Description: The Actuarial Innovation and Technology Steering Committee of the Society of Actuaries is sponsoring this competition to encourage contestants to find innovative usages for data visualization software. This contest seeks to give actuaries and non-actuaries the chance to showcase their ability to tell a story by creating data visualizations for one of two standard datasets that have been created for this purpose.

Description: Peer-to-peer (P2P) insurance is one such business model where individuals or economic agents join together and pool their resources for mutual aid. The aim of this project is to showcase the development of a P2P insurance model and analyze it from both technological and product perspectives.

Description: Decentralized insurance alternatives is a rapidly expanding sector of Decentralized Finance (DeFi), an emerging and growing financial ecosystem powered by blockchain technologies. The purpose of this report is to review and discuss the business models and operating designs of decentralized insurance alternatives, which may have significant implications for traditional insurance businesses, as well as the actuarial profession.

Description: The scope of this paper is to provide a technical overview of the tools and disciplines currently in AI as well as the forces at work that financial institutions such as insurance companies are using to modernize their analytical processes.

Description: Actuarial modeling has gone through several distinct phases largely defined by the underlying technology platform. Today, cloud computing is again redefining the technology foundations of actuarial modeling and related processes.

Description: This discussion looks at general topics associated with electronics such as storage methods. From Transactions of Society of Actuaries 1960, Vol. 12, No. 34.

Description: This paper stresses the importance and value of information databases. From Actuarial Research Clearing House 1993, VOL. 3.

Description: Research paper describing past and future in Information Technology. Contents based on address given at the 16th Annual Actuarial Research Conference

Description: Machine learning algorithms fit models based on patterns identified in data and can be very complex. In this report, we describe and illustrate a range of methods for interpreting machine learning models from the growing field of Interpretable Machine Learning (IML).

Description: This literature review provides insights on emerging technologies that interact with the actuarial profession within the space of microinsurance for the purpose of establishing a frame of reference for actuaries to use in their work. Furthermore, it intends to spark readers’ interest in, and create a vision for, how microinsurance and its associated technologies may impact the actuarial industry in the future.