Description: At the end of December 2020, Congress enacted the Consolidated Appropriates Act, 2021, which included revisions to Section 7702. Effective for policies issued after December 31, 2020, the fixed 4% and 6% minimum annual effective rates under these tests were changed to refer to a market-based rate called the “insurance interest rate”. For contracts issued in 2021, the insurance rate was set to 2% - defined as the lower of the Section 7702 applicable federal interest rate based on the 60-month period ending December 2019 (2%) and the Section 7702 valuation interest rate in effect for 2020 (3.5%). This reduction in the rates used for compliance testing required significant product, operational, and technology changes for companies to reach product compliance. After 2021, the insurance interest rate is redetermined annually with a minimum change floor.

Description: The objective of this paper is to provide a practical guide with concrete case studies to help actuaries implement artificial intelligence and machine learning (AIML) to help accelerate the speed of analysis for life and annuity actuarial modeling. We do so by researching the existing literature regarding AIML and its applicability to stochastic modeling and exploring case studies.

Description: The SOA Research Institute is seeking researchers to study the application of geospatial imagery, high-resolution imagery, and artificial intelligence in loss estimate analytics and underwriting within the insurance industry.

Description: This research study aims to understand the current and planned use of various technology types and tools and to highlight those technologies that are anticipated to grow the fastest among actuaries in 2019.

Description: Feature article describing what author thinks it will take for a life insurance company to be successful in the year 2020.

Description: Cloud computing is a major disruptor to nearly all software products, and actuarial software is no different. Insurers need to start thinking about how they are going to work with their venders to move to the next level of actuarial infrastructure.

Description: A story of one actuary's experience using technology over the past 25 years.

Description: The actuarial profession is at a tipping point and a combination of disruptive technologies and external pressures are creating a unique opportunity to move from results producer to insightful adviser. For a prudent but forward-looking professional, this is exciting and scary in equal measure. The ability to process large masses of business data to make more accurate calculations has become one of the most sought-after skills for leaders across all industries, including insurance.<br><br>The presenters will introduce current data technologies used to manage, process and visualize data. They will cover solutions like Microsoft BI, Tableau, Amazon Redshift, Hadoop, Alteryx, Python, etc. and their applications in data, process improvement, automation, reporting and predictive analytics. In particular, they will explore management reporting and how it leverages data analytics to help business leaders with strategic decisions making, how to evaluate the effectiveness of management reporting structures, drivers of change and ways to improve them, and proposed steps toward entrenching this dynamic and insightful approach to management reporting in which insurance leaders can have confidence.

Description: Ever wanted to do a Kaggle data science competition, but didn't know where to start? This presentation meets the needs of actuaries interested in predictive analytics and competitive data science. The presentation will describe the nature of competitive data science, and provide insights into lessons learned by competing in the Airbus Ship Detection Challenge at Kaggle, as well as other Kaggle competitions. The presenters will provide an introduction to neural networks and describe the nature of the Airbus Ship Detection Challenge and other Kaggle competitions, plus a solution approaches that can be used to obtain top scores using Convolutional Neural networks (CNNs), random forests and boosted trees.

Description: This article introduces IT DevOps to actuaries and how it is applicable to them to improve their modeling efforts and make them more efficient.