Insurance companies that find a partner, which analyzes, understands, and helps them to take advantage of IoT-based technologies, can reduce costs, paving the way for lower premiums and increased customer loyalty.
Many types of insurers record an unnecessary number of claims. By adding IoT sensors, real-time data can be attained and custom alerting can be configured to prevent claims from occurring. In addition, robust predictive models on historical sensor data can predict claims based on geography, even by a customer.
Let’s look at a situation where a company contracts out a service provider to monitor and maintain the health of four cold storage warehouses in South Florida. Each warehouse has many refrigerated rooms storing food, and each room is equipped with three sensors: one temperature, one humidity, and one open/closed sensor for the entry door.
By employing an app to use WebSockets, monitoring can be performed through dashboards, where individual data elements are refreshed without requiring any user interaction. Think of this view as a live status screen in the service provider’s operations center.
The system includes dashboards to monitor, alert, and proactively prevent claims. The warehouses and cold storage rooms dashboard provides a status summary for each room including how recently the sensors last updated. Room sensor data shows the graphical views of current and historical sensor data. Dials show some predefined thresholds for green, orange, and red alerts along with the current value. Then, line graphs show trends over the past few minutes, hours, and days.
IoT sensors catch anomalies and prevent claims before they happen. Because the refrigerated units are storing food, there are multiple scenarios that might result in a food spoilage claim. One might be if the temperature in the room crosses the threshold into orange alert and remains there for more than two hours. Another might be if the temperature ever crosses the threshold into red.
Alert notifications can be configured so that the policyholder gets notified via push notification, SMS and/or email when the temperature crosses the threshold into orange. Perhaps the door was left open, which can likely be resolved. However, if the temperature remains orange for more than 15 minutes, a message or work order is pushed to the service provider queue, which dispatches someone to investigate and proactively resolve the issue.
In addition, the system includes dashboards that insurance companies can leverage to generate business value. These predictive scenario dashboards slice the sensor data in various ways.
The manufacturer performance screen helps insurance companies determine the most effective sensor manufacturer, saving time and money from defective sensors. Another dashboard helps identify events and incidents, such as anomalies between the two sensors.
Another screen shows customer segmentation by sensor data. This helps insurance companies enable premium discounts based on lower claim probability. The historical loss ratio and claims analysis dashboard provides loss ratio by location and number of claims by location.
Additionally, claim prediction insights are provided. Using historical data, predictive models are created to predict the number of claims, total amount of those predicted claims, and number of claims avoided.
By incorporating IoT sensors into a telematics solution, policyholders can catch anomalies and proactively prevent claims. Insurance companies can leverage predictive scenario dashboards and predictive models to avoid claims, reduce costs, lower premiums, and therefore increase customer loyalty.