Risk analytics can give your organization a precise understanding of your risk retention capacity and reveal opportunities for enhanced value. This was the central theme of the Outsmarting Uncertainty webinar How to use analytics to make better decisions and enhance financial performance.
In the session, WTW experts considered a hypothetical scenario to demonstrate analytics in action. In this insight, we offer a summary perspective on some key risk finance areas where an analytical view can provide greater clarity to support your organization’s improved financial performance.
What methods does your business use to assess the additional losses it can retain and the likelihood of an insurance-limit breach? How does it define a bad or catastrophic year in this context? Although some of the world's largest and most successful companies are using analytics to get precision perspectives on these areas, many businesses are still using benchmarking or qualitative methods unlikely to provide an accurate view.
With the capabilities of data technology, the scalability of analytics and access to actuaries, we'd argue there’s no reason to do it in the ‘old-fashioned way’ which could leave your organization either exposed or over-insured. Analytics can enable your organization to calibrate its risk financing strategy to the most efficient trade-offs between retained and transferred risk by using rational, repeatable and non-subjective methods, bridging the gap between risk and finance.
While you can look at the probability of losses to understand what you could comfortably retain, that isn't always straightforward for the business. That’s because while risk managers may tend to talk about ‘return periods’ when they evaluate loss outlooks, finance stakeholders tend to think more in terms of percentiles. This represents a significant divergence between the language of those responsible for managing the finances of the company and those responsible for insuring them; it also signifies an opportunity for analytics to translate between the two.
Analytically evaluating gross losses against the impact of insurance and the probability of events enables you to make statements such as, Once every [period] we would expect a gross loss from this portfolio of [monetary value]. You can also look at total retained risk in ‘good’ and ‘bad’ years, revealing where you’ll be breaching your limits and could be retaining too much risk.
You can use the same insight to interrogate where you’re comfortable retaining a known level of risk, but the premium for the proportion you want to transfer appears too expensive in the context of what your analytics tells you about the likelihood of loss.
Risk analytics covers modeling using actuarial forecasting. This modeling can show the value of your risk financing approach, even when there hasn't been a loss.
You can use analytics to evaluate loss forecasts and guide decisions about risk retention and insurance structure, aggregating losses across different elements of your structure and critiquing your risk finance arrangements.
One of the key advantages of analytics is that it lets you find the savings by comparing alternative insurance structures before you make any decisions, affording you the chance to experiment with different structures and sub limits to reveal the most optimal arrangements.
Are your insurance limits sufficient? Are you buying too low or too high a limit? These are common questions facing risk managers, many of whom are under greater scrutiny in the current economic backdrop where they are pressures to find additional savings from finance colleagues.
Analytics can help you easily evaluate your excess layers, using modeling to reveal when you can expect to breach your limits. These assessments allow you to not only set your limits at the most efficient level, but to do so in line with your organization’s risk tolerance framework This may see you increase or reduce your excesses as appropriate in the next renewal cycle, with the evidence you need to defend your rationale.
Using analytics in this way aligns the risk function to finance, supporting the business in seeing the contribution of risk managers more in terms of value to organizational resilience, rather than purely the cost of insurance spend.
Analytics is key to shifting conversations around your current hedging program and; indeed, your entire approach to risk financing from ‘cost’ to ‘value’. This is about risk managers being able to accurately quantify both the risks the business is retaining and the potential impact this may have, moving beyond a simplistic focus on level of insurance premium.
Risk analytics insight also puts you in a position to challenge insurers’ view of your risk at renewal. Equipped with your own quant, you can engage with insurers more proactively and be confident you're not ‘leaving money on the table’ because of inefficiencies in cover. This is especially important against the backdrop of the hard market, where insurers are often increasing premiums while sometimes reducing limits.
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