Description: The presentation provides an overview of the motor insurance pricing. It will highlight some good practices and important skills desired by the actuaries.

Description: Panelists will discuss considerations identified and the challenges encountered by companies in developing and using predictive models in the life insurance underwriting process.

Description: LON-CAPA is a full-featured course management, learning content management, and assessment system. It was initially developed by Michigan State University under several National Science Foundation grants. You can run LON-CAPA for free on your own dedicated server. Purdue University has used LON-CAPA to create a robust online homework system for the Financial Mathematics material of the FM Exam. This homework system is in the public domain and may be used by any university running LON-CAPA. This session will provide additional information and include a demonstration of the system.

Description: Industry experts say the need for actuarial skills is growing as emerging markets across the world become more sophisticated. CAA Global aims to meet that need and offers a route to an internationally recognized qualification for those who don’t want to follow the traditional actuarial qualification pathway. The Certified Actuarial Analyst (CAA) qualification is a standalone qualification supported by the Institute and Faculty of Actuaries (IFoA) and the Society of Actuaries (SOA), two of the largest actuarial education bodies in the world.

Description: The Society of Actuaries (SOA) is a membership organization dedicated to education, research, and the profession. This session will provide an overview of the SOA and its various university programs and initiatives.

Description: Transitioning from college life to actuarial practice can be intimidating for students. Even after almost four years of studying actuarial science, many still wonder “what does an actuary do all day?” Our capstone course, Actuarial Applications in Practice, is designed to bridge the gap by exposing students to projects similar to what they might encounter in their first years in the industry, including how to present their results in both written and oral presentation formats. The course also incorporates Ethics and Professionalism topics to give them the tools they need to make sure the job is done right.

Description: Infrastructure investments are growing as an asset class in institutional portfolios because they present significant diversification benefits to investors, and importantly for pension plans, typically represent long-term projects. Infrastructure presents a unique opportunity for investors interested in long-duration products that help match liabilities. This session outlines the structure of infrastructure deals, how investments can be made through either equity or debt financing, the importance of ESG, and how to incorporate infrastructure in an institutional portfolio.

Description: FASB has provided broad guidance for application of long-duration targeted improvements (LDTI) in Actuarial Standards Update 2018-12 for U.S GAAP financial reporting. However, the broad guidance provided leads to several interpretations and technology, data and system implementation challenges. During this session, the presenters will focus on sharing the technology, system and data challenges and insights gathered from their FASB LDTI implementation journey, including lessons learned from collaboration with other discipline areas and stakeholders such as finance, investment and IT. The presenters will also discuss methods to overcome challenges and go beyond compliance.

Description: in the insurance industry, machine learning models are increasingly used to make decisions that affect people's lives. In order to ensure that models are fair, they should be audited for bias. There are no hard and fast rules for bias audit; metrics that can be used to evaluate fairness vary depending on the context in which the model is deployed. The presenters in this session present a flexible framework that highlights key considerations in bias evaluation that can be adjusted to suit your process.

Description: Predictive modeling continues to gain traction in the life insurance industry with the rapid growth of available data and maturity of open source tools. New methods and technology in predictive analytics have enabled the evaluation of extremely large data more quickly and allow us to incorporate features previously not considered. The presenters will provide background on predictive modeling tools and algorithms utilized by actuaries and data scientists for life insurance, highlighting applications from marketing to underwriting.