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: 2021 ImpACT Conference - Session 14A: Credit Risk & Small Diverse Businesses Within Underserved Communities 10.29.21 Recording

Description: As China’s population officially ages, the government has now escalated reform of China's social security system to a national strategic level. The report of the 19th National Congress further mentioned construction of an old-age security system and social environment, painting a bright future for development of the pension industry. At the moment, development of China's pension industry is beginning a new journey. Learn about the current status and future development of pillar 2 pension, which is core to China's pension system; framework and operation management overview of Enterprise Annuity and Occupational Annuity; possible evolution paths in contribution payment methods’ investment operation models, and development of professional pension managers.

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: This is the second part of a 2 part series on Real options analysis (ROA). This article looks into the limitations of using financial option theory when doing real options analysis with projects that are long-dated and uncertain, such as: 1. First-degree homogeneity, 2. Uncertainty must derive from Brownian motion, and 3. Risk neutrality.

Description: Hear Chief Risk Officer (CRO) perspectives on how COVID-19 has impacted Enterprise Risk Management (ERM). Presenters surveyed CROs from several Life insurance companies and will share key insights. Areas that will be covered include: • Action: Oversight role and responsibilities of ERM during the pandemic • Evolution: Impact to ERM frameworks • Lessons learned

Description: The mismatch between how interest rate impacts the value of assets and liabilities could have material negative impact to companies’ earnings and surplus. To quantify and mitigate the impact of such mismatches, companies have used matching a combination of duration and convexity. I will review these measurement techniques and their limitations.

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

Description: 2011 Enterprise Risk Management Symposium, Chicago. This study investigates whether simulation-based models can be used to predict liquidity risk for banks, which must comply with Basel III by January 2015. The paper looks at the process of developing a measurement framework using Black-Scholes and Merton’s asset-based models to measure liquidity risk.