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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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Document Processing Vs. Robotic Process Automation

AIIM

For many businesses, content and data capture tools are highly sought out, particularly in the banking and insurance sectors. With so many different types of documents required to operate and adhere to compliances, the need for capturing data accurately and quickly, especially unstructured data, is ever growing.

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Document Processing Vs. Robotic Process Automation

AIIM

For many businesses, content and data capture tools are highly sought out, particularly in the banking and insurance sectors. With so many different types of documents required to operate and adhere to compliances, the need for capturing data accurately and quickly, especially unstructured data, is ever growing.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

Cloud 57
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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

In today’s digital age where data stands as a prized asset, generative AI serves as the transformative tool to mine its potential. Businesses globally recognize the power of generative AI and are eager to harness data and AI for unmatched growth, sustainable operations, streamlining and pioneering innovation.

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Developing a data-first mindset in insurance

Information Management Resources

It is a powerful positioning for insurance carriers to view themselves as data companies first, incorporating that information across all facets of the organization.

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The 7 most common data quality issues

Collibra

Data-driven organizations are depending on modern technologies and AI to get the most out of their data assets. But they struggle with data quality issues all the time. Incomplete or inaccurate data, security problems, hidden data – the list is endless. What are the most common data quality issues?

Analytics 110