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Is Artificial Intelligence relevant to insurance?

IBM Journey to AI blog

In this first of two posts, I investigate the anatomy of artificial intelligence and its impact on insurance. Continued advancement in AI development has resulted today in a definition of AI which has several categories and characteristics. The early versions of AI were capable of predictive modelling (e.g.,

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The risks and limitations of AI in insurance

IBM Journey to AI blog

In my previous post , I described the different capabilities of both discriminative and generative AI, and sketched a world of opportunities where AI changes the way that insurers and insured would interact. As AI technologies continues to mature and use cases expand, insurers should not shy from the technology.

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Climate change examples

IBM Journey to AI blog

The impacts of climate change may be organized into three categories: Intensifying extreme weather events Changes to natural ecosystems Harm to human health and well-being Extreme weather events While climate change is defined as a shift in long-term weather patterns, its impacts include an increase in the severity of short-term weather events.

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How to build a successful risk mitigation strategy

IBM Journey to AI blog

An organization is always changing and so are business needs; therefore, it’s important that an organization has strong metrics for tracking over time each risk, its category and the corresponding mitigation strategy. An example of this is obtaining an insurance policy to cover property damage or personal injury.

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Feature Store Architecture, the Year of Large Language Models, and the Top Virtual ODSC West 2023…

ODSC - Open Data Science

Implementing Machine Learning for Fraud Detection in Insurance Claims Insurance fraud is rising, costing the industry billions annually. Dan will address the four categories of catastrophic AI risks: malicious use, AI race, organizational risks, and rogue AIs. For each error, we provide examples and solutions to fix them.

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The future of application delivery starts with modernization

IBM Journey to AI blog

My organization is able to develop solutions and capabilities faster.” ” Cost efficiency from the container-based approach, financial organization: “ The main advantage we found is greater infrastructure efficiency by moving the workloads to Liberty.

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Building an End-to-End Machine Learning Project to Reduce Delays in Aggressive Cancer Care.

Towards AI

Gilead Sciences provided a rich, real-world dataset that contains information about demographics, diagnosis and treatment options, and insurance provided to patients who were diagnosed with breast cancer from 2015–2018. You can find the application here and follow through with the discussion.