It’s been a tumultuous year. In just the span of a few weeks, COVID-19 emerged unexpectedly and abruptly altered almost every corner of the commercial insurance space. Stock market and GDP forecasts have whipsawed as economists and investors have tried to make sense of frequently shifting news. Now we’re in a contentious and unpredictable election cycle.
Divining the future is always a challenge, but lately it’s become especially difficult. During periods of intense change, traditional patterns and precedents lose their predictive power. Regression-style tools that provide data extrapolations become a useless blur. The average workers' comp claim duration of 2019, for example, will look very different than it will in 2020. Litigation and fraud may emerge in new forms, with most new types passing undetected by screens developed from prior data.
One approach that can help companies navigate the uncertainty is artificial intelligence (AI), which is highly sensitive to new data and tends to react immediately, creating a dynamically updated vision of the future. While much of the world has been focused on COVID-19 and the related economic challenges, the underlying technologies behind AI have continued to accelerate in speed, efficiency and predictive accuracy. For organizations looking to become more resilient, it’s an ideal time to consider integrating machine learning, natural language processing and other AI techniques into their operations.
While the promise of AI is great, so, too, is the hype. As a result, many people have a misconception of what AI actually is — and what it is not. Let’s take a look at how it really functions, what it can and cannot do and how it can help future-proof commercial insurance.
Two Types
AI is typically viewed in two fundamentally different ways. There is the futuristic “AI-is-taking-over” version (think Skynet or similar concepts brought to life by Hollywood). This form understandably makes people a little nervous that machines will grow to dominate society (or at least replace jobs at a time when we’re already seeing unemployment lines expand).
Then there is a more prosaic version in which AI complements what humans do. Think of how Google automatically surfaces structured answers to questions you type in or how Amazon knows which product you might want to buy next. In these cases, AI extends your capabilities while leaving you in the driver’s seat. It is this more practical version that will get organizations and teams excited about modern AI-based applications and is the game-changing application in the commercial insurance space.
AI that augments human capability is especially valuable in businesses like insurance, where there is simply too much data coming in quickly for people to keep up. Image and language processing can be applied to the dozens of structured documents typically associated with a claim but can also be used to interpret unstructured information, such as handwritten doctors' notes. Often, this approach finds important information — diagnostic codes that were considered, for example, but not officially associated with the case. Subtle cues can be detected across a wide range of files to create insights that would otherwise go unnoticed. Alerts bring those insights to adjusters’ attention, helping them take prompt action that can make all the difference in a claim.
In this way, AI becomes a kind of superpower for the adjuster. It helps adjusters see through the clutter and make decisions with speed, precision and scale. This helps adjusters become more productive and better able to focus on the claims that matter most. It also frees them up to handle the types of challenges that humans are uniquely suited for, such as detecting the hidden concern in a claimant’s words or enabling them to feel listened to during a challenging period.
See also: 3 Practical Uses for AI in Risk Management
Innovate Now to Secure the Future
AI can end up reshaping not just a single claim but how a business is managed. Claims leaders can now use it to optimize organizational practices, team performance and even partner networks. AI can score healthcare providers, for example, so carriers can direct claimants to highly rated doctors and even identify new ones to bring into the network. Carriers can also use AI to evaluate the effectiveness of their attorney panels based on specific outcomes. These are just a few examples of substantial business decisions that can now be driven by data and intelligence.
Despite the complexities and considerable challenges brought about by COVID-19 and other events this year, the insurance industry sits at a breakthrough moment. New uses for AI such as those highlighted above will continue to be identified and implemented, resulting not only in more efficient operations and empowered employees but also in better, faster, more valuable service to claimants.
As first published in Datanami.
