ISO s Data Management Roadmap. June 11, 2015

Transcription

1 ISO s Data Management Roadmap June 11,

2 ISO Data Innovation Two broad areas of focus: Improving the statistical reporting experience Reporting instructions (Statistical Plans) Tools for data quality and reporting (Statistical Web Services, Workers Compensation) Meeting emerging data needs Data for predictive analytics Additional data collaboration opportunities 2

3 Statistical Plan Usability Current phase Adding hyperlinks between TOC and individual data elements FAQs, explanations, examples Adding more of them Making them easier to find Under consideration Moving from PDF towards more interactive platform 3

4 Statistical Plan/Reporting Evolution How can statistical reporting evolve to help meet emerging challenges? Moving beyond traditional fixed-code, fixed-byte, flat file approach? XML format JSON format Communication via API Potential benefits Providing alternative options 4

5 Statistical Data Quality Current state Automated transactional data validation edits Heavy analyst involvement in identification of distributional anomalies and other issues not currently detectible by automated means 5

6 Statistical Data Quality Future State Automated methods for identifying issues Notify you of concerns as soon as possible after receipt of data Streamlining communication channels 6

7 Statistical Web Services Current phase Improved integration of ISO s transactional validation edits into company processing Mechanism to facilitate correcting misreported data Improved access to company submission history (status, alerts, errors, some distributional analysis reports) 7

8 Statistical Web Services Under development Additional data quality tools Communication Portal Integration with other data quality information (Annual Verification, Report Card) 8

9 Workers Compensation Leveraging analytics to improve WC data quality Improvements in data quality should improve WC predictive analytics Claims Policy data Medical data 9

10 Workers Compensation Current Phase State jurisdictions and WC carriers are using wcanalyzer to assess their overall compliance and identify data issues Version 2.0 of wcanalyzer design enhancements more intuitive dashboards Under Consideration Data Benchmarking & Predictive Analytics 10

11 Emerging Data Issues Biggest technological challenges around data*: Variety, Veracity Variety of formats (unstructured text, photos, social media, etc.) Expanding variety of data elements and sources due to emerging business issues Drones Home Telematics (Connected Home) Smart Car Technology Sharing Economy (e.g. AirBnB) Veracity: developing systems for verifying data accuracy * Strategy Meets Action, Big Data in Insurance (ISO/SAS co-sponsored white paper), June

12 Supporting Your Predictive Modeling Current phase Create enhanced predictive analytics to support insurance functions Provide carriers with the ability to append modeling/analytic data from multiple sources to their own data Under development/consideration Integrate with additional Verisk, third-party and social media data sources Collect international data Provide carriers with analytic infrastructure and tools to perform modeling 12

13 New Product: ISO RiskElements Provide archived data to P&C insurers to use as a significant source of the raw material for their in-house predictive modeling efforts ISO will build on and leverage its experience managing insurance data and assembling analytic datasets as well as its unique data assets Goal Become the first and primary source of data for predictive modeling projects for the P&C insurance industry 13

14 RiskElements Product Design RiskElements Data Asset Vintage: Delivery Modes Verisk Data Data appended to customersupplied file Public Data 3 rd Party Proprietary Data Analytic file built from scratch 14

15 ISO/Carrier Partnered Data Initiative Currently in ideation phase / assessment of interest ISO could provide data warehousing capabilities Integrate carrier s multiple data sources Provide cost-effective staging and analytics platform Enable automated statistical data feed Leverage and integrate with additional modeling data sources (Verisk, third party, social) Provide preferential access to new ISO benchmarking analytics 15

16 Partnered Data Initiative: Overview Ease of use Offerings Easy stat reporting Custom data mart Enhancement Offerings Enhanced data sources Advanced analytics 16

17 Partnered Data Initiatives: Benefits of Partnership ISO provides meaningful & accurate reports with deep domain expertise Our unique data assets embed in business workflows We intend to further extend our value through Partnered Data Initiatives: Aid Innovation Premium Access Premium Pricing Enhance insurance products to create niche Enhance retention, uw profits & loss prevention Enhanced data sources with ISO RiskElements Develop & customize your own analytics Preferred partner pricing Enhance data processes while reducing TCO 17

18 Use Cases on Key Data Areas Location / Building Benchmarking, exploratory data analysis, risk analysis and mitigation Business Entity Peer grouping, target markets, life time value, trends and portfolio analysis Quotes (Comparative Rater) Performance baseline, digital analytics, census and demographic assessment Audits / Loss Control Individual Loss histories, unstructured data analysis, pricing and loss reduction Advanced analytics using heterogeneous dataset connectivity 18

19 Questions? No part of this presentation may be copied or redistributed without the prior written consent of ISO. This material was used exclusively as an exhibit to an oral presentation. It may not be, nor should it be relied upon as reflecting, a complete record of the discussion.. Insurance Services Office, Inc., 2015