IBM Big Data Hub
JUNE 26, 2018
In this Q&A, IBM financial services solution architect Irina Saburova discusses an insurance use case with IBM Data Science Marketing Lead Rosie Pongracz.
IBM Big Data Hub
MAY 8, 2023
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. Usage risk—inaccuracy The performance of an AI system heavily depends on the data from which it learns.
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The Guardian Data Protection
NOVEMBER 11, 2023
Observer investigation reveals UK Biobank opened its biomedical database to insurance firms despite pledge it would not do so Sensitive health information donated for medical research by half a million UK citizens has been shared with insurance companies despite a pledge that it would not be. Continue reading.
eSecurity Planet
MAY 27, 2021
The explosion of ransomware and similar cyber incidents along with rising associated costs is convincing a growing number of insurance companies to raise the premiums on their cyber insurance policies or reduce coverage, moves that could further squeeze organizations under siege from hackers. Insurers Assessing Risks.
John Battelle's Searchblog
JANUARY 26, 2015
But earlier this month I met with another perfect exemplar: Metromile , a company that is already upending industrial-age assumptions about what “insurance” should be.**. Metromile began as the brainchild of David Friedberg , co-founder and CEO of yet another information-first insurance breakout, Climate Corp.
Information Management Resources
MARCH 9, 2018
From small, family-run businesses to big banks and insurance companies, jobs refining data and converting it into valuable insights now exist in almost every organization around the globe.
IBM Big Data Hub
FEBRUARY 13, 2024
Key considerations: Tech stack: Ensure your existing technology infrastructure can handle the demands of AI models and data processing. Teamwork: Assemble a team with expertise in AI, data science and your industry. Data: High-quality, relevant data is the fuel that powers generative AI success.
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