Those leading and/or involved in efforts to better utilize analytics in the insurance and financial services business, whether you represent the business or technology side.
Highlights
Big data, predictive analytics, and advanced analytics are critical to staying relevant in today’s insurance and financial services industry. This conference brings you high-level industry presenters and actionable content which will provide insights into the way insurance and financial services companies are harnessing the value in their data.
This year's program seeks to take full advantage of the Boston, MA location, which many call the big data capital of the world. Both structured and informal networking sessions provide plenty of opportunity to forge new professional contacts.
With interactive demonstrations, problem solving exercises, and hands-on training, you will increase your knowledge base and develop skills necessary to shine light on your data.
Pre-Conference Seminar
Conference registrants are invited to participate in a pre-conference Applied Analytics Experience, geared for those who are newer to data analytics. Based on the enthusiastic feedback from last year's sold-out seminar, we are also excited to announce that this year's event will be expanded to a full day! The experience will take place on Monday, June 20thwith an overview of how to approach a “big data” problem. Attendees will be grouped into teams, given a data set, a computer, and a data problem to solve. Each team will have a different tool set to work with and a tutorial on how to utilize the tool. This innovative seminar will conclude with presentations of your results and shared learning.
Managing Director and Chief Data and Analytics Officer, AXA
Louis’s background includes independent and corporate consulting where his experience ranges from financial services (asset management, retail banking), insurance (P&C, Life and Wealth Management), and government/military industries within the federal sector as well as Fortune 50 companies. He has lead programs internationally across the disciplines of business strategy, line operations/analytics and technology management. Louis is an Adjunct Professor at Rensselaer Polytechnic institute where he instructs in Lean Six Sigma methodology and Service Operations Effectiveness. In addition, he is a retired USAFR Colonel where his leadership, strategy and operations background had been honed for over 28 years as a Logistics and Aircraft Maintenance Officer.
Director of the Social Intelligence Lab, University of Maryland
Dr. Jennifer Golbeck is a computer scientist, Director of the Social Intelligence Lab, and a professor in the College of Information Studies at the University of Maryland, College Park. Her research focuses on analyzing and computing with social media and creating human-friendly security and privacy systems. Dr. Golbeck began studying social media from the moment it emerged on the web a decade ago and is one of the world’s foremost experts in the field, discovering people’s hidden attributes from their online behavior. Her research has influenced industry, government, and the military. Dr. Golbeck writes for Slate and The Atlantic and frequently appears on NPR, including as a regular guest host for The Kojo Nnamdi Show. Her TED talk was named one of the most powerful talks of 2014.
10:45 am - 11:45 am: THE FUTURE OF FINANCIAL DECISION MAKING USING COGNITIVE COMPUTING
Sridhar Iyengar, IBM TJ Watson Research Center
IBM Distinguished Engineer, Cognitive Computing Research
Sridhar Iyengar, is a technical leader at the IBM T.J. Watson Research Center. Sridhar leads the Cognitive Applications and Solutions Research agenda for IBM. His work brings IBM's innovative Cognitive, Mobile & Analytic technologies composed as Applications & Solutions to IBM customers. Sridhar has extensive experience working with teams in IBM and with the world’s leading system integrators helping implement best practices, tools and architectural guidelines. Sridhar is also an industry standards leader and has pioneered several core Architecture, Modeling, Semantic and Data Interchange standards at OMG.
Sridhar has over 30 years of experience in the software industry (12 years in IBM) and is an expert in Data, Business, Service and Semantic modeling, Application Life Cycle Management, Cognitive Computing, Middleware and Metadata Management. Sridhar holds several patents in modeling, metadata management and tools integration and is a frequent speaker at conferences worldwide.
Vice President, Data Science, Workplace Investing, Fidelity Investments
Victor S.Y. Lo is a seasoned Big Data, Marketing, Risk, and Finance leader and innovator with over two decades of extensive consulting and corporate experience employing data-driven solutions in a wide variety of business areas, including Customer Relationship Management, Market Research, Advertising Strategy, Risk Management, Financial Econometrics, Insurance, Product Development, Transportation, and Human Resources. He is actively engaged with Big Data Analytics, causal inference, and is a pioneer of Uplift/True-lift modeling, a key subfield of data mining. Victor has managed teams of quantitative analysts in multiple organizations. For academic services, Victor has been a visiting research fellow and corporate executive-in-residence at Bentley University.
Agenda
Concurrent Session periods 2, 3, 4, and 5 each include a Micro Summit.
Micro summits are highly interactive discussion sessions limited to approximately 15 people. These sessions allow attendees to engage with each other and share ideas on hot topics regarding big data analytics.
Participate in an overview of how to approach a “big data” problem. Attendees will be grouped into teams, given a data set, a computer, and a data problem to solve. Each team will have a different tool set to work with. We’ll conclude with presentations of the results and shared learning. Limited to 40 attendees. Additional registration fee applies.
Director of the Social Intelligence Lab, University of Maryland
Increasingly companies are seeking to leverage their social media strategy to maximize customer engagement. However, there is a desire to balance the need for the insight and the desire to respect customer privacy. Dr. Jennifer Golbeck, a world leader in social media research, tracks the rise of social networks and data analytics, how new computational techniques are revealing hidden traits of millions of people online, and how this impacts the future of business. Part creepy and part surprise, this opening keynote address looks at how scientists and companies are leveraging big social data to develop new insights into customers and what they want.
Louis DiModugno, Chief Data and Analytics Officer, AXA Equitable Life Insurance Company Victor S.Y. Lo, Vice President, Data Science, Workplace Investing, Fidelity Investments Moderator: Eric Sondergeld, ASA, CFA, Corporate Vice President, Strategic & Technology Research, LIMRA
Join us as we hear from a group of analytics leaders discuss some of today’s most critical aspects of advanced analytics. Topics discussed will include the emergence of cognitive computing, the role of analytics in strategic and tactical decision making, the challenges of advancing analytics initiatives, and the threat of legislation to the fair use of data. In addition, when registering for the conference, attendees will be able to suggest questions for our industry experts.
David P. Dorans, CLU, Senior Vice President, Scor Global Life Americas Derek Michael Kueker, FSA, MAAA, Actuary, RGA Moderator: Eric Sondergeld, ASA, CFA, Corporate Vice President, Strategic & Technology Research, LIMRA
Companies are actively addressing the consumer and seller experience within life insurance, specifically when it relates to the significant time and effort it takes to issue a policy. New data sources and data science hold promise for making instant or near instant decisions, eliminating the intrusive, costly and time consuming requirements traditionally utilized. This session will discuss the latest underwriting advancements being developed and used in the industry, how good the science is, and the regulatory and operational barriers that must be overcome to make automated underwriting a reality.
Shelley Blake-Pock, President and CEO, Yet Analytics, Inc.
What
does it mean to capture experience? In this talk, Shelly Blake-Plock, CEO of
Yet Analytics will describe how through a blend of the science of semantics and
the application of tracking technologies to human performance metrics, a new
branch of technology has developed which will have significant impact upon the
way that individuals and businesses understand and leverage the data of
experience. Focusing on how the experience of employees effects the outcomes of
business, we’ll examine how the data of experience is collected and made
sense of; and how a better understanding of employee experiences may boost the
capabilities of an organization. Surveying the current landscape of data
technologies, we’ll also look into the future and consider the consequences of
what today’s decisions about experience-based data models may ultimately have
both for business and society with regards to privacy, communications, and
emergent forms of artificial intelligence.
Tom Hamilton, Vice President, Head of Voya Financial's Center of Excellence, Voya Financial
Voya Financial is using predictive modeling to deliver targeted messaging that drives thousands of positive customer actions every year. Using data from millions of customers, Voya’s analytics engine helps to identify the best call to action for each individual, and then delivers that message by phone, web or email. In this session, you will hear:
How predictive modeling can be used to deliver targeted messaging that works
How you can measure success, and use measurement to drive continuous improvement Lessons learned about getting started, building a team, and maintaining momentum
What do you do with limited data? How can you use analytics to tackle business issues – simple and complex, small and large, core and non-core? Drawing on experience from implementing analytics solutions at carriers, Nirav Dagli, CEO of Spinnaker Analytics, will share lessons and best practices that drive insights through the use of predictive analytics spanning M&A, distribution, and operations. You are encouraged to submit questions ahead of time.
Brian Berry, Director, Technical Consulting, BlumShapiro Consulting David Bradley, EVP of Solution Management, R4 Technologies
Big Data requires a mental shift: what we lack in
cleanliness or completeness, we make up for in volume and variety. In many respects, partial data can tell us
more than seemingly complete data. This
paradigm shift lies at the heart of understanding how Big Data processing works
and how Big Data yields business value.
Sears Merritt, Vice President, Data Science, MassMutual
As companies seek out talent for their analytics initiatives, academia is rapidly evolving their curriculum to produce analysts with the requisite skill sets. Forward thinking companies are helping to shape this curricula by partnering with academia. Come and learn how one company has partnered with multiple universities to foster a pipeline for well-trained analysts.
David Moore, FSA, MAAA, Senior Technical Director, Nationwide
Predictive models provide insight that can be used to transform the insurance business. The challenge is, how do you communicate the results of very sophisticated tools and gain understanding from an audience that finds the topic complex and confusing.
Learn tools and techniques to explain the results of predictive models
Hear examples of how to present to different end-users of predictive models, both internal and external to your organization
An increasing amount of data, affordable computational
power and unprecedented access to a large number of algorithms to extract
information from the data have increased the importance of analytics
organizations like never before. The combination of the internet and a growing
philosophy of sharing have led to open source implementation outpacing proprietary
implementations. This session will provide a practical guide to adopting open
source algorithms in an analytics organization. Using a publicly available
dataset, attendees will learn how open source can be used to solve a business
problem - end to end: from data exploration to model development and
deployment.
Riccardo Baron, Ph.D., Big Data and Smart Analytics Lead Americas, Swiss Re
Tomorrow for some is today for others! One re-insurer has grasped the future and its potential by creating powerful B2B2C solutions that are driven by emerging technologies such as smart analytics and the Internet of Things (IoT). These solutions allow data to facilitate services that meet the needs of clients and, ultimately, the end consumer. While some view these trends as potentially disruptive, Swiss Re will share their vision of how this evolution can be leveraged in an enterprise-transforming manner.
Mark Birdsall, FSA, MAAA, CFA, MBA, Vice President, Lewis and Ellis Moderator: Marianne Purushotham, FSA, MAAA, Corporate Vice President, LIMRA
The advances we have seen in recent years in data-focused
tools and technology have opened doors to creating up to the minute views of
the drivers of business performance and profitability. Companies can not
only combine a multitude of data sources into a single view of current business
activity and financial health but can also employ these data sources along with
advanced statistical modeling techniques to create customer, agent and business
quality/value scores. This session will discuss the types of new data and
indicators being included in dashboard development and then present a template
for a Management Dashboard for insurance products including key indicators of
business performance developed using predictive analytics techniques.
Vishwa Kolla, Assistant Vice President, Advanced Analytics, John Hancock
The life insurance industry is ripe for disruption. To help manage this disruption, Data Science comes to the rescue. But the journey is not without challenges. This session will walk through the various places where Data Science can be embedded, discussing challenges and mitigation, and offering some practical solutions and best practices. The audience for this session is practitioners of Data Science. The session can get very technical.
Stephen Danco, Vice President, Marketing, New York Life Todd Parsons, Vice President, Acxiom
The benefit of an ongoing, two-way dialog with highly engaged consumers is full of allure, but insurance marketers need to determine how to effectively measure ROI in this new model, which spans across online and offline marketing channels. In this session, we’ll discuss what you need to know to shape your omni-channel marketing program and clearly understand its success. And, we’ll answer some key questions:
Do you have a 360-degree view of your customer, effectively tying on-line with off-line consumer attributes to engagement strategy?
Is your digital marketing helping to improve your KPI’s
How well do your digital marketing channels work with other channels? Which audiences are responding? Can you correctly measure and attribute their behaviors?
Are valuable marketing dollars being wasted due to redundancy across channels?
Geoffrey Andrews, Chief Operating Officer, Social Intelligence
The utilization of data analytics for social media and
next-generation data is disrupting the traditional insurance process, changing
the way carriers market to and engage with customers, assess risk, and process
claims. Traditional data sources, such as
credit scores and contributory databases, no longer provide insurers with the
whole story, particularly for millennials and individuals who typically fall
into the “unscorable” category. Next-generation data targets this information
gap, changing the way insurers conduct business and solving one of today's
biggest industry challenges.
Tara Paider, Assistant Vice President, IT Architecture-Strategy, Innovation and Architecture, Nationwide
Data Scientists and Business Analysts have historically gone around IT to get their jobs done because of platform and tool limitations, as well as IT's black and white view of "applications". These users would pull data out of certified repositories and create copies of data on their desktops to blend with other data and make meaningful discoveries. They spend significant time on non-value add tasks and increase information risk. Through Governed Data Discovery, we can enable the business and reduce information risk.
Sarah Hinchey, FSA, CERA, MAAA, Predictive Analytics Strategist, Milliman Matthew Olson, Vice President, Customer Marketing & Analytics
Most salespeople don’t have access to data or the tools to
analyze it, manufacturers do. While many companies began their analytics work
building lead generation and cross-sell programs, the types and sophistication
of analytics being developed to support distribution continue to increase. Come
to this session to hear how companies can leverage advanced analytics to support distribution.
Rahim Rajpar, Assistant Vice President, Strategy & Business Development Delin Shen, Senior Director, Risk Solutions, LexisNexis Patrick Sugent, Vice President, Analytics Solutions, LexisNexis Moderator: Michael Mocanu, Assistant Vice President, Analytics & Technology Solutions, Lincoln Financial Group
The frequency of the big data capture
from mobile devices exposes the regularity of specific human behavior and
represents a new frontier for Life Analytics, which hopefully can be used to
adjust actuarial assumptions.
The potential & speed bumps of innovation: [brief] presentations by Lexis Nexis, John Hancock, etc.
Introducing mobile device & telematics data into the mix
Customer acquisition – potential and limits of prospect targeting
Underwriting – advancing “traditional” UW using predictive analytics and combining mobile data with current applicant data
4 Steps to Dealing with telematics Big Data - meaningful summaries of data from mobile devices
Data Privacy & Security: state and federal & regulatory environment
John Wilson, Data Scientist, LIMRA Moderator: Eric Sondergeld, ASA, CFA, Corporate Vice President, Strategic & Technology Research, LIMRA
Do you still have questions that have not been
answered? If so, join us at the LIMRA
Analytics Town Hall where you will have a last chance to pose questions,
discuss analytics strategies, and participate in a “Q&A hackathon”!
IBM Distinguished Engineer, Cognitive Computing Research
Take
a journey with IBM to see how advances in cognitive computing can help:
An investment banking expert narrow mergers and acquisition targets by using cognitive assistants to leverage techniques like 'Bayesian Smart Swaps'
A financial sentiment aggregator derive investment sentiment and outlook by using a cognitive engine to consume investment reports
A compliance officer extract requirements and obligations from industry regulatory documents and map them to controls through a cognitive text analytics engine
A financial service company better tailor products and services to individual customers through analysis of psycholinguistic features from written text and images
We
will close with a demonstration of how Watson technology can provide timely and
relevant guidance and recommendations to a financial advisor by combining
traditional portfolio data with a stream of social, news, investment reports
and other unstructured data.
Registration
Registration Fees
EARLY BIRD — By May 24, 2016:
Conference & Seminar LIMRA Member: $1,890 LOMA (but not LIMRA) Member: $2,565 Nonmember: $3,235
Conference Only LIMRA Member: $1,195 LOMA (but not LIMRA) Member: $1,795 Nonmember: $2,390
After May 24, 2016:
Conference & Seminar LIMRA Member: $2,190 LOMA (but not LIMRA) Member: $2,990 Nonmember: $3,760
Conference Only LIMRA Member: $1,395 LOMA Member (but not LIMRA): $2,095 Nonmember: $2,790
Cancellation Policy
All cancellations must be received in writing. Cancellations received before May 27, 2016, will be refunded, less a $75 processing fee. Cancellations received from May 27, 2016, to June 10, 2016, will be refunded, less a $275 processing and administrative fee. No refunds will be issued after June 10, 2016.
In the event that a scheduled meeting or event is cancelled by LIMRA for any reason, LIMRA shall refund any conference registration fees that have been paid by the registrant. Under no circumstances, however, shall LIMRA be liable to the registrant for any other expenses including, but not limited to, airfare and hotel expenses incurred by the registrant
Please make your reservation using the link or by calling the reservations phone number and mention the LIMRA Big Data Analytics Conferences by May 24, 2016 to obtain the group rate of $289 single/double plus tax. Reservations made after May 24, 2016 will be at the prevailing rate and based on space availability. The group guest room rate will be offered three days prior and three days after the meeting dates and subject to availability of rooms at the time of your reservation. Reservations must be guaranteed with a major credit card.
