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.

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.

Before reading on, pause and consider: What strategy would you use if you were playing this game?

The Optimal Group Strategy

If we’re working as a team to find the number as quickly as possible, what’s our best approach? We need a systematic way to eliminate as many possibilities as we can with each question.

The optimal strategy is binary search – repeatedly halving the possible range by asking if the number is in one half or the other. For a number between 1 and n, this takes approximately logâ‚‚(n) questions. This is provably optimal from an information theory perspective – each yes/no question can at best halve our uncertainty. (This approach might be familiar if you’ve ever studied or used binary sort algorithms in computer science – the same principle of dividing the search space in half each time.)

Why does this work so well? Each question eliminates half the possible numbers, regardless of the answer. After k questions, we’ve reduced the possible range by a factor of 2^k. For example, with a starting range of 1-1000:

• Question 1: >500? Reduces to 500 numbers
• Question 2: >750 or >250? Reduces to 250 numbers
• Question 3: >875 or >375? Reduces to 125 numbers
  And so on…

The Competitive Dynamic

But here’s where it gets interesting. The class isn’t actually trying to find the number as quickly as possible. Each child is competing to be the first to identify it. This transforms our optimization problem into a game theory challenge.

Consider child A’s decision when it’s their turn. They now face a trade-off:

1. Ask a “narrowing” question that helps everyone by reducing the possible range
2. Make a direct guess at the number

This becomes a competitive sequential search problem, touching on three related areas of study:

1. Competitive Search Problems: How do agents search through a solution space when competing to find something first? This appears in various contexts, from R&D races between firms to parallel search algorithms in computer science.
2. Information Cascade Theory: How do individuals make sequential decisions while observing others’ choices? This typically studies how public information influences private decisions, leading to potential herding behavior.
3. Strategic Information Revelation: How do agents decide what information to reveal when that information might help competitors? This is crucial in contexts like patent disclosures and auction bidding.

The optimal individual strategy shifts as the game progresses:

• Early game: The search space is too large for guessing to be rational
• Mid game: There’s a tipping point where direct guesses become more attractive
• Late game: Once the range is sufficiently narrow, direct guesses become optimal

For a rational player, the decision at each turn should be based on:

1. Calculate probability of winning with a direct guess: p = (current range size)^-1
2. Calculate probability of winning later after a narrowing question, accounting for:

• Reduced range size
• Number of other players who might guess correctly before your next turn
• Number of turns until you go again

1. Choose the action with higher expected value

Crucially, this assumes all other players are also playing rationally – a strong assumption that might not hold in practice, especially with younger players!

The Finite Guesses Twist

Here’s another interesting variation: what if players are limited to a fixed number of questions? This creates a fascinating optimization problem even in non-competitive scenarios.

At some point, if you have k questions left and n possible numbers, random guessing becomes better than binary search. The intuition is that binary search might narrow down the range significantly but leave you unable to identify the specific number.

For example, with just two questions left and a range of five numbers, you might be better off making two direct guesses (probability of success = 2/5) rather than two binary search questions that could narrow it to 2 numbers but not identify which one.

The optimal strategy becomes a dynamic programming problem, where at each stage you need to calculate the expected probability of success for:

1. Using a binary search question
2. Making a direct guess

The mathematics behind this optimization is fascinating, but I’ll leave that for another post!

An Interesting Parallel

This competitive dynamic reminds me of the board game Cluedo (Clue in North America). While the optimal strategy is usually to gather information methodically, the game dynamic shifts dramatically when you suspect another player is close to solving the mystery. At this point, making an educated guess at the solution, even with incomplete information, might be your best play despite the penalty for guessing incorrectly.

This perfectly mirrors our number game – when you suspect other players are close to identifying the number, the rational strategy might be to take a calculated risk with a direct guess, even if you’d normally prefer to gather more information.

Final Thoughts

What started as a simple classroom game reveals layers of mathematical and game theoretical complexity. It demonstrates how individual incentives can lead to strategies that are suboptimal for the group – a common theme in game theory.

Have you encountered similar games or puzzles that seem simple at first but reveal hidden complexity? I’d love to hear about them in the comments.

Nudge Theory

• Concept: Small changes in choice presentation can significantly influence decisions.
• Application: Using social comparison feedback (e.g., “80% of homeowners in your area have flood insurance”) to encourage consideration of additional coverage. Also, implementing gamification elements in health insurance apps to promote healthier lifestyles, potentially reducing health-related claims.
• Replicability: Consistently strong results across various domains, making it a robust finding.

The Watching Eyes Effect

• Concept: Displaying images of eyes or a face can encourage honest behavior.
• Application: Used in various settings, including online insurance, to promote truthfulness.
• Replicability: Mixed results, with effectiveness varying by context.

Default Options

• Concept: Setting beneficial default choices (e.g., higher insurance coverage) can lead to better outcomes.
• Application: Widely implemented in insurance and savings products.
• Replicability: Generally reliable, though effect sizes can vary.

More on this in the excellent Freakonomics podcast episode 572

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

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.

I have been pondering whether IFRS17 makes life interesting for microinsurers given the wording of FSM2 “Valuation of Assets, Liabilities and Eligible Own Funds” for microinsurers (issued by the PA). The interpretation and application challenges actually predate IFRS17. FSM2 makes some silent and unlikely assumptions around treatment of premium debtors for typical microinsurance business. More on that in a future article.

IFRS17 does make life interesting (in the worst meaning of the word) for microinsurers, in that they must all apply IFRS17 to their insurance contracts. There’s no reason not to apply the Premium Allocation Approach given restrictions on policy term – and this simplifies many of the calculations significantly. Whether the audit firms looking at microinsurers understand IFRS17 or the required disclosures is an important quite separate topic, but one which must be resolved independent of the prudential reporting basis itself.

So here’s a wild idea. Why not drop FSM2 altogether and align the prudential balance sheet with the IFRS one?

Back to my world – often the best model is no model. If you must have a model, a simple model is better than a complex model. Simplifications aren’t just not a bad thing, they are good and necessary.

Complexity has massive downsides – run-time, increased risk of errors, more involved documentation requirements, longer development time, longer handover time, longer pick-back-up-months-later time, and harder to explain to clients.

Finding the appropriate simplifications is key to so much of what we do.  Approximations are not even just “harmless errors” they are a critical feature.

And yes, she totally killed her husband.

Business Rescue precludes creditors from applying for liquidation of the business. This is the removal of an existing right of lenders: “a temporary moratorium on the rights of claimants against the company or in respect of property in its possession”

From what I gather it’s not clear that this formally counts as default – might depend on specific loan or bond terms and how credit rating agencies respond to this.

How one “feels” about this is less relevant than the legal interpretation for cross-default provisions. It certainly feels like default to me.

For SAA, it’s also a step which means the government is no longer prepared to keep putting in money. That’s certainly a message about how likely any implicit (rather than explicit) governmental guarantees are for other entities.

Short aside on government debt and balance sheets

It’s not really so much that this is bad news, but rather this is the long-overdue recognition of how bad the news is around SOEs and their total contribution to the true Debt/GDP and their zero or negative contribution to the less-publicised Asset/GDP ratio. As I’ve mentioned before, another useful ratio would be (Debt-Assets)/GDP, which if measured carefully can be a more useful measure of the true financial position of a country and a better guide for decisions on whether to privatise an existing SOE.

A full balance sheet approach and one that considers return on capital (as well as also-important social-development, second-order, longer-term and positive externality items) should form a greater part of policy decisions.