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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

11

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Learnings

12

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Any Questions?

13