As the capabilities of artificial intelligence (AI) are growing, insurers are finding new ways to capitalize on this technology. And the benefits of AI in the insurance industry go beyond the typical cost and time reductions. Here are some of the most prominent advantages of Insurance companies adopting AI.
Improved Data Analytics
IoT (internet of things) refers to the interconnection of physical objects via the internet. These devices—things—are embedded with software and sensors for the purpose of connecting and exchanging data with other systems and devices over the internet.
The internet of things includes devices such as Google Home and Amazon Echo. But it also includes fitness trackers, smartwatches, and other wearable devices that can be of great use to insurance companies. And AI plays a growing role in IoT applications.
AI has the ability to quickly identify patterns and wring insights from the data collected by these types of IoT devices. By “digesting” the data from fitness smart devices, AI can help insurers better understand user preferences.
Essentially, AI-enabled IoT devices help insurance companies tailor personalized insurance products. For instance, insurers can use data from fitness trackers to keep track of the anomalies that can cost them money in the long-run. Based on the findings from real-time health records, an insurance provider may transition the insured from “healthy” to “high mortality risk.”
The auto insurance industry is also greatly benefiting from AI-enabled IoT devices. Since drivers can download apps on their smartphones or install devices in their cars, many insurance companies are using AI-enabled IoT technologies to track the driving behaviors of applicants and insured drivers.
For instance, some auto insurers give every applicant an IoT sensor to place in their car. The IoT sensor collects data about their individual driving habits, such as how wide their turns are or how hard they break. Then, the insurer can feed the collected data into their AI-predictive analytics software.
They can use the findings to decide whether or not they will onboard the applicant and how much their policy should cost. To offer the prospective customer a tailored insurance rate, the insurer can combine the customer’s demographic data with their IoT sensor data.
Auto insurance companies also use data collected by IoT sensors to figure out whether they should increase or decrease the premium an existing customer pays. Naturally, bad driving habits of a customer will lead the insurer to increase the price of their policy.
Better Customer Service
NLP (natural language processing) enables AI systems to process, analyze, and draw insights from human language. It is the root of conversational AI solutions, such as chatbots and virtual assistants.
More and more insurance companies are using conversational AI solutions to improve customer experience. There are many chatbots and virtual assistants that are specifically designed for the insurance industry. They allow insurance companies to deliver instant and efficient customer service—even outside of office hours.
For instance, the Claims Assistant developed by AI Insurance can help customers file a claim and gather the required information for processing. Moreover, it can reengage with customers throughout the complete process.
AI chatbots can also help customers schedule payments or get insurance quotes. They can answer customers’ questions about the insurance claims process, policy adjustments, and deductibles in a human-like manner. And, thanks to advancements in machine learning, chatbots can learn how to answer questions on their own.
Faster and More Efficient Fraud Detection
The health of the industry largely depends on fraud prevention and detection. The FBI estimates that insurance fraud costs insurance companies more than $40 billion per year. Since this is a constant battle for the industry, insurers are always trying to find more efficient ways to deal with fraud.
Because fraud detection is a knowledge-intensive activity, AI has shown to be of great use in this arena. AI fraud detection in the insurance industry is mostly made possible by deep anomaly detection—a form of machine learning. It allows AI systems to analyze genuine claims and form a model of what a normal claim looks like. An AI fraud detection system can apply this model to large data sets.
AI fraud detection systems can detect suspicious activity, such as unusually high claims, by evaluating millions of data points. Some AI tools can even cross-reference internal and external data sources, such as law enforcement databases, credit databases, and news sites, to uncover fraudsters in the company’s own customer database. This can help companies detect larger-scale frauds.
Insurance companies can expect to detect frauds much faster now that we have AI systems that can sift through claims histories in seconds. AI tools can help enforcement agents and fraud examiners build a body of evidence quickly and efficiently.
However, AI still has its limits when it comes to fraud detection. Sometimes, an activity that an AI fraud detection system flags as fraudulent can have a benign and valid explanation, so human experts should always have the final say.
