Category: AFIR / ERM / RISK - actuview - the international streaming platform for actuaries

Parasol Lost: Recovery Plan Needed

Fri, 24 Apr 2026 13:31:27 +0000

Oliver Bettis, co-author of the latest IFOA paper on climate change: Parasol Lost: Recovery Plan Needed, will present the findings of the report. The full report can be read here: https://actuaries.org.uk/news-and-media-releases/news-articles/2026/jan/...

AI Governance and Risk Management: Perspective from Insurance, Medicine and Space Sectors

Mon, 13 Apr 2026 13:35:30 +0000

Artificial intelligence is profoundly transforming several industries, including the insurance and space sectors as well as medicines regulation. Such transformation is both constrained and driven by the necessity to comply with EU legislative requirements (e.g. EU AI Act) and the availability of a wide range of tools. In this webinar, organised by the AAE, the speakers will explore how each profession is building frameworks for trustworthy and accountable governance around AI. The session will draw out the shared challenges such as the black box problem, bias and fairness, and professional accountability — and what each community can learn from the other.

Welcome and Introduction Esko Kivisaari, Chairperson of AAE AI and Data Science Working Group
Actuarial Governance & High-Risk AI Systems- Bogdan Tautan, Chairperson of AAE Risk Management Committee - Claudio Senatore Vice-Chairperson of AAE AI and Data Science Working Group
European Medicines Agency (EMA): AI in the Medicines Regulation — Perspective on Governance and emerging challenges Denise Umuhire and Orsolya Eotvos, EMA
European Space Agency (ESA): Impact Analysis of AI Regulation in the Navigation Sector Ora Buch Kornreich, ESA
Panel discussion AAE, EMA, ESA: Q&A All speakers & participants

YAI Connect: Development of an Early Warning System (EWS) for Banking Credit Risk

Fri, 10 Apr 2026 11:38:57 +0000

This master’s thesis presents the development of an Early Warning System (EWS) for banking credit risk, focused on the one-year Probability of Default (PD) within the Basel III framework. Using a synthetic retail credit portfolio and a Python-based implementation, several machine learning models are compared to assess their predictive power and robustness with respect to the nature and complexity of the problem.The analysis highlights the strong performance of boosting techniques in capturing non-linear relationships and complex risk patterns. Beyond model accuracy, special attention is given to variable behavior across risk ranges, model interpretability, and threshold calibration, all of which are critical for practical risk management applications.The results confirm that advanced AI-driven EWS can complement traditional credit risk frameworks by providing timely, interpretable, and operationally relevant signals. The study emphasizes a prudent integration of machine learning into regulatory-aligned decision processes, not only from a quantitative perspective but also from a qualitative one, as the proposed EWS incorporates both approaches, supporting earlier intervention and improved financial stability.

From Disaster Relief to Disaster Insurance: Premium Subsidies and the Development of Private Insurance Markets

Wed, 01 Apr 2026 12:48:52 +0000

Presentation from the DGVFM CPD Day in March 2026 on „Accumulation Risks and Risk Sharing in NatCat and Cyber“.

Evolving Climate Risks: Extreme Rainfall and Hail in Perspective

Wed, 01 Apr 2026 12:32:31 +0000

Presentation from the DGVFM CPD Day in March 2026 on „Accumulation Risks and Risk Sharing in NatCat and Cyber“.

Sustainability-Linked Debt, Capital Structure, and Endogenous Default

Mon, 30 Mar 2026 09:28:38 +0000

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We develop a structural credit model of perpetual debt financing in which firms issue sustainability-linked bonds (SLBs) whose coupons step up via penalty payments when predefined sustainability targets are missed. Focusing on firms that aim to reduce emissions, we show that SLBs operate through two distinct channels: the firm can choose a lower endogenous bankruptcy threshold while holding equity value constant, or it can attain a significantly higher total firm value. In the first channel—when the bankruptcy threshold is set lower—SLBs reshape default incentives, extend expected firm lifetime, and can raise debt capacity without proportionally increasing distress costs. As a supplementary extension, we incorporate carbon taxes and subsidies to reflect policy-driven effects on cash flows and incentives, without changing the central mechanism through which SLBs affect default and leverage choices.

Interpretable Ensembles: Enhancing Claim Frequency Modeling with External Socioeco-nomic Factors

Mon, 30 Mar 2026 09:18:42 +0000

The modeling of claim frequencies with interpretable risk factors is central for tariffing and risk classification in Non‑Life Insurance. Advanced ML can estimate the proven and interpretable (sparse) risk factors of a GLM in an automated and data‑driven approach [1]. Alongside the methodical advances, the value of high‑quality internal data histories is recognized by insurers. Additional external features, e.g. climate, spatial or socioeconomic information, can deliver further valuable insights for understanding the underlying risks [2,3,4]. The pooling of diverse external information and detailed internal claims creates a very comprehensive database for a more detailed claims analysis. However, most of the innovative methods are not designed to exploit the advantages of large datasets. Moreover, some of them have convergence difficulties with very large datasets in practice.In this work, we present a novel method to investigate the value of the combination of high‑quality data histories enriched with manifold socioeconomic information using a real dataset. Our approach, inspired by ensembles, enables an efficient modeling while the forecasts remain fully interpretable. In addition, the uncertainty and stability of the effects of single risk factors become visible. The results show quantitatively that both the addition of socioeconomic information and the utilization of concepts for large datasets significantly improve the forecasting quality of both established and innovative actuarial models. References.[1] Devriendt, S., Antonio, K., Reynkens, T., & Verbelen, R. (2021). Sparse regression with multi‑type regularized feature modeling. Insurance: Mathematics and Economics 96, 248‑261. [2] Tufvesson, O., Lindström, J., & Lindström, E. (2019). Spatial statistical modelling of insurance risk: a spatial epidemiological approach to car insurance. Scandinavian Actuarial Journal, 2019(6), 508‑522. [3] Knighton, J., Buchanan, B., Guzman, C., Elliott, R., White, E., & Rahm, B. (2020). Predicting flood insurance claims with hydrologic and socioeconomic demographics via machine learning: Exploring the roles of topography, minority populations, and political dissimilarity. Journal of Environmental Management 272, 111051. [4] NAIC (2025). 2021/2022 Auto Insurance Database Report. https://content.naic.org/sites/default/files/publication-aut-pb-auto-ins.... (Download on 11.08.2025)

Economic Capital for Natural Catastrophe

Wed, 25 Mar 2026 14:31:35 +0000

Natural catastrophes are one of the most significant sources of risk for the insurance industry, especially in countries with high exposure to earthquakes, tsunamis, volcanic eruptions, floods, and other climate-related events. Insurers therefore need not only good underwriting performance but also strong capital management to maintain solvency. Economic capital is a risk-based measure of how much capital an insurer needs to absorb extreme but still plausible losses.

This session introduces the concept of economic capital and explains its importance in managing natural catastrophe (Nat Cat) risk. It also provides an overview of catastrophe modeling and the role of actuaries in converting hazard exposure into financial risk metrics. The main steps in estimating economic capital are discussed, including risk identification, loss distribution modeling, aggregation, and the calculation of Value at Risk (VaR) at an appropriate confidence level.

A case study is presented using MAIPARK’s economic capital as the base scenario. The session then introduces the MAIPARK Facility, a structured reinsurance program designed to reduce Nat Cat exposure. Its impact on net retained risk, reinsurance premium, additional costs, and reinsurance commission is explained. By comparing the base scenario with the post-facility structure, the reduction in required economic capital is quantified. The results show that optimized catastrophe reinsurance can improve capital efficiency and also support a stronger credit risk profile. Overall, this session highlights the important role of actuaries in capital planning and in supporting sustainable solvency in high-catastrophe environments.

The Insurance Industry in India: Emerging Risks, Regulatory Transformation & the Evolving Role of Actuaries

Wed, 25 Mar 2026 14:24:28 +0000

Welcome & Presentation
Overview of India’s insurance landscape by examining market structures, emerging risks, ongoing IRDAI regulatory reforms, and the evolving role of actuaries

Panel Discussion & Farewell

Panelists:

Anjani Choudhary, Product and Pricing Actuary, CreditAccess Life Insurance Limited
Ankit Nanda, Manager of Actuarial Advisory Services, Optum Global Solutions
Vinit Dedhia, Director Actuarial, Marsh McLennan Global Services India Private Limited (MMGS)
Moderator: Shruti Gupta, Board Member & Co-Founder, SANA

At the Heart of Risk: The Evolving Role of Actuaries from Natural Catastrophes to Neural Networks

Wed, 25 Mar 2026 14:16:20 +0000

Actuaries have long applied mathematics and statistics to manage uncertainty across insurance and investments. Today, climate volatility and AI adoption are accelerating the profession’s evolution. This session uses two distinct but connected lenses. First, a natural catastrophe case study focusing on a traditional actuarial practice area. The speakers will focus on Cyclone Ditwah in Sri Lanka to explore protection gaps, disaster risk financing and what “resilience” requires from actuaries. The second presentation will consider an evolving actuarial practice. The speaker will focus on a practical look at how AI is reshaping pricing, underwriting, claims, reserving, capital and enterprise risk management, and the governance and control needed for responsible use.

Localising Global Best Practices: Building Back with Resilience

Cyclone Ditwah had a devastating impact on Sri Lanka, exposing the scale of the prevailing insurance gap, with less than 5% of damages insured. The session will explore best practices from several jurisdictions and consider what fits the local context.

Actuaries can support recovery by translating a complex loss event into practical financial responses. This includes quantifying the loss experience and the drivers of uncertainty using frequency and severity thinking to inform fair premiums and sustainable coverage. Actuaries can also strengthen claims readiness and recovery funding by supporting mechanisms such as national level arrangements to assist underinsured and uninsured households, and by designing pricing approaches that reflect catastrophe risk more explicitly. Further, actuaries can help close protection gaps by developing products and coverage structures that better match how losses arise. For example, the post-event discussion highlighted coverage limitations such as landslides not being included in some natural peril covers. While traditional actuarial skills play a critical role in insurer resilience we could also leverage them in building a climate resilient Sri Lanka.

Actuaries in the Age of AI: Evolving Roles, New Risks, and Responsible Innovation

The actuary is increasingly expected to move beyond model production towards the governance and stewardship of intelligent systems: assessing whether AI models are fit for purpose, understanding their limitations, challenging their outputs, monitoring unintended consequences, and ensuring that their use is consistent with regulatory requirements, ethical principles, and sound risk management. In this environment, actuarial value lies not only in technical proficiency, but in the ability to combine quantitative expertise with judgement, governance discipline, and a clear understanding of financial impact. The evolving relationship between actuarial science and AI therefore reflects a broader transformation in the profession itself. This changing landscape offers actuaries a timely opportunity to lead at the intersection of innovation, risk governance, and trust, ensuring that the use of AI is both forward-looking and responsibly grounded, considering the growing relevance of AI across the financial and risk-related sectors.

Opening and Plenary Session 1: Growth in Asia - The Strategic Role of Actuaries

Tue, 24 Mar 2026 06:21:51 +0000

Asia continues to be one of the most dynamic frontiers for the insurance industry, driven by rising incomes, expanding middle classes, and significant protection gaps. Yet the path to growth across markets is far from uniform. Each market presents its own mix of regulatory evolution, demographic trends, distribution models and consumer behaviour that shape how insurers scale sustainably.

This panel brings together senior actuaries and insurance leaders from Mainland China, India, and Indonesia - three of the largest economies in Asia - to explore what is truly driving insurance expansion across Emerging Asia and where the challenges lie. Drawing on practical market experience, panelists will discuss the evolving role of actuaries in balancing rapid growth with underwriting discipline, innovating to address large protection gaps, and leveraging technology to work strategically.

Signature-based Validation of Real-world Economic Scenarios

Fri, 20 Mar 2026 13:44:25 +0000

Motivated by insurance applications, we propose a new approach for the validation of real-world economic scenarios. This approach is based on the statistical test developed by Chevyrev and Oberhauser (2022) and relies on the notions of signature and maximum mean distance. This test allows to check whether two samples of stochastic processes paths come from the same distribution. Our contribution is to apply this test to a variety of stochastic processes exhibiting different pathwise properties (Hölder regularity, autocorrelation, and regime switches) and which are relevant for the modelling of stock prices and stock volatility as well as of inflation in view of actuarial applications.

A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada

Thu, 05 Mar 2026 12:50:35 +0000

There is mounting pressure on (re)insurers to quantify the impacts of climate change, particularly on the frequency and severity of claims from weather events like flooding. This is challenging, as it requires modeling at portfolio scale with enough spatial detail to capture local climate effects.In this webinar, we present a data science approach to assessing pluvial flood risk for insurance portfolios across Canada and the United States. The flood occurrence model quantifies financial impacts of short-term precipitation dynamics under current and future climate conditions using statistical methods, machine learning, and climate model data. It is designed for applications that do not require street-level precision, such as scenario or trend analyses.Our analyses show that climate change and urbanization will generally increase losses across Canada and the United States, though impacts vary across regions. Portfolio applications highlight the importance for (re)insurers of distinguishing between changes in hazard and exposure, as exposure may amplify or reduce the effects of climate change on losses. Read the paper here: DOI: https://doi.org/10.1017/asb.2024.19

Modélisation de l'impact direct de la température sur la mortalité

Wed, 25 Feb 2026 05:37:30 +0000

Le changement climatique constitue une préoccupation majeure ayant des conséquences sur l’ensemble des secteurs d’activité, notamment celui de l’assurance. L’augmentation des températures qui l’accompagne représente un risque sanitaire important, illustré par la canicule de 2003, laquelle a entraîné près de quinze mille décès en excès en France. Ces dernières années, la fréquence et l’intensité des épisodes de chaleur ne cessent d’augmenter et exposent à plus de décès futurs. Dans ce contexte, ce mémoire a pour objectif de quantifier l’impact direct des fluctuations de température sur la mortalité. Cette étude exploite conjointement des variables démographiques et climatiques et met en application les modèles additifs généralisés (GAM) qui allient flexibilité et contrôle du surapprentissage. Le modèle obtenu reproduit les principaux traits de la mortalité, notamment une mortalité élevée à la naissance, un excès de mortalité masculine et une baisse progressive au fil du temps. Les résultats montrent que l’effet de la température forme une relation en U, traduisant une mortalité accrue aux températures extrêmes et que les personnes âgées et les femmes sont plus vulnérables. Enfin, les projections démographiques et climatiques issues de l’INSEE et du GIEC ont permis d’estimer l’évolution future de la mortalité, révélant une hausse progressive du nombre de décès, d’intensité variable selon les scénarios. Ces projections conduisent, pour une personne née en 2000, à une diminution de l’espérance de vie d’environ un mois pour les hommes et de cinq mois pour les femmes dans le scénario 8.5, comparativement au scénario 2.6.

Besoin en capital à travers l'utilisation d'un modèle interne partiel, les limites de l'approche variance covariance

Wed, 25 Feb 2026 05:34:16 +0000

Le cadre réglementaire Solvabilité 2 encadrant les activités d’Assurance et de Réassurance depuis janvier 2016 prévoit la mise en place d’un capital économique réglementaire (SCR) correspondant au niveau de fonds propres nécessaires pour s’assurer que la compagnie ne soit pas en situation de ruine économique avec une probabilité 99,5% à horizon un an. Le régulateur européen propose différentes approches pour son calcul : la formule standard (FS), le modèle interne (MI) ou le modèle interne partiel (MIP), combinant les deux approches. Nous pouvons distinguer 3 types de modèles internes : la FS Entity Specific, le MIP, et le modèle interne total. L’agrégation des risques joue un rôle majeur dans la détermination du SCR au titre des différents risques et permet la prise en compte de l’interaction entre ces différents facteurs. L’ACPR a présenté fin 2023 de nouvelles notices relatives aux modèles internes, indiquant notamment son aptitude à pouvoir déterminer à tous niveaux d’agrégations et tous niveaux de confiance le quantile de la distribution de probabilité prévisionnelle sous-tendant le modèle interne, les contributions au quantile de la distribution de probabilité prévisionnelle des différentes composantes de risque et le comportement joint des facteurs de risques considérés dans le modèle interne. Ces contraintes entrainent la considération de méthodes d’agrégation plus minutieuses que l’approche variance-covariance. Ce mémoire vise à mettre en lumière les défis inhérents à l’agrégation des risques, tels qu’identifiés par l’ACPR. Pour ce faire, nous présenterons une méthodologie permettant la mise en place d’un modèle interne partiellement simulatoire, en concentrant notre étude sur une sélection de risques de marché. Nous évoquerons en articulier la méthode de Curve Fitting et la mise en place d’une structure de dépendance à l’aide de copules.

Clarity Podcast - Episode 3: The ASSA Climate Index

Mon, 23 Feb 2026 11:38:41 +0000

This new tool, developed by the ASSA Climate Change Committee, helps us understand how extreme weather events are impacting South Africa. We sit down with experts Prof. Rendani Mbuvha and Dr. Nadine van der Walt to discuss how this index can help actuaries, businesses, and policymakers manage climate-related risk, hosted by Pamela Hellig.

Insurance Recovery and Resolution Directive – what, why and when.

Wed, 18 Feb 2026 16:46:30 +0000

Welcome and Introduction Lauri Saraste, Chairperson AAE Insurance Committee Pre-emptive Recovery Plans Mike Claffey, Member AAE Insurance Committee This session will cover the requirement for insurers and reinsurers to prepare and maintain recovery plans in all EU countries following the implementation of the IRRD. We will discuss the risk function’s role in recovery planning and how the IRRD and the Solvency II directive overlap. Resolution of Failing Insurance and Reinsurance Entities Arjen Prinsen, De Nederlandsche Bank / Dutch Central Bank This session will cover the proposed mechanisms and authorities that will be established for the resolution of failing insurance and reinsurance entities in all EU countries following the implementation of the IRRD. Insurance Guarantee Schemes in the EU Lauri Saraste, Chairperson AAE Insurance CommitteeEIOPA and the European Commission have recently commenced a review of IGS within the EU. This session will discuss actuarial aspects and insights into current IGS and the IRRD and what this might mean for the future. Q&A With all the speakers discussing topics from audienceModerator: Stephanos Hadjistyllis, Actuarial Association of Europe

Insuring The Uninsurable - Enabling Regulations For Pooling Arrangements

Thu, 19 Feb 2026 08:59:27 +0000

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Actuarial Society Of South Africa Climate Index

Thu, 19 Feb 2026 08:38:47 +0000

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How to Embrace an Increasingly Dynamic Pricing Environment

Wed, 18 Feb 2026 11:45:31 +0000

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Climate Risk and The ORSA

Fri, 13 Feb 2026 09:51:24 +0000

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Merging Two Insurers During the Perfect Storm

Fri, 13 Feb 2026 09:07:50 +0000

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YAWC 2026 Eastern Semifinals

Thu, 12 Feb 2026 12:33:57 +0000

Watch this YAWC 2026 Eastern Semifinals and find out who will move to the finals taking place in Tokyo in November.

YAWC 2026 Western Hemisphere Semifinals

Thu, 12 Feb 2026 12:02:53 +0000

Watch the YAWC Western Hemisphere Semifinals and find out who will move on to the final round taking place in Tokyo in November.

Índice Climático Actuarial (ICA) para Colombia

Thu, 05 Feb 2026 08:25:15 +0000

En esta edición especial del Miércoles Actuarial se realizará la presentación del Índice Climático Actuarial (ICA) para Colombia, una herramienta sin precedentes en el entorno actuarial colombiano. El ICA permite medir con rigor el impacto de fenómenos climáticos extremos, como calor, sequía, viento y precipitaciones intensas, con el objetivo de fortalecer la capacidad de análisis prospectivo y apoyar la toma de decisiones frente a los crecientes desafíos del cambio climático.