Description: En el seminario hablaremos sobre los nuevos flujos de tarificación, y nos enfocaremos en la inclusión del análisis geográfico en el proceso de modelado para optimizar la extracción del riesgo en modelos de Machine Learning.

Description: This session will cover everything you've wanted to know about GLMs but were too afraid to ask. How do these generalized models relate to the plain linear regression, and how can we be sure that the models we implement are appropriate for the task at hand?

Description: The editorial board of the North American Actuarial Journal (NAAJ) announces the recipient of the NAAJ Annual Prize for the best paper published in 2023, “The Economic Impact of Extreme Cyber Risk Scenarios,” coauthored by Martin Eling, Mauro Elvedi, and Dr. Greg Falco. The NAAJ is the scholarly journal of the Society of Actuaries (SOA).

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: 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: 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: 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: Learn how modernization of data, models, and technology are influencing workflows. This webcast will address how workflows are changing in response to new regulatory requirements and the impacts the changes have on modeling and end-to-end future state operating models. Industry leading actuaries will discuss: How team collaboration can increase quality and speed of reporting to internal and external stakeholders How to strengthen controls and compliance frameworks across finance and actuarial departments How to modernize actuarial input/output for strategic analysis and insights How to attract and retain top talent by improving opportunities for actuaries There will also be dedicated time to ask questions of those who have made the transition.

Description: The Individual Life Experience Committee is holding a competition encouraging actuaries and other interested parties to predict 2017 industry mortality based on a data set containg 2009 - 2016 data. The competition is not only about predicting mortality, but also about explaining and presenting the results.