The moral imperative: embracing IoT for proactive risk management

Insurance is traditionally reactive, responding to claims after incidents occur. However, with IoT and real-time data analytics, these technologies enable a shift towards proactive risk management. Not only do the devices alert that an incident is going to happen/ starting to happen (e.g. a dripping tap before a water leak or a power draw before an electrical fire – thereby enabling a plumber or electrician to fix before there is a much bigger issue and a consequent claim), the analytics on the data also enables insurers to predict potential hazards based on data trends to further give risk engineering advice (i.e advice at a portfolio level). Despite the clear benefits however, the adoption of IoT in insurance models has been moving at a glacial pace. The question to explore here – Does this reluctance not raise ethical questions about the industry’s commitment to its foundational purpose: to protect?

At its core, the insurance industry is built on a moral imperative to safeguard insureds against unforeseen events. Part of this principle is of course to pay valid claims. Part is also a duty to actively enhance insureds’ risk resilience. IoT technology, with its ability to monitor, analyse, and predict risks in real-time, is a critical tool to deliver on this purpose of improving risk resilience.

This also leads to a further point of discussion that if, through the use of the devices and the data analytics, events are no longer unforeseen but foreseen, surely this changes how insurance operates today. Insurance is predicated on the concept of protecting against unforeseen and uncertain risks. When an event or loss becomes foreseeable or highly predictable, the nature of the risk changes, and with it, the approach to insurance must adapt.

Two main considerations:

1. If an insurer can foresee a risk and does not notify the insured to take steps to prevent it, they could be seen as complicit in the resultant loss. This places a greater moral burden on insurers to use the data they collect for the benefit of their clients.
   When insurers possess the knowledge and means to prevent losses but choose not to use or offer this technology to their insureds, the status quo is maintained where preventable losses continue to occur. This not only affects the insured parties but also leads to increased premiums and costs for the industry as a whole, perpetuating a cycle of reactive management that could be mitigated, if not avoided, through proactive measures.
   Neither should this be a reason to not deploy devices for the avoidance of knowledge that would improve risk, thereby going against the foundational purpose of insurance: to protect.
2. On a more positive note, IoT & real-time data offers an opportunity to redefine the essence of insurance, moving to a partnership-based approach that prioritises risk prevention and enhances the resilience of the insured against potential losses.
   For example, more dynamic pricing models where premiums are adjusted in real-time based on the risk behaviour monitored by IoT devices and as foundations for the newer usage-based, parametric or embedded insurance models.

The adoption of IoT technology in the commercial insurance sector is slow because it is not easy. The deployment of devices, the secure connection and flow of data, the data elements focused on risk and the supporting service models and behavioural changes to report to alerts and fix all to stop the bad stuff from happening. These are challenges to be navigated to realise the potential of IoT to transform risk management and mitigation which are too significant to be left in the ‘too hard bucket’ of initiatives..

Where insureds themselves are deploying IoT devices and using the data to optimise their operations.

Two main considerations here:

1. The principle of “utmost good faith,” or “uberrima fides,” is a key tenet of insurance: the necessity for transparency and honesty between all parties involved in an insurance contract. Utmost good faith mandates that all parties – insurers, insureds, and intermediaries – act with integrity, disclosing all material facts relevant to the risk being insured.
   Where insureds deploy IoT devices, they now have even more knowledge and insight into their assets to be insured. The duty of disclosure could/ should therefore extend to the IoT device data because this might influence the insurer’s risk and pricing decision.
   [Although this does raise questions about the relevance of certain data and whether the traditional model of disclosure by the insured is still appropriate given the vastness of the data flows with IoT devices.]
2. By deploying devices and where that device alerts the insured of an impending issue, and where the insured fails to act on this warning, could the insurer avoid the claim? This raises many (more) complex questions within insurance law and the principle of utmost good faith. Whether an insurer can avoid a claim would depend on various factors, including the terms of the insurance policy, the nature of the device warning and the expected actions of the insured as well as the jurisdiction’s relevant legal framework.

The adoption of IoT and real-time data analytics is not just a strategic business decision, it is a moral one. Insurers have a duty to protect their clients to the best of their ability, and in the age of digital transformation, this means embracing the technologies that can make real-time risk management and prevention a reality. The time is now for the insurance sector to reimagine its role in society, from one of passive compensation to active prevention.