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The insurance industry has a long and intimate relationship with fraud in many different ways. Insurance fraud can take place at a process or business function level, most notably in claims or underwriting. The different venues to commit fraud against an insurer are mind-boggling, with serious financial consequences.
I’ve had the pleasure to participate in a few Commercial Lines insurance industry events recently and as a prior Commercial Lines insurer myself, I am thrilled with the progress the industry is making using data and analytics. Another historic example is crop and livestock insurance in Germany in the 1700s.
Insurers are increasingly adopting data from smart devices and related technologies to support and service their customers better. I have been researching more about how we can use the new data from those devices to design more innovative insurance products while being aware that these should all be contingent upon customer opt-in.
By using Cloudera’s big data platform to harness IoT data in real-time to drive predictive maintenance and improve operational efficiency, the company has realized about US$25 million annually in new profit resulting from better efficiency of working sites. . Dataenables Innovation & Agility. Risk Management.
While there are clear reasons SVB collapsed, which can be reviewed here , my purpose in this post isn’t to rehash the past but to present some of the regulatory and compliance challenges financial (and to some degree insurance) institutions face and how data plays a role in mitigating and managing risk.
The patients who were lying down were much more likely to be seriously ill, so the algorithm learned to identify COVID risk based on the position of the person in the scan. A similar example includes an algorithm trained with a data set that included scans of the chests of healthy children.
Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process.
Healthcare data governance plays a pivotal role in ensuring the secure handling of patient data while complying with stringent regulations. The implementation of robust healthcare data management strategies is imperative to mitigate the risks associated with data breaches and non-compliance.
As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Would really like to explore this one in debate.
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