Description: Introducing Random Effects into Risk Score Models

Description: Different mortality projection methodologies are utilized by actuaries across applications and practice areas. As a result, the MIM Advisory Group developed a single framework to serve as a consistent base for practitioners in projecting mortality improvement.

Description: "As digitization and automation rapidly progress in today’s life and health industry, issues with misrepresentation during the insurance application process are also becoming a growing concern for insurers around the globe. A recent survey finds that misrepresentation in application forms costs the average insurance customer an estimated 5% to 10% in higher premiums. In order to reduce this risk, insurers must find and correct areas of misrepresentation, consult post-issue sampling, review the automated underwriting processes, and monitor the quality of financial advisory firms. Learn how predictive disclosure modeling detects and reduces misrepresentation by harnessing readily available underwriting data to analyze issues, helping insurers understand various drivers for disclosure rates and areas of misrepresentation.Advantages of this modeling to various stakeholders in the life insurance journey include improved risk selection, claims experience, and reinsurance terms for insurers. For customers, it leads to increased certainty of coverage, payout of the claim, and ultimately lower premiums on average. By the end of the session, attendees will understand: The disclosure modeling process at a high level The technical details of a standard approach to disclosure modeling: data cleaning, standardization, visualization, and predictive modeling Success stories about how predictive disclosure modeling has impacted insurers"

Description: Analyze financial risk and explore the foundation for pricing, valuation and other functions served by actuaries in the modeling profession during this webcast. Expect a focus on the importance of understanding and preventing bias. Observe the different types of bias, how it can enter into models, how to identify it in models and best avoidance practices. Join our presenter who is pursuing a Masters in Economic Analytics at Clemson University as he incorporates his recent economic research into the webcast material.

Description: The National Association of Insurance Commissioners (NAIC) is in the middle of a project to change the real-world economic scenario generator (RW ESG) prescribed for principle-based reserve and capital calculations. Explore a brief summary of the NAIC's RW ESG project and gain a general overview of RW ESGs. Learn how RW ESGs impact principle-based reserve and capital levels, their potential impact on life insurance companies and consider differences between the currently prescribed RW ESG and the proposed RW ESG.

Description: Electronic Health Records are here to stay. Take a deep dive into the world of electronic health records and how the industry is poised to utilize this new form of digital medical data to transform the way policies are underwritten and ultimately, transforming the client experience. Listen to industry experts speak about what they are doing to use this data most effectively and how this ultimately develops into ground-breaking solutions for the industry.

Description: Discussion on modeling Medicare Supplement insurance and the considerations when choosing an Actuarial Modeling Software (AMS). Focuses on model risk management, key modeling assumptions and inputs, and the complex interactions between modeling assumptions and why its critical to have a model that can handle that complexity. This article also touches on the incorporation the of accounting and regulatory regimes into the model, including Statutory, GAAP (Legacy and LDTI), and Tax regimes, and the modeling considerations for sensitivity testing and capital planning. Lastly, the article highlights the capabilities to look for when choosing an AMS for Medicare Supplement

Description: "Can you answer the question 'what are the chances we will lose more than $1 million next year?' without saying 'it depends'? If you miss a projection, can you quantify the chances that the miss was due to random variation vs. an incorrect projection? ten in as presenters demonstrate how to answer these questions and others using total risk analysis. Total risk analysis includes quantifying both the random variation risk and the projection risk associated with actuarial functions like pricing and reserving. After attending this session, you will be able to describe total risk analysis, apply total risk analysis to many actuarial functions."

Description: In this presentation, actuaries and data scientists from Cleveland Clinic and Milliman discuss the development of a sepsis prediction model using machine learning. Presented with a unique challenge of handling massive amounts of data for near real-time risk scoring, the team took their model development to the cloud and delivered a product in less than a week through a unique virtual engagement.

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.