Description: New digital data known as alternative data is everywhere. Our industry has seen the financial, and hi-tech industries leverage new digital data to expand their key offerings and core services. From the lens of the global life and health industry, new digital data is still searching to be further understood. Risk assessment is a current focus area for using alternative data. A key question is even though risk assessment has always been data-driven, can it now move to the next level with the arrival of this alternative data. Can we use alternative data to make the risk assessment process quicker, cheaper, or faster thereby driving more sales and better conversion rates. It is an exciting time! With the increased adoption of health and well-being apps, data such as physical activity, nutrition, sleep, and mental wellness is now readily available. Expanded data such as digital biomarkers, IoT data, electronic health records and many more can also be accessed. However, how to effectively implement alternative data remains a challenge across the industry. We firmly believe it is, and will continue to be, imperative to take a structured approach to alternative data through a set of key considerations and a framework of principles.

Description: This article offers ways to make use of Excel more efficient, by applying software development and design principles

Description: Countries developing universal health care via an insurance vehicle face a variety of challenges. Deciding which benefits to include, where to proactively manage health, and how to reimburse network providers are just a sampling of the issues governments concurrently manage. Optimal choices are data-driven responses. For example, high rates of cervical cancer or increasing narcotics prescriptions are trends that can be managed through product changes, modified network payment structures, or even employer based outreach. This kind of information is typically gleaned from established health insurance claims data. However, in emerging health insurance markets, this level of granular claims data is largely missing. It is difficult to manage medical trend when the root causes are unclear. This article explores a pilot medical underwriting project in Jordan.

Description: This article focuses on the market risk benefit (MRB) measurement model and will examine a generic guaranteed minimum death benefit (GMDB) in the context of LDTI and its impact from both the ceding entity and the reinsurer standpoints.

Description: A special issue of the Annals of Actuarial Science, focusing on insurance data science, was published on July 1. As explained by the editors—Katrien Antonio (KU Leuven), Christophe Dutang (Université Paris Dauphine), and Andreas Tsanakas (City, University of London)—the theme of this issue grew out of the rapid and transformative developments in the field, with the increased use of computational statistics, machine learning and artificial intelligence models in insurance applications. While the special issue has been associated with the Second Insurance Data Science Conference, held in June 2019 at ETH Zurich, the published papers come from a wider and very distinguished pool of authors.