If you’ve ever applied for property or casualty insurance, filed a claim or tried to work through a problem with customer service, you’ve probably been frustrated by lots of paperwork and slow response times.
But that’s all changing. Insurance carriers are transforming their operations with the help of cutting-edge technologies such as artificial intelligence (AI), cognitive computing and robotic process automation (RPA).
Most consumers are accustomed to the slick one-click shopping experience at digital-native companies such as Amazon, and they want that same experience when interacting with their insurance carriers. But insurers face some unique challenges.
First, there’s a long history of using paper-based systems and manual methods, so the deployment of digital processes represents a significant hurdle in terms of training, culture change and making the transition from legacy systems in a seamless way.
Also, insurers operate in a highly regulated industry, and those regulations can unexpectedly change, requiring companies to change processes in a short period of time. In addition, no other industry is as affected by natural disasters; between hurricanes and wildfires that have caused death and destruction from Florida to California, insurers have had to pay out billions of dollars. The result is that insurers are tackling digital transformation efforts on tighter budgets.
The importance of AI
The key to digital transformation in the insurance industry is AI, an umbrella term that encompasses RPA, cognitive computing and advanced analytics.
This transformation starts with simple RPA, in which software systems automate low-level processes such as data transfer from one system to another. The limitation of RPA is that if there’s an exception, the system is unable to process that transaction. AI can serve as an exception handler that uses intelligence to complete the transaction without the need for manual intervention.
Cognitive computing systems can automatically handle customer service calls, helping the company answer more calls and improve customer service with less staff. And if there’s a complex question that a system like IBM’s Watson can’t answer, that session can be escalated to an experienced customer service rep in a call center.
In addition, cognitive computing serves as the underpinning for self-service platforms that allow customers to make payments, submit claims or submit digital forms of documentation such as photos or videos.
Visions of an AI future
The advantage of adopting digital systems is that as more data is collected, aggregated and analyzed, the AI system gets better and better at improving and speeding up processes. For example, a first step might be to have employees review a customer’s digital photographs of a property to be insured. That process can then be automated so the system will analyze those photos, compare them against underwriting guidelines and help score the risk. By incorporating mapping technology that shows the location of the property and what’s surrounding it, the risk score can be refined at an even more granular level.
Over time, more data is collected, and the AI systems learn the rules of the business. That translates into business process optimization. For example, instead of customers having to fill out a lengthy application form, they might be asked only a handful of questions, and the AI-based system will be able to make a decision almost instantaneously about whether to accept or reject the risk. And underwriters and other skilled workers will only have to look at a small percentage of applications.
Digital transformation with AI-based systems is expected to help insurers boost customer service, improve processes and cut costs, and eventually it may even help companies bring new products to market.