Description: Data science, predictive analytics and AI are certainly the buzzwords these days. They are heavily used and developed in underwriting and marketing but for most actuaries, they might/may as well be science fiction. The presenters will demonstrate how a normal actuary can utilize data science techniques in their daily job function without forming an official data science team within a company. It can be done in a gradual fashion so that normal business is not disrupted and improvements are made over time. The usage of data science techniques will include demonstrations of the following areas: - Regression analysis - Economic scenario generator - Experience study - Data quality checks - Inforce compression for explicit hedging

Description: Using the Internet as a Pricing Tool clinical background information, defining the change in coverage, collecting data, data quality and data limitations. Issue No. 39.

Description: Volatile interest rates, repositioned investment portfolios, and stress in the banking sector are driving insurers to manage market risk and counterparty credit risk. Our experts in investments, derivatives, and hedge accounting will discuss this new market environment and its impact on hedging. The conversation will include practical case studies, including hedging future bond purchases, hedging floating-rate CLOs, and counterparty credit risk management.

Description: Open source programming languages have become a common part of the actuarial toolkit over the years. Using tools like R and Python, highly technical actuaries can automate onerous processes, easily work with massive amounts of data, create models and generate reports. Although these tools excel at turbo-charging analysts, it can be difficult for benefits to inure to the rest of the organization given the learning curve (“Can’t you just put this in Excel?”), control risks (“So your entire process could break overnight if some random person in Nebraska changes something?”), and internal IT environments. Listen in on a panel discussion where presenters share their personal stories of working with open source in a production setting. Hear about real world business problems, how open source tools were used, what risks were present, how they were overcome and the final business result.

Description: Learn more about the predictive modeling that was applied to industry data for the lapse and mortality experience in the post-level term period. Novel approaches were taken to model the shock lapse, subsequent lapse, and mortality experience. Observe a demonstration of the Tableau tool, which was built to allow users to analyze data on their own.

Description: The supplemental health market is changing. Carriers are looking to simplify claims processes, proactively identify missed claim opportunities, and reduce barriers to claim payment. As a result, more and more companies are looking at ways to use data from medical diagnostic and treatment codes. Take an introductory look at the most used medical codes—ICD (9 and 10), CPT, and HCPCS. Discuss the history and purpose of each code system and decipher the structure. Dive into how medical codes can be used in the supplemental health market (automatic claims adjudication, fraud identification, pricing), as well as common pitfalls encountered when using medical coding. By attending this session, you will have a basic understanding of the different types of medical codes, their actuarial applications, and common pitfalls.