Using big data to enhance and protect lives

The benefits and challenges of using big data in heath insurance

Big data analytics bring new insight, knowledge and opportunities especially to areas in insurance that were previously difficult to explore.

The analytics can impact all parts of the insurance value chain. From marketing and sales analytics that focus on customer acquisition through to the more operational analytics covering underwriting, claims management and customer service.

One difference in health insurance is the personal nature of the analytics and the opportunities that this brings. A better understanding of the underlying patterns and associations in the data offers an opportunity to improve care and people’s health.

For example, advanced analytics can be used to profile patients and actively identify individuals that might benefit from preventative care or lifestyle changes. Similarly it is possible to analyse a patient’s characteristics and the cost and outcomes of care to identify the most cost and clinically effective treatments, thereby influencing provider behaviour.

Advances in big data and technology have made it possible to combine various health and lifestyle data sources to create a more holistic view of a person’s health. These advances are utilised by Vitality to enhance and protect lives.

Shared value

Vitality ties its analytics with a shared value approach that focuses on creating a win-win situation for the company, its customers and society as a whole. The approach is based on principles of behavioural economics; clinical, actuarial and lifestyle data, and integration with technology. Vitality Healthy Rewards is dynamic and actively works with members to enhance the quality of their lives. It is also a socially-advanced model where actuarial surplus resulting from healthier lives is reinvested to the benefit of the customer and the insurer.

Benefit for the customer

Taking a big data approach to health insurance offers specific benefits for customers. The main advantage is that data can help them understand their health better and also make monitoring and improving health much easier. For example, after completing a health review, a personalised health pathway and health goals are determined. Progress towards these goals is then tracked and incentives used to nudge positive behavioural change.

Vitality age

To help customers understand their own health, a measure called Vitality Age is used. Vitality Age gives a snapshot of someone’s overall health based on lifestyle choices including diet and exercise habits and clinical factors such as cholesterol and blood pressure. The measure specifically takes into account how these lifestyle choices and factors impact on life expectancy. For example, a 45-year-old male with a poor diet, high BMI and low levels of physical activity might ha ve a higher Vitality Age of say 51.

Once an individual has their Vitality age determined, personalised health goals such as exercise targets can be set and the health impact of achieving these goals illustrated. Personalised rewards and incentives then play a vital role in helping individuals achieve these goals.

All of this is facilitated by big data and ultimately benefits the customer through improved health and reduced medical and healthcare costs.

Benefits for the insurer

The big data driven approach also has a number of benefits for the insurer. Helping customers lead healthier lives lowers the incidence and cost of claims.

Furthermore, rewarding healthy behaviour resonates with healthier individuals and drives positive selection. This is in contrast to traditional insurance that often suffers from negative selection, i.e. the product is taken out by people who are more likely to claim.

Another advantage of the big data approach is that it brings the insurer in closer and more frequent contact with the customer. Most insurance companies typically only interact with their customers at renewal or when a claim occurs. This more interactive and personalised approach with customers provides a better customer experience resulting in lower lapse rates.

Challenges of using big data: Privacy

Data protection is a key consideration in health insurance given the sensitive nature of the data. Vitality respects the privacy of personal health data and adopts all measures to protect and secure the data using sophisticated technology. Personal data is also anonymised for analytical purposes.

Using data from multiple sources

One of the challenges of working with big data is managing the quality and variety of the information from different sources. For example, historical data often comes from legacy systems that might have recorded information in different formats or inconsistent ways. Even modern data, for example from tracking devices, can provide challenges because of different readings for similar activities.

A lot of work is often required to ensure data quality before getting the most value out of big data.


Even though there are some challenges in getting the most out of big data, the benefits it brings far outweighs the costs. Big data is helping businesses in every industry become more efficient and productive. In health insurance it can play a significant role in improving customer’s health and in the process creating shared value to the customer, insurer and wider society.

Pierre du Toit is head of big data analytics at Vitality (UK). The views expressed in this article are the author’s own.

Photo credits:
By Suronjitkumar (Own work), By 73.santi (Own work) [Public domain], By Ruslan Kalendar (Own work)