Description: After research involving auto insurance is retracted due to fraud, I revisit my own book review and unskeptical quoting of that now-debunked research. A lesson in ASOP 23, on Data Quality, ensues, as it seems data in the research was falsified. There is also a lesson in ASOP 56, Modeling, which includes aspects of relying on outside experts for model input. At the end of it all, the value of our actuarial professional standards, in light of other professions seemingly having no standards (or no serious repercussions for breaching said standards), shines through. Also, be skeptical of 'one simple trick' approaches to transform the insurance industry.

Description: Even in published scientific research, we find fraudulent data. What is an actuary to do? Let's consider our actuarial principles and standards of practice to question our data quality and truthfulness. In specific, the article addresses ASOP 56 on Modeling and considerations of model risk as well as ASOP 23 on Data Quality. Recent examples are given from a Harvard research fraud controversy as well as questionable sumo statistics.

Description: First from a comparison of U.S. and Japanese interest rates, abrupt switch to sumo, because sumo is life! Okay, it is not -- in March 2022, there was an upset win when a tall but li wrestler won the tournament. Just as in sumo, when it's not the more massive man who wins, we need to question our assumptions in our models.

Description: As of September 2021, there are 8 recorded webinars available for free to Modeling Section members. Each of the 8 are described, as well as how to access them. There are other Modeling Section-related materials also pointed out (podcasts & newsletter)

Description: A look at the COVID-19 crisis in 2020, and how it differs from both prior financial crises and pandemics. The COVID-19 pandemic gives actuaries an opportunity to assess different ways risk may interact, and thereby adjust the profession’s work for the future.

Description: A retelling of the exploits of the little-known Batman villain, The Actuary, with lessons in professionalism and the limitations of predictive models.