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.

Risk Appetite Measures and Limits

Risk appetite articulates the level of risk an organisation is willing to accept in pursuit of its goals. This encompasses various metrics and limits that inform decision-making, balancing the pursuit of opportunities with sound risk management. Clear and transparent risk measures empower organisations to evaluate their risk exposure and make informed decisions.

Common measures might include SCR cover, Earnings at Risk, Maximum Single Loss, Maximum and Minimum claims ratios, among others.

Good vs. Bad Reasons to Change Risk Appetite Measures

Organisations frequently confront pressures to adjust their risk measures. Understanding the motivations behind these changes is crucial for effective governance.

Bad Reasons to Change Risk Measures

1. Risk Normalisation: Organisations can become desensitised to risk, gradually accepting higher levels as “normal.” This often surfaces when:
   • Risk indicators linger in amber or red for extended periods without corrective action.
   • Erosion of margins is attributed to market conditions rather than acknowledged underlying issues.
   • Management pressures lead to subjective adjustments of risk ratings to green, creating a façade of control.
   This normalisation breeds complacency, masking potential crises that may arise when unaddressed risks materialise.
2. Strategic Helplessness: When organisations cite perceived limitations—such as outdated systems or legacy portfolios—as reasons for inaction, they fall into a trap of strategic helplessness. Research by Power, Ashby, and Palermo indicates that this can lead to:
   • Ignoring legacy challenges until they escalate to critical levels.
   • Cultivating a culture that discourages acknowledging risks, perpetuating a cycle of poor decision-making.
3. Cultural Complacency: When risk management becomes an afterthought, adjustments to risk measures may reflect organisational inertia rather than genuine risk appetite. This can result in:
   • Diminished engagement from risk teams who feel sidelined in decision-making.
   • A growing disconnect between stated risk appetites and actual practices.

Good Reasons to Change Risk Measures

In contrast, there are valid motivations for revisiting risk appetite measures:

1. Regulatory Changes: New regulations can necessitate adjustments in risk management practices. The introduction of IFRS 17, for example, represents a significant shift in how insurers recognise earnings and assess risk, prompting a thorough reassessment of existing measures.
2. Evolving Market Conditions: Shifts in the external environment, such as economic fluctuations or emerging risks, may require organisations to recalibrate their risk appetite to remain competitive and responsive.
3. New Data and Insights: Advances in data analytics and innovative thinking can enhance calibration processes, enabling organisations to refine their risk measures more accurately. Incorporating new methodologies allows for a more nuanced understanding of risk exposure and leads to more informed decision-making.
4. Strategic Objectives: As organisations evolve and pursue new goals, reassessing risk appetite becomes essential to ensure alignment with broader business strategies.

Example: IFRS 17

The implementation of IFRS 17 demands changes in limits relating to profit, presenting an opportunity for a broader overhaul of risk management frameworks.

Changes to Earnings Recognition and Volatility

IFRS 17 alters earnings recognition by replacing compulsory margins, zeroisation, and discretionary margins—with potentially dramatic impacts on investment guarantee reserves and related insurance contracts—with the Contractual Service Margin (CSM). Key implications include:

• The CSM applies only to profitable contracts and offsets non-economic assumption changes, potentially increasing overall volatility.
• Insurers with minimal prior margins may experience a decrease in volatility as a result of these changes.
• Different choices regarding risk adjustment levels and classifications of directly attributable expenses will impact the size of the CSM, affecting the assessment of onerous contracts and the degree to which severe stresses can deplete the CSM.

IFRS 17 introduces significant complexities related to risks arising from the CSM:

• Matching the CSM is particularly challenging, especially with how it accrues interest based on forward rates locked in over prior decades.
• Insurers now face more intricate decisions regarding whether to hedge Embedded Value (EV), solvency, or IFRS earnings, necessitating a reevaluation of existing risk management strategies.

These changes may require risk limits to adjust with a new subjective acceptance of risk or could place greater pressure to manage risk elsewhere to offset this new volatility.

By recognising these shifts, organisations can make informed decisions about adjusting their risk appetite measures and limits in a manner that reinforces governance and accountability.

Conclusion

Effective risk management in insurance requires a sophisticated understanding of risk appetite measures and the motivations behind changes to these frameworks. By distinguishing between detrimental reasons for adjustment—such as the pitfalls of risk normalisation and strategic helplessness—versus constructive motivations like regulatory changes, shifts in the market, and additional data for calibration, risk functions can seize the opportunity to enhance their risk management systems.

Understanding the Basics: Banks vs Insurers

The classic banking model of liquidity risk is straightforward: banks transform short-term deposits into long-term loans. This maturity transformation creates inherent liquidity risk – even a perfectly solvent bank can face a crisis if too many depositors demand their money simultaneously. This fundamental risk drives the existence of central banks as lenders of last resort.

Insurance traditionally operated differently. With predictable claims patterns, regular premium income and unoptimised balance sheets, insurers weren’t thought to face significant liquidity risks. However, modern insurance practices and product designs have created more complex liquidity dynamics that challenge traditional frameworks. These liquidity-risk-increasing practices include some risk management choices (hedging and use of derivatives) and balance sheet sweating.

Sources of Liquidity Risk for Insurers

Insurance companies face several distinct sources of liquidity risk, some traditional and others emerging from modern practices:

Derivatives and Modern Asset Management

Modern investment strategies create significant liquidity demands:

• Use of illiquid assets through debt origination, greater use of corporate paper in general to provide higher yields for annuities and guaranteed/fixed bond products, private equity and other alternatives seeking additional yield
• Variation margin calls on derivatives require immediate cash as markets move
• Derivative roll risk creates periodic liquidity needs
• Rolling medium term corporate paper maturities into new instruments has elements of liquidity risk as part of the broader roll-risk universe
• Repo arrangements require careful liquidity management
• Hedging programs, while reducing other risks, increase liquidity demands

Policy Surrenders and Lapses

The liquidity impact of surrenders and lapses varies significantly by product type:

• Savings policies backed by liquid assets present limited liquidity risk
• Corporate policies often include liquidation notice periods
• Market value adjustments can share losses with policyholders
• Risk policies with negative liabilities create complex dynamics – while lapse might improve solvency ratios, the loss of positive cash flows can create future liquidity strains
• Loss of shareholder value is still likely the major risk for lapses and surrenders – and as a result it usually gets plenty of attention without the liquidity risk lens.

Internal Hedging and Optimisation

Insurance liquidity isn’t just about having assets to meet claims. Insurers often use positive cash flows from some policies (particularly risk policies with negative liabilities) to fund claims on other, especially older or maturing policies. This practice, while potentially efficient in normal times, creates hidden liquidity risks.

If these positive cash flows diminish (through lapses or reduced new business), the liquidity characteristics of the underlying assets become crucial. An insurer might appear to have strong liquidity based on expected premium inflows, but this can quickly change if those inflows reduce or stop.

Further, using negative liabilities (from profitable, early duration risk policies) to match positive ones (e.g., guaranteed savings products) creates hidden liquidity risk. This practice is another example of the “improvement” of an old, “lazy” matching approach that missed this opportunity for internal hedging, but perhaps reduces implicit buffers we may have come to rely on.

Claims Concentration

Sudden spikes in claims can create liquidity pressure:

• Natural catastrophes affecting property insurance
• Pandemic-related death claims
• Industrial accident clusters
• Legal or regulatory changes triggering multiple claims

Throughout these claim concentration risks, the performance of reinsurance and cash timing is also critical.

Premium Collection Disruption

Disruption to premium income can occur through:

• Economic downturns affecting customer ability to pay
• Operational disruptions to collection processes (South Africa experienced this a few years ago with the failure of a notable, concentrated exposure to a single premium collector)

Investment Portfolio Liquidity

Asset liquidity can become constrained through:

• Property/Real Estate holdings requiring time to sell
• Private equity/debt with limited secondary markets
• Complex structured products becoming illiquid in stress scenarios
• Market-wide liquidity stress affecting even traditionally liquid assets
• Money market fund holdings proving less liquid than assumed when stressed

Regulatory plans for improved liquidity risk management and reporting for insurers

Regulators are understandably keen to get a better handle on liquidity risk within the insurance sector – and are keen for insurers to take liquidity risk more seriously. Existing measures are widely considered imperfect (at best).

While we don’t want perfect to be the enemy of the good, there seems to be an opportunity to aim for better than current proposals.

The High-Quality Liquid Assets (HQLA) Paradox

A crucial distinction between banks and insurers lies in their access to central bank facilities. Banks can convert HQLA to cash via central bank discount windows, making these assets effectively cash equivalents. Insurers, lacking this access, face a different reality: even “highly liquid” assets can become illiquid during market stress. Insurers and other non-bank financial institutions may want access to the discount window, but my understanding is that this idea is a non-starter.

This creates an interesting regulatory paradox. Bank-style liquidity reporting, with its focus on monthly reporting, micro bucketing of asset maturities, but with implicit and assumptions about central bank access, may be suboptimal for insurers. Yet some regulatory frameworks still look to apply bank-centric thinking to insurer liquidity management.

Systemic Risk and Money Market Funds

A particular concern arises with money market funds, often assumed to be perfectly liquid. While an individual investor can usually liquidate their money market holdings easily, this isn’t true for the market as a whole. If the underlying instruments become illiquid, large-scale redemptions become impossible.

This creates a systemic risk: the appearance of liquidity in normal times masks the potential for market-wide liquidity crises. When multiple institutions rely on the same sources of apparent liquidity, the system becomes more fragile.

Testing Liquidity – Easier Said Than Done

Testing the ability to liquidate assets remains challenging. Current approaches to estimating liquidation costs are still maturing in many markets. Desktop exercises and historical analysis of liquidity crunches provide insights but have limitations.

Testing available liquidity by transacting in large volumes under normal conditions is expensive and, more importantly, tells us little about the ability to transact in disrupted markets. Tests of notional volumes may generate a false sense of security rather than inform real liquidation measures.

The true test of liquidity often only comes during stress events – precisely when you most need it to work.

When “Liquidity” Masks Solvency Issues

Some apparent liquidity crises are actually solvency issues in disguise. A prime example is minimum surrender guarantees in a rising rate environment. When interest rates rise significantly, policies with guaranteed surrender values can become deeply unprofitable. Each surrender crystallizes a real economic loss – no amount of liquidity support solves this underlying problem.

Policyholders can withdrawn their funds, benefit from the rising interest rate environment and re-invest in a new policy or other structure taking advantage of higher interest rates. It should be no surprise that this is the result of the dangerous combination of higher interest rates and guaranteed surrender values. (There are ways, complex, expensive ways, to manage this risk, but that first requires an appreciation of the risk. This requires at least adequate liability measurement, robust scenario testing that doesn’t assume prior low volatility periods will continue, and consideration of dynamic policyholder behaviour.)

Is this a liquidity risk? Firstly it is a solvency risk. Th value of “matching” assets has declined while the value of liabilities has not. A liquidity risk is only a liquidity risk if the provision of liquidity solves the problem.

When measuring liabilities and therefore solvency, it seems dangerous to rely on assumed policyholder irrationality (expecting them not to surrender when it’s clearly in their financial interest to do so) to support solvency calculations. Good risk management and appropriate liability measurement must recognize that policyholders will likely act in their financial interests, especially when the benefits of doing so become obvious.

Now there may also be a liquidity risk. If surrenders require liquidation of illiquid assets that may further depress asset prices, increasing yields and/or spreads. Resultant concerns around insurer solvency can also lead to a run on the insurer. It’s a mistake to think of all of this as a liquidity risk.

Implications for Risk Management

Liquidity risk is real, and may still be underestimated by many insurers. Insurers should be carefully evaluating their risk management systems for adequate coverage of liquidity risk.

These complexities demand sophisticated risk management approaches:

• Regular stress testing must consider both solvency and liquidity impacts
• These stress tests must be severe enough and must consider interactions
• Liability measurement needs to incorporate realistic policyholder behavior assumptions
• Investment strategies must balance efficiency with liquidity needs
• Liquidity buffers should consider both immediate and slow-burn scenarios
• Risk frameworks must recognize the limitations of market liquidity assumptions
• Consider when your sources of liquidity (money market fund contractual promises) may necessarily fail in systemic liquidity challenges

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

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.

At a minimum, the contribution to group surplus/deficit Own Funds (in excess of, or the deficit where Own Funds don’t cover the SCR), should be shocked for currency risk. This makes sense as soon as you think about what the risk to the group’s SCR cover is on currency depreciation. (Where there is a deficit, foreign currency appreciation is the risk, not depreciation. The opposite is true – and more intuitive – when there is a deficit.)

The final answer is that ICS will likely not be applied to everyone in South Africa, but it may inform the development of SAM group reporting. It may also be the basis of choice for subsidiaries in other jurisdictions. ICS is probably more relevant than you thought.

That’s the ballpark figure I usually work with as the minimum number of micro insurance policies required for scale. The expenses of running even a micro insurer are not that trivial.

For underwritten products within a full life licence? Larger premiums per policy but definitely more complexity. Competition is tougher too. Hyper local brands don’t translate into trust at this level. Viable niches may exist, but at what volumes?

You might wonder if there is scope to sell greater value products at higher premiums that can bring that number down in some contexts?

The rise of embedded insurance

Turns out this has been given plenty of thought already – “micro” insurance is the less popular name these days from a product and provider perspective. Inclusive Insurance certainly sounds better and more inclusive (!)

I think part of that push though was recognising the challenges and limits of truly “micro” insurance, at least at an individual level in providing commercially viable options that meet needs at the scale necessary.

Inclusive Insurance has been eclipsed in some words for “embedded insurance”, a term that talks less to the needs and objectives for society, and more to one that is practical and viable commercially. Embedding insurance in other products are services can drive down some of the costs, but then by virtue of being embedded, the absolute amount of premium is even further limited. Volumes may go up – and there have been some success stories here – but margins typically remain fine so I’m going to guess that my 40,000 may be too low in these instances. The success stories are in the 6- and 7-digit volume space.

Microinsurance licence restrictions

Back to “microinsurance” and the regulatory restrictions that apply in South Africa:

• Savings elements might seem attractive to increase premium size and provide “value” rather than a set price point. But savings elements are not permitted in microinsurance policies in South Africa.
• Loyalty schemes or cash back may be a way to attach greater value to a product, but again are not permitted in the microinsurance framework.
• Fairly large sums assured are possible within microinsurance – often attracting increased adverse selection or outright fraud.

Can product tailoring increase average premium?

Product tailoring can be expensive and can counter plans for
economies of scale while simultaneously targeting a smaller market. I’d still like to see more of this rather than pure commodity products. I’d be happy to be wrong if this approach meant a viable micro insurer could provide genuine value, see strong demand, and require fewer than 40,000 policyholders or comfortably sell more than that.

Microinsurance pros and cons – an important choice

A key point here is whether a standalone microinsurer is the right vehicle for a truly niche insurer? The increased governance and compliance policies effected by the major cell providers have frustrated cell owners and entrepreneurs, slowed down innovation and led them to look elsewhere. A microinsurance licence is a great option for some, but not a panacea for everyone.

I’ve helped insurers apply for licences, buy licences, consider alternative arrangements, and I’m sure at some point I’ll be working with micro insurers to transfers portfolios to other insurers and close down licences.

There is also opportunity to apply to the Prudential Authority for scope to do more with the licence, with careful consideration of the risks and capital.

Does digital fix everything?

Digital sales is a complex area. Some insurers have had some success with purely digital sales. But when these distribution channels are owned by someone else, the costs are not as low as “digital† might make you think. If NTUs are high, and premium collections are low, it can quickly become expensive. There’s a fine line between removing friction from a sales and underwriting process (which definitely improves sales) and making it so easy to “sell† that the customers haven’t really decided that they want what they’ve bought.

Parametric insurance – watch this space!

We should be doing far more with parametric insurance in South Africa. Thinking around climate risk and the positive role insurers can provide in this space (rather than only worrying about the risks it poses to them) may present some new opportunities. Insurers can apply their expertise in understanding and pricing risk, while providing a socially and economically beneficial product at a price that shows value and profit.