But for many, this promise is being hindered by a foundational legal concept: The Principle of Indemnity.

By insisting that property insurance must always be a contract of indemnity (meaning you cannot recover more than your actual, audited loss) regulators have forced the industry into a structural kludge known as the “Dual Trigger.” It’s a legal “fix” that satisfies the status quo but creates a cascade of inefficiencies for insurers and consumers alike.

The Mechanism of the “Dual Trigger”

In a rational parametric model, the data event is the payout. In the regulated world, however, two hurdles must be cleared:

1. The Data Trigger: The physical event occurs (e.g., wind speed, rainfall).
2. The Indemnity Proof: The policyholder must provide evidence that their actual loss equals or exceeds the payout.

This second trigger creates what we might call the Indemnity Trap. It caps the payout at the lower of the two values, fundamentally changing the nature of the risk.

Where the Principle of Indemnity comes from – and why it is a good idea in traditional insurance

Traditional insurance needs indemnity. It ensures the contract restores you rather than enriching you. In the non-life market, we insure the uncertainty of a loss. We don’t just insure the occurrence of an event.

If you could collect a payout that far exceeded your actual loss, you’ve moved from a safety net to a lottery ticket. This “Lotto Effect” turns insurance into a legally sanctioned wager. That windfall potential creates a toxic moral hazard. It invites fraud like arson or staged theft. It also rewards negligence. Why protect an asset when you are worth more if it burns?

By capping payouts at the Ultimate Net Loss, we align the policyholder’s interests with the asset’s survival. Insurance remains a stabilizing force. It protects wealth. It doesn’t generate profit from destruction.

The Problem: Asymmetric Basis Risk

This structure creates a profound misalignment. When we layer an indemnity cap onto a parametric trigger, we create a one-way street of risk:

• When the data misses: If the storm causes massive damage but the sensor doesn’t hit the trigger, the policyholder gets nothing. This is the “Negative Basis Risk” everyone acknowledges.
• When the data hits: If the sensor hits the trigger but the physical damage is light (perhaps because the owner invested in resilience), the indemnity rule steps in and caps the payout.

The result is a structure where the payout can be lower than the data suggests, but never higher. This isn’t a malicious choice by insurers; it is a structural constraint that leaves the risk transfer incomplete. It also reintroduces the very thing parametrics were meant to kill: payout delays. The moment you require a loss audit, the “instant cash” benefit of the parametric model is lost to the administrative friction of the indemnity process.

The Pricing and Underwriting Friction

This isn’t just a headache for policyholders; it complicates pricing.

To price a “clean” parametric policy, an actuary only needs weather data. But to price a policy with an indemnity cap, they must also predict the probability of the cap being hit. This requires traditional, granular underwriting of the asset. We’ve replaced a low-cost, scalable model with a high-cost, bespoke one, simply to satisfy a legal definition.

Assessing the Regulatory Responses

Why do regulators cling to the indemnity requirement? While the intentions are often centered on market stability, the logic behind these defenses deserves a closer look.

Argument 1: The Mitigation Incentive The traditional logic is that indemnity prevents moral hazard. The fear is that if people “profit” from a disaster, they will want the disaster to happen. However, this overlooks a critical reality of resilience. Traditional indemnity insurance actually discourages mitigation. If you spend your own capital to save your factory with sandbags, your indemnity payout simply drops to match your lower loss. In a parametric model without an indemnity cap, you are rewarded for that foresight. You keep the surplus as a “resilience dividend.” The current rules are, in effect, a structural barrier to climate adaptation.

Argument 2: Speculation vs. Insurable Interest There is a concern that without a proof of loss, insurance becomes a “Lotto” or a wager on the weather. But the gatekeeper against speculation should be Insurable Interest, not Indemnity. If a buyer demonstrates a legitimate economic exposure to the event at the point of sale, the speculative element is already addressed. We do not need a cumbersome audit at the back-end to solve a licensing and gatekeeping question at the front-end.

Argument 3: The Life Insurance Precedent It is often argued that property must be treated differently from life insurance because assets have a market value that must not be exceeded. Yet, the Life, Disability, and Critical Illness sectors function perfectly well as “valued contracts.” These are multi-trillion dollar industries that rely on Insurable Interest and a Reasonable Sum Assured. There is no fundamental logical reason why a crop, a solar farm, or a retail business could not be treated with the same “valued contract” logic we already apply to human life.

The Path Forward: The “Ought”

We shouldn’t be trying to “fix” parametric insurance by adding indemnity caps. We should be updating the regulatory framework to recognize Index-Based Insurance as a distinct legal category.

A modern, rational framework would require three things:

1. Provable Insurable Interest (Ensuring the buyer has skin in the game).
2. Reasonable Sum Assured (A cap based on total economic exposure, not just physical damage).
3. Objective, Independent Data Triggers that are demonstrably correlated with the risk exposure

The current “Dual Trigger” system isn’t a design choice; it’s a symptom of a regulatory system that hasn’t changed fast enough. I’d argue the regulations are focused too much on the potential cost and risk of change, while glossing over the downsides of not changing.

Is it time to stop forcing 21st-century risk tools into a 19th-century legal box?

This raises an important question: Should developing markets, including South Africa, adopt SFCR-style public disclosures? How do weigh the costs and benefits, and is this calculus different than in Europe?

The Case for Public SFCR Reporting

Enhancing Industry-Wide Risk Management

• Public disclosures let insurers benchmark themselves against their peers, highlighting best practices and exposing weaknesses.
• Insurers gain valuable insights into what “good” looks like, thus driving overall improvements in industry risk management standards.
• To my own interests, having more detailed information to understand the insurance sector and perform benchmarking would be invaluable. Hopefully my work has some value for individual insurers and maybe even the industry as a whole, but I recognise this point may have less weight for others.

Transparency and Trust

• Detailed reports provide analysts and policyholders with greater clarity into insurers’ operations, solvency, and risk strategies.
• It becomes significantly more challenging for insurers to differently represent (a range from gentle positioning to heavy spin to outright misrepresentation) their financial or risk positions to different stakeholders such as management, control functions, boards, analysts, and regulators when comprehensive information is publicly available.

Better Stakeholder Discipline

• Enhanced transparency makes it more difficult for insurers to conceal emerging solvency or risk issues, thus prompting earlier and more effective regulatory or market intervention.
• Analysts and rating agencies benefit from having direct access to consistent, detailed data, promoting market discipline and investor confidence.

The Downsides and Challenges

Cost and Complexity

• Producing detailed SFCR-style reports is resource-intensive, requiring substantial actuarial expertise, time, and money—resources that are often scarce in developing markets. This is not generally true in South Africa, but is absolutely true across the rest of the continent. Anyway, just because there are resources in South Africa doesn’t automatically mean this is the best use of their time, or that additional demands on these resources won’t impact the supply-demand equating level of salaries and therefore costs for insurers.
• Many insurers in developing markets face significant skills shortages, making it challenging to produce consistently high-quality reports. The level of current internal reporting could benefit from additional resources and time as it is.

Competitive Sensitivities

• Public disclosures risk exposing sensitive strategic insights to competitors, potentially placing companies at a disadvantage in competitive markets. This is often mentioned by insurers – it came out with the original IFRS4 disclosure requirements and again with the IFRS17 disclosure requirements.
• The thing is – I don’t know how many people trawl through competitor financial disclosures to uncover secret strategic source. I’m not dismissing the point, but I am questioning how much of an issue this is. With staff turnover and rotation through industry, there are plenty of mechanisms for more crucial practices to disperse across insurers.

Quality and Utility Concerns

• My experience across large numbers of South African insurers suggests that many insurers already go through the motions, incurring costs without value, in producing ORSA (Own Risk and Solvency Assessment) reports that are not used internally for anything other than compliance.
• Without careful oversight, SFCR-style reports risk becoming tick-box exercises—costly documents that serve regulatory compliance rather than genuine risk management.

Finding the Right Balance

Considering these points, adopting SFCR-style public reporting in South Africa and other developing markets should be approached cautiously:

• Incremental Implementation: Gradually introduce public disclosures, starting with key sections but with a clear roadmap so that insurers know now what they are building towards. There is merit in starting and producing something rather than having endless projects to produce some grand opus in 5 years’ time.
• Proportionality Principle: Ensure reporting requirements align with the insurer’s size and complexity – but this can’t mean that small insurers do nothing. The relevance of risks to each insurers must be considered.
• Standardisation with Flexibility: Provide clear reporting templates to minimise redundancy, enabling insurers to leverage internal reports such as ORSAs, thereby enhancing ongoing risk management practices. There is value in allowing insurers to customise their approach, especially for an ORSA, so that it is most useful for their internal purposes. However, the SFCR is an external document. There is arguably greater merit in standardisation for the reader (ease of navigation, ease of comparability) and for the producer (less time spent changing structure and content and wondering what is expected). Sometimes paint by numbers can great bang for buck.

Final Thoughts

Public SFCR reporting undeniably offers valuable transparency, improves risk management practices, and strengthens market discipline. However, the real challenge is striking a balance—achieving meaningful disclosures without imposing excessive burdens. If implemented thoughtfully, tailored to market realities, and aligned with insurers’ practical capacities, SFCR-style reports could become an essential part of strengthening insurance markets in South Africa and beyond.

In a world where even detailed internal reports like the ORSA are often unread compliance artefacts, is it naïve to think public SFCRs will be any better? Maybe. But transparency has a strange way of forcing people to care. It may be that the SFCR, being publicly available to analysts, regulators, academic researchers, students, and consultants (!) will find more traction and more use than most ORSAs.

The act of writing for an external audience can clean up fuzzy thinking and force clearer articulation of risk positions—something that internal-only reports often fail to achieve. It’s one thing to desire diverse views on a Board, but group-think and anchoring are all too common. I’ve lost track of the number of times the discipline of writing things down has made me realise the ideas in my head weren’t quite as brilliant or even consistent as I’d thought.

Perhaps SFCRs can do that at scale.

This article outlines a collection of common and problematic pitfalls I’ve seen in ORSA stress and scenario testing, capital modelling, and governance. Some are technical, some cultural, and all are worth addressing if we want the ORSA to do what it should: support better decision-making under uncertainty.

These insights reflect my experience across a wide range (and varying quality) of ORSAs, including independent reviews, informal and formal regulatory feedback (including from the Prudential Authority), informal discussions with regulators, and public statements from supervisors across multiple jurisdictions.

1. Toothless Scenarios and Soft Stresses

• Many ORSA scenarios are too mild to test anything meaningful.
• Often there’s no indication of severity. Is this a 1-in-5 or 1-in-50 event? Without context, interpretation is impossible.
• Firms are sometimes surprised they survive a 1-in-200 scenario, forgetting that survival at that level is by design.

2. Recycled, Stale, or Misaligned Scenarios (and Ignored Emerging Risks)

• Same tired stresses reused each year without meaningful refresh.
• Narrative scenarios assigned numerical calibrations that don’t match the story.
• Horizon scanning is often absent or perfunctory; emerging risks must be systematically identified and tested.
• Scenario testing should anticipate what could plausibly happen next, not merely repeat past events.

3. Implausible or Alienating Scenario Design

• Unrealistic or inconsistent scenarios alienate management and the board.
• Severe scenarios are valuable, but they must be framed with historical precedent or research to be credible.
• Overconfidence in models is dangerous; even the best models can fail catastrophically, as history shows.

4. Over-Engineering vs Usefulness

• Attempting to build the “most accurate” pandemic scenario misunderstands the point: scenarios are for learning and planning, not for prediction.
• Prioritise strategic insight over technical perfection.

5. Investment Returns Detached from Reality

• While not common, flat investment income across stress scenarios is a serious modelling failure.
• Investment returns must reflect changes in asset levels and market conditions under stress.

6. LACDT: Tax Calcs Behaving Badly

• Deferred tax recoverability often lacks robust testing.
• Future stressed profits must first create a DTA before any LACDT benefit can be recognised. Tiering here can hit you – more than you considered for the base SCR calc and your QRT.
• Income vs capital gains treatment and tax fund nuances are often overlooked.
• Just because LACDT can’t be negative (per the FSIs), doesn’t mean you can’t have existing DTAs fail recoverability testing in a stress and have loss amplification from deferred taxes!

7. Tiering and Fungibility Constraints Not Considered

• Capital tiering restrictions often ignored under stress.
• Assumed fungibility between entities or tiers can be unrealistic, especially under stress scenarios.
• See the point about DTA and tiering above too.

8. Over-Reliance on Standard Formula Extrapolation

• Normal distribution assumptions are often inappropriate; t-distributions, Lognormal, Pareto tails, or piecewise fittings are better suited.
• Ideally your own experience should be able to inform 1 in 10 stresses and act as a sanity check on scaled 1-in-200 stresses.
• Thin historical experience leads to poor calibration of rare-event risks, especially for equity markets.
• And really, there are several standard formula stresses that are probably not appropriate as a starting point. Some non-life cat stresses may be too conservative – and mass lapse has its critics, but life cat risk, expense risk, and retrenchment risk stresses are likely too low.

9. Unrealistic Business Volume and Expense Assumptions

• Base cases often adopt stretch targets as certain outcomes.
• Expenses are incorrectly assumed to scale perfectly down with policy volumes, ignoring the reality of fixed costs.

10. Incurred vs Paid Confusion

• Claims incurred and claims paid are routinely confused. The impact on profit vs balance sheet and cash can be counter-intuitve.
• Timing differences, especially under IFRS 17 (LCI/CIP dynamics), matter for liquidity and solvency modelling.

11. Short Projections for Long Risks

• Three-year horizons are insufficient for long-burn risks including the obvious candidate – climate change.
• Five years should be the baseline internally, with qualitative insights over longer horizons. Yes, the reliability decreases as the term increases, but it can still be informative. You may chose to disclose only 3 years more broadly, but the longer view is important to at least understand trends.
• Long-term (10–30 year) qualitative assessments should supplement the ORSA, accounting for amplifying systemic interactions.

12. Disconnect Between ORSA and Management Forecasts

• Management runs the business based on one view; the ORSA is prepared using another.
• Without alignment, the ORSA cannot pass the use test or add value to strategic decision-making.

13. Ignoring Dynamic Risk Interactions

• Risks are often modelled in isolation.
• In reality, correlations and feedback loops matter: lapse impacts guarantees, claims experience shifts reinsurance pricing, and market volatility affects lapse and claims simultaneously.

14. Either No Management Actions, or Superhero Versions

• Some ORSAs model no management actions (overly conservative but unrealistic).
• Others assume immediate, flawless actions without delay or cost (equally unrealistic).

15. Unexplained Profit and NAV Changes

• ORSA profit projections must reconcile to balance sheet movements.
• Adjustments between IFRS and SAM/Solvency II frameworks should be clearly documented.

16. ORSA Process Too Slow to Be Relevant

• A nine-month ORSA development cycle leads to stale outputs.
• ORSA timing must be aligned with the business planning cycle and responsive to external shocks.

17. Weak QA and Model Review

• Detailed, independent model review is often absent.
• Common failures include claims timing mismatches, unrealistic ROEs, omitted asset growth dynamics, and unstated assumption interactions.

18. Boilerplate Overload, Insight Underload

• ORSAs are often bloated with standard wording, burying the important insights.
• Focus must remain on what is changing and what genuinely informs management decisions.

19. No Trigger or Process for Out-of-Cycle ORSA

• Firms sometimes only trigger an out-of-cycle (OOC) ORSAs for an SCR breach — far too late. If the risk or solvency situation (internal or external) has changed, it’s time for an OOC.
• Proportional, trigger-based OOC ORSAs must be defined and actioned when material changes occur.
• An OOC doesn’t need to cover the entire process or the full 80 page report. Just the key parts that have changed.

20. Reverse Stress Testing as an Afterthought

• Reverse stress testing needs to explore genuinely different failure modes, not just ramp up severity.
• Defining what constitutes “failure” (capital breach, strategic collapse, or profitability death spiral) needs careful thought.

21. Weak or Missing Rationale for Scenario Selection

• Documenting why scenarios are chosen reveals how the firm prioritises risk.
• Disconnects between identified risks and tested scenarios highlight critical weaknesses.

22. Board Engagement and Use Test Failures

• Board sign-off without meaningful engagement misses the point.
• Effective risk functions bring ORSA components to the Board repeatedly during the year to drive strategic debate.

In Closing

None of these issues is inevitable. Most stem from habits — some from lack of scrutiny, others from good intentions that weren’t tested hard enough. But if the ORSA is to support real-world resilience, it has to reflect how capital and risk actually behave. That means grounding assumptions, engaging the business, and constantly asking: “Would I act on this?†

If the answer is no, the ORSA needs work. If the answer is yes, you’re on the right track.

Regulatory Ambiguity: When Is a Dividend Foreseeable?

The official guidance under Solvency II and SAM states that foreseeable dividends must be deducted from Basic Own Funds (BOF). But when does a dividend become foreseeable?

The European Insurance and Occupational Pensions Authority (EIOPA) defines it as follows:

“A dividend is foreseeable when the payment becomes likely considering the dividend payment history of the company, the business development throughout the year, the reference date of the assessment and, where appropriate, other relevant circumstances.†

Similarly, the South African Prudential Authority (PA) states:

“A dividend is foreseeable at the latest when it is declared or approved by the board of directors, regardless of any requirement for formal approval at an annual general meeting.†

On the surface, this sounds reasonable. But what does “likely† mean in this context? More than a 50% probability? Should a dividend that is merely probable be deducted against a 1-in-200 stress scenario? The dividend itself is not independent of financial stress—if an insurer were actually facing a severe loss event, that dividend likely wouldn’t be paid.

Defining the latest time to recognise a dividend as foreseeable doesn’t help in deciding when a typical or expected time might be. The PA released “technical observations” on this a little while back. Even while taking pains to highlight that technical observations don’t count as regulation, they were still unclear around what is expected.

The crux is that the regulatory guidance provides no clear answer on whether insurers should assume dividends payable from the preceding financial period, or always consider the next 12 months of “likely” or expected dividends. Equally, they also aren’t clear that insurers should not take a multi-year view. Some regulations on subordinated debt require a five-year term to prove permanence. Should insurers also be considering a 3- to 5-year horizon for foreseeable dividends? That doesn’t seem to be expected, but the reasoning and application aren’t consistent across different parts of the regulations.

The Problem of Capital Permanence, Availability, and Loss Absorption

Under Solvency II and SAM, regulatory capital must meet three key criteria:

1. Permanence – Capital should be available for the foreseeable future.
2. Availability – It must be accessible to absorb losses when needed.
3. Loss Absorption – It should genuinely absorb financial shocks.

The rationale in deducting foreseeable dividends is that once a dividend has been communicated to the market or approved by internal management structures, even before shareholder approval, it is nearly impossible not to pay it. That capital is no longer available.

However, requiring insurers to deduct a full year’s dividend in advance assumes earnings have already been generated. If those earnings fail to emerge (as they wouldn’t in a 1-in-200 scenario), then the dividend would likely not be paid. The dividends can absorb these future losses. There’s a parallel here for liquidity risk – Should cash be held now to ensure liquidity for dividends months into the future, even though expected premium receipts will exceed even adverse claims—meaning the dividend could be comfortably funded from future positive cash flow?

Are insurers being asked to treat dividends like senior debt obligations rather than discretionary equity distributions? If so, does that undermine the core purpose of equity funding?

Divergent Industry Practice and Alternative Approaches

Given this uncertainty, industry practice varies widely:

• Many insurers argue that only dividends expected in terms of prior financial periods should be deducted, and then only once the decision has been made to pay the dividend.
• Some insurers take a conservative approach, deducting dividends 12 months ahead, taking a double hit from recently declared dividends and dividends for another year. This depresses reported SCR cover ratios, but should not change absolute required capital levels. Targeted SCR cover levels will often be determined using earnings at risk or economic capital models, or adverse scenarios from an ORSA – all of which will factor in the economic reality that distant future dividends are loss absorbing.
• Other insurers accrue foreseeable dividends based on assumed payout ratio and earnings retained to date. This approach has much to recommend it, including being consistent with many banks’ treatment.

The FCA’s approach under Capital Requirements Regulation (CRR, which applies to banks, not insurers) summarises this last option:

“Before the management body has formally taken a decision or proposed a decision on the distribution of dividends, the amount of foreseeable dividends to be deducted shall equal the amount of interim or year-end profits multiplied by the dividend payout ratio.†

This effectively accrues foreseeable dividends over time rather than imposing a sudden drop in solvency ratios when dividends are declared. While not part of Solvency II or SAM, it is an interesting approach that could bring greater stability to insurance solvency ratios.

Determining SCR Cover Targets: A Practical Approach

Given the uncertainty in regulatory guidance, insurers should ensure that foreseeable dividends are integrated into a broader capital strategy rather than treated as a compliance checkbox. The key is to align foreseeable dividends with SCR cover targets, earnings at risk, and capital models that reflect economic reality.

Rather than simply applying rigid deductions, insurers should consider:

• Economic Capital and Earnings at Risk: Many insurers set target SCR cover ratios based on earnings at risk, ensuring capital sufficiency over a medium-term horizon. Since distant future dividends are inherently loss-absorbing, capital models should reflect that rather than treating them like fixed obligations.
• Scenario-Based Capital Planning: Insurers often use adverse scenario testing to set SCR cover targets. These scenarios should reflect dividend flexibility—how payouts might adjust in stress events rather than assuming mechanical deductions.
• Aligning Regulatory and Economic Views: The disconnect between regulatory capital and economic capital is well known. A structured approach to foreseeable dividends should integrate both perspectives, avoiding artificial volatility in reported solvency while maintaining a robust risk framework.

Insurers that take a strategic approach to SCR cover target setting—factoring in foreseeable dividends dynamically rather than through arbitrary deductions—are better positioned to maintain both solvency resilience and investor confidence. In a regulatory environment that lacks precise guidance, a clear, defensible methodology can differentiate well-managed insurers from the rest.

As the parametric insurance market evolves, so too must our approach to capital modeling. The challenges are significant, but so are the opportunities for innovation and more accurate risk assessment.

In the world of insurance regulation, few mechanisms are as misunderstood as the equity symmetric adjustment (ESA), also known as the equity dampener. This feature, present in both the Solvency II framework in Europe and the Solvency Assessment and Management (SAM) regime in South Africa, is often incorrectly associated with the concept of mean reversion in equity markets. This blog post aims to clarify the true purpose of the equity symmetric adjustment, explain how it works, and explore its implications for insurers and market dynamics.

The Real Purpose of the Equity Symmetric Adjustment

Contrary to popular belief, the ESA is not designed to predict or capitalise on market rebounds. Its primary purpose is to prevent pro-cyclicality in insurance regulation. But what exactly does this mean?

Understanding Pro-cyclicality

Pro-cyclicality refers to the tendency of financial variables to fluctuate around a trend in the same direction as the overall economic cycle. In the context of insurance regulation, pro-cyclical behavior can amplify market stress and potentially contribute to systemic risk.

For instance, during a market downturn:

1. Equity values decrease
2. This reduction in asset values could push insurers’ solvency ratios below regulatory requirements
3. To restore their solvency position, insurers might be forced to sell equities
4. This selling pressure could further depress equity prices, exacerbating the market downturn

This cycle can create a feedback loop, potentially deepening financial crises. The ESA aims to mitigate this risk by adjusting capital requirements based on market movements.

How the Equity Symmetric Adjustment Works

The equity symmetric adjustment modifies the standard equity capital charge based on the current level of an appropriate equity index relative to its average level.

In Solvency II and SAM, the adjustment is calculated as follows:

1. The reference level is the average level of an appropriate equity index, calculated over the last 36 months.
2. The current level of the same index is compared to this reference level.
3. The adjustment is equal to half the difference between these two levels, subject to a maximum adjustment of ±10%.

For example:

• If the current index level is 20% below the reference level, the adjustment would be -10% (capped at the maximum).
• If the current index level is 10% above the reference level, the adjustment would be +5%.

This adjustment is then applied to the base equity shock. For instance, if the base shock for type 1 equities is 39%, and the symmetric adjustment is -7%, the final shock applied would be 32% (39% – 7%).

It’s worth noting that in the recent Solvency II review, EIOPA proposed increasing the cap on this adjustment from ±10% to ±17% to enhance its effectiveness (EIOPA, 2020). There are no immediate plans to change this for South Africa’s regulations.

Dispelling the Mean Reversion Myth

The misconception that the equity symmetric adjustment is based on mean reversion likely stems from its symmetrical nature and its use of historical average index levels. However, it’s crucial to understand that the mechanism functions independently of any assumptions about future market movements.

Mean reversion in financial markets is the hypothesis that asset prices and other market indicators eventually return to their long-term average levels. While this concept remains a topic of debate among financial economists, it’s not the basis for the equity symmetric adjustment.

A comprehensive study by Spierdijk, Bikker, and van den Hoek (2012) found evidence of mean reversion across 18 OECD countries over the 20th century. However, they noted that the speed of mean reversion varies significantly over time and across markets, with half-lives ranging from 1.7 to 23.8 years. This variability underscores the complexity of market behavior and the risks of relying on mean reversion assumptions for short-term regulatory mechanisms.

Moreover, there are numerous examples of prolonged market declines that challenge simplistic mean reversion models. During the Great Depression, the U.S. stock market experienced multiple significant declines before reaching its bottom, and it took over 25 years for the market to regain its pre-crash peak (Mishkin & White, 2002). More recently, during the 2007-2009 financial crisis, global equity markets continued to fall for months after initial sharp declines (Bartram & Bodnar, 2009).

Market Performance After Significant Declines

While not directly related to the equity symmetric adjustment, it’s worth examining market performance following significant declines, as this often informs risk management decisions.

Batnick (2020) found that after 2 standard deviation drawdowns in the S&P 500, the average 1-year forward return was 23.8%. While this figure is impressive, it’s crucial to compare it to typical mean returns. The long-term average annual return of the S&P 500 is about 10% (Damodaran, 2021).

This data might suggest stronger performance post-decline, aligning with some mean reversion theories. However, it’s essential to remember that:

1. Past performance doesn’t guarantee future results
2. Some periods saw continued declines after initial drops
3. The timing and magnitude of any recovery can vary significantly

These factors underscore the importance of careful, context-specific analysis in risk management decisions.

Does the ESA increase or decrease risk?

The application of the ESA results in insurers holding less capital than would be required by a strict 1-in-200 calibration. While this reduction in capital may increase the risk of undercapitalisation and potential failure for individual insurers, the broader systemic benefits must also be considered.

By easing the capital burden during market downturns, the ESA help prevent insurers from being forced to sell assets at depressed prices, which could exacerbate market crashes and contribute to systemic risk. This stabilising effect reduces the likelihood of a market-wide financial collapse, arguably lowering the overall risk to the financial system. However, this trade-off comes with the inherent risk that insurers, holding less capital than prescribed, may face increased vulnerability in the face of prolonged downturns or unexpected shocks.

Balancing these risks is central to the argument for counter-cyclical measures in regulatory frameworks like Solvency II and SAM

Implications for Insurers: LACDT and DTA Recoverability

Understanding the true nature of the equity symmetric adjustment and the complexities of market dynamics is crucial when insurers calculate their Loss Absorbing Capacity of Deferred Taxes (LACDT).

When determining the recoverability of Deferred Tax Assets (DTA) from unrealised capital losses, insurers must carefully consider any assumptions about market recovery or mean reversion. While historical data may support some recovery expectations, it’s crucial to be conservative in these estimates.

The European Insurance and Occupational Pensions Authority (EIOPA) has emphasised the need for prudence in LACDT calculations, particularly concerning assumptions about future returns (EIOPA, 2019). Insurers should ensure that any assumed post-stress returns are well-justified and consider a range of potential scenarios.

Conclusion

The equity symmetric adjustment is a regulatory mechanism designed to mitigate pro-cyclical behavior in insurance markets, not a tool for capturing mean reversion. Its design reflects an understanding of market dynamics and the potential for regulatory requirements to inadvertently exacerbate market stress.

For insurers, it’s crucial to understand both the regulatory perspective of measures like the equity symmetric adjustment and the underlying market dynamics. When conducting internal risk assessments, such as economic capital calculations or Own Risk and Solvency Assessments (ORSAs), a nuanced understanding of market expectations and risks is essential.

Caution is warranted when assuming market recovery after catastrophic events. While historical data may show a tendency for markets to recover over time, the timing and path of such recoveries can be highly uncertain. Improving solvency positions based on optimistic recovery assumptions could expose insurers to significant risks if markets don’t behave as expected.

Effective risk management in the insurance industry requires balancing regulatory compliance with a deep understanding of financial markets, always erring on the side of prudence to ensure long-term stability and policyholder protection.

References

1. Bartram, S. M., & Bodnar, G. M. (2009). No place to hide: The global crisis in equity markets in 2008/2009. Journal of international Money and Finance, 28(8), 1246-1292.
2. Batnick, M. (2020). Here’s what happens after a massive stock market decline. The Irrelevant Investor. [Accessed 25 September 2024]
3. Damodaran, A. (2021). Historical returns on stocks, bonds and bills: 1928-2020. New York University Stern School of Business.
4. European Insurance and Occupational Pensions Authority (EIOPA). (2019). Report on insurers’ asset and liability management in relation to the illiquidity of their liabilities.
5. European Insurance and Occupational Pensions Authority (EIOPA). (2020). Opinion on the 2020 review of Solvency II.
6. Mishkin, F. S., & White, E. N. (2002). U.S. stock market crashes and their aftermath: implications for monetary policy (No. w8992). National Bureau of Economic Research.
7. Spierdijk, L., Bikker, J. A., & van den Hoek, P. (2012). Mean reversion in international stock markets: An empirical analysis of the 20th century. Journal of International Money and Finance, 31(2), 228-249.

Even for a leanly capitalised (re)insurer (SCR cover 1.2x) this implies a CQS of 8, better than the largest, most conservatively capitalised insurers in South Africa.

No externally rated insurer or reinsurer in South Africa has a CQS of better than 11 or 12. The table in 10.9 ignores sovereign or country risk in the default risk assessment. Therefore, it significantly understates spread and default risk.

The question here is not whether there is an absolute sovereign cap that no South African entity can be rated above. The issue is that applying this table almost certainly understates the risk and CQS relative to rated entities because it ignores sovereign risk.

In terms of the sovereign cap, the risk of exposure to South Africa is (and should be) factored into the rating for entities with significant exposure (asset, operations, profit sources, regulatory risk, inflation, appropriation et al) in South Africa. This usually results in predominantly South African businesses not having a credit rating better than the sovereign.

There is more to reinsurance optimisation that interpreting the FSIs. The application of the sovereign cap is also mostly a distraction from the choices of reinsurer and reinsurance programme to manage risk and capital.

#capitalmanagement #reinsurance #CQS #optimisation #sovereigncap #creditrisk

• Growing regulatory acceptance as parametric solutions prove their value. (Issues of insurable interest have posed problems. Currently in testing in “sandbox” regulatory environments in a few countries including South Africa, where it has traditionally been viewed as non-compliant.)
• Addresses previously uninsurable risks for corporates and governments, filling protection gaps. Good application for captive insurers (I’ll cover this more in a later post)
• Complements reinsurance by covering areas traditional policies often exclude
• Primarily used for commercial lines, but personal applications are emerging
• Significant applications for transferring country-level risk for governments and certain NGOs
• Basis risk remains a consideration, but can be mitigated somewhat through careful structuring

Exciting developments include parametric ETFs, allowing investors to participate in this innovative market. We’re also seeing creative applications using new data sources, like phone signals to assess footfall.

I can get theoretically excited about smart-contracts for parametric insurance, but in practice this quickly feels like unnecessary complexity with limited current benefit.

Parametric insurance can compete with reinsurance, but it’s often best used in combination, or as a tool for reinsurers to spread risk

As always, professional advice is crucial when exploring these solutions.

Suggestion – Introduce the equivalent of the UK’s Skilled Person Review

We must find ways to intervene with struggling insurers well before it’s time for a statutory manager or curator. Curators and statutory managers are expensive, invasive, and disruptive – and because of this, implemented as a last resort, meaning the prognosis is usually poor.

The UK’s FCA and PRA have the power to ask for a “Skilled Person Review† often termed a Section 166 review after the section of the Financial Services and Markets Act it falls under.

A skilled person review can entail a variety of roles, including assessing a firm’s governance, risk management, systems, controls, and compliance with regulatory requirements. The skilled person may also recommend remedial actions and provide oversight during their implementation.

These reviews might be triggered by a low or declining solvency level, a question around governance, risk and compliance practices, concerns over product designs and the treatment of customers, or questions related to regulatory compliance in any area.

Early intervention through a skilled person review can help identify and address potential issues in a struggling insurer. This proactive approach can prevent larger problems from arising and potentially avoid the need for more invasive and expensive measures such as placing the insurer into curatorship.

A Skilled Person Review will involve an independent third party with the appropriate skills to perform the review. The review itself could take several weeks or months, with the scope defined by the specific need.

However, insurers might request similar reviews for their internal purposes if the management team or Board have concerns in a particular area.

Benefits for the insurer include:

• Identifying and addressing weaknesses in risk management, governance, and controls.
• Reducing the likelihood of regulatory action due to non-compliance.
• Improving the insurer’s reputation and relationship with regulators.
• Gaining independent insights and recommendations for business improvements.

In South Africa, our regulator doesn’t have the same specific tool in current legislation. There is arguably enough general “investigations† scope in the Financial Sector Regulation Act or the Insurance Act to implement this. The clarity provided by the Section 166 review scope and format, and history of application in the UK provides regulatory certainty for everyone. It also means this regulatory action is less likely to be opposed by insurers.

Earlier investigations that get to the bottom of issues quickly, or allay concerns, may have a role in improving outcomes for policyholders and shareholders alike

With a hefty additional dose of approximations, I get about the same figure all the way back to 1998.

This amounts to an insurer failing every other year.

The primary causes? In every case it’s more than one thing. Here are some of the recent common causes – I’ll expand on each of these in a series of posts.

1 Underwriting risk and pricing

Mispricing, particularly when moving into new markets or new lines of business is a common starting point.

Funeral insurers feeling competitive pressures are looking for new markets – typically semi-underwritten life products, misguided savings products, niche legal expense cover products, or further afield into non-life proper. Here be dragons.

For all the benefit of diversification from a statistical perspective, the research says that focussed insurers fail less often.

Climate change is going to break underwriting and pricing models, meaning that even previously well understood risks increase the chance of failure.

Non-life insurers need to get claims inflation under control – or at least continue the unpopular premium and excess increases to restore sustainability to premium rates.

2 Cost of customer acquisition outstripping funding and VNB

Rapid growth may be many insurers’ dreams.

However, too rapid growth can strain capital adequacy. Rapid growth can also be a telltale sign of under-pricing, leading to large volumes of unprofitable business. Selling many policies that don’t cover their acquisition expenses is a short cut to real trouble.

A worrying sign here is the reduction in VNB margins across broad sectors of the underwritten life insurance space. This ramps up pressures to dilute new business metrics, which is a terrible idea.

3 Misuse, and misrepresentation of (financial) reinsurance

Reinsurance is a fundamentally important tool to manage risk, manage capital requirements, gain expertise in a new market, and to provide liquidity.

Reinsurance, especially financial reinsurance when misused, can obscure the deteriorating solvency position of an insurer and lead to a false sense of security for risk managers, NEDs, and regulators.

The principles on how to treat financial reinsurance and contingent commissions are about right – but the detailed rules and the rigour and honesty with which those principles are implemented sometimes are not.

The overall lesson is – the improvement in your solvency should reflect the actual risk transferred and economics of the transaction.

The most egregious error is claiming that a FinRe deal has resulted in an increase in assets without an increase in liabilities. Tricks of claiming that repayment of the commission (a loan) is contingent on future profits and therefore isn’t a liability are invalid. Games with contract boundaries include recognising the upfront commission (which is to be repaid over many years of renewing contracts), but not recognising years of future reinsurance premiums because the in-force policies have annual contract boundaries.

On contingent commissions, the key question to ask is “has my SCR gone down by more than the risk transferred?”. If one reinsures 70% of the portfolio using QS, but 90% of that risk comes back through contingent commission, then applying the FSIs blindly can result in a 10x overstatement of the benefit of reinsurance. You have shared 7% of the risk, not 70%.

My rule of thumb is not to take advice on the regulatory, solvency, or accounting treatment of the reinsurance from the one selling you the reinsurance.

4 Complex, incestuous asset transactions, and poorly controlled ALM

Aggressive asset valuations, typically of unlisted, illiquid investment that have some related party in the mix, are one of the clearest red flags for an insurer about to fail.  There is always the next Warren Buffet wanting to “invest the float† and make money in some undeveloped property, associated business, or beautiful basket of tulips.

Careful ALM is critical for long-tailed policies. There it needs to be managed carefully and regularly. Monitoring isn’t enough – there needs to be a mechanism to change the portfolio when mismatch parameters breach thresholds.

For other portfolios, sometimes a simpler portfolio that introduces less complexity, fewer tax risks, less operational and liquidity risks, is better than a supposedly more ALM-tuned portfolio that actually increases risks of catastrophic failure.

Asset concentration has been a primary cause of at least one major South African insurance failure before too. Although, as always, this wasn’t the single cause.

5 Taking large (binary) risks when already in trouble

As solvency positions decline, some CEOs, seeing the writing on the wall, choose to take significant risks that will either solve their solvency problem, or increase the impact of insolvency to policyholders.

Something as simple as continuing to write business, especially long-term business, when the solvency capital isn’t available to support this business places existing and new policyholders under additional risk.

Pinning hopes (and management bandwidth) on big-bang investment deals without addressing underlying operational concerns usually don’t pay off.

6 Failed corporate governance

Corporate governance failures are usually the second or third thing to go wrong. Poor internal controls, ineffective or insufficiently independent risk and compliance teams, and outright financial statement fraud mean that serious problems are overlooked, sometimes for years.

Fraud is more often a response to problems (especially where management believes they are in the right and it’s just a matter of time before markets/the cycle/business turns). In select cases, insurers are used as vehicles to instigate fraud as first step

Some boards and shareholders deprioritise good governance. When times are good it’s easy to emphasise good governance. What about when governance gets in the way of decisions executives want to make? Or when it raises awkward questions about pet projects? Or where the business is struggling but management is confident they can trade out of the difficulty as long as they are given the space and time?

It’s easy to do the right thing when it doesn’t come with costs.

7 Slow regulatory intervention

Too often, regulatory intervention is too slow and not targeted at the underlying causes. It’s hard to blame the regulator entirely, given the massive opposition to statutory managers and curatorships.

There are many amazing, skilled, and experienced individuals at our regulator. Are there enough? Is the quality and approach consistent? Are they hamstrung by insurers under resourcing their own control functions and lines of defence?

Can anything be done to decrease failure rates?

Having a strong, experienced, and independent actuary who pays close attention to the regulations and guidance is crucial. Your head of actuarial function should provide good advice on business issues. They should also occasionally constrain your options and make you rethink your positions.

A solid, experienced, and independent Head of Actuarial Function goes a long way.

Appropriate risk management and governance practices are defined in multiple different places, and they can all work well enough if followed diligently. Making sure the teams are experienced and skilled and empowered to tell truth to power is rather more difficult.