The insurance industry has often been characterized as cautious and slow to adapt. Changes are typically incremental, not the sea changes you sometimes find in other industries. In recent years, however, the digital age has claimed its stake in our modern world. With so many tools now available, insurers find themselves scrambling to ensure they are using them intelligently to improve both internal operations and external customer engagement.
The value of AI in the insurance industry
As an industry, insurance is beginning to shed its stigma of shying away from emerging technology. Artificial intelligence (AI) is opening new doors and allowing for better customer service and smarter product offerings.
AI serves two clear purposes in the insurance sphere: data analytics and automation. Both allow for greater precision and speed in basic insurance practices and procedures.
The modern customer is steadily becoming less inclined to accept generic, one-size offerings that feel as though they’ve come fresh off the conveyor belt. Instead, personalization and a data-driven understanding of customer needs is the expectation, and insurers must rise to the occasion. While there is no end to the complexities of insurance models, we are starting to see examples of where both data analytics and automation are helping to meet customer expectations in exciting new ways.
With each digital innovation, our world becomes faster and more agile. Speed and accuracy are especially important for the insurance industry—by nature, more cautious—allowing it to match stride with others in the digital world. Collecting big data can enable a provider to better understand its customers and cater to their individual and collective needs. Thus, the understanding of AI-driven data analytics has the potential to open new opportunities to the providing company and, by extension, the industry itself.
The old approach to data analytics meant surveying spreadsheets, painstakingly analyzing trends, and programming algorithms for extended periods. AI-driven data analytics offer something else entirely. Information gathered through machine learning and predictive analytics provides not only a more accurate and timely snapshot of data across the customer base, but it also can efficiently help insurers anticipate need.
Data analytics proves especially helpful in times of unexpected disaster. Disasters and insurance losses reached a record high in 2017 and left millions of people around the world in a tailspin. Between Hurricanes Harvey, Irma, and Maria, flooding in the southern United States and fires in the West, insurers had to be on high alert. In these situations, AI offers insight into relevant data that can help customers receive what they need when it matters most. While customers in the past may have had to wait in these dire situations for insurance claims to be settled, with the help of AI, applicable data can be in the hands of those who can help in just seconds, significantly speeding the claims process.
Claims, policy issue, and underwriting can take up a significant amount of time and money in the industry, and while they are necessary, historically these practices have felt tedious and repetitive. With the help of AI in the form of voice technology and chatbots, these important tasks can be managed by machine, streamlining the process for the insurer and the client. This form of AI is both cost- and labor-efficient, and can benefit both parties in the process.
It would be a mistake in this digital-first world to dismiss new technologies such as voice and chatbot automation. Rather, insurers would do well to position themselves as leaders in the industry and stay ahead of these technological advances. Customers agree, according to Accenture’s 2017 Global Distribution and Marketing survey. Three-quarters of respondents said they would use entirely computer-generated support specifically for purchasing insurance.
One large insurance company turned to robotic process automation (RPA) to automate 35% to 40% of its claims value chain process, and in so doing experienced a 68% jump in productivity and enhanced accuracy of 95%. AI allows thousands of people-hours to become available. In fact, the RPA market share is predicted to exceed $5 billion in the United States by 2024. While it may feel comforting to hold on to standard practices and procedures that have worked well in the past, the fact is that automation frees up human resource talent and skill that can be best used elsewhere. As more and more companies transfer toward AI chatbots and voice technology, the market will grow to expect improved efficiencies.
What’s more, automation can be tied directly to increased customer engagement. As the underwriting and application process is accessible in real time, the likelihood of prospects buying a policy once they apply increases from about 70% to nearly 90%. The role of AI-based automation is primed to have far-reaching impacts across every facet of the industry.
To make the most of emerging technology and embrace AI, insurance companies would do well to first institute a culture of change internally, and openly investigate how new technologies can help provide better solutions for today’s needs. Additionally, insurance companies must also consider how strategic partnerships—whether with entrenched tech solution providers or insurtech startups—can offer crucial insight and support in adopting new technologies like AI.
The value of AI-based technologies and machine learning capabilities cannot be underestimated, and the resulting improvement in both data analytics and automation will allow the insurance industry to grow with its customers.