Artificial Intelligence (AI) is revolutionizing industries across the globe. Healthcare and insurance are no different. In fact, AI in health insurance is changing the game by improving processes, lowering risk, and creating a better customer experience. Whether it’s identifying fraudulent claims or providing customized policy pricing, AI is transforming the landscape of how insurers and policyholders create interactions.
What makes AI important in this case is that it applies large amounts of medical and financial data at high speed, accuracy, and efficiency in real time. Where traditional methods are often limited in these areas, AI establishes a framework for automation, predictive analytics, and informed decision-making to target these efficiencies, for both parties. In this sense, a system that is a win-win for both the insurers and patients, allowing for transparency, speed, and cost-effectiveness.
While the full scope of AI adoption in health care is still being realized, it is already changing a developer’s perspective on health insurance software development. Let’s look at some of the best use cases where AI is proving its value.
Top 5 Uses Cases of AI in Health Insurance Software Development
Let’s explore some of the top use cases!
Fraud Detection and Preventation
Health insurance fraud is one of the biggest issues faced by insurers costing the industry billions each year. Anything from false claims, to artificially inflated hospital bills, to even identity theft can use up resources and create distrust among customers. For decades, health insurers relied primarily on human intervention and manual review for fraud detection. It can be time-consuming, inflexible, and isn’t appropriate to identifying subtle patterns.
This is where AI comes into support systems. Machine learning models can process thousands of claims at once and find some unusual behavior that would otherwise go unnoticed.
An example of this might include a claim that contained treatments that were inconsistent with the patients medical history, which AI could recommend an investigation at scale and very rapidly. Predictive analytics increases this utility by not only identifying upfront risk, but also warning the insurer about suspicious activity. Furthermore, real-time fraud monitoring tools give insurers the ability to intervene rapidly, rather than wait weeks for the usual consequences of a manual review.
The implications are considerable. AI saves insurers millions of dollars in fraudulent payouts, while also making sure genuine policyholders receive fair treatment without delays. More simply, AI helps build and develop a trust-worthy insurance environment.
Intelligent Claims Processing
Simply ask any policyholder to describe their biggest grievance. The chances are that they will cite the claims process. Health insurance claims can involve a lot of paperwork, lengthy approval cycles, and excessive instances of claims processing errors. This serves to exhaust customers’ patience and create toil for insurance personnel engaged in repetitive and time-intensive tasks.
In addition to that, AI is rewriting the rules of the game, streamlining almost every aspect of a claims journey. Natural Language Processing (NLP) allows the AI to pull and validate data right from the medical document, eliminating the time wasted on excessive manual data entry. Robotic Process Automation (RPA) can then address time-consuming administrative tasks, performing many of the manual tasks with consistency and speed. And, for added ease, AI chatbots guide customers from step to step of a claims submission while answering any questions along the way, reducing the chances for customer confusion.
The end result is that claims processes that once took several weeks can go from submission to approval in a matter of days, or hours, depending on the claim submitted. As a result, customers are able to enjoy a better, faster, and easier experience, while insurers are able to demonstrate cost efficiencies and reduce error.
Personalization of Policy Pricing and Underwriting
For many years, health insurance policies were developed on a “one-size-fits-all” basis. Premiums were determined by demographic data such as age and gender, resulting in some instances of unfair pricing and lack of accuracy in pricing. A policyholder who has a healthy lifestyle, and one who lives a less healthy lifestyle, may at times have the same premiums, which could result in frustration for the policyholder.
With AI, the personalization of the insurance product comes to life. With AI supporting the insurance process, dynamic algorithms can establish pricing based on past lifestyle data, some medical history data, and even data from wearable devices to determine the individual person’s overall health.
AI gives insurers the power to pin point risk at an individual level instead of using historical data across a group. With more dynamic risk assessment, the customer with health issues can pay very little for a policy, while the healthy customers can pay economical premiums based on what their lifestyle is.
AI also helps underwriters make more accurate and less biased decisions when pricing insurance policies. Their decisions will be based on facts, not outdated assumptions. AI is allowing insurers to create policies that can reflect adversely in terms of pricing and will be fairer and more aligned with modern health trends, resulting in happier customers, more effective risk management, and reduced friction between insurance companies and customers over time.
Predictive Analytics for Preventive Care
Health insurance has always been covering treatments and hospitalizations after a disease has occurred. But, what if insurers could help their insurers stay healthier and avoid costly treatments? It is possible with AI-enabled predictive analytics.
Analyzing medical history, wearable device data and lifestyle data, AI can identify patients at higher risk for chronic conditions such as diabetes, heart disease, or hypertension. For instance, if an AI model identified a pattern of rising blood pressure readings from a wearable device, it could flag a member as high risk and advise a better diet, increased exercise, or enable tele-health intervention.
This proactive approach is helpful to everyone. Insured members receive personalized health reminders and preventive check-up reminders, or wellness programs, while insurers have reduced claim costs by encouraging adherence to a healthful lifestyle before expensive medical treatment is required. Thus, it helps eliminate expensive hospital visits, and long-term medical cost savings.
Customer Support and Engagement
Policyholders typically find it challenging to track claims properly, or even decide which plan is most suitable for their lifestyle. Consequently, the only options were sitting on hold for extended periods of time to get customer support or having a lengthy email exchange with customer support representatives. AI is ensuring we do not have to experience those types of pain points with our insurers any longer.
By utilizing AI-powered chatbots or virtual assistants, customers can achieve their desired outcome and receive immediate responses to their questions 24/7. Whether that outcome is checking claim status, clarifying benefits, or securing personalized plan recommendations, these digital assistants are meant to simplify complicated processes. Sentiment analysis of customer interactions will also help insurers gauge how customers are feeling during those interactions, leading to a more empathetic adjustment in support.
Conclusion
Artificial intelligence is revolutionizing the health insurance world by changing how health insurers and their customers interact, from analog models with tedious paperwork to data-driven models that enhance speed, time and ultimately customer satisfaction.
AI is helping the health insurance ecosystem by fighting fraudulent claims, improving automated workflow systems, personalizing pricing, and enhancing customer interaction. AI has real value in health insurance as it lowers costs and tedious burdens on insurers, providing fairness, transparency and convenience for customers.