The dawn of a new wave of internal models for Solvency II


Thursday, June 17, 2021 | By Paolo Laureti, Product Manager, SS&C Algorithmics

The dawn of a new wave of internal models for Solvency II

Why do we see an increasing demand for sophisticated Enterprise Risk Management (ERM) platforms coming from European insurers, and what lies ahead

At the onset of Solvency II, only a selected group of insurance and reinsurance undertakings—very unevenly distributed across European regions—went for an internal model approach. Five years have passed, during which the risk management culture has matured, with complex ERM systems being adopted by an increasing number of companies.

This process has dramatically accelerated in the last few months, as we witness a new wave of simulation-based economic capital implementations, particularly in those countries where the first wave left out a few significant players. Many such initiatives have been brewing for some time, and the COVID-19 crisis just added the final straw. Others are just beginning to emerge, so it is still unclear whether they will lead to an internal model application in the short term.

But what are the reasons for this new appeal for advanced ERM solutions? While each firm has its unique drivers, such as a change in the management structure or a shift in the business focus areas, we can identify a few common traits.

The insurance landscape has been reshaped by numerous mergers and acquisitions, which have had a huge impact on risk and governance. Meanwhile, regulatory frameworks are evolving; market-consistent balance sheet has come to be the standard for financial reporting, and a major review of Solvency II is ongoing. Those changes motivated some companies to reconsider the advantages of a customized capital management system.

Overall, the benefits brought about by accurate risk oversight have become apparent. European economies have been hit by widespread uncertainty and lockdowns after years of low rates, with dramatic impact on the investment portfolios of many firms. At the same time, new applicants can now profit from past experience, leveraging a widespread knowledge base supported by mature software solutions, which can be deployed on cloud infrastructures to ultimately lower the total cost of ownership.

The pandemic exerted tremendous pressure on financial institutions worldwide, insurance firms being no exception. They had to face the direct impact of outbreaks on their business operations and an increase in mortality rates affecting their life portfolios. Most importantly, high market volatility called for more active risk and portfolio management, while the underlying economies were slowing down and credit spreads started widening. Companies endowed with advanced risk dashboards have often been able to run ad-hoc stress tests and to rebalance their asset allocation efficiently, which gave them a competitive advantage.

While the recent market turmoil demonstrated once more the importance of risk-aware business decisions, the necessity of precise asset modeling has been around for a much longer period. Since interest rates started plummeting over a decade ago in advanced economies, insurers have changed their portfolio composition in search of yield to fulfill high guarantees on the liability side. Corporates, infrastructure and alternative investments have often replaced the traditional long-term government bonds, resulting in riskier and credit-intensive P&L distributions. Standard formula approaches to capital calculation were not designed to capture them and proved inadequate in many cases.

The novel demand for industrialized ERM platforms, whether it is driven by regulatory pressure or business stakeholders, originates in most cases from market risk, but it is often complemented by integrated credit risk management requirements. Cash-flow projections and proxies for the liabilities are part of typical solutions, where the scope goes beyond regulatory compliance to embrace the entire asset and liability management process. Efficient data sourcing and cloud bursting capabilities are also part of streamlined ERM procedures, where clients often want to overlay portfolio optimization routines to support the strategic asset allocation functions.

Are we at the dawn of a new wave of internal model applications for Solvency II? It is very possible, and it is generally a step in the right direction.

For more information about how to enhance your risk management analytics, explore our SS&C Algorithmics Risk for Insurance product page.



Insurance, Regulation


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