Will insurers mandate digital ecosystems for energy assets by 2025?

Insurers will likely mandate risk-mitigating digital ecosystems for energy infrastructure by 2025, according to tech pioneer Akselos. 

“Data driven platform technologies underpinned by engineering machine learning will usher in a new era of reliability and resilience, that will see the asset quality of risk greatly improved”, says CEO Thomas Leurent. 

“Digital ecosystems with predictive models will enhance traditional engineering risk assessment and underwriting techniques to allow insurers to accurately price risk. More accurate predictions about risk and future structural health will improve the position of both insurer and asset owner at a time where costs are under increased scrutiny.” 

Gavin Narainsamy from insurance broker and risk management firm Marsh, said: “The benefits associated with the adoption of a digital ecosystem certainly outweigh the potential risks. Digital ecosystems could be a transformational tool in stemming losses in the energy sector.  The scale of the potential economic savings could act as a trigger to change behaviour at a faster pace than we’re used to.” 

Marsh JLT Specialty’s latest ‘100 Largest Losses In The Hydrocarbon Industry’ report cites that the total of the 100 largest losses in the downstream energy sector from 1974 to 2019 equates to $43.2billion, and four of the top twenty largest losses since 1974 occurred between 2018 and 2019. This financial loss is often covered by insurance, in the form of the physical repair or replacement of the asset but also the loss of associated revenue for the assets during its period of interruption.   

These numbers are without doubt leading companies operating in the risk and insurance space to deploy solutions to stem these losses, and one of the most promising solutions is digitalisation.  

While digitalisation is not new to the energy sector, its use in the risk management space has been more limited. Despite the advances we’ve seen with the fourth industrial revolution and the vast amount of information available for learning, Marsh JLT Specialty’s report suggests while some of the losses can be explained by the economics and risk profile of a low oil price world, there is significant potential for digitalisation to avoid large losses in the future.  

Human error is often a significant factor when it comes to losses. Digital systems can support and inform better and more accurate decision making, while the use of big data and machine learning can provide vastly improved information on areas of potential weakness and maintenance priorities.  

Marsh JLT Specialty’s report shows that the root cause of many of the major incidents in the energy sector are deficiencies in systems of work, inspection regimes, and emergency response plans – all areas where data driven platform technologies can make a big difference. 

Thomas Leurent continued: “It’s now possible to accurately measure the health of an asset in real-time as well as predict future failures. As a result, the insurance world is beginning to recognize that physics-based platform technologies are powerful tools to avoid large losses. It stands to reason that leading insurers will encourage, if not mandate this kind of technology adoption sooner rather than later.” 

The energy transition will also see an increasingly complex network of energy infrastructure, and things like extreme weather patterns and cyber-attacks will both raise the stakes and become harder to predict. Ensuring resilience in this new world with cutting edge digital technologies will become paramount.  

Gavin Narainsamy continued: “The world’s energy infrastructure is one of the core pillars of modern society. Accordingly, it represents some of the highest value assets on the planet. While the financial risk is significant, the greatest risk of all is that to human life. It is clear that greater use of digital ecosystems can be a step change towards making infrastructure more reliable, and safer for the people it serves.”