Data quality and data architecture are now recognized in insurance and most other industries as the fuel needed to meet our biggest challenges. Building the digital core of any organization only works when you have the data quality to act on it.
In this issue of Insurance News Analysis, Abbey Compton and I talk about how insurance companies use data to adapt to the changing risk landscape. At Davos, there was a lot of discussion about phasing out investments and emission guarantees in both the coal industry meet the net zero targets and to prevent premiums from rising. Because insurance companies are considering taking out alternatives for clean energy, they will not have the same actuarial data or loss history that they have long used for fossil fuel companies.
As heat-related illnesses and deaths rising with global temperatures, we see community-based organizations popping up to collect data at hot spots where the risk of illness and injury can be unusually high. Insurance companies across the spectrum of Life, Workers Comp, and Group & Voluntary Benefits can look at these public-private partnerships to help clients mitigate and manage heat-related risks.
In my previous blog I described three levels of insurance industry data analysis. A new survey of European insurers shows that 80% of those who use predictive analytics report positive business effects. But they also say they are struggling with internal facilities that are stretched past large amounts of data. This is also a challenge for the workforce, as insurance companies are looking for the type of talent needed to perform data analysis work.
We also discuss skills required for protection against cybercrime and how it is progressing VR insurance simulations can play an increasingly important role in talent development as the metaverse expands.
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Disclaimer: This content is provided for general information purposes only and is not intended to be used in consultation with our professional advisors.
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