Description: The Survey of Emerging Risk has been successfully conducted in North America for 16 years, consistently providing reports that track risk managers' opinions on emerging topics transcending the current business cycle, with strategic plans extending over decades. Since 2022, the survey has been specifically introduced to the Asia-Pacific markets with local language support, aiming to gauge actuarial and risk management professionals' opinions on emerging risks in the Asian market.

Description: The Society's Group Disability Insurance Experience Committee has completed their study of termination experience for the period 2009-2017. Included is a preliminary report, consolidated database (CDB), pivot tables and appendices.

Description: Experience report for life insurance policies with face amounts of $1 million or higher.

Description: In this article, we introduce a novel machine learning-based model that analyzes and predicts policyholder behaviors at the individual policy level. Policyholder embedding representations are learned using a Recurrent Neural Network (RNN) that takes into account the sequence of historical transactions associated with a policy. Additionally, a Neural Network with a multi-head architecture is trained to predict the policyholder's next action based on the policyholder embedding and other policy attributes. The resulting model offers several advantages over traditional experience studies and assumption-setting methods, including the ability to set policy-level assumptions that improve reserve accuracy, predict multiple behaviors simultaneously while capturing the interrelationships between them, and generate policyholder embedding representations that are useful for segmentation.

Description: The presenters will cover the latest research undertaken by the Individual Life Experience Committee (ILEC). With several years of very robust individual life insurance experience data accumulated through the mandatory Statistical Agent data calls, this vast amount of data allows for various deeper dives into specific segments of business, such as large face amount, older age or juvenile. Speakers will cover studies the committee is currently involved in, future planned efforts, and results from a variety of sub-segments of business. Attendees will learn about emerging statistical techniques in scrubbing data, more refined quintile-grouped data segments, and interesting ways of conceptualizing how A/E results have changed from year to year. There will be something for everyone!

Description: sources of Health Care data Issue No. 37.

Description: The purpose of this survey is to provide international actuaries with benchmark assumption data.

Description: In this session, attendees will understand the role of AI in risk management and underwriting. You will see insightful case studies highlighting AI-driven techniques for enhancing precision and efficiency in these areas. Additionally, the session will cover advanced AI applications in claim management and fraud detection, showcasing cutting-edge strategies to mitigate risks and streamline operations.

Description: This report is presented in the form of a Tableau dashboard and is the sixth public release from this report series and contains the results of an excess mortality analysis for the fourth quarter of 2021. Data from 30 companies representing approximately 69% of the industry’s face amount inforce were included in the analyses in this report. A total of 3.2 million death claims from individual life policies from 2015 through December 31, 2021 make up the basis of the analyses. The report also compares the experience under COVID-19 of the insured population versus the general population.

Description: Understanding Asian Capital Regimes