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Perplexing Impacts of AI on The Future Insurance Claims

Smart Data Collective

We previously talked about the benefits of data analytics in the insurance industry. One report found that big data vendors will generate over $2.4 billion from the insurance industry. However, major advances in AI have arguably affected the insurance industry even more. Capturing data from documents.

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Commercial Lines Insurance- the End of the Line for All Data

Cloudera

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.

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Examples of IBM assisting insurance companies in implementing generative AI-based solutions  

IBM Big Data Hub

IBM can help insurance companies insert generative AI into their business processes IBM is one of a few companies globally that can bring together the range of capabilities needed to completely transform the way insurance is marketed, sold, underwritten, serviced and paid for.

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What Are the Industries That Benefit Most from Big Data?

Smart Data Collective

Big Data is more than a trend or a buzzword. In 2020, the size of the global Big Data market reached 56 billion, and it’s on track to exceed 103 billion by 2027. Consumers are generating huge amounts of data at a rapid rate, and it is estimated that up to 90% of all data was generated only in the past two years.

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. A leading insurance player in Japan leverages this technology to infuse AI into their operations.

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The most valuable AI use cases for business

IBM Big Data Hub

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. AIOps is one of the fastest ways to boost ROI from digital transformation investments.

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Create an Apache Hudi-based near-real-time transactional data lake using AWS DMS, Amazon Kinesis, AWS Glue streaming ETL, and data visualization using Amazon QuickSight

AWS Big Data

With the rapid growth of technology, more and more data volume is coming in many different formats—structured, semi-structured, and unstructured. Data analytics on operational data at near-real time is becoming a common need.