Description: The IFRS 17 implementation deadline is near and companies have decisions to make. While many decisions pertain to specific IFRS 17 requirements, others are more strategic in nature. This session will explore key considerations and decisions faced by stakeholders as they finalize their implementation work and determine ongoing best practices in light of this new standard.

Description: Level funded products often target the small group market (2-50) and can result in many manual and tedious processes for underwriting to perform risk assessment. Learn how a carrier used technology to help automate risk assessment without the need for paper medical questionnaires, and exposed a risk engine for broker quoting to enable near real-time of pricing for risk-based products. The approach reduced labor and allowed underwriting to focus solely on fallout cases while also improving pricing consistency. Discuss broader trends in the health market for risk assessment, including new machine learning cost predictions that can be used for automation and better predictions of future costs. Discussion topics will include underwriting guidelines, business rules, risk scores, and machine learning. By attending this session, you will have a better idea of new trends in risk assessment for small groups where no claims experience is available. And, better understand business rules that are common in underwriting for flags for review as well as how risk scores and machine learning can be used during the underwriting process.

Description: Examine initial insights on LDTI modeling best practices, as well as high-level principles that enable successful LDTI model implementation, during this GAAP webcast. Many companies are finalizing their LDTI reporting before their "go live" date of January 1, 2023, and this LDTI Modeling Lessons Learned from AXIS, Prophet and Polysystems webcast details what they've discovered during implementations. Learn about key principles for LDTI modeling, in addition to useful functionalities from AXIS, Prophet and Polysystems software. Explore the AXIS US GAAP Historical Database for ways to import, store and manage historical data for LDTI calculations, Polysystems suite of data tools and software to support LDTI and the Prophet Disclosure Library and LDTI Toolkit that allows self-contained calculations of disclosure entries for LDTI balances.

Description: Innovation in technology has disrupted nearly every industry, creating mounting internal and external pressures on organizations to accelerate the adoption of their digital agendas. The COVID-19 pandemic further brought to light the need for tools and technology to be adaptable, powerful, and scalable. As the insurance industry leaps into the future, actuaries must not only proactively refine their roles and responsibilities within insurance organizations but also seek opportunities for improvements and optimization in their day-to-day work. Discuss a variety of opportunities to streamline, accelerate, and optimize actuarial processes by using modern technology. Cover a wide spectrum of actuarial solutions from automation of actuarial data transformation to actuarial reserve calculations and calibration of economic scenarios. By attending the session, you will: Be able to articulate how modern low-code/no-code technology can help actuaries automate, streamline and optimize processes in yourday to day work tohelp focus on higher value tasks.

Description: Watch as presenters highlight the SOA's work on an updated Medicaid underwriting margin model. This research project includes the model along with a set of instructions and a paper describing the key components of underwriting margin, including cost of capital and risk margin. The model was created as a tool for Medicaid actuaries representing both MCO and state principals to determine appropriate underwriting margin components within Medicaid managed care rates. In addition, explore a brief description of the motivation for an underlying theory behind the model. Walk through different model inputs and run through some realistic scenarios that Medicaid actuaries may encounter in states where they operate.

Description: Asset liability management is an important task for any insurer, where tools like Excel play an important role from an analytics perspective. Dashboard tools like Power Bi and Tableau can supercharge an organization’s ability to perform ALM with real-time precision and monitoring of risk/imbalances. The dashboard can provide insights into potential risks posed by asset allocation and concentration, allowing for informed decision-making to mitigate those risks. The presenters will walk the audience through an example of ALM use case, including how to build key performance indicators such as cash flow, asset allocation, and risk exposure. Additionally, we will demonstrate how these types of dashboards can be customized to fit the specific needs of your organization.

Description: In the light of growing adoption of AI in life insurance and with it a growing emphasis on the need to safeguard the data used against reidentification,traditional approaches to de-identifying data mitigate these risks but often fail to protect against more sophisticated attacks. Find out more about data anonymization methods, geographic differences in regulation (PIPEDA, HIPAA) and special considerations when dealing with particular data types By attending the session, you will: Gain knowledge of various data anonymization techniques and understand the differences in how data anonymity is defined across different regulatory schemes.

Description: Regression to the mean (RTTM) is inflating your health care intervention evaluations if you are not carefully managing it's omnipresent and significant impact RTTM is the statistical phenomenon which arises when comparing sequential data points when an initial observation is extreme or an outlier, and states that with no other intervention, future observations will be closer to the average. Members who had high costs last year will, on average, have lower costs this year, even in the absence of any intervention or clinical program, simply by 'regressing' to the mean. This means that if your clinical programs are simply targeting members who had adverse medical experience last year, you’re targeting the wrong people. And if your savings methodologies are simply last year’s costs minus this year’s costs, the savings are inflated. By attending this session, you will be able to identify situations where RTTM will be a significant factor, how to eliminate it's impact when performing retrospective evaluations, how to identify prospects for clinical intervention with RTTM in mind, and more.

Description: 2021 Life Meeting - Session 8B: Proxy Discrimination in Life Insurance 9.1.21 Recording

Description: This webcast will detail interpretable machine learning techniques for participants to gain an intuition and understanding about the use of these techniques. We will discuss how to apply them, how to understand them, and how to avoid potential pitfalls.