Description: Equity-Based Insurance Guarantee Webcast Series

Description: Learn from panelists from different companies as they come together to discuss their experiences.

Description: The speakers will discuss the replication of long-term options, including a discussion of issues such as liquidity, transaction costs, slippage, impact of policyholder behavior, and machine learning algorithms to improve hedge effectiveness.

Description: The speaker will discuss the training of neural networks to compute future Greeks of liabilities (or options) without the use of nested stochastics.

Description: This paper provides a new insight to the previous work of Briys and de Varenne [1994], Grosen and Jørgensen [2002] and Chen and Suchanecki [2007]. It shows that if an insurance company follows a risk management strategy, it can significantly change the risk exposure of the company, and that it should thus be taken into account by the regulators.

Description: How adopting a risk champion model can help insurance companies, create a clear distinction between the first line and the second line of defense and ensure proactivity in identifying and addressing risk

Description: The Federal funds rate increased by 4.25% in 2022 with further increases in 2023, which have already resulted in a liquidity crisis for a few banks. As the rapid increase of the interest rates pushed the new money rates above the yields of many life insurers’ investment portfolios, insurance companies are facing a dilemma between compressed margins from peer pressure and the concern with liquidity shortfalls and realized capital losses should mass surrenders happen. This paper discussed main emerging risks under rising interest rate environment, and several ways to mitigate these risks.

Description: How adopting a risk champion model can help insurance companies, create a clear distinction between the first line and the second line of defense and ensure proactivity in identifying and addressing risk

Description: In order for an organization to benefit from artificial intelligence/machine learning (AI/ML) models, it requires the involvement of different business areas. During this webcast, professionals from data analytics, audit and risk areas will address challenges and provide solutions for working together to develop, implement, use and risk manage AI/ML tools. Throughout the discussion, the presenters will discuss: • Defining and exploring the challenges and objectives between data scientists, domain experts and control functions • Risk management – model risks and other risks • End-to-end model validation • Model performance vs. interpretability/understandability trade-offs • What to audit – auditor’s challenge and solutions

Description: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.