Digital health – for insurers “the digital transformation”, the “oil of the 21st century” – has been a hot topic for almost a decade now. So have digital opportunities now been fully embraced and a tidal wave of health data leveraged to the benefit of individual/insureds, healthcare systems and Life & Health insurers?
With an estimated 90% of the world’s data collected in the last two years, digital strategies are evolving rapidly. But how do we make business decisions with all the data that is available? What does it mean for underwriting?
Here is an inside look on how life insurance solution providers adapted and innovated to these new challenges in 2020.
How insurers use big data and artificial intelligence to support their claims and underwriting strategies is likely to accelerate as a result of the Covid-19 pandemic.
Dr. Tom Fletcher, VP Data Analytics, North America Life, shares his perspective on the component strands necessary to build and maintain ethical standards in predictive modeling.
The center questions the use of factors such as employment class and education level in marketing, underwriting and pricing.
Munich Re assessed the effectiveness of Milliman Irix® Risk Score 2.2 in stratifying the mortality for the U.S. insurance applicant population.
This two-part article aims to review some of the important concepts and considerations for insurers wishing to use data and technology to become a partner rather than just a payer for their policyholders. These include ethical considerations, understanding exactly what data is, the implications of data misuse and of ethical intelligent data use, and the importance of integrating data from various sources, ultimately enabling us to grasp the true potential of data.
This two-part article aims to review some of the important concepts and considerations for insurers wishing to use data and technology to become a partner rather than just a payer for their policyholders. These include ethical considerations, understanding exactly what data is, the implications of data misuse and of ethical intelligent data use, and the importance of integrating data from various sources, ultimately enabling us to grasp the true potential of data.
 |
 |
 |
 |
 |
 |