Agenda

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Presenter(s): Marc Sofer, FFA FIAA, MBA, Head of Data and Strategic Analytics - Asian markets, RGA Reinsurance Company

This practical business focused session will provide an overview of the different types of data science projects being worked on across the globe, go through real life cases highlighting learnings and outline considerations for the implementation of data science solutions. Case studies will include cross-sell/up-sell applications, underwriting triage, the use of alternative data sources, streamlined underwriting, agency force management and fraud risk management.

Attendees will hear about the different ways advanced analytics are being used within the life insurance industry and learn about successes and failures. 

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Presenter(s): Eileen Burns, FSA, MAAA, Principal in the Seattle Life insurance consulting practice of Milliman; David Wang, FSA, FIA, MAAA, Principal in the Seattle life practice of Milliman

This session will discuss how predictive analytics can be used, more efficiently leveraging data, to studying policyholder behaviors such as base and dynamic lapse. This session will cover methodology (for data preparation, modeling and validation) and communication via visualizations and reports, using a case study to demonstrate each topic. Additional applications in the realm of policyholder behavior will also be discussed. After the session, attendees will understand the practical side of predictive analytics and some common pitfalls encountered.

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Presenter(s): Travis M Short, FSA, Data Innovation Lead, Pacific Life Re

How do companies and actuaries supplement current skills and talent across teams to address predictive analytics into the future? This session will cover both how to ‘upskill’ as actuaries through SOA offerings and beyond, scoping tools and team structuring to get ahead through predictive modeling.

• Upskilling actuaries into the ‘data science’ space
• Pandas, Python, and Hive … oh my! Where to begin with tools and software?
• Who does what and the value of domain knowledge as an actuary?

With data science as a hot topic, actuaries are in a crossroads where past methods of quantification and management of risk are shifting rapidly to additional data sources and techniques. High level analyses are quickly evolving to a plethora of potential information. Beyond managing risk, do actuaries have the background and training to contribute to analytics across the ‘full stack’ of insurance and risk management? This session helps actuaries with practical advice on focusing their efforts to learn predictive analytics, how companies might structure teams and tools/resources to consider.

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Presenter(s): Wing Wong, FSA, MAAA, Principal , Milliman; Stanley Hsieh, Actuarial Analyst, Milliman

Life insurance companies rely on experience studies for predicting lapse rates of insurance policy. Traditional actuarial lapse studies require subjective judgement and consider only a limited number of factors such as policy durations and product grouping. For life insurance companies to improve the prediction of lapse behavior, better methods and more factors, such as more internal policy related data or external economic data, should be considered. With the improvement in technology and advent of big data, machine learning techniques can be applied for the prediction of lapse rate. This session will cover how machine learning technology is being applied to predicting lapse rates by going through a real-life case study. Machine learning methods which are being applied on the case study, including Generalized Linear Model, Decision Trees, Random Forest and Gradient Boosting Machine will be introduced. How machine learning models generate a more accurate result than traditional experience studies will be discussed. At the end of the session, what life insurance companies have to do to start taking advantage of data analytics will be covered.

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Presenter(s): Lichen Bao, Ph.D, Data Scientist, RGA Reinsurance Company

The session will provide an overview of the various modelling techniques available e.g. artificial intelligence/machine learning, how data scientists choose which algorithms to use, how actuaries can get involved in data science projects, and how predictive analytics helps to redefine products and pricing risk of Life products. It will also describe the different hardware/software packages we use, the common pitfalls in a data science projects and the learning programs we have implemented at RGA.

 

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Presenter(s): Ashim Avinash Sahu, Associate Director, Data Sciences, Business Analytics Centre of Excellence for AIA Bhd.

Most insurance firms want to explore the possibility of using advanced analytics like predictive modeling and Machine Learning, but not sure how to go about it. The session will showcase how one goes about setting up an inhouse Advanced Analytics department, the pros and cons, and what and when can they expect the value creation from it. 

 

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Presenter(s): Ing Chian Ching, FSA, SOA Greater Asia Committee Member, Organizing Committee, Chief Actuary, AIA Bhd.

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