Practical Application of Least-Squares Monte Carlo to VA Pricing

VA pricing requires stochastic-on-stochastic modeling to predict future reserves and capital requirements based on value at risk or conditional tail expectation. Usually brute-force simulation approach cannot accommodate the time constraint in a real business world. Least-Squares Monte Carlo (LSMC) built on predictive models such as GLM, Random Forest, and Gradient Boosting Machine, when designed appropriately, can significantly reduce model run time with a highly satisfactory accuracy.

The presenters will use a case study to introduce LSMC based VA pricing, and more importantly, discuss the challenges and practical solutions in a real business case.
• How do we construct a meaningful training data set in a short window?
• How do we select explanatory variables? How do we interpret and compare different models?
• How do we balance between time and accuracy?
• How do we determine when we need to recalibrate the models?

With a focus on the implementation side, this webcast intends to help practitioners improve and accelerate their VA pricing process. It can also be used to project reserves and capital requirements using inforce data.
At the conclusion of the webcast, attendees will be able to:
• Design a practical LSMC process for VA pricing
• Analyze the pros and cons of different predictive models for LSMC
• Use feature engineering to improve LSMC accuracy
• Use sensitivity tests to assess the right time for model recalibration

Kailan Shang, FSA, ACIA (Moderator)

Associate Director, Aon PathWise Solutions Group

Kailan Shang FSA, CFA, PRM, SCJP, is Associate Director at Aon PathWise Solutions Group. His major responsibility is to provide VA modeling, predictive analysis, and risk management solutions to clients. He has fifteen years’ actuarial and risk management experience, including product development, day to day risk management, risk appetite and risk limit setting, risk quantification, asset liability management, economic scenario generation, economic capital modeling, market consistent embedded value calculation, strategic capital management, and the like. He graduated from York University with a M.A. in Economics. He worked on many research projects. He was awarded the Emerging Issues Prize from the CAS in 2011 for the paper titled “Loss Simulation Model Testing and Enhancement” and the Best Paper Award for Practical Risk Management Applications from the JRMS in 2016. He is enthusiastic about volunteer works. From 2006 to 2010, he participated in the Loss Simulation Model Working Party sponsored by the Casualty Actuarial Society (CAS). Since 2013, he have been serving on the Subject Matter Expert Quantitative Group of the Professional Risk Managers’ International Association (PRMIA). In addition to professional volunteer works, he is active in improving the communities though programs such as Habitat for Humanity.

Yu (Maggie) Lin, FSA, FCIA

Associate Director, Aon

Maggie Lin is Associate Director at Aon PathWise Solution Group in Toronto. She has years of experience as a life actuary, which spans consulting and life insurance companies. At Aon, Maggie has worked with many life and annuity products, and has helped many clients improve their pricing and valuation process.

Rachel Yap, FSA, FCIA

Director, Sun Life Financial

Rachel is a Director at Sun Life where she currently works in a Corporate Actuarial function focusing on Regulator advocacy of upcoming changes in IFRS 17 for capital rules. Previously, she has led teams and projects in Segregated Fund Pricing, Segregated Fund Valuation, Insurance Pricing, Non Par Valuation and Inforce Optimization. Rachel volunteers with the SOA and CIA in a variety of roles.

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Webcast Session
07/13/2020 at 4:00 PM (EDT)  |  Recorded On: 07/16/2020
07/13/2020 at 4:00 PM (EDT)  |  Recorded On: 07/16/2020
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