Description: Article describes how to write effective model documentation

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: Reunite with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, IFRS 17, product strategy, cross-border communication and discussion, and more. Advance your career through learning and networking opportunities, and share your experiences in the finance and insurance industries, as well as other fields related to actuarial science.

Description: An overview of the articles in the November 2019 issue of The Modeling Platform, and a plea for submissions! Please! Send us articles!

Description: Learn from panelists from different companies as they come together to discuss their experiences.

Description: The article warns against treating the results of a stochastic model with more deference than other actuarial analysis, and describes some hidden risks involved with choice of model and calibration.

Description: Actuarial Standards of Practice (ASOP) #12 on Risk Classification is being revised while the Academy of Actuaries Issue Brief on Discrimination, published in August 2023, is shaping how bias and discrimination are thought through as actuaries. Individual states like Colorado and New York are suggesting approaches, and the Society of Actuaries, the Casualty Actuarial Society and other actuarial associations are providing the actuaries the tools to address practical cases.

Description: This session will examine bias from a social science perspective. It will discuss the three types of systemic biases using the National Institute of Standards and Technology (NIST) model. The NIST model details the three types as historical bias, societal bias, and institutionalbias. The session will also provide several examples of each type to provide a framework for identifying the social structure of bias.

Description: Come discuss modeling costs and its governance, as well as introduce some platforms for more granular asset modeling.