Description: CMS provides ACOs with monthly claims data for members, including their medical visits and ACO program eligibility. This data can be divided into Membership and Claims tables through the ETL process. However, when calculating PMPY at specific levels of detail using these tables, issues arise due to unrelated dimensions, leading to inaccurate and understated results. This article presents a solution to this problem by utilizing Tableau's data blending capabilities.

Description: Applying Predictive Analytics for Insurance Assumptions Setting: high level principles.

Description: A new project combining survey data from people across the country with data from John's Hopkins and the CDC on COVID cases and deaths. This project provides weekly data for individuals, businesses, and policy makers to understand which COVID mitigation efforts are in place in their area, how they are working, and how different COVID mitigation methods have been working in different parts of the country.

Description: Deep learning neural network applied to experience analysis for post-level term lapse and mortality.

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.