Description: This article discusses the reliance the banking industry placed on sophisticated mathematical models.

Description: The roots of the crisis are understood on a simplified basis, by 3 Ls: a Lack of accountability b Leverage and c Liquidity. Historically, people requiring mortgages sought their mortgages from local institutions that would conduct the evaluation and hold the risk. Loan officers of these institutions were accountable for the outcomes of their decisions – defaults were a direct reflection on their judgment. Leverage was a second key factor. Institutions guaranteed mortgages against default. The third L, liquidity, because a problem. When property values eventually evidenced their inevitable fall, defaults occurred at historically high rates.

Description: Political figures and journalists have tended to blame deregulation and greed for the credit crisis. However, we would like to suggest that these were not the primary cause of the credit crisis. The real cause of the crisis was faulty regulation and arrogance. Flawed regulation in the over-reliance on complicated capital models and arrogance in believing that the complex mathematical formula in risk models overcame the limitations on input availability and enabled companies to capture returns that were greater than the cost of capital, have led Wall Street by creating CDOs and similar instruments to repackage risks and take out the systematic excess risk charges as profits, and have also allowed companies to run “prudently” on leverage ratios that were in hindsight over the limit.

Description: This article highlights some of the results from the Society of Actuaries SOA 2010 update to the 2005 Reflecting Risk in Pricing Survey. The survey focused on how companies are trying to price for and understand the risks inherent in the products they sell in various product lines—life and annuity, health, and property and casualty P&C insurance—and showed results for various countries of location and business focus.

Description: This article discusses the causes of the 1918 influenza pandemic, the reasons it occurred and the likelihood that it could happen again. In addition, the author discussed ways, in general, to model and manage risks that occur infrequently, yet have a significant impact.

Description: Results of the 2020 survey on the effects of the Pandemic

Description: In this article, the authors discuss measuring and understanding the more holistic value of risk management. In particular, organizations are struggling with how to best determine the market value of risk management strategies.

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: This paper evaluates the current practice of operational risk management in the insurance sector. Operational risk is nothing new in insurance, but, because of regulatory requirements, companies have initiated computation of risk capital for their operational losses. The current effort to manage operational risk is not a naturally evolving phenomenon, and operational risk, in the Basel Committee on Banking Supervision’s Basel II definition, is unlikely to be a significant cause of insurers’ failure. In addition, the current Basel II definition of operational risk is not suitable for the insurance sector. Consequently, the invention of models and tools based on the definition is incomplete and illusionary. My findings are based on the analysis of dozens of interviews with insurance industry professionals. I demonstrate the way operational risk is quantified in practice, show that the result obtained from this computation is of littl e use in managerial decision making and propose a set of policy recommendations illustrating the characteristics of operational risk in insurance. This study can be used as a platform for launching dialogues to initiate fresh thinking about operational risk in insurance beyond the current artificial and narrow boundaries.

Description: Results of a Survey of JRMS members re claims changes due to COVID