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CIAM in insurance: A unified, secure user experience with a single login

Thales Cloud Protection & Licensing

CIAM in insurance: A unified, secure user experience with a single login madhav Fri, 05/26/2023 - 07:33 In recent years, the insurance industry has transformed from a singularly focused entity to a multi-brand or multi-service type of business. Adding value to the user experience (a top priority for 59% of insurers) 2.

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The risks and limitations of AI in insurance

IBM Big Data Hub

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. One example of this is facial recognition being used for the illegal tracking of people’s movement.

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GUEST ESSAY: How to secure ‘Digital Twins’ to optimize asset use, while reducing exposures

The Last Watchdog

Add in an increasing focus on data becoming a crucial enterprise asset—as well as the introduction of countless database and analytical tools, digital twins, artificial intelligence, and machine learning—and we are dealing with unprecedented technical complexities and risk. Access security challenges. Leveraging digital twins.

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Delivering business value for insurance companies

Collibra

Recapping a discussion moderated by Stijn Christiaens and featuring insurance data experts from Deloitte UK . Insurance is a data-intensive business. Insurance companies need data to better assess risks and price policies competitively, but also profitably. Mobilizing data governance programs.

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Mastering healthcare data governance with data lineage

IBM Big Data Hub

Healthcare organizations need a strong data governance framework to help ensure compliance with regulations like the Health Insurance Portability and Accountability Act of 1996 (HIPAA) in the US and the General Data Protection Regulation (GDPR) in the EU. Inaccuracies might also lead to more delays or complications with insurance coverage.

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Securing AI Deployments: Striking the Balance

OpenText Information Management

If it’s not accurate, accessible, and secure, organizations won’t get the desired results. Since AI relies on data to learn and improve, organizations must ensure their data is accurate, accessible, and secure. Examples include names, mailing addresses, phone numbers, social insurance numbers, and credit card details.

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Threat actors offer for sale data for 50 millions of Moscow drivers

Security Affairs

Alexei Parfentiev, head of the analytics department at SerchInform, confirmed this scenario: “It looks more likely also because the requirements of regulators to such structures as the traffic police, in terms of protection against external attacks, are extremely strict,” he says. ” reads the post published by the Kommersant website.

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