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Lessons from Retail Banking on Data Solutions for Structuring Insurance Data – with Ermir Qeli of Swiss Re

Like much of the financial services space broadly, the insurance industry is growing interested in adopting AI. The technology holds immense potential to revolutionize insurance, enhancing efficiency and accuracy across various processes such as claims and underwriting. However, concerns surrounding data privacy and integration complexities have prompted a measured approach among industry leaders.

AI at Nationwide

Artificial Intelligence at Nationwide Insurance- Two Use Cases

Nationwide Mutual Insurance Company, commonly known as Nationwide, is a primary US insurance and financial services company headquartered in Columbus, Ohio.

Cultivating ‘Value Driven Data’ in Insurance-1-min

Cultivating ‘Value Driven Data’ in Insurance – with Edosa Odaro of Tawuniya

Business processes are defined in large part by the data within an organization. Value-driven data, by definition, represents higher-quality data. The importance of high-quality data cannot be overlooked. Research from MIT, even from before the pandemic AI boom, showed that insufficient data can cost as much as 25% of the revenue for most companies.

Driving AI Adoption
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Driving AI Adoption in Insurance – with Ryann Foelker of American Family Insurance Group

As a rule, AI adoption tends to take more time for legacy industries compared to digitally-native sectors. As a profile from June 2021 in Harvard Business Review explains, insurance companies are data-rich but have long relied on actuarial approaches to data and analytics.  The insurance industry has several concerns regarding the integration of AI. Insurance companies obviously have regulatory compliance as a top priority, so any AI solution implemented needs to comply with existing regulations regarding consumer protection and data security, among others. 

Easing Patient Pain Points Between Healthcare and Insurance Workflows – v.3-1-min

Easing Patient Pain Points Between Healthcare and Insurance Workflows – with Tom Hayes and Gareth Dabbs of IQVIA

The applications of AI in the healthcare and life sciences industries are vast, with data-powered algorithms and analytics promising to upend the status quo. Applications, including the use of AI to interpret medical imaging, optimize drug discovery and development, analyze large-scale data sets to identify patterns among patient populations, and streamline provider workflows, are already transforming the industry. 

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