Applying Artificial Intelligence And Machine Learning In Insurance
For as much noise as the insurance, the world has made about the transformative potential of artificial intelligence, the technology has yet to fully permeate much of the industry. The reality is that many insurance giants aren’t quite sure yet how to best use AI to their advantage, while others have yet to experiment with it at all. Even those that are invested in AI-powered systems are typically using them for little more than fielding common policyholder questions and improving customer experience — important tasks to be sure, but not exactly a brave new world for healthcare providers.
Yet as AI technology grows more sophisticated and widely accepted, its applications within the health insurance world are gradually evolving in lockstep. With the industry on the precipice of a new technological wave, here’s a look at two use-cases for AI in health insurance that is starting to make headway.
Smart, Personalized Premium Calculations
Non-communicable diseases (NCDs) — which include cardiovascular diseases like heart attacks, strokes, cancers, and chronic respiratory diseases like asthma and diabetes — are the biggest issue globally in health care, according to the World Health Organization. These diseases cause 70 percent of deaths worldwide and the cost to fight these diseases is estimated to grow to $47 trillion by 2030, according to WEF (World Economic Forum).
NCDs can cause the cost of healthcare to skyrocket by driving up the burden of medical claims. As a result, insurers are spending their financial reserves to treat these diseases instead of conducting further research to help prevent them.
However, instead of calculating insurance premiums using the traditional set formula based on historical data collected by actuaries, AI is allowing insurers to embrace personalization and reward healthy behaviors with lower premiums.
For example, policyholders are being offered tools like smartwatches that use data to encourage them to get into a preventative health program. With this data, insurers can send positive feedback on fitness activity, invite policyholders to participate in fitness or sleep challenges and even quiz them on nutrition. Artificial intelligence can then use the data from the preventative health program to calculate and set a participant’s insurance premium then re-price over time based on their behavior. The data can also be used to calculate the claims costs of various diseases reported by program participants. Of course, this raises important privacy and data security questions that will have to be worked out by insurers in coordination with their policyholders.
Over time, insurers will receive direct insight into the effectiveness of their wellness programs on various disease groupings, highlight claims expense savings and improves efforts for disease interventions. The results will be not only healthier policyholders but also a reduction in claims costs, an increase in profitability and improved health plans.
Easing Claims Processing
In the health care claims process, AI has the potential to dramatically speed up claims approval. For instance, when claims are being processed, automatic checks are performed to establish whether an authorization is required, whether it has been granted, and whether the claim is within the defined limits.
However, an AI/ML system can look at the claims data on how often certain claims require manual processing and try to figure out whether those can be automated moving forward. Every time a claim is approved, the AI/ML system knows to automatically complete that action moving forward. This will dramatically increase efficiencies on both the front end and back end of the claims process, resulting in improved customer experience.
Additional applications of AI technology in health insurance will likely emerge in the coming years. By centralizing data and operations on cloud technology, insurers will be able to build, train and deploy AI-powered solutions. This will not only lead insurers to greater operational efficiencies and better customer experience but into the next frontier of insurance.