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Speaker Information

 Scott Hallworth
Scott Hallworth Chief Data Officer & Chief Model Risk Officer Capital One Financial
Scott T. Hallworth
FCAS, MAAA

Senior Vice President, Risk Management
Capital One Financial

In August 2011, Scott Hallworth joined Capital One as Senior Vice President and Chief Model Risk Officer overseeing the company’s models, leading its analytic research and development group, as well as the statistician and quantitative analyst community. Further, to advance data across the company, in March 2014 Scott’s role expanded to be the Chief Data Officer developing and leading its data strategy.

Before joining Capital One, Scott was most recently a Chief Actuary of Travelers Insurance, leading their advanced analytics, modeling, data, and business intelligence initiatives. Prior to that he developed extensive experience in a variety of business and analytic disciplines through multiple roles at Hanover and MetLife Insurance Companies including leading analytic/research groups, lines of business, mergers and acquisitions, as well as a variety of corporate consulting roles.

Further, Scott has been active across industries where he has served on the Casualty Actuaries of New England Board, a member of the Highway Loss Data Institute (HLDI) and Information Institute for Highway Safety Boards (IIHS), Teradata Advisory Board, as well as college/university Education Panels.  Currently, Scott is an active board member for the Academy of Hope providing high quality adult basic education to help improve the DC community.

Scott received his Bachelors of Science in Business Administration with a major in Applied Actuarial Mathematics from Bryant University, is a Fellow of the Casualty Actuarial Society, and a Member of the American Academy of Actuaries.



January 28th, Day 2

8:20 AM The Future of Talent for Data Science and Analytics

Today Big Data has become foundational to nearly every industry on earth including retail, healthcare, manufacturing, telecommunications, energy, financial services, tourism, advertising, entertainment, and government.  As Big Data has become ubiquitous, the need for data scientists has grown exponentially, with demand far outpacing supply.  However, the educational infrastructure, for the most part, is not presently set up to produce the kind of data scientists needed by most industries: few academic data science programs exist, and those that do predominantly teach rote memorization of data analysis techniques rather than deeper problem-solving skills.  In this talk, I describe how we need to train the workforce differently to set both employees and businesses up for success in the new Era of Big Data.

9:40 AM Big and Fast Data Analytics - A Fundamental Shift for Enterprise Decision Making

We have moved from an information-poor to an information-rich society. Practically unlimited availability of data, computing, networking, and socio-mobile connectivity are fundamentally altering our world. In particular, they are enabling businesses to become more effective and efficient by using big data analytics - collecting all relevant data and automating their processing to drive decision-making. This represents a fundamental shift from traditional business analytics where limited amount of structured data is batch-processed to produce standard Business Intelligence reports. We will assess the current state of big data analytics, technology and business trends, and their enormous implications to the future of all businesses.
 
This session will focus on the following
  • How Big and Fast Data analytics is different from traditional business analytics
  • What businesses are getting out of big data analytics
  • How Big and Fast Data analytics will become critical to every business
  • How you should enter into Big Data analytics or do more of it
With examples using unstructured data, digital data, automated data quality notifications/usages to drive business decision making.