Health insurance players can also use predictive intelligence algorithm to develop personalised outreach mechanism for consumers, across marketing channels
Predictive Artificial Intelligence (AI) can personalise experience for health insurance consumers. While the process has begun, health insurance sector has a long way to go before it brings significant benefits to consumers through AI.
Chatbots
Chatbots are becoming an obvious choice for customer interaction, with most people on smartphones using chat apps to interact. Its 24X7 availability for consumers, also makes chatbots more effective. Chatbots can use natural language processing and sentiment analysis to understand customers better and answer all type of queries related to claims or products selection and also help marketers in reaching out to relevant customers.
Underwriting to speed up the policy decision
Traditional underwriting process is tedious and time consuming. With increase in adoption of smart wearables like fitness trackers and smart watches by customers to track their fitness, there is growth in the amount of data available with health insurers. By using this data and social profile of customers, insurance companies have new opportunities to underwrite customers differently. Predictive analytics of data can help complete the underwriting process faster, thus saving time and money for health insurers.
Early detection of diseases
Patients' historical data – medical reports, diagnosis, images can be fed to the machine-learning algorithm to make it learn from it. Over the time this algorithm can help in diagnosing the onset of diseases and alert the customer to take necessary measures before it's late.
In Stanford University, researchers used the images to train an algorithm to diagnose skin cancer using deep learning. US FDA has approved medical device to use AI to detect eye diseases in adults who have diabetes. This can help customers live healthier lives and also help health insurers save money.
Hospital claims management
The long turnaround time for settling insurance claims is one of the biggest challenges in the health insurance sector today. Two major factors that contribute to the delay are a) Fraudulent claims and b) Manual processes to make claims assessment by mainly third party administrators. As per statistics "out of the total outgoings in health insurance, nearly 25% are fraudulent claims."
This is not the scenario in India alone but even in other countries. The nationwide cost of inpatient treatment in Germany for instance amounts to EUR 73 billion and makes up 30 to 40% of a typical health insurer's total budget; on an average, however, between 8 and 10% of all claims received are incorrect. Identifying the genuineness of these claims can save healthcare/insurance providers, huge amount of money as well as improve the turnaround time for claim settlement for consumers.
AI will play a key role here in the future as a lot of work is being done on this in the industry. The intelligent algorithms will help identify fraudulent claims and inform the respected parties about inaccuracies in the claims. AI will help learn from historic cases or data, and improve efficiency to a great extent. First estimates in Germany indicate that health insurers there could save in about EUR 500 million each year through this.
Health insurance players can also use predictive intelligence algorithm to develop personalised outreach mechanism for consumers, across marketing channels.
The writer is MD & CEO, Max Bupa Health Insurance
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