Evaluating captive retention structures in a hard market

One of the primary objectives for independent actuarial consulting firms is helping clients analyse their current or prospective risk retention structure. A significant portion of this objective involves evaluating optimal retention levels. Due to a lack of time, resources, or knowledge, the structure a company or captive uses to retain risk may not be regularly evaluated and, thus, it remains static from year to year.

However, this shouldn’t necessarily be the case. Retention structure plays a crucial role in the overall cost of risk, so companies should be proactive in evaluating their structures and reacting in accordance with the analytical results.

If companies or captives are not proactive in this pursuit, they are subsequently forced to become reactive due to external pressures or circumstances. When compared to recent years, in 2021 we have received close to double the questions relating to retention levels. The hardening market is likely the cause for this surge, as companies have been forced to reconcile with increased costs associated with their current retention structures.

Companies which are already placing some risks in a captive are already at an advantage at this stage due the captive industry’s resistance to traditional market fluctuations. This advantage does not mean that they’re immune to any economic impacts, though. Parent companies in the present economy may be forced to evaluate increased retentions for their captive’s existing risks or whether they should shift additional risks into the captive structure. To do so in an effective manner, a retention analysis is necessary.

At its core, a retention analysis contains loss projection analytics under multiple retention structures or scenarios. The results between each structure should vary, as the retained risk increases or decreases based on the “loss layer” between retentions. While retention analytics always include prospective structures under consideration, they may also include a “benchmark” loss projection using the current structure. Even if this option is no longer available in the market, including a benchmark allows decision-makers to better understand when it makes sense to deviate from their existing structure.

Once the retention analytics are completed, the results can be assembled into a matrix in which the rows represent various confidence levels, and the columns represent each retention or scenario under consideration. By formatting the loss projections in such a manner, one can better evaluate the probabilities associated with the retained risk in each scenario.

For example, a higher retention may offer better overall cost efficiency than the current retention if losses continue at an expected level, but in the event of an adverse loss scenario, the increased retained risk may be beyond a company’s appetite.

Helpful for premium negotiations

Often, the retention analysis for captives is an iterative process, as the cost of excess insurance plays such an important role in evaluating optimal retention levels. Pricing information may lag behind the initial analysis, meaning important decision points may need to be revisited after quotes become available. Proactive parent companies can prevent these timing issues from being purely detrimental, as the loss projections used in a retention analysis could easily be used to assist in premium negotiations.

If the risks in question are low in frequency but high in potential severity, or if loss levels have not historically met the retention being considered, statistical loss simulation methodologies may be necessary. In these situations, specific parameters such as claim frequency and severity are first selected to represent the underlying risk. From there, thousands of iterations are created using modelling software to simulate potential loss level scenarios.

While a handful of these simulated scenarios may not be considered credible when viewed in isolation, the model gains credibility through the law of large numbers. Claim severities are truncated during this process to reflect the impact of the selected aggregate or per-occurrence retentions. As both the selected retentions and confidence levels increase, retained loss levels should similarly go up due to the added potential for volatility.

In instances where the risks in question display the low-frequency/high-severity characteristics mentioned above, simulations and modelling often serve as the bedrock for creating credible loss projection analytics, especially when the evaluated retentions are relatively high. Knowing the parameters used to produce these models can also be helpful during negotiations, as they provide an additional discussion point for both parties to consider.

Hardened markets often force companies to increase their risk retention, as elevated premium pricing can significantly reduce the cost effectiveness of existing retention levels. For companies with captive structures, this becomes an especially important consideration, as it may result in the parent company shifting additional risk into the captive.

While placing a risk into a captive allows the parent company to avoid the traditional marketplace for the primary layer, reinsurers must be engaged to handle excess layers. Market prices for these layers then become a similarly vital data point in a captive retention analysis. As an example, for captives with deductible buyback policies, increasing a policy’s retention or deductible level inherently adds additional risk that the captive will need to cover.

Cost of risk calculations

When considered in tandem, the retained losses and excess premium costs often drive decisions relating to the total cost of risk (TCOR). These calculations can have varying definitions, but they typically include retained losses, excess premium costs, capital charges (or risk margins), and additional expenses. A similar formula whose usage has increased in recent years is known as the economic cost of risk (ECOR), which is often defined as an expanded version of TCOR.

Capital charges come from the company’s need to cover unexpected outcomes on the losses being retained. For example, if losses diverge from the expected level and reach an amount associated with a higher confidence level, such as the 80th percentile, the additional costs must somehow be covered. Since the funding used to cover this charge could be used elsewhere, it may be estimated in a TCOR calculation as the 80th percentile losses minus retained losses, then multiplied by an internal cost of capital. Obviously, this serves as a singular example, and this calculation will vary throughout the industry.

Other expenses incorporated into TCOR calculations may include the cost of the collateral instrument for retained losses. Administrative expenses may also be considered. An important but potentially overlooked issue in cost of risk calculations is the timing of payments on retained losses. In economic periods featuring beneficial rates of return, discounting calculations can be included within the formula and generally work to make increased retained losses more favourable.

One of the key items to understand during the process of a captive retention analysis is that the data points relating to excess premium quotes may arrive from multiple carriers over a relatively wide timeframe. This, in turn, may dictate the need to revisit the analysis subsequent to discussions with a carrier, as initially unconsidered retention levels, risks, or policy structures may need to be evaluated.

The iterative nature of this process could become frustrating for those involved, because it often feels like “starting from scratch”. As such, it’s important that all parties understand and embrace these characteristics prior to preparations for such an analysis.

Another crucial preparatory step involves agreeing on the decision framework and defining the decision metric (such as TCOR). Since the analytics surrounding these topics will play a significant role in the decision-making process, they should be determined beforehand to ensure decision points are clearly and commonly understood.

Optimising retention levels is a practical process requiring market quotes in an often disjointed and non-instantaneous process. It grows even more complicated as the number of analysed risks and structures increases. Ultimately, however, it is well worth the investment in terms of both energy and resources. Having an analytical foundation for making decisions relating to risk retention grants them the importance and focus they deserve, especially when considering the potential economic impact each decision could have.

When the market hardens, companies may be forced to find alternative solutions to their risk retention structures. Fortunately, it also serves as a fantastic opportunity to investigate whether a piece of the answer lies within the captive insurance industry.

Enoch Starnes is an actuarial analyst at SIGMA Actuarial Consulting Group. He can be contacted at:  enoch@sigmaactuary.com

Michelle Bradley is a consulting actuary at SIGMA Actuarial Consulting Group. She can be contacted at:  mb@sigmaactuary.com