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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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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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5 misconceptions about cloud data warehouses

IBM Big Data Hub

Organizations looking to increase adoption of ML are turning to cloud data warehouses that support new, open data formats to catalog, ingest, and query unstructured data types.

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How generative AI delivers value to insurance companies and their customers

IBM Big Data Hub

Insurers struggle to manage profitability while trying to grow their businesses and retain clients. Large, well-established insurance companies have a reputation of being very conservative in their decision making, and they have been slow to adopt new technologies.

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4 ways insurers can improve data veracity

Information Management Resources

Managing this crucial component of data management will help carriers get better results from their analytics, AI and blockchain initiatives.

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Data governance use cases – 3 ways to implement

Collibra

Data lake management: Prevent a data swamp. A data lake is a storage repository that holds a vast amount of raw data in its native format, including structured, semi-structured and unstructured data. The data structure and requirements are not defined until the data is needed.