How can a business better get to grips with the range of risks that they are exposed to, and anticipate those risks that are just over the horizon? As data is gathered and fed into increasingly advanced risk analytics tools, how are insurers using their insights to help businesses make the decisions that can affect their futures and prevent prospective losses?
As the commercial benefits of globalisation and interconnectedness become apparent, shifts in the way businesses operate have given rise to the development of new and often invisible risks. In the absence of hard data to model and to help us understand these emerging risks, an almost instinctive form of risk management has been applied, based on ‘gut feeling’. This makes the creation of an effective risk management strategy and its substantiation somewhat challenging.
For the more traditional property and casualty based risks, many tools are available to help a business compile a general understanding of existing risk factors and their relative importance. As well as this being a one-dimensional view of risk at a single point in time, the data’s relevance is often limited due to the time that passes between its capture and its application.
Insurers are becoming more aware of the hunger for sector-specific insight
While we cannot wholly depend on the past to inform our understanding of future risks, captured data nonetheless presents a base from which to begin the journey towards deeper understanding. Businesses are increasingly using historical data to build insights into the types of risks that are most likely to impact their organisation down the line and what a future risk management strategy should look like. Simply put, businesses are striving to make insight-led decisions, which is where insurers are well-positioned to provide support - data having been the lifeblood of the insurance industry since its formation.
Through activities such as claims handling, underwriting processes and visits to customers’ premises, insurers have been gathering huge amounts of data and insight into trends in the sectors in which they specialise. Historically insurers have not been expected to share their knowledge outside their own organisations. However, there is a shift developing as insurers become more cognisant of the hunger among their customers and partners for sector-specific insight which in turn is driving greater innovation and functionality in the tools they are using.
Most current risk management tools are IT systems that provide workflow tracking of risk management activity and risk data collection from site surveys and desktop/prospect reviews. However, as analytics tools become more advanced they are evolving to offer:
- Real-time updates to risk improvements flowing through to show the impact on risk profile;
- Risk quality benchmarking across own portfolio of locations and against peers;
- Inclusion of multifaceted data from publicaly available sources;
- Business intelligence software allowing bespoke insights to be uncovered, and bridges to be built linking data sets; and
- User-friendly content with full and transparent access for businesses.
Advances in risk analytics have been highlighting the gaps in traditional insurer methods of evaluating risk. One notable example is the long-established property site survey programme provided by insurers and/or brokers that aims to help a business reduce the frequency of a loss event occurring - and reduce the severity if it does.
Frequent mid-sized losses have the same effect on the bottom line as one single large loss
For large businesses that operate across various sites, this survey programme typically has been deployed to locations based on a matrix that drives focus towards the higher financial value, higher hazard locations. Generally speaking though, these sites already have a significant understanding of risk and a good risk mitigation strategy in place and a correspondingly good loss record.
Joining together incident/loss data with site risk data has identified an increasing trend that smaller value/lower hazard, often ‘off radar’ locations pose a level of risk that has been escalating and it is no longer enough to rely on these sites interpreting and applying centrally-issued corporate risk standards. It should be remembered that frequent mid-sized losses have the same effect on the bottom line as one single large loss, but it is generally easier and more cost effective to work with a single site to improve their risks than many sites.
As analytics tools develop, achieving the panacea prediction of when, where and what will be the impact of the next loss remains a goal for the future, particularly considering that humans are involved – we remain the root cause of many a loss. But identification of the markers of a location or situation that has an increased propensity for a loss to occur can be achieved, thereby allowing a degree of proactive intervention to avoid or minimise the predicted loss.
With all this data at their fingertips, insurers are in an enviable position and they are increasingly sharing the insight the data provides more openly in order to help businesses better understand their risks and reduce them, and ultimately inform future decision-making.
Shouldn’t we stop looking in the rear view mirror at the risks we failed to anticipate, and spend our efforts using analytics to help avoid those coming towards us?
Neil Strickland is Director of Risk Consulting at RSA
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