Professional Development
2019_pa_seminar_790px_255px_en

Predictive Analytics Seminar – February 27, 2019 – Toronto

Program at a Glance

Wednesday, February 27

07:00–17:00    Registration and Information Desk

07:30–08:30    Buffet Breakfast

08:30–08:45    Opening Remarks

Marc Tardif (FCIA, FSA), President-elect, Canadian Institute of Actuaries (CIA)
Jim Christie (FCIA, FCAS), President, Casualty Actuarial Society (CAS)
Mike Lombardi (FCIA, FSA, MAAA, CERA), Immediate Past President, Society of Actuaries (SOA)

08:45–09:35    Session 1 Opening Plenary

Life and Health Predictive Analytics – a Property and Casualty Actuary's Perspective
Moderator: 
Ben Marshall (FCIA, FSA, MAAA, CERA), Staff Fellow, Canadian Membership, SOA
Speaker: 
Chris Cooney (FCIA, FCAS), Vice-president, Pricing, TD Insurance 

This session examines several categories of predictive analytics techniques as applied to property and casualty insurance, and the corresponding crossover to life and health insurance applications. This discussion will include the presenter's experience in applying these techniques to life and health problems, along with associated challenges and opportunities.

09:40–10:40    Concurrent Sessions

Session 2 Privacy and Bias Considerations of Predictive Models
Moderator: 
Patrick Duplessis (ACIA, FSA, CERA), Manager, Investments and Risk – Pension Investments, Air Canada
Speakers: 
David Elder*, Counsel, Stikeman Elliott
Hareem Naveed*, Data Scientist, Integrated Analytics Team, Munich Re

In the insurance industry, machine learning models are increasingly used to make decisions that affect people's lives. To ensure that the models are fair, they should be audited for bias. The metrics available to evaluate fairness vary by the context in which the model is deployed. In addition, the fields of big data and data analytics are increasingly raising privacy concerns for many, including important issues respecting data sourcing from third parties and “publicly available” sources, de-identification, algorithmic transparency, and the rights of data subjects to control the use of their data. In this session, we will walk through some of the privacy considerations that arise with respect to data sourcing, model design, and transparency. We will also identify the metrics available to assess fairness, discuss open source tools that can be used for bias audit, and finish with a case study discussing a deployed model.

Session 3 Are You behind? (CIA/SOA Predictive Analytics Survey Results)
Moderator:
Ben Marshall (FCIA, FSA, MAAA, CERA), Staff Fellow, Canadian Membership, SOA
Speakers:
Jean-Yves Rioux (FCIA, FSA, CERA), National Director, Actuarial Rewards & Analytics, Deloitte
June Quah (FCIA, FSA), Assistant Vice-president, Integrated Analytics, Munich Re

In this session, we will discuss the results from the SOA-CIA-sponsored survey on analytics practices of the Canadian life and health insurance industry. This is an opportunity to understand what other companies are doing and benchmark your practices with those of your peers. Gain deeper insights about potential applications and their perceived value and effort.

Session 4 Practical Aspects of Predictive Models
Moderator:
Adam Scarth (FCIA, FCAS), Director, Business Analytics, Northbridge Financial Corporation
Speakers:
Kristen Dardia*, Principal Data Scientist, Verisk
Jean-Francois Larochelle (FCIA, FCAS), Director, DataLab R&D, Intact
Michael Regier*, Senior Lead Data Scientist, Verisk

The speakers will explore the practical aspects of bringing models to production, maintenance, and management through their entire lifespan. Topics covered include production considerations, versioning, documentation, peer review, and monitoring the model over its lifespan.

10:40–11:00    Networking/Refreshment Break

11:00–12:00    Concurrent Sessions

Session 5 Predictive Modelling Pitfalls. . . and How to Avoid Them
Moderator:
Adam Scarth (FCIA, FCAS), Director, Business Analytics, Northbridge Financial Corporation
Speaker:
Jeffrey Baer (FCIA, FCAS), Assistant Vice-president, Advanced Analytics and Business Intelligence, Economical Insurance
Dihui Lai* (ASA), Senior Data Scientist, RGA

Predicting the future is not easy. In this interactive session, we will discuss four critical pitfalls that can turn any predictive model from useful to useless—and at worst, destructive. He will illustrate each predictive modelling pitfall through a short case study, and will discuss how you can prevent or mitigate the impact of each one.

Session 6 Advances in Cyber Risk Modelling
Moderator:
Craig Sloss (ACIA, ACAS), Technical Specialist, Economical Insurance
Speakers:
Thomas Harvey*, Senior Manager, RMS Cyber Product Management 
Joshua Pyle (FCAS), Actuarial Director, CyberCube
Scott Stransky*, Assistant Vice-president, Director of Emerging Risk Modeling, AIR Worldwide

The cyber risk modelling field is rapidly evolving. In this session, our panel will explain the key drivers of cyber risk, the data and modelling techniques used to calibrate and validate cyber-risk models, and the output and use of probabilistic models. By the end of this session, you will know how cyber risk models can support product development, underwriting, pricing, portfolio optimization, and capital allocation for the cyber line of business.

Session 7 Cross-Selling
Moderator: 
Kevin Pledge* (FSA), CEO and Founder, Acceptiv
Speakers:
Adam Rentchler*, Adam Rentchler*, Data Solutions Consultant, RGAX
Jane Wang*, CEO, Optimity

As companies look for growth opportunities in a saturated, competitive marketplace, selling additional products to existing customers is a very attractive proposition. The challenges become identifying customers who would benefit from additional products, determining the right product for each customer, and tailoring communication so that the customer is receptive to the offer. This session will explore how to use predictive modelling to address these challenges and drive an optimal cross-selling strategy.

12:15–13:00    Luncheon

13:10–14:10    Concurrent Sessions

Session 8 Experience Studies, Mortality Modelling Using General Linear Models (GLMs), and Machine Learning Techniques
Moderator:
June Quah (FCIA, FSA), Assistant Vice-president, Integrated Analytics, Munich Re
Speakers:
Dragos Capan*, Director, Advanced Analytics, Manulife 
Adnan Haque*, Integrated Analytics, Munich Re
David Keirstead*, Head of Canadian Division, Advanced Analytics, Manulife

For many years, actuaries have been privileged with robust experience data to use in setting model assumptions like lapse rates, mortality, and morbidity. Recent increases in computing power and the advent of predictive analytics present an opportunity to enhance the traditional actuarial experience studies and assumption-setting process. This session will explore how multivariate statistical analysis and machine learning can provide greater accuracy of forecasts, improve understanding of the risk drivers, improve granularity of risk segmentation, and drive tangible benefits for pricing and valuation.  In this panel discussion, experts in the industry will share their experience using these techniques. What have they learned? How did they choose which tools to use, how do they validate this approach, and how do they communicate and explain results and bring innovative change to the industry?

Session 9  Make It Shine: Collecting and Cleaning Your Data
Moderator: 
Patrick Duplessis (ACIA, FSA, CERA), Manager, Investments and Risk – Pension Investments, Air Canada
Speaker: 
Justin Fountain*, Consultant, Willis Towers Watson
Thomas Naraindas*, Data Scientist, Munich Re

Companies can leverage both internal and external data to support predictive analytics. In this session we will discuss common internal and external data sources that underlie analytics in the insurance industry, as well as techniques to appropriately clean this data prior to analysis.

Session 10 Disability Claims Analytics
Moderator: 
Kevin Pledge* (FSA), CEO and Founder, Acceptiv
Speaker: 
Thomas D. Fletcher*, Vice-president, Data Analytics – North American Life, PartnerRe

Claims scoring techniques for disability claims can be developed by a bucketing process based on likely time to resolution. Claims that can be resolved quickly can be assigned to less-experienced claim handlers, or automatically paid with the goal of saving on expensive resources. Claims that are likely to become permanent should focus on expense management, including the possibility of social security offset. However, it is the claims in the middle that offer the greatest opportunity for management and improvement.

14:20–15:20    Concurrent Sessions

Session 11 Life and Health Underwriting
Moderator:
Kevin Pledge* (FSA), CEO and Founder, Acceptiv
Speaker:
Derek Kueker* (FSA, MAAA), Vice-president and Senior Actuary, RGAx
Dihui Lai (ASA), Senior Data Scientist, RGA

Many life insurers want to simplify the insurance application and underwriting process to meet the needs of today's client. Limited personal data can be captured from a client and supplemented with third-party data and models to predict other risk factors. Predictive models can also help determine whether an applicant is eligible for a simplified underwriting process. This session will explore how insurers have successfully used predictive analytics to simplify the application and underwriting process while navigating through concerns of adverse selection.

Session 12 • Model Selection and Implementation
Moderator: 
Dom Yarnell (FCAS, MAAA), Vice-president and Pricing Actuary, Everest Re 
Speakers: 
Bob (Robert) Sanche* (CSPA), Second Vice-president, Research and Development, Travelers Canada
Jim Thanos (ACIA, FCAS), Director, Research and Development, Travelers Canada

Picking a model involves a multitude of considerations. This session takes you through the process of choosing a modelling methodology, variable considerations, evaluating model fit and performance, explaining models to the business, and deployment. Phew! Specific topics include factor assessment, goodness-of-fit tests, validation error, tools for explaining machine learning, and the role of domain expertise and business acumen. This session addresses the trade-offs and opportunities between model fitting and business pragmatism.

Session 13 Fraud Detection
Moderator: 
Jean-Yves Rioux (FCIA, FSA, CERA), National Director, Actuarial Rewards & Analytics, Deloitte
Speakers: 
Linhui Dong* (CSPA), Vice-president, Data Science, RGA
Satish Lalchand*, Principal, Deloitte Transactional and Business Analytics

The speakers will describe how to use predictive modelling techniques to detect fraud. In this session we will nuance how predictive fraud analytics differs from and can be built upon traditional approaches and will provide actionable insights on how to enhance your fraud detection processes with these techniques.

15:20–15:30    Networking/Refreshment Break

15:30–16:30    Session 14 • Plenary Session: Keynote Speaker David Coletto

How to Thrive or Survive in the Millennial Age

There are powerful new forces at work in the modern workplace and consumer market, a dynamic driven by the intersection of disruptive technology and a new generation of consumers and employees who were raised differently, have different values, and different expectations.

This revolutionary, generational change represents enormous risk but also creates an incredible opportunity for the insurance industry and actuaries.

As one of Canada's foremost experts on generational change and youth, Mr. Coletto has spent over eight years as the founder and CEO of Abacus Data trying to understand his generation and working with brands, associations, and public sector organizations to reorient themselves for this millennial-dominated world. He is convinced that a generational analysis is critical to understanding the forces at play in the workforce.

As Canada's leading authority on his generation, Mr. Coletto promises to deliver an engaging and data-filled presentation that explains why using his “SHIFT” lens  is critical to leading and succeeding in today's marketplace. 

Don't miss the founder of Canada's only research firm dedicated to helping organizations navigate the unprecedented threats being caused by the generational change in Canada and around the world.

16:30–17:30   Networking Reception

Sponsors

Contributor

Munich RE

Sponsorship Opportunities

To learn more about sponsorship opportunities, please contact Kelly Fry.