n 1970, Americans spent $74.5 billion on healthcare—$448 billion in today’s dollars. But by 2017, that price tag had ballooned to $3.5 trillion flowing to and from insurers, Medicare and Medicaid via patient premiums and claims payouts to healthcare providers and drug companies.
All told, keeping the U.S. healthcare system spinning took six billion insurance-related transactions (an increase of 1.2 billion transactions from 2016), according to the nonprofit Council of Affordable Quality Healthcare. That’s roughly 11,450 transactions per minute.
For insurance companies, it’s a cumbersome, complex, and expensive system. Could artificial intelligence (AI) technologies help control the industry’s rising costs and tsunami of paperwork?
Experts say yes. Insurers could save up to $7 billion over 18 months using AI-driven technologies by streamlining administrative processes, according to a recent Accenture study. By automating routine business tasks alone, the study projects that health insurers could save $15 million per 100 full-time employees. But AI’s promise extends beyond reducing wasteful spending—it could also help insurers improve consumers’ overall health.
“More and more, you’re seeing investment in AI to intervene on behalf of customers to change behavior in ways that actually result in better healthcare outcomes,” says Christer Johnson, health care data and analytics advisory leader at Ernst & Young.
Health insurance companies are aware of this potential and acting on it. Roughly three-quarters of health insurance executives (72%) say investing in AI will be one of their top three strategic priorities for the coming year, an Accenture survey reveals.
72% of health insurance executives say investing in AI will be one of their top three strategic priorities for the coming year.
And while health insurance leaders’ eyes are on the prize of long-term savings and improved patient health, AI’s impact is already rippling across the industry. Here are four areas where the technology is transforming the industry today.
Engaging Customers With AI Bots
When consumers reach out to ZhongAn Tech, China’s largest insurance company, to apply for coverage, check their benefits, or file a medical claim, 97% of the time they interact with an AI chatbot. Only the thorniest inquiries (3%) are directed to a human representative.
In the future, expect AI-based customer engagement to be the rule, not the exception. By 2030, chatbots will be the primary touchpoint for most insurance customers, with 70% to 90% fewer human personnel engaging with customers than in 2018, according to a McKinsey report.
Today, 68% of insurers are already using chatbots in various segments of their business, an Accenture survey finds. And the consulting firm reports that health insurance companies could save more than $2 billion annually by using AI to manage customer interactions.
Increasingly, health insurance customers are becoming acclimated to human-machine interactions, according to Torben Nielsen, VP of innovation and strategic investments for Premera Blue Cross.
68% of insurers are already using chatbots in various segments of their business.
“We’ve done a ton of research into our member experience, and we’ve found that more and more people are very comfortable engaging with technology solutions versus talking to a person,” Nielsen reveals.
With 2.2 million members, Premera is the Pacific Northwest’s largest health insurer. In 2017, it launched Premera Scout, a 24/7 chatbot to help customers quickly access information on claims, benefits, and other Premera services.
“What members want is a personalized experience,” Nielsen explains. “AI allows us to take complex data and really extract value out of it in a much more personalized manner for the individual.”
Cigna and Humana are among the other major health insurers engaging customers with bots. Cigna’s Answers chatbot uses natural language processing to understand and respond to more than 150 common questions with personalized benefits information. Thanks to Answers and Cigna’s digital One Guide service platform, the company reports that customer satisfaction rose by 20% in 2017.
While bots are primarily handling basic customer interactions at present, Nielsen envisions them eventually dispensing customized, data-driven health guidance.
“In the future, bots will access your personal health information and identify gaps in care that you weren’t aware of,” he predicts. “They will really become a guide in your healthcare journey.”
Faster, Smarter Claims Management
Out of every 10 healthcare claims submitted, insurers flag as many as eight as unusual—that is, as potentially incorrect or fraudulent—based on the company’s guidelines, according to a McKinsey study. That means up to 80% of all claims must be reviewed by adjusters, a process that requires a great deal of time, money, and human effort.
But AI is transforming claims processing across the insurance industry, as algorithms detect anomalies in seconds, rather than days, weeks, or months.
“Over the years, claims acceptance or denials have been primarily based on set rules that are hard-coded in processing systems,” explains Johnson. “Now they are starting to embed more machine-learning models that can take into account multiple factors, instead of just a hard, fast rule.”
Among the largest investment in AI tech in the insurance industry has been in fraud detection, with more than 75% of insurers reporting the use of machine-learning algorithms to flag fraud cases in 2016, according to the Coalition Against Insurance Fraud.
Faster fraud detection means faster processing. How fast? A pilot program spearheaded by Prudential in Singapore credits AI with reducing the time to process hospital claims by 75%; a claim that once took nine days to process can now be settled in a mere 2.3 seconds.
Still, EY’s Johnson finds that AI automation in claims processing has progressed more slowly than many had hoped, hindered by challenges such as preparing, cleansing, and aggregating unstructured data from diverse silos such as hospital facilities, doctor’s offices, and pharmacies.
“If you had asked me five years ago where we’d be today, it’s been slower than I would have expected,” says Johnson. But, he adds, “It’s happening.”
Predicting ER Visits With AI
Many major insurers are exploring how to leverage AI solutions to prevent negative health outcomes before they happen—and investing in tech startups to tap their innovative analytics.
Case in point: In 2017, Premera Blue Cross took an early stake in Cardinal Analytx, a healthcare AI startup incubated at Stanford University that uses predictive modeling to recommend healthcare interventions in advance of medical crises.
“Cardinal is able to, with a high degree of certainty, predict when a member is about to have a severe health event,” Nielsen says. “That’s much better for the individual because they’re avoiding something big and nasty. And it allows us to reduce costs that we would otherwise have incurred.”
Similarly, Cigna has invested in Prognos, which applies AI to lab diagnostics. Analyzing a database of 14 billion medical records, the insurer reports that it can predict when a customer is most likely to visit an emergency room, need hip or knee replacement within six months, and pinpoint a diagnosis of depression three months before an antidepressant is ever prescribed.
Early intervention especially benefits patients suffering chronic illnesses. “Today, roughly 75% of total healthcare costs are related to chronic conditions such as non-terminal cancer and diabetes,” Johnson says, citing CDC research.
Johnson explains that predictive analytics, based on indicators like when a patient searches online for information about symptoms or visits a specialist, can indicate an impending negative health event. By reaching out early, insurers can engage them in preemptive care.“
With AI, you can identify patterns that suggest this is the right moment in time for a person with a chronic condition to get an intervention call,” he says. “We’ve actually seen that if you call at the right time, you can increase engagement by over 800%.”
Live Healthier, Pay Less
In 2014, Progressive Insurance launched a mobile app for its Snapshot program, offering to reduce premiums for safe drivers based on AI analysis of millions of data points on speeding, braking hard, or texting while driving. Major insurers like Allstate, State Farm, and Nationwide, among others, have since offered similar incentives based on telematic data, saving consumers billions in premium costs.
And car insurers have saved billions in accident payouts for themselves in the process. Studies show that vehicle telematics can reduce speeding events by 60% and lower catastrophic accident rates among young drivers by 35%.
Given the widespread popularity of wearable sensors such as Fitbit and health data tracking via smartphones, behavior-based premiums seem like an inevitability in health insurance.
“We’ve already seen some examples of insurance companies starting to experiment with it,” says Nielsen. “If you walk a certain number of steps on a daily basis, there may be an incentive for you, such as money being allocated to your health savings account.”
In 2018, John Hancock announced that it would stop selling traditional life insurance and sell only interactive policies that track health data through smartphones and wearables. The insurer’s CEO Brooks Tingle explained the shift to The New York Times, saying, “The longer people live, the more money we make.”
But, Nielsen emphasizes, it’s still early days for behavior-based policies in the health insurance sector. “The industry is still trying to determine whether that is something that should be further scaled up,” he notes.
Consumers, for their part, seem very willing to trade personal data for cheaper insurance; nearly half of 1,194 U.S. consumers surveyed by Troubadour Research said they would share their biometric data with health insurers in exchange for premium discounts.
The Road Ahead: Personalization Through AI
While major health insurers are eyeing behavior-based products warily, several insurance-technology startups already offer them.
BioBeats and FitSense are using AI tech to crunch data generated by fitness wearables to offer personalized employee health plans. Other AI-driven health insurance startups innovating more personalized products include Collective Health, Bind, and Oscar, which is pioneering a white-glove “concierge for all” plan.
Nielsen, for one, believes the new, tech-fueled entrants into the sector will ultimately benefit all healthcare insurers—and their customers.
“I see startups coming into the health insurance marketplace as a positive, and I think we all do in the industry,” he explains. “They bring new thinking, and it allows us to really take a close look at what our core competencies are and to make sure that we’re developing products for what future healthcare may look like.”
Ultimately, this shift toward personalization is fundamentally transforming health insurers’ traditional business model. For generations, insurance companies have based their coverage on risk pools determined by statistical sampling. Now AI is allowing them to mine huge data sets in real time to predict health outcomes for a single consumer instead of a group.
And insurers are optimizing those insights to help consumers live healthier lives.
“Natural language processing, bot technology, machine learning—these processes are not just playing a key role in creating efficiencies for companies,” says Nielsen. “They’re creating a better health experience for members.”