Description: In *From Distress to Distinction*, Chris Droussiotis explores a novel approach to valuing distressed companies using option pricing theory, drawing parallels to the financial challenges faced by startups. With over 30 years in banking and startup advising, he emphasizes that both distressed firms and early-stage ventures endure periods of negative cash flow but retain potential for recovery. He combines Discounted Cash Flow (DCF) and the Black-Scholes Option Pricing Model to evaluate distressed firms’ recovery prospects and debt sustainability. A case study on Spirit Airlines illustrates this approach: though its current equity value is negative, projected future cash flows suggest significant potential recovery. Droussiotis concludes that strategic valuation, using trend, peer, and expected analysis, can reveal hidden value in distressed companies, guiding effective investment and restructuring decisions.

Description: The Smaller Insurance Company/Chief Actuary Forum presents a unique format for focusing on issues faced by actuaries in leadership positions or actuaries supporting the Chief Actuary. By discussing critical issues with your peers, you will leave with ideas to incorporate in your business environment. The Forum will feature presentations to introduce several of the discussion topics, followed by an opportunity to break into smaller discussion groups and rotate among topics.

Description: Actuarial projects have become more intricate, involving external resources and requests beyond the actuarial team's purview. Whether a task appears minor or exceptionally complex, adept project and change management play a pivotal role in successful execution. In this session, we explore practical strategies for tailoring implementation management approaches.

Description: This article is the final installment of our three-part series on economic scenario generators (“ESGs”). Part I and II were published in the November 2019 and August 2020 issues of The Modeling Platform. Part III contextualizes the framework for selecting, building, and validating ESGs and focuses on the Academy Interest Rate Generator (“AIRG”), the most commonly used real-world ESG for US actuaries

Description: An overview of bias and fairness in machine learning models, as they apply to use cases in life insurance.

Description: Dive into this review on Artificial Intelligence and Machine Learning (AIML) techniques for actuarial modeling for life & annuities. Presenters will showcase learnings from the recent SOA research paper "Predictive Analytics and Machine Learning – Practical Applications for Actuarial Modeling" (Nested Stochastic). The researchers will go over models and methodologies used to develop high-fidelity proxy models for various life & annuity applications.

Description: The Society of Actuaries (SOA) Research Institute received a grant from the U.S. National Science Foundation (NSF) to educate insurance actuaries on the use of wildfire risk datasets and models to be developed by researchers from academia and the U.S. National Aeronautics and Space Administration (NASA).

Description: Overview of the session “Analytics You Should Know, but Don’t” which took place at the 2007 SOA Annual Meeting in which R, an open source language for statistical computing, was discussed.

Description: Part 2 of a six-part series on the evolution of risk management continues with this article on dynamic financial analysis.

Description: Generative artificial intelligence (AI) tools like ChatGPT will redefine the nature of work across industries in coming years, What does this mean for the actuarial profession? Delivering generative AI tools to actuaries capable of leveraging them effectively will dramatically modernize how actuaries work and contribute to organizational growth. In this educational session, explore how generative AI can accelerate actuarial model development. Gain an introduction to generative AI and its implications for actuarial modeling. Learn how it specifically helps actuaries improve accuracy, reduce errors and save time in model development. Then explore use cases, including how generative AI can improve data cleaning, model building, as well as simulate scenarios and test model robustness. Close with a discussion on how to integrate generative AI into actuarial modeling workflows effectively, including common challenges actuaries may face during implementation and tips to overcome them. You will come away with a deeper understanding of how generative AI can accelerate actuarial model development.