Part 1 of a two-part series.
Considered a key component of the Fourth Industrial Revolution, the IoT is set to dramatically change how business is conducted around the world. For commercial insurers, IoT is also spurring an identity crisis, particularly when it comes to underwriting risk. Key questions revolve around traditional notions of the scope of risk coverage: Is it merely a tangible asset (e.g., a car), or does it include the software that makes the asset smart and controls its behavior?
Consider the fatal crash that occurred last year, in which car manufacturer Tesla Motors held both the driver and its own autopilot technology responsible for the crash. While federal investigators determine final liability, the accident raises a key question: How can insurers assess risk and assign liabilities among the car’s occupant, another vehicle, the car manufacturer and the developer of the autopilot software?
Given that IoT investments are growing exponentially, it’s time for commercial insurers to stake their claim in this evolving landscape and assume the role of a value-added partner. Insurers need to rethink how liabilities will change with the advent of new smart assets, and how risk should be assessed and managed to remain competitive. Carriers also need to adopt IoT technologies quickly to support the smart assets they insure, and develop an application environment to consume the data sets that will be generated. Data-driven risk modeling will also be needed to provide a clear picture of what insurers face.
Promising IoT Applications
Leading commercial insurers are already working with top IoT innovators to understand how real-time analytics from sensor data will open new opportunities. Others are going the extra mile to create and invest in IoT incubators. So far, the most promising applications include:
Smart buildings. Commercial carriers are developing intelligent building management systems that track energy usage through connected thermostats, electric asset performance and HVAC system conditions. They are also monitoring building structures to detect liabilities.
Fleet management. Organizations are tracking fleet usage and performing predictive maintenance and itinerary redefinition using real-time data on traffic and weather conditions.
Connected supply chain. Carriers could make use of instantaneous data on temperature, package arrival time, driver fatigue, etc. FedEx offers an IoT tracking device that can share key parameters of shipments in real-time.
Manufacturing operations. Intelligent, interconnected components could automate information exchange, trigger actions and activate machine control.
Drones. These devices are currently being tested by insurers for claims adjustment and risk analysis of high-risk events and property damage.
Blockchain. Some carriers are exploring blockchain transactions such as smart contracts for tracking the exact origin of a loss event in the supply chain.
3-D printing. With this technology, insurers could offer replacements of lost or stolen items by “printing” replacements in agreement with the customer.
Each of these IoT applications presents a unique set of challenges. In-depth analysis is required to align the technologies with various real-life scenarios involving an insured’s assets.
Commercial insurers need to rethink how they conduct business, namely by moving to a proactive way of assessing risk and determining liability. They need to develop new capabilities, such as real-time risk assessment, failure and loss prevention, and predictive behavior assessment.
Insurers also need to focus on optimizing data collection and management, building a supportive IT foundation and creating new business models that align with prospective IoT revenue streams. Internal processes also need to be synchronized with new IoT-aligned product offerings. For example, claims processes should be revamped to support real-time asset-monitoring applications that would automatically trigger a claim following an equipment failure.
This will involve an enterprise-wide overhaul of products, people and processes (see interactive figure below).
We recommend a four-phase approach to IoT adoption:
Smart risk assessment.
Create proofs of concept to determine scale and encourage customers by offering incentives for IoT adoption. Develop smart devices, and partner with industry players.
Smart risk detection and claims processing.
Develop an ecosystem that enables the collection of real-time data from smart products and develop capabilities for anomaly detection and alerting mechanisms.
Risk prevention/mitigation while building a partner ecosystem.
Include third-party data providers in the ecosystem; develop risk models that can process real-time data generated by sensors to help mitigate risk.
Rethink business models.
Shift the emphasis to value-added services and connected insurance products based on data and analytics that can help target new markets.
In part two, we’ll examine how commercial insurers can determine their role in the IoT value chain, forge an effective partner ecosystem, and prepare for the challenges of deploying real-world solutions.