Description: Much of the work performed by disability insurance actuaries depends on the availability of accurate and detailed data, which is not always as simple as it sounds. Explore a variety of data challenges faced by disability actuaries, along with potential solutions. Potential topics include finding relevant data, the impact of poor data on valuation work, the impact of new privacy rules, and the potential bias in the data used to develop predictive models.

Description: How are regulation and innovation intertwined? How do we regulate AI/ML in the insurance industry? We will cover how regulators are striking the balance between protection of their constituents and supporting innovation. We will zoom into the case of Predictive Analytics and the regulatory attempt at avoiding undue discrimination. Let's discuss what this really means.

Description: You’ve written the position papers, updated the models, and designed the required disclosures, but you may be wondering how to explain the results during interim financial reporting periods to company management as well as other stakeholders. This session will explore ways to adapt existing management reporting and offer ideas for new metrics. We will explore various methods for analyzing DAC amortization patterns, market risk benefit reserve patterns, and Liability for Future Benefits (LFPB) movements. In addition, this session will explore ways to integrate changes in LDTI with business planning and other broader business issues such as product pricing considerations and reinsurance strategy.