Description: As the insurance industry continues to evolve due to a pandemic and rapidly changing economic and regulatory conditions, the role of data scientists and actuaries has become increasingly important. In an interview with the Atidot data science and actuarial team, we discuss what it is like to work at an InsurTech, how data scientists and actuaries can collaborate, and look at some concrete technical examples of where the innovation is having an impact. This article explores what collaboration can look like and how the role of data science and actuary may evolve in the InsurTech industry in the future.

Description: This article delves into the transformative realm of Business Intelligence (BI) tools. We explore the fundamental functionality and structure of these tools, and through case studies illustrate how they offer valuable insights into carrier experience and underwriting dynamics. From real-time data visualization to in-depth data analysis, discover the essential features that empower businesses to make better informed decisions.

Description: This article highlights the findings of a recent SOA survey on accelerated underwriting (AU) practices, including the amount of AU business ceded, the results of three opinion questions, and an estimate of mortality slippage among AU programs.

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: A discussion of the experiences of an actuarial volunteer consulting and training in Samara, Russia

Description: An application of GLM trees to mortality modeling using the Individual Life Experience Committee 2009-2015 dataset. GLM trees are a hybrid of GLMs and decision trees which are analogous to the way actuaries have analyzed data. The major benefits include speeding up actuarial analytic workflows, improving data understanding, and improving data visualization.

Description: Methods and assumptions used in the valuation of savings by external care vendors

Description: Description and welcome to the 2020 Canadian Reinsurance Conference including highlight of the key note speaker

Description: We compare two predictive analytics methods - GLM and GBM in terms of predictiveness vs. interpretability.

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