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A Successful Data Strategy for Insurers in Volatile Times (ASEAN)

  1. ASEAN WEBINAR A Successful Data Strategy for Insurers in Volatile Times
  2. Speaker Paul Moxon SVP Data Architectures & Chief Evangelist, Denodo
  3. Agenda 1. Top Trends for Insurance in 2020 2. COVID-19 – Accelerating Changes 3. Data Virtualization – Agile Data…Fast 4. Customer Case Study 5. Q&A 6. Next Steps
  4. Key Trends for Insurance in 2020
  5. 5 Shift to Services and New Products Source: A demanding future – The four trends that define insurance in 2020, Deloitte LLC
  6. 6 Mergers & Acquisitions Source: A demanding future – The four trends that define insurance in 2020, Deloitte LLC
  7. 7 M&A Poor Success Rate Source: A demanding future – The four trends that define insurance in 2020, Deloitte LLC
  8. 8 Digital Disruption Source: A demanding future – The four trends that define insurance in 2020, Deloitte LLC
  9. 9 Coronavirus Pandemic – Accelerating Changes • Disruption of the distribution chain • Brokers and agents cannot meet clients face-to-face • Acceleration of distribution disruption – move towards aggregators and direct • Less auto travel, but premiums are still rising • Accelerate move to UBI or on-demand auto insurance • Life insurance medical exams under lockdown? • Life Insurance firms are using other data and AI to set life insurance rates in absence of medical exams
  10. 10 Common Factor in These Trends?
  11. 11 Data Integration – A Journey Through Time… S Data Sources Data Ingestion Staging S Data Transformation External Data Consumers Web Logs, Click stream GEO location data Social Networks Sensor data Machine Generated New Data Sources
  12. 12 Typical Data Architecture
  13. 14 Adaptive Data Architectures • Organizations need an adaptive data architecture • An architecture that can flex and adapt to new technologies, new data sources, new formats, new protocols, new data uses, etc. while minimizing the impact on the consumers • Future-proofs the architecture • We can’t predict what technologies will emerge in next 3-5 years (or 5-10 years), but we can build architectures that will accommodate them • Allows users to access new data, new technologies using existing, familiar tools • e.g. read data from a Parquet file using Excel (via the Data Virtualization Platform) • A Data Fabric – built on Data Virtualization – provides this adaptability and protects your existing technology investments and de-risks the adoption of new, emerging technologies
  14. 15 Gartner – Technology Trends
  15. 16 Data Fabric in an Adaptive Architecture Source: Financial Services Technology 2020 and Beyond: Embracing Disruption, PwC DATA FABRIC
  16. 17 Data Fabric Architecture Reporting Analytics Data Science Data Market Place Data Monetization AI/ML iPaaS Kafka ETL CDC Sqoop Flume RawDataZoneStagingArea CuratedDataZoneCoreDWHmodel Data Warehouse Data Lake Data Virtualization Platform Analytical Views Data Science Views λ Views Real-Time Views DWH Views Hybrid Views Cloud Views UniversalCatalogofDataServices CentralizedAccessControl Enterprise Data Fabric
  17. Customer Case Study
  18. 19 AXA XL – Untangling the Data Mess • AXA XL is the Property & Casualty (P&C) and Specialty Risk Division of AXA • Serving clients in over 200 countries • AXA acquired XL Group in Sept. 2018 • #1 global P&C commercial lines insurance platform • Over 30 lines-of-business including Property, Casualty, Cyber, Construction, Professional Liability, Financial Lines, Accident & Health, and Environmental Webinar: AXA XL: Data Virtualization in the Cloud – Paco Hernandez, Director, CoE Lead - Semantic & Data Modeling at AXA XL
  19. 20 AXA XL Before Data Virtualization Source System A Data Mart X Source System B Source System C Data Mart Y Operational DS 1 Staging DS 1 Operational DS 2 BI Tool A BI Tool B BI Tool C BI Tool D Interim DB 2 Data Mart 1 Data Mart 2 Data Mart 3 CSV Interim DB 1 Semantic Layer A Semantic Layer C User-generated File User-generated File Legacy System CSV
  20. 21 AXA XL Before Data Virtualization • Inconsistency in data § Multiple versions of the same truth § Unreliable figures presented to stakeholders § Lack of understanding of data deficiencies • Lack of data access control § No tracing of who access what data and when § No role-based access to information • Loose representation of business terminology § Inconsistent naming conventions in multiple systems § Limitations of field naming options from systems (e.g. column names with no spaces, acronyms, contractions) • Excessive data replication § Multiple data jumps § Replication leading to inconsistencies • High data latency § Outdated information presented to users § Changes to data definitions slow to reach all users
  21. 22 AXA XL – Data Ecosystem & Engagement Platform (DEEP) Source System A Data Mart X Source System B Source System C Data Mart Y BI Tool A BI Tool B BI Tool C BI Tool D User-generated File Legacy System Engagement Platform Data Virtualization Landing Zone Standardized Zone Analytical Zone Data Ecosystem Data Governance & Data Quality Data Lake Workbench (Self Service) Operational Zone
  22. 23 AXA XL with Data Virtualization • Higher level of consistency in data § One leap closer to “One version of the truth” § Much more reliable calculations and traceability • Complete control on access to data § Role Based Access Control (RBAC) to every data structure and element through LDAP § Full traceability of queries • Improved representation of business terminology § High integration with Data Governance § Flexibility in naming of structures and fields to represent Business terms • Minimize data replication § Do not move data; access it from the source § Architecture based on reusable data assets § Only high-cost operations performed during ETL • Increased Agility § Changes in data definitions seamlessly performed and quickly implemented
  23. 24 Prudential Financial – Data Democratization with a Data Fabric Webinar: Data Democratization at Prudential with Logical Data Fabric – Ralph Aloe, Director, Enterprise Information Management at Prudential Financial
  24. 25 Prudential Financial – Data Challenges
  25. 26 Prudential Financial – Architecture
  26. 27 Prudential Financial – Benefits
  27. 1. Data is a critical asset to any organization – and insurance companies are no different. 2. Traditional technologies and data replication don’t cut it anymore. 3. Data virtualization makes it quick and easy to expose data from multiple source to your users while still maintaining governance and security 4. Data Virtualization is core to a Data Fabric and accelerates a wide range of initiatives; from self- service analytics to data marketplaces to regulatory reporting and compliance. Key Takeaways
  28. Q&A
  29. 30 Next Steps Access Denodo Platform in the Cloud! Take a Free Trial today! GET STARTED TODAY
  30. Thanks! © Copyright Denodo Technologies. All rights reserved Unless otherwise specified, no part of this PDF file may be reproduced or utilized in any for or by any means, electronic or mechanical, including photocopying and microfilm, without prior the written authorization from Denodo Technologies.