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: 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: Actuarial models and modeling processes continue to grow in complexity, accelerated by the changes in U.S. Statutory, U.S. GAAP and IFRS reporting requirements in the past few years. Modeling and valuation teams are expanding their toolkits beyond the traditional vendor-maintained actuarial software and the MS Office suite of tools. Companies have started to use a variety of tools to improve model dev and valuation processes, including: - Data management - Automation and workflow - Reporting and analytics

Description: CMS has required hospitals to publish their chargemaster rates, cash discounts and negotiated rates as of January 1, 2021. Our panel is comprised of a data strategist, an executive from a large hospital system and an actuary.

Description: Stochastic modeling requirements are resulting in more 'run time' and less 'analysis time'. An expensive solution is leveraging cloud infrastructures and robust computing grids. The presenters will explore the use of cluster modeling and present case studies showcasing this automatable and robust technique, which could allow actuaries to recover the time lost to 'run time'. Developing automatable and clustered models requires robust governance practices to ensure credibility of results.

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: Discuss various analytics and use cases using payer published reimbursement contract data under federal mandate of Transparency in Coverage. These contract rates are publicly available in machine readable format (MRF) starting July 1, 2022, and refreshed monthly. By attending the session, you will have a better understanding of the state-of-art development and analytics using MRF data, including the technologies used to extract and analyze huge MRF files, validation and limitations of published rates, and their use cases.

Description: Come discuss modeling costs and its governance, as well as introduce some platforms for more granular asset modeling.

Description: Modeling teams are getting larger to deal with more complex models and to support more enhancement requests from business and actuarial teams. Actuarial modeling teams can adapt tools and techniques used in the broader IT industry to be more efficient, handle large number of requests while maintaining their quality of work. Explore DevOps tools to track requests, progress made, work assignment and version control systems. See Azure DevOps in action as presenters use it as an illustrative tool to showcase these activities and how they can be beneficial to an actuarial modeling team (regardless of their preferred actuarial modeling system).

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"