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The implementation of IFRS 17 presents a major challenge for insurance and reinsurance companies. This new forward-looking accounting standard requires a thorough understanding of the entire value chain of the insurance business, given its multidimensional nature. This accounting encompasses managing the timing of underwriting, the associated underlying risks, and the strong interaction between liabilities and assets.
The new prospective accounting will now reflect the profitability of the insurance contract by combining technical profitability (claims expense), financial profitability by taking into account the time effect (discounting of cash flows) and investment income from segregated assets and the underlying risks involved (technical and/or financial depending on the valuation model).
This dynamic interaction requires the implementation of a risk mapping system (technical and financial), the implementation of the best estimation and projection models (recognition of model risk in governance manuals) and the establishment of performance keys based on the quantification of risks (expected vs estimated).
The identification, evaluation and monitoring of these metrics over time are at the heart of IFRS 17; this process will enable the construction of an efficient provisioning model, the optimization of experience gaps in the future and reflect as faithfully as possible the commitments made by companies.
Leveraging the strengths of the Solvency II (SII) prudential standard is highly recommended. Indeed, the risk hierarchy under SII provides a comprehensive (although not exhaustive) overview of the risks companies face and can serve as a starting point for developing a risk map tailored to IFRS requirements. Similarly, the Best Estimate models for technical provisions can be used to calibrate IFRS provisioning models, the consistency of which should be enhanced to optimize the adjustments made based on experience (behavior, inflation, tail factor, exchange rates, trend detection, etc.). The quantification of inherent volatility in the models could also be based on the SII standard model (or used as a benchmark) to calibrate the Adjustment for Risk block, which reflects the uncertainty associated with actuarial models.
Own Risk and Solvency Assessment (ORSA) is defined as a set of processes constituting a decision-making and strategic analysis tool aimed at continuously and prospectively assessing the overall solvency requirement in line with the company's risk profile (risk appetite expressed through tolerance thresholds). ORSA is an undeniable tool for managing the SII standard, given their similarity in terms of empirical data analysis for projection purposes, the projection horizon, and the consideration of the company's own risk profile (risk appetite, unidentified risks under the first pillar of the SII standard, implementation of management strategies in the quantification process, etc.).
ORSA also allows us to define the strategic projection assumptions necessary in the first accounting under IFRS 17 and to perform stress tests regarding their deviation in order to quantify their impact on the profitability of the insurance contract as well as its impact on the solvency of the company.
Similarly, accounting under IFRS 17 could be examined under the two metrics, profitability and solvency, by synchronizing the work (the strategic assumptions) in order to optimize the need for equity as well as their profitability in the short and medium term.
