Life insurers across Europe are navigating one of the most volatile and complex investment environments in decades.
With inflation pressures persisting, market cycles shifting, and regulatory frameworks like Solvency II and Solvency UK evolving, insurers are under pressure to strengthen their Asset-Liability Management (ALM) strategies. Yet, many still rely on simplistic, spreadsheet-based Strategic Asset Allocation (SAA) models that struggle to account for today’s risks and market realities.
Ortec Finance, which offers technology and solutions for risk and return management, has released a report exploring why EU life insurance firms need sophisticated ALM models.
While spreadsheets have long been the backbone of insurance modelling, their limitations are becoming clear. They fail to capture non-linear risks, optimise multiple objectives, or integrate evolving regulatory capital requirements. Insurers are already accustomed to using sophisticated modelling in actuarial valuations—now, it’s time to bring that same rigour to the asset side, Ortec explained.
As insurers increasingly diversify into private credit, infrastructure, and other alternative asset classes, the need for more sophisticated modelling intensifies. These assets promise yield and diversification but also introduce new risks, such as illiquidity and irregular cash flows. Without robust models, insurers may misjudge how these assets perform under stress, leading to asset-liability mismatches that can undermine capital efficiency and solvency.
Capital optimisation is central to maintaining a competitive edge. Under Solvency II, the capital charges tied to specific asset classes directly influence portfolio construction. Advanced ALM models integrate these capital considerations into portfolio optimisation, allowing insurers to balance returns and regulatory requirements more efficiently. By doing so, insurers can identify high-return, low-capital-consumption assets—enhancing solvency ratios and freeing capacity for reinvestment, dividends, or growth initiatives.
Furthermore, stochastic ALM models take capital efficiency a step further by simulating thousands of economic scenarios. These stress tests help insurers anticipate how solvency ratios respond under varying market conditions, ensuring that stability is never sacrificed for yield.
The modern investment landscape is rife with uncertainty, from the persistence of inflation to the trajectory of interest rates and the performance of private versus public markets. Advanced ALM models enable insurers to explore and compare these diverging economic narratives. Through scenario analysis, insurers can assess outcomes across multiple horizons, testing bespoke situations such as trade disruptions, stagflation, or climate-related shocks.
The case for advanced ALM models in life insurance is therefore clear. As balance sheets grow and investment landscapes evolve, insurers must move beyond spreadsheets to harness modern, data-driven tools that can capture complexity, enhance capital efficiency, and strengthen long-term resilience.
For more insights, read the full story here.
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