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The future of risk analytics

Phil Ellis and Ben Fidlow | 20th April 2015


As the ‘internet of things’ continues to grow, we have access to more and more data on anything and everything. This is good news - more information tends to lead to greater understanding. However, in this age of information overload, it is important to make sure you are using the right data, and applying the correct assumptions, to answer the appropriate questions. To this end, insurance brokers are increasingly taking their clients data and applying advanced risk analytical methods to help them make better strategic decisions about the risks they face.

A conversation with Willis’ Phil Ellis and Ben Fidlow

How is the rise of risk analytics changing the insurance industry?

The rise of analytic tools in corporate insurance is making a significant difference in the way risks are understood, measured, mitigated and transferred. Companies are used to getting a professional fact-based decision making approach from management consultants, bankers and lawyers, but they traditionally have not had the same level of decision making support from the insurance industry. We are at the start of the journey, but the insurance industry is catching up fast.

How does risk analytics benefit corporate risk managers?

In three main ways: by providing them with at least as good information about their risks as the insurance markets have; by giving them the fact base on which to make good decisions; and by providing a clear decision trail and logic that will stand up to scrutiny by management and regulators. The main aim of what we do is to support stronger decisions by our clients. And one of the ways this is done is by demonstrating how effective insurance can be as a hedge to protect corporate financial performance. This is a different way of thinking about insurance and it elevates the conversation to where it ought to be in an organization.

The focus has been on controlling cost, but with enhancements in data and applied analytics, all types of risks are being measured and mitigation processes are being implemented.

Where should risk managers start?

One of the best uses for risk analytics is to identify where the biggest risks and failure points are for an organisation, before a major event even happens. Risk analytics can be used to make senior management aware that at some point they are likely to go through a “reversal of fortune,” and then better understand the consequences of that and take adequate measures to prepare.

Willis’s research on corporate catastrophes has shown that the largest companies undergo a severe reversal of fortune on average every eight years. Most companies believe that they are immune from such reversals but, given that the average tenure of a chief executive is around ten years, they should expect at least one reversal while they are in the job.

Which sectors would benefit most from risk analytics?

Currently, we see the most up-take of risk analytics among energy, power and utilities, and healthcare companies. These companies are already quite advanced in their use of data. Retail companies can also benefit by gaining a better understanding the impact of a data breach, or exploring economic metrics, for example, when looking at where to open a new store.

How do risk analytics help when buying insurance?

Companies can use risk analytics so they can make insurance buying decisions in the way they would any other investment - by taking a return-on-investment view. With a quantified view of risk, now the return versus risk continuum can be analysed, allowing for financial based decision making around whether to even buy insurance, and the best way to do so – limit, retention and individual layer costs.

Is there a sweet-spot for the use of risk analytics?

The more data the more confident we can be in the outcome of analytics. So one might think that the ‘sweet spot’ is high-frequency, low-severity risks. But some of our most important work is on the game-changing risks in the low-frequency and high-severity range where there is little or no data. In these instances, we can use processes we’ve developed to elicit quantification of these risks from experts within a client’s organization. Or if a client has never suffered from a severe downturn we can look for downturn experience from related companies or industries and draw conclusions based on modelling these risks.

Can risk analytics help find new solutions for transferring risks?

Once risks are quantified, it is easier to attract financial markets. Risk analytics will set the stage for new investment classes, as we have already seen with the development of catastrophe bonds for property exposures. There is also a role for analytics in making intangible risks – like reputation or contingent business interruption – more insurable because armed with sound analyses, brokers will be able to make a better case for the placement of those types of risk to both traditional and non-traditional capital markets.

What challenges need to be overcome to increase the adoption of risk analytics?

I believe that the biggest barrier currently is the training and skills required to work with and interpret analytics. We want all of our client discussions to be analytically-based. And Ben’s team is making great progress in ensuring this happens.

One of the biggest hurdles I see, is that of getting our hands on the relevant data. Often companies already hold the data, but it is usually spread across the organisation and is difficult to aggregate. The support of senior management in helping to gain access to this data is crucial but these people are busy running the company so this may not be a top priority for them. For that reason, the value of harnessing data needs to be presented in a concise and impactful way in order to gain senior management buy-in.

Are risk analytics becoming more accessible?

It’s only a matter of time before risk modellers become an integral part of corporate risk management teams. This will be driven by company treasury departments and senior management who will increasingly demand it, while risk managers will need to demonstrate that risk management investments and insurance decisions have been made with analytical rigour.

Where next for the use of analytics?

Within the next five to ten years I would expect to see risk managers become much more involved in strategic business decisions. As we’ve said, insurance is a hedge and as such, can be applied to any investment decision where there is insurable risk. It’s a great new frontier for insurance.

The big game changer will come when risk analytics are integrated with company financials and applied to strategic decision making.

About the authors
Phil Ellis
Phil Ellis is Global Head of Strategic Risk Consulting for Willis Risk & Analytics
Ben Fidlow
Ben Fidlow is Global Head of Core Analytics for Willis Risk & Analytics
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