Description: Many ERM programs fail to include an active step of actual risk treatment and are therefore rightfully characterized as Entertainment Systems. Real ERM will use risk assessment to drive decisions about risk acceptance and risk mitigation. Entertainment systems use risk assessment to create reports and to hold discussions. No actions are taken often because ERM is not empowered to do anything.

Description: Introduces the concept of total risk analysis, a methodology used to answer questions like "what are the chances we will lose more than $1 million"

Description: This article will further discuss decentralized and centralized model development frameworks and provide tips and rationale for transitioning toward centralized model development.

Description: This article will highlight the issue that the sum of key-rate metrics does not add to metrics derived by parallel shift to the entire curve, even at very low shift size. Additionally, in the article I will outline how to define a single rate change to be applied to a key rate (or the entire curve) since the rate changes are generally not level or parallel.

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.

Description: Strategic Risk Management was given lower priority in a recent survey of ERM Objectives. This article tells how the author believes that recent events have caused many to shift to a more short term focus and in the future there will be a shift back to a priority for the longer term view that stands behind Strategic Risk Management when the environment settles down and things again seem to be more predictable.

Description: In this article, the interviewers will discuss the pros and cons of centralized modeling function vs a business unit based modeling function. Their experience will help us in identifying factors in contributing to a successful centralized model function and understand how to set expectation with modeling stakeholders.

Description: Our previous article, “Introduction of Cashflow Matching Strategic Asset Allocation (SAA) Framework,” introduced the concept and included a real-world case study that developed a liability-driven investment strategy for a single line of business (LOB) for a life insurer. This article expands the framework and the case study from a single LOB to simultaneously optimize asset allocation across multiple LOBs. It discusses how this multi-line SAA framework can enable an insurance company to efficiently tag its asset holdings to each LOB, identify opportunities in the public and private asset markets to enhance risk-adjusted returns, and develop a deeper understanding of the trade-off between the degree of cashflow matching and risk-adjusted returns across LOBs.

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: There will be inflection points in the value of an instrument when interest rates change. These inflection points could materially impact the approximation of value change using ALM metrics. In this part of the seven-part series, I will highlight: • How to identify the inflection points; • the range of rate changes where ALM metrics may be relied upon i.e., the “validity” range, outside of which recalculation of the ALM metrics is required and the potential that one needs to rebalance the portfolio; • a technique to improve on the approximation of value change beyond the validity range; and • a technique to convert non-linear change on the yield curve to be used with duration and convexity.