Updated: May 7
The commercial property insurance market in 2021 is ripe for modernization
The commercial property insurance market of 2021 is ripe for modernization. Loss costs and expenses remain too high as evidenced by Lloyd's property insurance results which show a loss of £2.6bn for the period 2016-2019; driven by increases in both man-made & natural hazard losses.
Whilst insurers work hard to improve their performance and deliver an acceptable return on capital, it is the customers of the sector who are losing out, paying in excess of 30% of premium on non-risk bearing activities. The hardening market further affects customers, who face an inevitable increase in premiums and restrictions in both coverage terms and available capacity. The latest Marsh “Global Insurance Market Index” as of Q4 2020 highlights this trend with UK Commercial Property insurance pricing rising 24% in the fourth quarter of 2020 which was the eighth consecutive quarter of price increases.
There is however a silver lining. Technology and data-enabled solutions are creating the tailwinds for change. It is vital the market embraces these opportunities to rethink how it serves its customers; the buyers of its products and services.
According to EY 2020 UK Insurance Outlook, the UK insurance market is entering one of the most significant and intense periods of change in its history.
“The explosion of data and the corresponding focus on analytics to drive insights across the value chain will continue, but is yet to generate sufficient value as insurers fail to adapt quickly and lag behind big technology leaders.”
An inefficient business model
Allowing for some exceptions, the commercial property underwriting model suffers from inertia and trapped inefficiencies, with business processes not having evolved a great deal over the past half a century. Insurers still largely base their risk selection, decision making, and pricing on an annual cycle, based on historical pricing of data, provided by the commercial property insurance buyers and their brokers, which leads to siloed business processes and a lot of friction in a federated model. There is very little transparency in how data is shared across the ecosystem and too much time is spent on administration and not enough on proactive management of risk.
This model is outdated and needs a rethink to enable better insights on the drivers of underlying performance within a portfolio, using the power of data. Risk management and risk engineering services should help better differentiate risk, but a typical insurer can only afford to send risk engineers to approximately 5% - 10% of insured locations representing 20%-25% of the risk exposure. This means that a huge proportion of insured properties are not visited, and the statistical models used to predict the risks in the 90% plus of unseen locations are, inevitably, more prone to error which can lead to unexpected losses and unknown exposure.
Where risk engineers do visit customer sites, this is likely only once every 3 years, with inconsistent risk descriptions and differing layouts making it hard for underwriters and clients to consume, analyze, and action. This has resulted in only 1 in 7 identified risk improvements being resolved by larger clients*. Whilst one cannot underestimate the value of having an experienced engineer onsite, there is clearly a call to action for data-driven insight, that would benefit all parties.
This point is succinctly made in the Deloitte UK Insurance trends report for 2020:
“Disruption from new technologies is a given. It wends its way through all other trends. But acknowledging it and acting on it are very different propositions. Insurance companies need to know how to deploy the right technology for the right purpose or they risk being left behind.”
Making SENSE of IoT to drive change
Internet of Things (IoT) technology is one of a number of technologies that is already shifting the market towards data-driven, real-time risk management. Customers can act on risk insights that allow for proactive and predictive risk maintenance. As with telematics in the motor market, IoT and other disruptive technologies will revolutionize commercial property risk management. Whilst it has taken time to penetrate the commercial market, the pace of adoption of these technologies is increasing, and there are clear benefits to exploring opportunities.
Commercial property customers can benefit from external and internal IoT to help identify and notify ‘when something is about to go wrong. External IoT examples include river sensors that measure river flow and height every 30 minutes and provide accurate hyper-local prediction models that enable customers to act on the data and avoid or mitigate loss. IoT weather sensors can provide forecasts of hail and other weather events that customers can use to, not only, enhance their risk management but the data can also greatly assist the claims process post-event too.
Leveraging the power of IoT in commercial buildings enables real-time data extraction from Building Management Systems (BMS) that can be used to monitor, predict and prevent loss.
Examples of sources of data are:
Sprinkler and fire suppression systems
Heating and manufacturing systems (that can be used to prevent business interruption and machinery breakdowns, and improve maintenance and lower energy costs)
Mechanical and electrical equipment
Boilers, hot water, air source heat, and other pump driven water-based systems
Chillers and refrigeration
Co2 and air quality generally in the building itself
Building Information Management (BIM), the design of the building and how it compares and aligns to the actual operation
There are numerous positive case studies that have helped mitigate loss and reduce costs. The following use cases, based on IoT devices connected to BMS, are already providing tangible benefits to customers.
Avoiding Water Damage - Leak Detection
Industry statistics from the Association of British Insurers show that one in five of all property and contents claims relate to escape of water.
IoT can really help in this area. As a positive example, a customer noticed that their Heating, Ventilation & Air Conditioning units (HVAC), and other mechanical and electrical equipment had caused a slow leak and build-up of moisture in condensate drains in Air Handling Units (AHU). The build-up of humidity in the system was detected by data feeds from the IoT device and repaired before any material damage was sustained. This type of leak was not detectable through any normal ‘human’ means, e.g. risk engineering assessments, normal maintenance cycles etc. Because the leak included the AHU serving the main offices and IT room, further damage could have been significant and costly including additional business interruption.
Enhancing Fire Safety – monitoring of Fire Protection systems
Another customer wanted to monitor their sprinkler system using additional sensors attached to the key equipment such as the jockey pumps, generators, and back-up generators. The data was collected via their overall building IoT device for a holistic view of their operations.
The sensors detected that the jockey pump was coming on 4-5 times per hour, when in fact it should only be kicking in 4-5 times per day. In this instance, a leak was detected and found in the supply from the pump room to the factory site. It was quickly fixed, another example of an IoT device detecting damage and enabling early repair ahead of a possible loss.
Environmental and sustainability benefits
One hugely significant benefit is the ability for IoT devices to monitor energy usage. In another example, the sensor picked up that both heating and cooling devices were coming on at the same time. By optimizing when heating and cooling operate, the return on investment for the IoT project has been proven to be self-funding alongside the many risk management benefits.
The cliché of ‘we don’t have a technology problem, we have an adoption problem,’ also applies to IoT-enabled risk management in the commercial property market. To achieve sustainable change requires leadership to shift how the market collaborates, to drive innovation that delivers a better risk management solution for the customers of the sector.
A number of challenges must be addressed, including:
1) Breaking down internal silos
To underwrite a commercial property risk, there are four viewpoints that must come together: the underwriter, the pricing actuary, the risk engineer, and the claims expert. All of these separate functions must collaborate to stitch together all the intelligence and data for each policy and all the insured locations, but this is a largely manual task today as data is often disconnected.
2) Building and maintaining data-driven risk profiles for all properties covered
Today only 5-10% of insured properties are visited by risk engineers, so underwriting decisions have to be made using incomplete data with clients often struggling to properly differentiate their risk in the marketplace. New developments in digital twinning, for example, can help to solve this.
3) Lack of available data to model exposures
One of the obvious drivers for change is the analysis of claims trends over time. As more external data is sourced to complement existing data sets, more granular analytics on exposure data can be undertaken to identify clusters of similar claims and help direct risk management activity. This however takes time and does hinder the development of rapid solutions to mitigate loss sooner.
4) Lack of experience in using real-time data
Due to the size and scale of commercial property risks, many policies are underwritten on a subscription basis, where each subscribing underwriter will have different systems and processes. This makes it more difficult to both ingest and act upon real-time data.
In addition, many insurers also lack the technology experts and data scientists needed to augment the underwriting process and grasp the potential opportunity. To overcome this challenge, the market will need to collaborate to change for the benefit of the overall ecosystem.
IoT is one technology that is driving insights into commercial property risk and risk mitigation. New sources of data can be extracted and used in risk management to help modernize commercial property underwriting and provide greater value to customers seeking to buy commercial property cover.
The real-time data available provides the opportunity to drive proactive risk management, prevent losses and enable the competitive pricing of known risks, rather than a guess based on limited historical data.
Customers already using IoT in property know there are immediate financial returns and quantifiable benefits based on energy savings, sustainability, and asset optimization. Extending those benefits with data-driven risk management and supporting insurance propositions will be a major competitive differentiator for insurers, as market conditions continue to harden and make additional value add services important.
In the next editions of this white paper series, we will also cover People & Adoption, Digital Twins of Risk, and Cyber Risk.
*Based on an analysis of over 10,000 risk mitigations, carried out by Intelligent AI Limited in 2020