Innovations in our homes, at work, and at play improve the quality of our lives. New technologies continue to change and have evolved from fire and the invention of the wheel, to the development of the assembly line, the internet and the use of Wi-Fi; and now the evolution of cognitive computing and robotics.
This evolution is no less true within the insurance industry, which has always adapted to the world’s changing risk landscape. But the recent explosion of powerful tools like cognitive computing and predictive analytics are beginning to provide significant impacts and exciting new opportunities.
"Carriers have developed models that improve the outcomes for injured workers and customers by identifying certain types of claims that would benefit from early nurse intervention"
For the past 30 years, insurance carriers have relied on some form of automation to add value for their customers and themselves. This traditional IT automation requires integration of interfaces between legacy systems and applications, which can be costly and time-consuming. Complexity of the overall architecture grows as the interfaces grow, making eventual replacement of underlying systems problematic.
Today, carriers – especially within claims – are seeing cognitive computing and predictive analytics as positive disrupters enabling better outcomes and helping the industry learn from their data to mitigate risk; and reduce costs for customers through more efficient processes.
Scale plays an important part in this disruption. For example, if you are an insurer building a robot to perform a number of steps that save five minutes per claim per adjuster, carriers that have sufficient size and scale would generally receive a higher rate of return on investment as opposed to carriers with less scale.
Three types of technologies that are in the process of disrupting the insurance industry are robotics, cognitive computing and predictive analytics.
Robotics: Like any other kind of computer, robots excel at tasks that follow a standard process. Robots can be used in claims to automate routine repetitive and low-complexity tasks so claim handlers can devote more time to customer-focused activities, solving complex issues, and concentrating on getting better outcomes.
Most of this work focuses on developing Robotic Process Automation (RPA) software, which interacts with IT systems the same way people do to process simple, labor-intensive tasks. Not every task lends itself to a robotics approach. Those best suited are opportunities where there are high volumes of consistent, repeatable tasks.
The way the RPA software works is fairly straightforward. A process is initiated – say an email to the robot generated by a claim adjuster – then the robot follows prescriptive instructions to open files, copy data, save files, etc. In action, it can look like a macro, or any action or set of actions that people can run as many times as they want, working across applications.
Cognitive Computing: Robotics is limited to routine tasks performed by a computer, with little variation. Cognitive, on the other hand, involves the use of Natural Language Processing (NLP), data mining, data summarization, pattern recognition, and other techniques to mimic the way the human brain works.
Some insurers use cognitive computing to improve adjuster accuracy and speed in the review of voluminous records and reports. Cognitive can be especially useful with injury cases: the word “back,” for example, a cognitive solution can identify all references to the “back” embedded in the records and reports and provide the adjuster the opportunity to determine what is relevant and not relevant to the evaluation.
Claim professionals can use cognitive tools to efficiently review thousands of claim records, such as demand packages, as part of the claim evaluation process. NLP engines review the documents, comprehend the context in which the words are used and extract key concepts into a summarized view. Generally, cognitive computing isn’t used as a decision making tool but as a “decision enhancement tool” by ensuring the decision maker has evaluated all information relevant to the evaluation of an issue.
Predictive Analytics: Predictive analytics is about strategically mining data and developing insights to mitigate customer risk. The use of analytics helps improve claim performance and outcomes and enables the ability to detect fraud and provider payment abuse. It’s about turning data into a practical form that offers solutions for specific business problems.
Carriers using predictive analytics tend to have a better, more complete, understanding of the underlying risks facing their customers and can use them to guide them on ways to mitigate those risks. In claims, predictive analytics is being used to help identify key opportunities for improvement at critical junctures of the adjudication process.
The predictive analytics process is only as good as the data that drives it. Carriers have large amounts of structured and unstructured data to inform decisions in many areas, including underwriting and claims. The ability to mine the data and build tools to make more informed, insightful decisions is the differentiator.
Carriers are developing a variety of models to address a broad range of issues related to risk. With medical costs continuing to rise driving up the percentage of overall indemnity costs in workers’ compensation, the healthcare industry is causing insurers to take notice – and begin developing more sophisticated tools. Predictive models and data analytics can help mitigate medical claim costs, identify billing errors, and reduce overall costs.
Carriers have developed models that improve the outcomes for injured workers and customers by identifying certain types of claims that would benefit from early nurse intervention. Other models identify patterns of suspicious billing activity to expose medical provider error, as well as fraudulent activity. Models also can be built to identify higher severity and more complex claims for assignment to the appropriately skilled adjuster.
Robotics, cognitive computing and predictive analytics are just a few of the technological innovations starting to take hold within the insurance industry. Overall, such tools have a positive influence on claims organizations by enhancing decision making and helping customers reduce their total cost of risk. The emerging technologies offer many benefits, and over time they will continue to evolve. Soon, these new technologies will become the rule, rather than the exception.