Solvency 2 and IFRS 17 reconciliation with SAP Integrated Financial and Risk Architecture, FPSL, PaPM and FRDP

Bridging the Gap: Leveraging Solvency II for IFRS 17's Risk Adjustment IFRS 17 and Solvency II represent two significant regulatory pillars for the insurance industry. While both aim for an economic valuation of insurance liabilities and share fundamental concepts—like the use of probability-weighted cash flows and discounting—they stem from different objectives and regulatory mandates. Consequently, a direct, one-to-one mapping to determine the IFRS 17 cost of risk directly from Solvency II parameters is not possible. However, the industry’s substantial investment in Solvency II systems and the inherent overlap in underlying risk calculations mean that insurers frequently leverage their existing Solvency II framework as a foundational starting point for IFRS 17 compliance. The journey from leveraging to successfully achieving compliance, however, requires significant adaptation. This article breaks down how Solvency II parameters can inform and be adjusted to calculate the IFRS 17 Risk Adjustment (RA)—the IFRS 17 equivalent for the compensation an entity requires for bearing non-financial risk uncertainty. 1. Conceptual Alignment and Key Divergences The most relevant component for comparison is the Solvency II Risk Margin (RM), which is part of the Technical Provisions. Solvency II Risk Margin (RM) vs. IFRS 17 Risk Adjustment (RA) A. Primary Objective Solvency II Risk Margin (RM): Policyholder protection; covering non-hedgeable risks in a transfer value context. IFRS 17 Risk Adjustment (RA): Compensation for bearing uncertainty about the amount and timing of future non-financial cash flows. B. Methodology Solvency II Risk Margin (RM): Prescribed Cost of Capital (CoC) approach (typically 6% of the SCR for non-hedgeable risks). IFRS 17 Risk Adjustment (RA): Principles-based. No prescribed method. Requires disclosure of the method and the equivalent confidence level. C. Scope of Risks Solvency II Risk Margin (RM): All non-hedgeable risks, including non-financial risks and sometimes a component for operational risk. IFRS 17 Risk Adjustment (RA): Explicitly focuses only on non-financial risks. General operational risk is excluded. D. Reinsurance Solvency II Risk Margin (RM): Calculated net of reinsurance. IFRS 17 Risk Adjustment (RA): Calculated separately for gross liabilities and for reinsurance contracts held. E. Aggregation Level Solvency II Risk Margin (RM): Entity level or Line of Business. IFRS 17 Risk Adjustment (RA): Group of Contracts level (disaggregated into annual cohorts and profitability groups). 2. Required Adaptations: Bridging the Differences To effectively transition from the Solvency II RM to the IFRS 17 RA, insurers must systematically adjust their methodology: A. Scope and Risk Definition Risk Isolation: The Solvency II SCR covers a broader set of risks. Insurers must carefully delineate which components of the Solvency II capital requirement (e.g., insurance risk, lapse risk, expense risk) qualify as non-financial risk under IFRS 17, and explicitly exclude general operational risk and financial risks. This exclusion, however, presents a challenge of demarcation. While pure, general operational risk (e.g., system failure, fraud) is excluded, components of operational failure that are inextricably linked to the uncertainty of future non-financial cash flows—such as errors in claims processing, policy administration, or expense inflation due to poor process control—may be considered an inherent part of Insurance Risk or Expense Risk. Actuarial judgment is required to determine which elements of operational risk contribute to the uncertainty of the contractual cash flows and should therefore be captured within the RA calculation. Granularity Challenge: Solvency II RM is typically calculated at a higher aggregate level. IFRS 17 requires calculation or allocation down to the Group of Contracts level, necessitating either finer-grained model runs or robust allocation methodologies. B. Methodology and Parameter Calibration Cost of Capital Rate: While Solvency II mandates a 6% CoC rate, IFRS 17 requires the use of the entity's actual own cost of capital to compensate for bearing non-financial risk. This rate is not prescribed and is a critical area of actuarial judgment and debate. In practice, insurers often determine this rate by referencing their Weighted Average Cost of Capital (WACC), adjusted for the specific non-financial risks embedded in the insurance liabilities. Other approaches might involve a Capital Asset Pricing Model (CAPM) adjustment or a reference to market surveys of required returns for illiquid, non-hedgeable risk capital. The chosen rate must reflect what a potential transfer entity would require to hold the non-financial risk. While referencing internal metrics like the WACC or employing models like the CAPM provides a strong starting point, the ultimate selection and justification of the CoC rate for the IFRS 17 RA must be supported by observable market evidence. IFRS 17 fundamentally views the RA as the compensation a hypothetical market participant would require to assume the non-financial risk. Therefore, insurers must perform robust benchmarking, potentially referencing market surveys of required returns for illiquid or non-hedgeable capital (e.g., private equity or specialty reinsurance returns), and demonstrate how the chosen rate reflects actual transfer pricing or market risk premiums. This adherence to market-consistency is essential for compliance and passes critical regulatory and audit scrutiny. However, it is crucial to acknowledge the inherent practical challenge and subjectivity in obtaining observable, reliable market data for such a specific and illiquid risk premium, often necessitating heavy reliance on expert judgment to bridge the data gap. Crucial Distinction: CoC vs. Discount Rate: It is essential to distinguish the CoC rate from the discount rate used for calculating the present value of the cash flows. Time Horizon: The Solvency II SCR is a 1-year Value-at-Risk (VaR) measure. The IFRS 17 RA must reflect the uncertainty over the full remaining duration of the contract. This requires projecting the relevant capital requirements over the lifetime of the contracts and discounting these future capital figures. Confidence Level Disclosure: While Solvency II uses a 99.5th percentile (1-year VaR) to derive the Solvency Capital Requirement (SCR), the resulting Risk Margin (RM) is calculated as the present value of future capital requirements (SCRs) multiplied by a 6% Cost of Capital (CoC) rate. Because the CoC rate is typically lower than the expected rate of return required to hold the capital, and because the future capital charges are discounted over the full contract duration, the resulting RM amount, when reverse-engineered into a single confidence level over the contract's lifetime, usually equates to a much lower figure—often in the 75%–85% range—for the IFRS 17 RA. This distinction is critical and necessitates actuarial judgment to justify the chosen RA calibration. Alternatively, some insurers adapt their existing Value-at-Risk (VaR) models used for Solvency II by adjusting the confidence level to meet their IFRS 17 risk appetite and aligning the time horizon with the contract duration. C. Reinsurance Treatment: Decoupling and Allocation Challenges The requirement to calculate the IFRS 17 Risk Adjustment gross of reinsurance and then a separate RA for reinsurance contracts held contrasts sharply with Solvency II's net-of-reinsurance calculation. This demands the implementation of distinct processes to model both components independently. A critical complexity arises in the allocation of the premium and the calculation of the RA for the Reinsurance Assets (Reinsurance Contracts Held). Gross RA Calculation: This must be performed as if the reinsurance contract did not exist. Reinsurance RA Calculation: This separate component represents the compensation a hypothetical transfer entity would require to assume the non-financial risk transferred to the reinsurer. Since the amount and timing of cash flows from reinsurance are inherently uncertain (e.g., potential disputes, reinsurer default risk, or cash flow matching issues), the reinsurer's RA is not simply a proportional offset of the gross RA. It must be determined separately by assessing the specific uncertainty associated with the expected cash flows from the reinsurance contract. The Allocation Challenge, Particularly for Non-Proportional Reinsurance For proportional reinsurance, assigning the reinsurance premium to the correct Group of Contracts (GoC) is straightforward. However, for non-proportional reinsurance (e.g., excess-of-loss treaties), a significant complexity arises. Insurers must develop robust actuarial methodologies to allocate the non-proportional premium and the resulting Reinsurance RA to the specific underlying GoCs that benefit from the protection. This often involves marginal allocation techniques or stochastic modeling to attribute the cost of protection across the protected portfolio. This complex allocation ensures the ultimate net position for each GoC is accurately reflected in the financial statements. The Stochastic Modeling Challenge for Non-Proportional Reinsurance Non-proportional reinsurance, by design, protects a layer of the aggregate loss distribution, making the benefit non-linear and difficult to allocate linearly. The core challenge in stochastic modeling is determining the marginal reduction in risk each underlying Group of Contracts (GoC) contributes to the overall reduction in the entity's non-financial risk due to the reinsurance. Specifically, insurers often employ the following techniques, which rely on running the stochastic model under two scenarios: Scenario 1: Gross Risk (with Reinsurance Premium): Model the full gross liabilities to determine the total capital requirement (or the risk measure used for RA). Scenario 2: Net Risk (Post-Reinsurance): Model the liabilities net of the non-proportional treaty. The difference between these two results provides the overall benefit of the reinsurance. The challenge is distributing this benefit coherently (meaning the sum of the allocated parts equals the total) across the affected GoCs. Tail Risk Attribution: Non-proportional cover primarily reduces tail risk. The allocation method must accurately attribute this reduction in tail events (e.g., the 99.5th percentile loss) back to the specific GoCs that contributed to those severe losses in the gross portfolio. This typically requires conditional expectation techniques within the stochastic framework, such as the Euler Allocation Principle applied to the non-proportional reinsurance benefit. Model Correlation: The allocation must account for the correlation structure between the underlying GoCs, as the reinsurance benefit depends not just on the loss of an individual GoC, but on how that loss interacts with the losses of all other GoCs protected by the treaty to hit the treaty's attachment points. Monte Carlo simulations are typically used to capture this complex correlation and loss aggregation behavior across the portfolio. This complex allocation ensures the ultimate net position for each GoC is accurately reflected in the financial statements. 3. Critical Implementation Challenges For a successful implementation, two complex practical challenges must be addressed: A. Treatment and Allocation of Diversification When allocating capital (or the resulting RA) down to the granular Group of Contracts level for IFRS 17, insurers must determine how to appropriately attribute the benefit of this group-level diversification to each specific group. This is a crucial actuarial judgment. Common methodologies used for allocating the capital requirement while maintaining mathematical coherence include: Euler Allocation Principle: A widely used method that allocates capital contributions based on the marginal contribution of each risk component to the overall diversified capital. This method is often preferred because it maintains mathematical coherence (the sum of parts equals the whole) while reflecting the marginal risk contribution of each Group of Contracts to the total diversified capital. Marginal Methods: These methods involve calculating the change in the total capital requirement when a specific risk component (or group of contracts) is slightly increased or decreased. Stand-Alone or Pro-Rata Methods: While simpler, these methods (allocating based on a ratio of the undiversified SCR) often fail to fully reflect the true risk contribution and are less common for robust RA calculations. The choice of method is critical as it directly impacts the risk profile and resulting RA assigned to each Group of Contracts. B. Link to the Contractual Service Margin (CSM) The Risk Adjustment (RA) has a direct and significant financial impact on the balance sheet: CSM Impact: The RA is deducted from the Contractual Service Margin (CSM) (the unearned profit). A higher (more prudent) RA directly leads to a lower initial CSM and thus a slower release of profit over the contract period. P&L Release Mechanism (The Other Side of the Coin): As the entity's exposure to non-financial risk on the group of contracts reduces over time (i.e., less uncertainty remains), the Risk Adjustment is expected to decrease. This decrease in the RA is released directly to the Income Statement (P&L) as part of the Insurance Service Result, effectively recognizing the margin required for bearing risk as that risk dissipates. This gradual release over the life of the contract is the mechanism by which the profit component related to the RA is recognized. Onerous Contract Test: Crucially, the granularity of the IFRS 17 RA calculation—down to the Group of Contracts—is vital for the onerous contract test. If the sum of the estimated future cash flows and the Risk Adjustment (RA) is negative, the group of contracts is deemed onerous (loss-making). Stated mathematically, the group is onerous if: PV (Future Cash Flows) + RA < 0 When a group is identified as onerous, the resulting loss must be recognized immediately in the Income Statement (P&L). Consequently, if an insurer's Solvency II- derived methodology produces an RA that is too high (i.e., too prudent), it could inadvertently push a marginally profitable group into an onerous position, triggering a significant and immediate opening loss upon transition to IFRS 17. This immediate P&L consequence underscores why the calibration of the RA is one of the most material and scrutinized areas of actuarial judgment. Furthermore, the granularity of the IFRS 17 RA calculation—down to the Group of Contracts—provides valuable management information beyond mere compliance. The RA serves as an explicit, market-consistent metric for the cost of bearing non-financial risk, allowing management to better inform strategic decisions related to product pricing, setting risk appetite thresholds, and optimizing the use and structure of reinsurance contracts. By viewing the RA as an economic cost and not just a balance sheet item, insurers can drive more profitable and risk-aware business development. The need to justify the RA level and its allocation becomes paramount given its immediate consequences for financial reporting. 4. The Role of Technology in Integration In essence, Solvency II offers a robust foundation and valuable data, but determining the IFRS 17 Risk Adjustment requires careful adaptation, recalibration, and re-execution of models. This complex data-intensive process is only feasible with an integrated and flexible technological infrastructure. The SAP Integrated Financial and Risk Architecture—supported by components like Financial Products Subledger (FPSL), Profitability and Performance Management (PaPM), and Finance and Risk Data Platform (FRDP)—provides the necessary holistic architecture. This architecture is key because it: Enables Contract-Level Granularity: All analyses are performed at the maximum granularity (the individual contract), with results aggregated upward according to specific IFRS 17 groupings while maintaining full traceability back to the source data. Facilitates Holistic Analysis: It allows for the unified analysis of capital consumed and value generated across different regulatory and management views. Ultimately, by integrating risk flows from the Real Economy with the corresponding hedging and financial contracts in the Financial Economy, such an architecture opens the door not only to compliance but to true Capital Optimization. Given that SAP systems manage a significant portion of the world’s GDP, achieving this comprehensive integration is an attainable goal. 5. Expanding the Context: A Global Perspective While this article focuses on leveraging Solvency II due to its widespread adoption in Europe, the core challenges and adaptation principles apply globally. Many other national regulatory frameworks, such as those in Hong Kong (GL3/5) and Singapore (RBC 2), also utilize a capital-based approach, often involving a Cost of Capital (CoC) methodology for determining technical provisions or solvency capital. Insurers operating in these jurisdictions face similar translation problems: they must isolate non-financial risks, adjust the prescribed CoC rate (if applicable) to align with IFRS 17's market-consistent principles, and implement the necessary granularity for allocation. Therefore, the necessity of systematic adaptation remains a consistent global theme, regardless of the starting regulatory pillar. Connect and Stay Informed: Join the Conversation: Connect with fellow professionals in the SAP Banking Group on LinkedIn. https://www.linkedin.com/groups/92860/ Stay Updated: Subscribe to the SAP Banking Newsletter for the latest insights. https://www.linkedin.com/newsletters/sap-banking-6893665983048081409/ Explore More: Visit the SAP Banking Blog for in-depth articles and analyses. https://sapbank.blogspot.com/ Connect Personally: Feel free to send a LinkedIn invitation; I'm always open to connecting with like-minded individuals. ferran.frances@gmail.com I look forward to hearing your perspectives. Kindest Regards, Ferran Frances-Gil. #CapitalOptimization #SAPIFRA #SAPIBP #SAPFSDM #DigitalTransformation #sapinsurance #RiskManagement #SupplyChain #SAPINDIA #SAPERP #RealTimeData #sapbanking #capitaloptimization #baselIV #ifrs17 #sapbankanalyzer #sapfpsl #sapjobs