Smart wearables & your Insurance Premiums

This article is the second installment of my previous article which covers the revolution that AI & ML will bring into healthcare. If you haven’t read it, I urge you to go through it to figure out the possibilities.

You and I are aware of the term “Insurance” and how useful it is to have one. There are many types of insurance available in the market which cater to different populations. Each insurance policy is designed for a particular group of people and the policy premium is usually calculated considering the risk that the policy covers. Currently, the software, programs, and models use to calculate this premium lack the power of dynamic pricing.

You can go to any website and you would note that once you enter some basic parameters about yourself, the premium would be shown to you. If someone enters those same parameters again, they will see the same premium. What the website lacks is “How do you verify if those parameters are correct?

The entire world is moving to a personalized experience and the Insurance Industry is not planning to be left behind. The next revolution that they want to ride is with smart wearables.

Understanding Insurance

Insurance is a contract in which one party receives financial protection against any losses. There are multiple types of Insurances, such as, Car Insurance, Home Insurance, Health & Term Insurance, Critical illness Insurance, etc.

If Person A obtains a contract from a Company B and is insured for health. Company B is liable to pay Person A in an event of illness (as long as the illness is covered in the issued contract). But to obtain this contract, Person A needs to pay a premium to Company B in the starting of contract. This premium is usually a fraction of overall price that the Person A will get when he gets ill.

The person enjoys the benefit of being financially covered if he falls ill and the company enjoys the benefit of retaining the sum if the person doesn’t fall ill.

Prevalent Issues in the existing system

Since a company can only benefit if a lot of its subscribers don’t use the service, otherwise they would go bankrupt. Thus, the premium is calculated based on associated risks. The risks are calculated by health check-ups, undertakings, and medical history that the patient fills during buying insurance.

This system has flaws such as:

  1. The person can lie during buying Insurance
  2. Health is a dynamic parameter and it will change on basis of individual actions that the company doesn't know

Introduction of Smart wearables in the Insurance Industry

While the majority of the public is leaning towards smart wearables as a fashion statement, the Insurance industry wants to capture this tide.

Smart wearables include a range of wearable items such as watches, bands, clothes, helmets, glasses, etc. At the same time, other devices which enable recording of user health and biological parameters can be integrated to collect all sorts of data regularly. This data can help identify how the public is evolving.

While You and I are fascinated by the number of steps that we are walking in a day, your health insurer wants to use it to identify if it will result in effective diabetic control. Also, the person who is active is less likely to develop obesity and less likely to require treatment in the near future.

What types of data are being collected?

Currently, the smart wearable industry has devices capable of monitoring the SpO2, Blood pressure, heartbeat rate, activity levels, sudden accidents, sleep cycles, etc.

More research is going on to design devices that monitor and analyze your sweat (chemical sensors), blood concentration, eye movements, body movements, stress, micro-movements, etc.

How the data will be Used?

The overall aim is to develop a biological profile of any individual and use artificial intelligence and machine learning to predict if they are going to fall ill or require medical assistance in near future. The monitored data would be stored on an encrypted server where it will be used to design risk models.

The risk models would be developed on basis of geography and family history. It will help the Insurance providers in two ways. First, it will be easy to identify the risk associated when issuing insurance. Second, it will help them devise customized plans in association with medical check-up teams and hospitals to generate a smooth revenue stream.

Designing Personalised Insurances

Person A has high activity level, high traveling activity (Car & Plane — Intercity travel). Another Person B has a desk job with low activity level and low traveling activity. The insurance companies can use analytics to identify that Person A would be more healthy but have more risk of getting into accidents. While Person B would fall ill in coming times due to less activity but is less prone to accidents as compared to Person A.

Earlier, it was not possible to track the individual so accurately but the smart wearables and IoT integrated medical devices offer this function.

Both Individuals would be provided with different options. Thus, while the health insurance premium for Person A would be less than that of Person B, his term insurance premium would be higher than that of Person B.

Designing strategies suiting for a particular region

The power of AI and ML is best exploited when there is enough data to support the analysis. If the number of users is increased and the analysis is carried out on the entire region, the company can make good decisions.

The insurer can identify what kind of services the customers require and thus accordingly collaborate with those service providers. Knowing what is driving sales, would enable the insurance providers to target money only on effective collaborations and thus save money that would have gone on unnecessary services.

E.g. If the majority of customers are traveling to Area 1 daily and the number of customers in Area 1 is negligible, the company can still invest to collaborate with hospitals working in this Area 1 to increase its goodwill.

E.g. If the majority of people are diagnosed with Malaria. The insurance provider can collaborate with a medical facility that tests and provides treatment of Malaria. It will increase the penetration of services, enhance goodwill and also save money that the company would have spent without any collaboration.

What’s happening right now?

All the above details are currently being experimented with, along with a lot of other things. Since the entire data collection, analysis, and preventive health diagnostic services are still at a nascent stage, the number of players active in the domain is less.

There are multiple start-ups in the domain that are working on some of these parameters. Some are using the data to connect people to hospitals and others are enabling insurance providers to make decisions.

In the future, it wouldn’t be any surprise if you see any health insurer collaborated with Apple (due to data collected by Apple watch) and a hospital chain. They would have more chances of adding consumers and would have a higher profit margin.

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