External , Structured , Unstructured ) at Low cost. Capability to curate and expose Business Views on Demand. Data Fabric to support different workloads (Operational and Analytical). Support Rapid Change cycles. Enable metadata management and data Lineage. Govern where required don’t govern everything. Scaling up should be a low cost effort. Enable business Friendly tooling
“Make App , Analytics and Data a seamless process “Spee
d
App
Analytics
Data
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Zurich Data Lake – Conceptual Architecture
6
CRM PolicyMgmt
ClaimMgmt
ERP
Life GC UK-GI BU
CustomerPolicyClaim
CustomerPolicyClaim
CustomerPolicyClaim
CustomerPolicyClaim
Customer Policy Claim
Raw StoreEverything with History
EnterpriseProvisioning
Curation Layer LoB Views
CurationGroup Level Views
Consumption
Real-time Interactive Batch
FlatteningLabelling
Data Sources
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Zurich Data Lake - Technical Architecture
Batch Ingestion
Micro Batch
Real Time
Ingestion Framework
s
Adapters
Ingest Persist ,Process, Provision Curate
RAW Layer
Enterprise Provision layer
LoBViews
Corporate Views
Security MgmtMetadata Mgmt
Operations Mgmt
Consume
API
Interactive SQL
Batch SQL
SOURCE
KerberosAD
IBM
Ambari
RANGER
Hcatalogue
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Putting the Customer First
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Getting to our dataLegacy technology landscape
9
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Customer MatchingGuess Who
10
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Tapping the Data lakeIn the Pipeline
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Learnings
12
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Any Questions?
13