By Juan Bernal
The Internet of Things (IoT) and the advent of real-time data presents both an opportunity and a challenge for the insurance industry. According to Statista and ResearchGate, they predict that there will be circa 75 billion IoT devices by 2025 generating an enormous 79 zettabytes of data. That is a lot of data! This endless stream of data will come from devices such as smartphones, wearables, cars, leak detection devices, industrial sensors, and sensors integrated within all manner of industrial machines and smart buildings. Whilst this will transform industries worldwide, insurance companies face a complex puzzle in integrating this wealth of data into their processes.
The path to IoT and real-time data integration isn't straightforward for insurers or brokers. The sheer volume of data generated by IoT devices creates a "herculean task" for insurers and brokers according to ValueMomentum. Insurance companies must develop robust systems capable of managing and integrating vast amounts of data into several parts of the value chain (risk assessment & claims to name but two) while maintaining efficiency and accuracy.
Before even considering which devices, for which purpose, insurers and brokers need a vision and a strategy. Yet FC Business Intelligence reports that 40.7% of insurance carriers identify the lack of a clear strategy as their primary barrier to IoT adoption. Indeed, the SENSE Consortium’s own research has revealed 21 adoption blockers for IoT and real-time data in the complex commercial insurance industry.
Before even considering which devices, for which purpose, insurers and brokers need a vision and a strategy. Yet FC Business Intelligence reports that 40.7% of insurance carriers identify the lack of a clear strategy as their primary barrier to IoT adoption. Indeed, the SENSE Consortium’s own research has revealed 21 adoption blockers for IoT and real-time data in the complex commercial insurance industry.
For example, companies must make crucial decisions about whether to supply IoT devices themselves (such as Sky as part of their Sky Protect offering) or partner with existing technology vendors (such as Inigo’s Samsara partnership for commercial fleets), choices that will shape their future success and benefits realisation through early warning of incidents.
Data security and privacy are also key considerations. KPMG US highlights the increased risk of data breaches, hacker attacks, and unauthorised access via IoT devices. With sensitive information continuously flowing through these systems, device users must implement comprehensive security measures alongside establishing data ownership responsibilities among device makers, service providers, and insurers themselves.
Forward-thinking insurers and brokers are beginning to explore IoT and real-time data integration, recognising its potential to improve risk assessment, reduce and prevent incidents and provide insights to support the claims process. McKinsey & Company notes that IoT technologies enable more precise risk determination, offering a glimpse into insurance's future. For example, long standing solutions include:
Aviva who has successfully incorporated telematics data from connected vehicles to offer usage-based insurance policies that reward safe driving with lower premiums.
In the health insurance sector, South Africa's Discovery uses data from wearables through its Vitality program, incentivising healthy lifestyles by offering rewards and discounts for physical activity.
The direct B2C relationship has made adoption easier, and now B2B insurers and brokers are following suit.
The ‘how’ is key:
A measured and strategic approach is needed, starting with developing a clear strategy aligned with organisational goals and capabilities
Analysis of claims data to identify incident hotspots for targeted IoT usage
Determine the ‘buy’ or ‘partner’ approach
Find a willing collaborator - which broker and insured to work with
Start with pilot projects in specific areas for example: commercial water leak sensors or fire pump monitoring in order to understand both the data flows, which data is meaningful for risk v the ‘noise’ and then the analytics and intelligence from the data. Here, AI is essential. Then it’s about driving behavioural change and responses to alerts.
IoT and real-time data will likely surface previously unseen risk issues, a collaboration with brokers and insurers is needed to work together to resolve these in a partnership approach rather than simply increasing the premium.
Building an ecosystem. For example, with commercial water leak sensors, is there a network of plumbers or facilities managers that can respond early to the alerts and fix issues before they become incidents?
Robust data management systems are essential, as is training and educating employees about IoT's implications and potential
Over time, the challenge is then how to adapt pricing models to accommodate this new risk insight and how the real-time data can support the claims process where incidents do occur.
The integration of IoT data into insurance processes is challenging and transformative to shift the insurance industry from one that pays claims to one that predicts and prevents claims. Success requires collaboration, an ecosystem of industry experts, strategic partnerships with technology providers, and robust data security.
Comments