IFRS 17: How May Future KPIs Look Like?

Key performance indicators (KPIs) are essential in order to monitor and communicate a life insurance companies’ financial results, and effectively manage the business. This presentation will illustrate how the currently used KPIs may develop and evolve with the adoption and implementation of IFRS 17. Will the IFRS 17 insurance revenue be an appropriate measure for growth? Will the profitability and new business value measures be different? The panelists will discuss the implications of IFRS 17 on the existing KPIs and the possible changes that may lay ahead.

Ralph M Ovsec FSA,FCIA,MAAA (Moderator)

Senior Director; Willis Towers Watson

Ralph is a Senior Director with the Insurance Consulting & Technology business of Willis Towers Watson in Toronto, Canada. Ralph’s expertise include financial and regulatory reporting, financial modeling, reinsurance, mergers and acquisitions, embedded value calculations and life insurance securitization, Canadian GAAP actuarial valuation, asset liability management, earnings analysis and public disclosures, experience analysis, capital requirements and product pricing.Ralph is the Willis Towers Watson global lead on the IFRS 17 on responding to internal queries on IFRS 17 interpretations and developing responses to specific client-related questions. Ralph also leads our external communication on IASB updates and developments.

Dan Kim FSA,CERA,MAAA

Willis Towers Watson

Dan is a director with the Insurance Consulting Technology business of Willis Towers Watson in Atlanta. He has been with Willis Towers Watson since 2007. His experience include financial reporting and risk management with expertise in IFRS 17, embedded value, economic scenario generation, economic capital modeling, and predictive analytics. Dan is a key member of the firm’s IFRS 17 team monitoring the impacts throughout the industry, assessing the impact on our clients and developing strategies and solutions to help clients successfully prepare and implement IFRS 17. Dan’s IFRS 17 related experience includes financial reporting framework development, IFRS 17 calculation engine implementation, developing and reviewing guidance notes/technical papers, and financial impact analysis using IFRS 17 calculation engine.Dan has used predictive modeling tools for experience study, model efficiency, risk analysis purposes. He supports Predictive Analytics Initiative at Willis Towers Watson in researching and published an article on using Bayesian analysis to review uncertainty of predictions.

Thorsten Wagner

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Webcast Session
08/31/2020 at 1:45 PM (EDT)  |  Recorded On: 09/10/2020
08/31/2020 at 1:45 PM (EDT)  |  Recorded On: 09/10/2020
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