Description: The cyber insurance market looks like it’s growing—rapidly, in fact. However, there’s more to the cyber insurance market than the outward appearance of strong growth. Worldwide aggregate premium’s upward trend may even be cause for alarm. The increase in premium against a flat rate of insured exposure is a key sign that the market could turn from growth to constriction if a solution isn’t found in the near future. If the cyber insurance sector hopes to reach such lofty goals as exceeding $30 billion in global premium by 2028, it’s going to need more capital. Whether directly into the insurance sector or via support from reinsurance and retrocession, fresh capital should help insurers achieve greater market penetration, build a broader foundation for ongoing expansion, and chart a course for long-term sustainable profitable growth. The same sources capital insurers have used since the early days of the market won’t be enough, though. Thankfully, the insurance linked securities (ILS) market seems poised to help, particularly with several promising recent transactions. New sources of capital could bolster the foundation for future cyber re/insurance growth.

Description: Read the April 2020 issue of Risk Management, published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

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: 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: 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: 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 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: Commentary on practical observations resulting from constructing and running Economic Capital models. Possible standardization of assumptions and result interpretation are morphing even though use of E.C. models has now been around for years.