2017 Big Data Analytics Conference

Learn 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.

Shankar Vedantam

 Science Correspondent, National Public Radio

Big data promises to unlock all sorts of mysteries, and holds out tantalizing possibilities for understanding how the brain works. Simultaneously, however, our fascination with big data raises important questions and concerns — including the risk that techniques involving big data might unintentionally amplify our unconscious biases. This presentation explores how our minds process information and data, and the importance of keeping the "Hidden Brain" front and center as we design data systems.

A growing number of companies are implementing streamlined or automated underwriting programs. At this session, two companies will share their experiences with algorithmic underwriting. Topics covered will include the impact on the new business process, new ways of asking health questions, the roles of reinsurance and vendor scoring systems, metrics used to track progress, and how these companies are scaling up to make this capability available to a larger part of the business.

Lessons learned from building a Data Science team from scratch. Hear about decisions such as building from the outside or within, choosing software “A” or “B”, fitting into the organization, etc. Come get your questions answered and join in on the discussion by sharing your experiences.

Financial spending and saving in isolation is a rich area of exploration for big data studies. What is absent is the exploration around people’s attitudes about spending and saving, as well as their behaviors leading up to those actions. In this session, you will learn how one financial services company is studying the analysis of financial behavior and the events that take place around the targeted behavior and combining the latest behavior science with data-driven technology and simple consumer experiences to improve ROI. 

Micro summits are small, facilitated groups where you can discuss issues with like-minded peers. Choose from the following discussion topics:

• Applications of Analytics 
• Analytics in Underwriting
• Data: Sources, Management, and Strategy
• The Tools of Analytics
• Building a Culture of Analytics

As health information becomes digitized, how might insurance companies one day leverage this data for improved underwriting and product design? Susan Wehrman from RGA Re will describe the current state of EHR, what needs to happen in order for the industry to leverage them for underwriting, and lead a discussion with the audience around the role the industry can play in hastening that reality.

For many, predictive modeling is simply feeding data into a “black box” and getting output, but understanding basic algorithm creation is critical to efficient use of models. Geared towards those who have NEVER built a predictive model, we invite you to join us as we delve into the creation of a simple model and the process that underlies it. In addition, we will share the approach and results of graduate students from the University of Connecticut who were tasked with developing models based on the same data.

As more and more companies consider shifting to a cloud-based approach, it’s important to have a good grasp of why it makes sense and how it can benefit your organization. In this session, we’ll examine the advantages and disadvantages of cloud-based analytics over a traditional on-premise approach. Learn how other insurance and financial services firms have approached it, and what lessons they’ve gained (do’s and don’ts) as they’ve transitioned their analytics efforts to the cloud.

The evolution of technology has likely had no greater impact in the life insurance industry than in underwriting. This session will feature advances in underwriting technology and opportunities to use new technology to create a better consumer experience by collecting more than initial underwriting data. Attendees in this session will gain insight into opportunities to collect and use data from remote-monitoring devices and sensors including fitness equipment and patient wellness applications that can capture health and fitness behavior data for a policyholder’s lifetime engagement.

How can we use newly available capabilities to micro-segment our messages to a world where each customer can belong to multiple segments depending on their life-stage, their current situation, and so many other factors? How do we fine-tune our interactions to make each one count? Can omni-channel be achieved, and what might that look like? Come and learn how customer centricity can start to be operationalized throughout the organization.

By the year 2020, some analysts estimate that there will be close to 30 billion connected IoT devices.  From connected buildings, cars, factories and medical devices, nearly everything will have an IP address capable of transmitting data for analysis.  Are we to wait for the data to find its way back to a central core repository so Data Science unicorns analyze and make sense of the ever growing mountain data for the business?  How will banks and insurance companies leverage this data deluge in the age of IoT?  What new business opportunities are out there?   Learn how to leverage open source and the algorithm economy to help make sense of it all.

Life insurance isn't the only industry that needs to underwrite client risk. Learn how the mortgage lending industry is using data to streamline and automate underwriting decisions. 

Customers today expect insurers to understand their particular journey, and the key to a long, fruitful relationship with policyholders lies in building an experience that is meaningful to them. Join us to learn how a reimagined digital experience uses a robust analytics process to drive policyholder lifetime value. Attendees in this session will gain insight into applying analytics to drive customer journeys in different market segments, personalize journeys based on interactions with policyholders, and leverage the wealth of data generated by policyholders to proactively position the most relevant products and services.

James Guszcza, Ph.D.

U.S. Chief Data Scientist, Deloitte Consulting

The big data revolution is giving rise to an artificial intelligence renaissance that is set to reshape business and societal landscapes alike. In parallel with this technological revolution is the revolution in our understanding of human psychology ushered in by Daniel Kahneman, Amos Tversky, and their followers and collaborators. This talk will explore the ways in which our deepening understanding of human psychology enables us to design AI systems that extend human abilities and facilitate better choices. While discussions of AI tend to focus on automating away human involvement, real-life AI applications often involve augmenting human capabilities. And effective augmentation requires human-centered design applied to the field of AI.

As companies grow their advanced analytics capabilities, the demand is high and data scientists are hard to come by. But what if you had some of the skills you needed in other areas of the organization? Learn how companies are using the skills of actuaries to improve their data analytics programs.

From historic to batch to streaming, where is your firm on the data continuum? There is an abundance of real-time data that you can use to anticipate consumer needs and engage them with more meaningful, relevant, and helpful experiences. What steps can you take to accelerate your firm’s data and analytics maturity? This session will highlight how organizations can fully leverage the abundant data assets available and showcase examples of what this can look like.

We live in a world with rapid adoption of new technologies, new sources of data, and innovative data uses. These advancements have incredible benefits but also come with serious risks. You probably know that you should be doing something to govern the data that you use to mitigate those risks, but with limited time, knowledge, and resources, where do you start? Each of these new data flows also has compliance issues and considerations that we must understand, navigate, and ultimately follow. This mission-critical talk also addresses the ethical use of data with consumers in today’s digital, multi-touch, client-centered environment. Key guidelines for navigating the sensitive and critical world of client privacy in a data-obsessed environment will be provided.

This presentation is geared toward directors and hands-on users of consumer data and will provide key guidelines for beginning to think about data governance and consumer privacy and implementing a data governance program — with even the most limited resources.

Pranav Pasricha

CEO of Insurance Products, Intellect SEEC

The confluence of artificial intelligence, big data, IoT and mobility will make robo advice more accessible, more reliable and for buying insurance than with a human. Underwriting will be more precise, faster and less intrusive. Almost every industry function can be eliminated or greatly transformed resulting in significant customer experience enhancement, better decision making and orders of magnitude lower operating expenses. Come to this session to hear about each of these technologies and how companies can adopt them in a practical way to make sure your organization is ready for the tsunami of disruption about to hit the sector.