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Big Data: Promoting Trust Between Health Insurers and Clients

Posted on the 14 October 2020 by Pacificprime @ThePacificPrime

Big data has been around since 2005 when it was first coined and publicly announced by Roger Mougalas from O'Reilly Media. Its impact today is far-reaching with several industries ranging from manufacturing and retail to healthcare embracing the phenomenon of invaluable raw data.

As for the global health insurance industry, big data has become a cornerstone of the health insurance plan design, human-centric services, tailored-product offerings, and much more.

In this article by Pacific Prime, we look specifically at what big data is, how it can be used by health insurers, and what it can do to promote trust between health insurers and clients.

Big data: Promoting trust between health insurers and clients

What is Big data?

Big data is a phenomenon associated with large amounts of data that come in different forms, at varying levels of accuracy and reliability. They can be unstructured or structured depending on their source. According to cloudmoyo, the bulk of all the data comes from three primary sources:

  1. Social data, which comes directly from the interactions on social platforms like tweets, retweets, likes, comments, video uploads, and general media.
  2. Machine data, which is recognized as information generated by industrial equipment or sensors that are integrated into machines such as satellites, game consoles, smart meters, and anything electronic that measures specific parameters.
  3. Transactional data, which is generated from daily transactions that are recorded both online and offline, such as payment orders, monetary payments between financial institutions, and more.

How health insurance companies use big data

Up until recently, health insurers were unable to interpret the masses of raw data. But as the quality, type, and size of information grew, it soon became apparent that analytical tools were needed to comprehend the data. Some of these analytical technologies include:

    Predictive analytics, which constructs models to forecast client behavior and other future developments relating to the health insurance industry.
    Machine learning or artificial intelligence (AI), which is used extensively especially in the healthcare sector, and has the potential to make simple if not complex decisions. This will be particularly important in preventing fraud and corruption within the insurance industry.
    Deep learning, which is a more advanced branch of machine learning.

Advances in these analytical technologies may allow health insurers to optimize the design of health insurance policies, forecast premiums, improve sustainable reporting (to study the performance and operations of the organization), establish specific tools for loss mitigation, and develop a more robust and clear understanding of factors relating to health insurance.

The main challenge: Building trust between insurers and clients

Trust is what keeps relationships between health insurance companies and clients strong and a lack of it is considered unsustainable for the health insurance industry. For clients to be confident that their needs are being met and information provided is being used securely, health insurers look for ways or channels that promote trust.

Fortunately, big data could improve the understanding of human interactions, and provide opportunities to involve clients in how their personal data should be managed and governed. Health insurers can introduce participatory mechanisms that empower clients in making decisions on how their data are used and so promote trust in the insurer. As well as promote trust, health insurers can use big data analytics to potentially offer better quality, and more personalized products and services that make an impact without losing value.

Global health insurance and technology trends in 2020 and beyond

According to Pacific Prime's 2019-2020 State of Health Insurance Report, 2020 has been a turbulent one as the coronavirus ( COVID-19) pandemic continues to burden countries around the globe, their healthcare systems, and the lives of billions of people. However, as economies slow, big data will continue to proliferate due to:

    The release of high-performance smartphones and tablets, such as the iPhone 12 by Apple Inc., coupled with cloud technology. With 5G connectivity now available on the device, users will be making information transfers faster than ever before.
    The explosion of advanced computers that offer power and substantial storage, enabling the collection and streamlined analysis of vast amounts of data. As technology advances, these devices will be able to produce more data and process them to allow users like health insurers to gain invaluable information about clients, such as behaviors and the probability of claiming.

The future seems bright for big data and health insurance, but to truly promote trust and harness the benefits, the insurer-regulator relationship should grow in tandem and be increasingly participatory and collaborative.

Download the 2019-2020 State of Health Insurance Report

To gain more insight into how big data is affecting health insurance globally and in the region where you are, download the report for free now, or contact us to speak to an advisor who can offer impartial advice across different plans and solutions, including:

Big data: Promoting trust between health insurers and clients

Big data: Promoting trust between health insurers and clients

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