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AI / Data Science
Earth, Wind and Fire – Finding and Using Climate Data
Climate data is everywhere. Accessible climate data for actuarial modeling, not so much.
Building on the American Academy of Actuaries’ paper "Climate Data: Actuarial Perspectives on Quality, Challenges, and Effective Risk Quantification", this webinar explores the current landscape of climate data through the lens of various actuarial practice areas. The presentation highlights significant issues regarding data quality and availability, specifically addressing blind spots such as the reporting lag bias in Property & Casualty loss data and the complexity of attributing Life and Health experience to climate changes or weather events. By identifying these cross-practice data gaps, the discussion focuses on potential approaches for improving data accessibility, integration, and usability to support future pricing, reserving, and effective risk quantification.
Speaker: Peter Ott
After a brief stint as a high school math teacher, Peter Ott has been in the insurance and reinsurance industry since 2012. Over his career he has worked on admitted lines, excess and surplus products, and reinsurance. His background includes traditional pricing, catastrophe modeling, data management, stochastic reserving, and actuarial research. In his current role, he serves as Director at Howden Re. Peter is the current Vice-Chairperson for the Climate Change Joint Committee and Chairperson of the Actuaries Climate Index Work Group (ACI/ACRI) of the American Academy of Actuaries.
Speaker: Daniel Pribe
Daniel Pribe is a seasoned actuary and industry leader with expertise in balancing risk and reward, particularly within the healthcare sector. He founded Iris-Edge as a boutique consultancy dedicated to delivering focused, data driven insights that provide clients with a competitive edge. He has over 35 years of experience working in the health care field with extensive experience and expertise in strategic planning and forecasting, Value-Based-Care contracting, contracting, experience and ROI analyses, and medical plan design and pricing for MA, Commercial, and Medicaid lines of business. Dan has written or co-written several articles for the SOA and the American Academy of Actuaries and has spoken on various healthcare related topics such as healthcare reform, climate change, and end of life care in an aging world. He is currently a member of the Society of Actuaries Board of Directors. Dan received his Bachelor of Science degree in Mathematical Statistics from The Ohio State University. He is a Fellow of the Society of Actuaries and a Member of the American Academy of Actuaries.
Moderator: Marc Slutzky
Marc Slutzky an actuary with more than 50 years of experience. At the present he is a Board Member of IACA and is a Member of the Board of Trustees of The Montclair Foundation. During his career he was involved in advising insurers on capital management, mergers and acquisitions and on regulatory and tax issues. He has worked at the Equitable Life Insurance Company, the Home Life Insurance Company and most recently spent 23 years as a Principal of Milliman, Inc. He is a Fellow of the Society of Actuaries, a member of the American Academy of Actuaries and a Chartered Enterprise Risk Analyst.
Building on the American Academy of Actuaries’ paper "Climate Data: Actuarial Perspectives on Quality, Challenges, and Effective Risk Quantification", this webinar explores the current landscape of climate data through the lens of various actuarial practice areas. The presentation highlights significant issues regarding data quality and availability, specifically addressing blind spots such as the reporting lag bias in Property & Casualty loss data and the complexity of attributing Life and Health experience to climate changes or weather events. By identifying these cross-practice data gaps, the discussion focuses on potential approaches for improving data accessibility, integration, and usability to support future pricing, reserving, and effective risk quantification.
Speaker: Peter Ott
After a brief stint as a high school math teacher, Peter Ott has been in the insurance and reinsurance industry since 2012. Over his career he has worked on admitted lines, excess and surplus products, and reinsurance. His background includes traditional pricing, catastrophe modeling, data management, stochastic reserving, and actuarial research. In his current role, he serves as Director at Howden Re. Peter is the current Vice-Chairperson for the Climate Change Joint Committee and Chairperson of the Actuaries Climate Index Work Group (ACI/ACRI) of the American Academy of Actuaries.
Speaker: Daniel Pribe
Daniel Pribe is a seasoned actuary and industry leader with expertise in balancing risk and reward, particularly within the healthcare sector. He founded Iris-Edge as a boutique consultancy dedicated to delivering focused, data driven insights that provide clients with a competitive edge. He has over 35 years of experience working in the health care field with extensive experience and expertise in strategic planning and forecasting, Value-Based-Care contracting, contracting, experience and ROI analyses, and medical plan design and pricing for MA, Commercial, and Medicaid lines of business. Dan has written or co-written several articles for the SOA and the American Academy of Actuaries and has spoken on various healthcare related topics such as healthcare reform, climate change, and end of life care in an aging world. He is currently a member of the Society of Actuaries Board of Directors. Dan received his Bachelor of Science degree in Mathematical Statistics from The Ohio State University. He is a Fellow of the Society of Actuaries and a Member of the American Academy of Actuaries.
Moderator: Marc Slutzky
Marc Slutzky an actuary with more than 50 years of experience. At the present he is a Board Member of IACA and is a Member of the Board of Trustees of The Montclair Foundation. During his career he was involved in advising insurers on capital management, mergers and acquisitions and on regulatory and tax issues. He has worked at the Equitable Life Insurance Company, the Home Life Insurance Company and most recently spent 23 years as a Principal of Milliman, Inc. He is a Fellow of the Society of Actuaries, a member of the American Academy of Actuaries and a Chartered Enterprise Risk Analyst.
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AI / Data Science
Introducing AI in Pension Planning – A Comparative Study of Deep Learning and Fuzzy Mamdani Inference Systems for Estimating Replacement Rates
Introducing AI in Pension Planning: A Comparative Study of Deep Learning and Fuzzy Mamdani Inference Systems for Estimating Replacement Rates
Funded pensions have gained considerable attention as a strategy for securing supplementary income in retirement. This presentation aims to provide a comparative analysis of two methods for estimating the replacement rate: a deep learning model and a Fuzzy Mamdani Inference System (FIS). Since AI has gained considerable ground in the actuarial universe, an obvious step would be to investigate AI techniques, such as neural networks and fuzzy logic, in the realm of pension planning. Initial results indicate that these methods provide accurate estimations, warranting further analysis.
Speaker: Georgios Symeonidis
Moderator: Jennifer Alonso Garcia
Funded pensions have gained considerable attention as a strategy for securing supplementary income in retirement. This presentation aims to provide a comparative analysis of two methods for estimating the replacement rate: a deep learning model and a Fuzzy Mamdani Inference System (FIS). Since AI has gained considerable ground in the actuarial universe, an obvious step would be to investigate AI techniques, such as neural networks and fuzzy logic, in the realm of pension planning. Initial results indicate that these methods provide accurate estimations, warranting further analysis.
Speaker: Georgios Symeonidis
Moderator: Jennifer Alonso Garcia
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AI / Data Science
Hodge Conjecture Millennium Problem Solved?
In the twentieth century, mathematicians developed powerful methods to study the shapes of complex objects by approximating them with simple geometric building blocks of increasing dimension. These techniques proved so useful that they were widely generalized, producing tools that helped classify many mathematical objects—though the geometric origins became obscured, and some added pieces lost direct geometric meaning.
The Hodge Conjecture claims that for certain well-behaved spaces called projective manifolds (smooth projective algebraic varieties), the pieces known as Hodge cycles are actually rational linear combinations of geometric pieces called algebraic cycles.
Although the topic seems far from actuarial science, applications may arise through discrete Hodge theory on graphs and simplicial complexes, which turns these geometric ideas into computable linear-algebraic tools.
Speaker: Simone Farinelli
Session Moderator: Brian Fannin
The Hodge Conjecture claims that for certain well-behaved spaces called projective manifolds (smooth projective algebraic varieties), the pieces known as Hodge cycles are actually rational linear combinations of geometric pieces called algebraic cycles.
Although the topic seems far from actuarial science, applications may arise through discrete Hodge theory on graphs and simplicial complexes, which turns these geometric ideas into computable linear-algebraic tools.
Speaker: Simone Farinelli
Session Moderator: Brian Fannin
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AI / Data Science
Responsible and Human-Centric AI: Why It Matters for the Actuarial Profession
Amidst the recent flurry of activity around AI, actuaries will be in good company as they consider how to extract the benefits of AI advancements, while avoiding their downside risks. Actuaries that develop and deploy AI systems must consider how to deliver the potential gains in accuracy and speed, while avoiding risks like biased decision-making. At the same time, they must carefully consider how AI systems will integrate into employee workflows. Responsible AI and human-centric AI offer valuable guidance to address these issues and can assist actuaries in realising the benefits of AI.
Speaker: Maura Feddersen
Moderator: Ernst Visser
Speaker: Maura Feddersen
Moderator: Ernst Visser
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AI / Data Science
A Maximum Likelihood Approach for Uncertain Volumes in Additive Reserving
The additive reserving model assumes the existence of volume measures such that the corresponding expected loss ratios are identical for all accident years. While classical literature assumes these volumes are known, in practice, accurate volume measures are often unavailable. The issue of uncertain volume measures in the additive model was addressed in a generalization of the loss ratio method published in 2018. The derivation is rather complex and the method computationally intensive, especially for large loss development triangles.
We present an alternative approach that leverages the well-established EM algorithm, significantly reducing computational requirements.
Speaker: Ulrich Riegel
Session moderator: Brian Fannin
We present an alternative approach that leverages the well-established EM algorithm, significantly reducing computational requirements.
Speaker: Ulrich Riegel
Session moderator: Brian Fannin
Members Only
AI / Data Science
Constructing Insurable Risk Portfolios
This talk presents a method for constructing insurable risk portfolios using a data-driven approach to devise risk retention programs that safeguard firms from a multitude of risks. Because firms face many risks, including fire damage to their buildings, liability from management misconduct, and external threats like cyber attacks, this talk treats these potential liabilities as a "portfolio." Drawing inspiration from Markowitz portfolio theory, it leverages techniques from probability, statistics, and optimization to build algorithms that construct optimal risk insurable portfolios under budget constraints.
Through engaging case studies, viewers will learn how to build optimal insurable risk portfolios.
The talk illustrates a frontier that depicts the trade-off between the uncertainty of a portfolio and the cost of risk transfer. This visual representation, mirroring familiar Markowitz investment tools, enables informed decision-making and easy adoption by risk advisors. The talk outlines the mathematical groundwork for constructing optimal insurable risk portfolios in an effective and aesthetically pleasing manner.
Speaker: Edward (Jed) Frees
Moderator: Brian Fannin
The talk illustrates a frontier that depicts the trade-off between the uncertainty of a portfolio and the cost of risk transfer. This visual representation, mirroring familiar Markowitz investment tools, enables informed decision-making and easy adoption by risk advisors. The talk outlines the mathematical groundwork for constructing optimal insurable risk portfolios in an effective and aesthetically pleasing manner.
Speaker: Edward (Jed) Frees
Moderator: Brian Fannin