Who Should Attend

Meet Senior Decision Makers From Insurance Carriers In The US & Canada Across:


  • Private & Commercial Auto Insurance
  • Home & Property Insurance
  • Life & Health Insurance
  • Workers Compensation Insurance

With Job Titles Including:


Managing Directors, CEOs, CIOs, COOs, SVPs, AVPs, VPs, Chief Knowledge Officer, Directors, Heads of, Chiefs, Analysts, Leads of...

  • Data Science
  • Data Strategy
  • Predictive Analytics
  • Advanced Analytics
  • Actionable Analytics
  • Risk Insights
  • Data Integration
  • Governance & Stewardship
  • Human Resources
  • P&C Business Intelligence
  • Architect/Architecture
  • Claims
  • Underwriting
  • Fraud Management
  • Customer Engagement, Experience & Retention
  • Social Media

Plus Key Suppliers Including:


  • Insurance Data Management And Analytics Firms
  • Full Cycle Data Management Companies
  • Predictive Analytics Development Platforms, For Use In Underwriting, Reserving, Marketing, Pricing, and Claims
  • Predictive Analytics Technologies
  • Data Governance Tool Providers Including, Data Stewardship Platforms & Data Quality Platform
  • Data Platforms Including Hadoop Platforms & SQL Analytics Platforms
  • Data Visualization Platforms &Software
  • Data Integration Services Including, Data Warehousing & Cloud Analytics
  • 3rd Party Data Aggregators
  • Fraud Analytics Platforms &Tools
  • Workforce Management Solutions
  • Business Intelligence Firms
  • Internet of Things (IoT) For The Insurance Industry

Main Conference Agenda: September 21 & 22, 2016

Day One: Sharing Working Examples From Multiple Insurance Business Lines On The Execution Of Data Analytics Strategies To Grow Customer Revenues And Profit

8:50 Chair's Opening Remarks

Chaired by : Richard Pluschau, VP, Head Of Data Standards And Data Life Cycle Management, AIG Insurance

OPENING KEYNOTE PANEL: LINKING DATA ANALYTICS TO PROFIT AND REVENUE GROWTH

9:00 Strategies And Techniques For Connecting Data Analytics To The Business To Grow Customer Revenues And Profits: What Are Insurers Doing With Big Data To Positively Impact The Bottom Line?

  • Data-Driven Organization > Insight-Driven Organization : Assessing measures that were taken to change the business culture and make the shift to incorporate data analytics-based decision making
  • Driving Profitable Growth : Evaluating how business outcomes were found in using data and analytics to drive profitable growth
  • Ensuring Positive Bottom Line Impacts : Understanding how strategies were developed to ensure the analytics program was effective at positively impacting the bottom line
  • Executive Education & Skill Sets : Understanding how the insurer undertook executive education for its employees on the benefits of analytics
  • Data Governance : Assessing how to implement and use data governance programs as an integrated information management solution
  • Staying Ahead of The Big Data Trend : Learning what are the new predictive models that are being built and implemented to stay ahead of the big data trend
  • Moving Beyond Telematics : Driving results from big data in commercial and personal lines, beyond automotive telematics

Moderated By: Richard Pluschau, VP, Head Of Data Standards And Data Life Cycle Management, AIG Insurance

Panelist : Jodie Lewan, Data Governance, Zurich North America

Panelist: Christine King, AVP Analytics, CNA Insurance

Panelist: Alexander McGinley, VP US Marine, XL Catlin

9:30 Extended Questions & Answer Session

USING ANALYTICS TO SUPPORT PROFITABLE DECISION MAKING

9:40 Strategies For Structuring A Data Analytics Program To Enable Improved Information Handling To Support Profitable Decision Making

  • What Data Is Going To Have More Business Value? Learning what data is unique for each organization based on the markets they serve and the appetite for risk
  • Bringing In Real-Time Data With Existing Data : Assessing the changes that needed to be made to combine existing data and new data sources to improve the analytics program and develop decision making
  • Formulas For Pricing Risk : Learning what kind of data was helpful in understanding risk: What were the elements of risk and how were they analyzed?
  • Dealing With Lack Of Data : Discussing how to use analytics where you have sparse data for insurance decisions
  • Delivering Benefit from Analytics: How to get started at no cost? How to keep up with the demand and continuously deliver benefits in a more mature analytical environment.

Case Study 1 : Alexander McGinley, VP US Marine, XL Catlin

10:10 Morning Networking Refreshments

10:40 Case study 2 : Carl Lambert, VP National P & C Business Intelligence, The Co-operators Insurance

11:10 Question & Answer Session

NEXT-GENERATION ANALYTICS: COGNITIVE COMPUTING

MAKING THE SHIFT FROM 3RD GENERATION PREDICTIVE MODELS TO
4TH GENERATION COGNITIVE COMPUTING

4TH GENERATION - COGNITIVE COMPUTING

11:20 Understanding Ways To Build And Implement Cognitive Capabilities And How It Applies To The Insurance Business Across All Lines

Initiating A Cognitive Computing Strategy

  • Demonstrating working examples on how cognitive computing and artificial learning has been applied to improve claims handling, underwriting risk selection and increase customer engagement
  • Comparing the effectiveness of different cognitive computing solutions to effectively settle claims
  • Discussing how cognitive computing can replace call center employees and provide more efficient and cost-effective customer service
  • Learning how to use cognitive computing to read underwriting guidelines and risk submissions to expedite the underwriting process

Neal Silbert, Predictive Analytics Vice President, Zurich North America

11:50 Question & Answer Session

IMPLEMENTING THE DATA GOVERNANCE PROGRAM TO IMPROVE THE DATA ANALYTICS OPERATION : WHERE DO YOU START, AND HOW DO YOU SUCCEED?

IMPLEMENTING DATA GOVERNANCE PROGRAMS

12:00 Assessing Best Practices For Effectively Implementing The Routes
For A Data Governance Program: Where Did They Start And How Did
They Succeed?

Get Answers To Key Questions: Get a 360-Degree View
  • How is the business set up?
  • Did they have buy-in from all of the different department and lines of business?
  • What type of data governance program did they try to set up and who was their executive sponsor?
  • Did they set it out of IT, was it a part of finance was it part of the data organization?
  • How have they succeeded?
  • Is there a push to put a potential office of data governance to support the data governance needs?
  • How to keep interested participation from the members?
  • How to use Data Governance as a component of an integrated Information Management solution?
  • Where and how have they failed ? Was it a support or enterprise issue?
Key Takeaways To Improve Your Data Analytics Operation
  • Knowing how to catalogue and understand the types of data sets available for analytics
  • Establishing how appropriate governance stewardship controls can be used for smarter pricing decisions
  • Concluding the most effective tools and strategies to validate data for accurate pricing models

Case Study 1: Lydia Reid, Information Standard & Governance Manager,
American Family Insurance

12:30 Questions & Answer Session

12:40 Networking Lunch

1:40 Data Governance Case Study 2 : Kenneth Patria, Data Strategy Manger, Liberty Mutual Insurance

2:10 Questions & Answer Session

DATA ANALYTICS EXECUTION MODELS

USING NEW CUSTOMER-DRIVEN INSIGHT MODELS TO DELIVER REAL BOTTOM LINE IMPACT FOR THE INSURANCE CARRIER AND CREATE NEW REVENUE STREAMS

CASE STUDY 1: STRATEGIES FOR INCREASING CUSTOMER LOYALTY

2:20 Leveraging Predictive Analytics To Increase Customer Retention And
Improve Loyalty

  • Discussing how predictive modelling platforms were employed to generate smarter value propositions that increases customer loyalty
  • Learning how to link customer data derived from different data sources to better understand customer opinions on service
  • Discussing how to leverage consumer data from new state-of-the art technologies technology to better understand customer expectations on customer service
  • Measuring Commercial Benefits & Impacts : Concluding how impactful an influence predictive analytics can have on increasing customer retention and loyalty

Heather Mills, Digital Touchpoints Sr Analyst, American Family Insurance

2:50 Questions & Answer Session

3:00 Afternoon Networking Refreshments In The Exhibition Area

ADVANCED ANALYTICS FOR BETTER CLAIMS MANAGEMENT & FRAUD
REDUCTION

3:30 Hearing Success Stories For Employing Predictive Analytics To
Reduce The Amount Of Hard And Soft Fraud And Improve Claims Handling

Get Answers To Key Questions: Get a 360-Degree View
  • What implementation methods did they use?
  • How did they use predictive analytics to do insurance claims better?
  • How did they look at the claims to understand where there was most fraudulent activity?
  • Was it just change of software package or was real-time scoring incorporated as part of the plan?
  • What did they choose to do with it and what were the obstacles that occurred?
  • What tool was chosen? Why did they choose that tool? What worked and what did not perform? What were the challenges of implementation?
Key Takeaways To Improve Claims & Fraud Management
  • Knowing how to improve the insurance claims process when you first notice loss
  • Establishing how to use predictive analytics to see how many accidents are likely to occur, how do these accidents occur and what are the most common factors

Case Study 1 : Richard Pilotte, Assistant Vice President & Actuarial Director, Zurich North America

Case Study 2: Dominic Fortin, Sr Director Business Intelligence Solutions & Advanced Analytics, The Co-operators Insurance

4:30 Questions & Answer Session

5:00 Day One Concludes With Closing Remarks From Richard Pluschau, Head Of Speciality Insurance Data Product, AIG Insurance

5:10 - 6:10 Networking Drinks Reception In The Exhibition Area

Day Two: In-Depth Look At New Data Sources, State-Of-The-Art Technologies & Next-Generation Cognitive Computing.

> Data Sources & Data Ownership Breakouts: Auto, Health, Property

8:50 Chair's Opening Remarks

Chaired by : Richard Pluschau, Head Of Speciality Insurance Data Product, AIG Insurance

NEW DATA SOURCES: HIGH-LEVEL KEYNOTE PANEL DEBATE

9:00 Strategies For Capitalizing On New Data Sources That Could
Revolutionize Every Line Of Insurance Within The Next 5 Years: Enrich
Policy Holder Insights, Improve Customer Relationship

  • Social Media & Internet Cookies : Hear how using policyholder's internet cookies and monitoring social media activity can determine whether they have been shopping/spending money to determine their insurance rate
  • Weather Data : Learning how this new unique data source can be used across all lines: What are insurers' plans?
  • Wearables : Life insurance companies are using wearable devices but what implications do they have for workers compensation. See how insurers can draw the connection across lines
  • Geo-Location : Learning how geo-location data can be gathered and analyzed to improve underwriting decisions for property insurers
  • Smart Homes : How can insurers leverage this data through IoT?
  • Smart Auto Telematics : Hearing the auto insurers perspective on the impact of automation and next-generation telematics technologies: What new data will now be available and how can it be used to develop better scorecards?
Key Takeaways From The Discussion
  • Increase agility in managing data and analytics
  • Take relevant new data and use it in a new way to add value to the business
  • Establish a wider collaboration within the industry through information sharing without compromising trade secrets

Moderated By : Richard Pluschau, VP, Head Of Data Standards And Data Life Cycle Management, AIG Insurance

Panelist : Cameron Swofford, Director of Business Intelligence & Analytics, National
General Insurance

Panelist : Conor Jensen, Analytics Program Director, Zurich North America

9:30 Audience Participation And Questions & Answers Session

WEATHER UNIQUE DATA SETS

9:40 Examining New Modelling Techniques And The Impact Of Changing Weather Patterns On Commercial Insurance Lines

Weather data is vital to both policyholders and insurers and has historically been used to a certain degree. It has been quietly available, but now you have more computing techniques and computing power to harness it, and look at it on a more granular level

Learn How To Use This Data To Differentiate And Become Essential
  • Understanding all the impacts and implications of independent variables on certain weather predictions and how that ties back to policy claims Findings ways to not only use weather data but also incorporate the ability to understand liability and patterns of weather
  • Establishing how effective weather data has been in intelligently writing risk and developing pricing plans

Conor Jensen, Analytics Program Director, Zurich North America

10:10 Questions & Answer Session

10:20 Morning Networking Refreshments

SOCIAL MEDIA DATA SETS

10:50 Examining New Modeling Technologies And The Impact Of New Social Media Data On Increasing Customers

11:20 Questions & Answer Session

CASE STUDY 2: IDENTIFYING NEW, MORE PROFITABLE CUSTOMERS

11:30 Sharing Key Approaches For Sourcing, Integrating And Applying Data
To Identify New, More Profitable Customers In Commercial Lines

  • Understanding how data was collected and which sources were found most effective
  • Using different analytics around customer experiences across commercial lines to highlight opportunities to new revenue streams
  • Hearing new segmentation approaches for business owners versus fleet management companies and the impact of those tools
  • Measuring Commercial Benefits & Impacts : Delivering results on the bearing predictive analytics had on increasing customer numbers

Cameron Swofford, Director Of Enterprise Business Intelligence & Analytics, National General Insurance

12:00 Questions & Answer Session

12:10 Networking Lunch

OVERCOMING DATA ANALYTICS CHALLENGES

DEALING WITH LACK OF DATA | USING 3RD PARTIES FOR ANALYTICS

EFFECTIVE ANALYTICS DESPITE LACK OF DATA

1:10 Discussing How Commercial Insurance Companies Are Using Analytics In The Absence Of Thorough Datasets

  • Understanding how data was gathered and organized to ensure uniformity
  • Evaluating ways to store third party data and need for any encryption
  • Learning what kinds of different technologies are used to implement the analytical algorithms
  • Understanding ways to identify the most significant rating characteristics to utilize in a multivariate product
  • Learning how to better understand the risks customers are exposed to when you only have incomplete data to work with

Crystal McQueen, Predictive Analytics Manager, Great American insurance

1:40 Questions & Answer Session

HUMAN CAPITAL MANAGEMENT

UNDERSTAND HOW TO CONTINUE TO GET THE TALENT YOU NEED AND RETAIN THEM TO BUILD A COMPETITIVE ANALYTICS WORKFORCE AND REDUCE HIRING & TRAINING COSTS

ATTRACTING & HIRING TALENT

1:50 Benchmarking Best Practices For Attracting Talent That The Industry Is Looking For And Matching Skill Sets To Roles To Build A Competent Work Force

Real data-scientists are a rare breed. And while many people will claim the title over the next few years, few will have the skills to drive innovative insight within their organizations.

  • Addressing the challenge of attracting the right human capital to set strong foundations for a data analytics team
  • Learning what skills and traits insurers should be looking for to increase employee engagement with the role and reduce turnover
  • Learning whether or not the insurance industry can hire people from outside the industry: Are skills transferable and applicable?
  • Hearing how organizations are linking business goals, HR recruitment strategies and workforce requirements and understanding how data analytics has fit in into the equation

Dominic Fortin, Sr Director Business Intelligence Solutions & Advanced Analytics, The Co-operators Insurance

2:20 Question & Answers Session

HEALTH & WORKERS COMPENSATION INSURANCE

3:00 Discussing The Impact Sharing Wearable Devices Will Have Policyholder's Agreements And Deliver More Clarity On How To Recover Data And Ultimately Price Premiums Accurately

  • Wearable Devices : Learn which wearable devices coming on the market that qualify as medical devices and identify which data is medically protected and has fewer privacy implications
  • Legal Perspective : Understand the new data regulations are governing wearable technologies.

Jun Sheng, Sr Director Of Advanced Analytics, John Hancock Insurance

3:30 Question & Answer Session

LESSONS LEARNT

DRIVING BUSINESS VALUE  THROUGH THE APPLICATION OF ANALYTICS FOR  ALL PROPERTY AND CASUALTY INSURANCE LINES

DRIVING BUSINESS VALUE ACROSS ALL LINES: CLOSING ROUNDTABLE

3:40 Fully Leveraging Predictive Analytics And Real-Time Customer Engagement To Deliver Better Decision Making, Higher ROI And Greater Profits Across All Lines

The audience and speakers engage in an interactive, round table workshop environment to consider several topics and come to the closest conclusion on their impact on results. Strategic insurance heads responsible for creating and executing analytics strategies will be the greater benefactors of this closing round table.
   

  • Evaluating how insurers are measuring what they have tried and whether it been successful or not?  Have results improved enough to justify the costs involved in doing this?
  • Sharing business cases where practices similar to those shared over the two days have also been cost-effective and have expedited retrieve for real-time applications
  • Demonstrating ways to manage a data science team and motivating them to move something from an idea to a product

Moderated by: Richard Pluschau, VP, Head Of Data Standards And Data Life Cycle Management,AIG Insurance

4:10 Question & Answer Session

4:20 Chair's Closing Remarks

4:30 End Of Conference The Profitable Data Analytics Insurance 2016

Speaker

Key Takeaways

Solutions At A Quick Glance: Helping You Apply Your Analytics Program And Prioritize Resources

  • Attract New & More Profitable Customers
  • Improve Customer Relationships Through More Sophisticated Segmentation
  • Retain Existing Customers For Longer And Cross Sell Additional Products
  • Increase Profitability, Improve Process Efficiency And Reduce Administration Costs
  • Create New Revenue Streams And Increase Sales
  • Optimize Pricing & Risk Selection In Underwriting And Fight Fraud

Strategic Level Learning Solutions Include:

  • Execution : Structure Your Data Analytics Program To Maximize Commercial Value And ROI Across All Lines
  • Leadership : Learn Best Practices For Recruiting And Retaining Human Capital And Build A Competitive Workforce And Save Money On Re-Hiring
  • Data Governance & Stewardship : Understand The Different Routes For Data Governance Program: Where Do You Start And How Do You Succeed?

Benchmark Against The Latest Innovative Approaches & New Ideas

  • Create New Revenue Streams : Learn What Needs Done By Insurers Across All Lines To Encourage Data Sharing From New Sources

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