Revolutionising Health Insurance: How Wearables And AI Can Be Used For Tracking Customer Health Behaviour

The healthcare industry is transforming by using cutting-edge technologies, such as wearables and artificial intelligence (AI), to improve patient outcomes and reduce healthcare costs. Health insurance providers are also leveraging these technologies to track customer behaviour and health patterns, leading to personalised insurance policies offering various benefits.

Today, Wearables have become the most common technology used to track customer behaviour, with devices such as smartwatches, wristbands, and smart scales being popular choices. Insurers use a combination of AI and machine learning models to assess and price risk, offering customers a reduction in renewal premiums, cover boosts, and superior products. Customers provide consent for the use of their data, and steps are taken to protect their privacy and security.

Health apps are also popular, offering tracking of activity levels, daily fitness endeavours, and personalized diet and exercise plans, among other features. The latest addition to health apps is Facial Bio Scan, which provides key health vitals through a selfie in just a few seconds.

Insurers can leverage customer data to encourage healthier behaviours and reduce the risk of chronic disease through AI-led premature mortality and chronic disease risk prediction models. These models can be adapted to any disease or population group, with early diagnosis leading to a much higher chance of survival.

AI and machine learning also plays a vital role in the development and implementation of health insurance policies. Customized health insurance plans are designed for individuals based on their historical data and current health conditions, offering a personalized approach instead of a "one size fits all" approach. AI and machine learning are also used to predict and diagnose illnesses, process claims faster, and detect fraud.

Developing fair and unbiased algorithms is crucial to ensure that the customer data used to analyze and assess risk is ethical. Insurers must monitor parameters used in modelling continuously to ensure fair algorithms and provide feedback to teams on how to regulate machine learning models.

Ethical considerations involve informed consent, safety and transparency, algorithmic fairness and biases, and data privacy. Insurers take steps to educate customers about how their data is being used and the potential benefits and risks of sharing this information.

In conclusion, the use of wearables and AI is revolutionizing the healthcare industry, leading to personalized insurance policies that offer a range of benefits to customers. Insurers must continue to take steps to ensure that the algorithms used to analyse customer data are fair and unbiased while educating customers about the benefits and risks of sharing their data.

About Author
Rohit Boda, Managing Director - J.B.Boda Group Founder - RB Ventures & Co-Founder - Alpha Edge Consultan