Advanced Business Analytics

Date

November 30 - December 02, 2016

Location

Deloitte
Chicago, IL

  • External Forces & Industry Knowledge
  • Results-Oriented Solutions
  • Strategic Insight and Integration
  • Technical Skills & Analytical Problem Solving

 

This seminar has sold out.

It is anticipated that this seminar will be held in 2017 but dates and locations are not yet finalized. SOA will post information on the 2017 offerings as soon as possible.

To be placed on a waiting list for the Nov.30 - Dec. 2, seminar in Chicago, IL, please email Marni Smith in SOA Customer Service at msmith@soa.org . Should spaces for the seminar become available (e.g., due to cancellations), potential registrants will be contacted in the order in which their requests were received.

Business analytics became a major force for innovation in the insurance industry and beyond in the past decade. Inexpensive computing power, rich data sources and increasingly powerful analytical tools become more widely available each year. As a result, quantitatively skilled professionals have unprecedented opportunities to bring scientific rigor to areas of strategic importance to their organizations. For actuaries in particular, the business analytics revolution affords opportunities to ground traditional actuarial work in rigorous statistical methodology and enable actuaries to enter new domains. 

The SOA is offering a seminar in Advanced Business Analytics on Nov. 30 - Dec. 2, 2016, in Chicago, Illinois, to better enable our members to participate in the business analytics revolution. This interactive, hands-on seminar will impart practical working knowledge of statistical and machine learning techniques that are broadly relevant in actuarial work. Core techniques, like regression analysis, generalized linear models, survival models, time series analysis, decision tree analysis and "unsupervised learning" techniques like principal component analysis and clustering will be covered.

This seminar is a blend of theory and practice with theoretical discussion that emphasizes concepts and intuitions rather than mathematical formalism. The theoretical discussions enable attendees to better interpret, communicate and critically examine model outputs. Practical working knowledge of data analysis methodology will be imparted through a series of data analysis case studies. Seminar participants will receive datasets and computer code to work through the examples with the instructor.

Inherent to modern statistical and actuarial practice is the ability to compute with data. To that end, the medium of the seminar will be the open-source R statistical computing environment. R is widely considered the working language of modern data analysis and provides users with exceptional facilities for manipulating, graphically exploring and modeling complex datasets. Attendees will receive a self-contained introduction to R package prior to the seminar that explains how to install and begin using R. Working knowledge of R of will be further cultivated during the workshop as participants analyze data in real time.

At the conclusion of this seminar, participants will be better able to:

  • Perform basic data manipulations and fit a variety of standard models in the R statistical computing environment;
  • Graphically explore data to motivate various modeling choices and graphically criticize models and motivate model improvements;
  • Interpret and critically examine standard model output; 
  • Test the performance of models on holdout data; and
  • Translate a business problem into the design of a data analysis strategy.

This seminar will convey foundational material; a general understanding of statistics is the only prerequisite. However, a working knowledge of applied data analysis in R cannot be gained in only a few days. Therefore, the goal of the seminar is to convey a theoretical framework and computational toolset sufficient for participants to continue to gain expertise on the job.

Note:

  • To create an optimum learning environment, this seminar will be limited to 35 registrants
  • Attendees will be required to bring their own laptop computers to this seminar

Seminar Instructor

James Guszcza is the chief data scientist for Deloitte in the US and is a member of Deloitte's actuarial, risk, and advanced analytics practice. He is a Fellow of both the Casualty Actuarial Society and Society of Actuaries, has a Ph.D. in the philosophy of science from the University of Chicago. Mr. Guszcza spent the 2011-12 academic year as an assistant professor in the actuarial science, risk management and insurance department of the University of Wisconsin-Madison. A frequent author and conference speaker, Mr. Guszcza is the designer and co-teacher of the Casualty Actuarial Society's Predictive Modeling Limited Attendance Seminar.

 

Back

Legend

Communication

Demonstrating the listening, writing and speaking skills required to effectively address diverse technical and nontechnical audiences in both formal and informal settings.

Professional Values

Adhering to standards of professional conduct and practice where all business interactions are based on a foundation of integrity, honesty and impartiality.

External Forces & Industry Knowledge

Identifying and incorporating the implications of economic, social, regulatory, geo-political and business changes into the design and delivery of actuarial solutions.

Leadership

Initiating, innovating, inspiring, creating or otherwise acting to influence others regardless of level or role toward a common goal.

Relationship Management & Interpersonal Collaboration

Creating mutually beneficial relationships and work processes toward a common goal.

Technical Skills & Analytical Problem Solving

Applying the actuarial knowledge, skills and judgment required to provide value-added services.

Strategic Insight & Integration

Anticipating trends and strategically aligning actuarial practice with broader organizational business goals.

Results-Oriented Solutions

Providing effective problem solving that addresses relevant interests and needs.