Remove Data Quality Remove Insurance Remove Risk
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Solving the Insurance Industry’s Data Quality Problem

Corinium

Unfortunately for the insurance industry’s data leaders, many data sources are riddled with inaccuracies. Data is the lifeblood of the insurance industry.

Insurance 221
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DataOps Risk Insurance & Mission Control

DataKitchen

Chris Bergh shares how to manage data quality and pipeline risk through implementing a 'Mission Control' center for DataOps. The post DataOps Risk Insurance & Mission Control first appeared on DataKitchen.

Insurance 130
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Are enterprises ready to adopt AI at scale?

CIO Business Intelligence

Whether it’s a financial services firm looking to build a personalized virtual assistant or an insurance company in need of ML models capable of identifying potential fraud, artificial intelligence (AI) is primed to transform nearly every industry. But adoption isn’t always straightforward.

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12 Cloud Computing Risks & Challenges Businesses Are Facing In These Days

datapine

Like many other branches of technology, security is a pressing concern in the world of cloud-based computing, as you are unable to see the exact location where your data is stored or being processed. This increases the risks that can arise during the implementation or management process. Cost management and containment. Compliance.

Risk 237
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Unlocking the full potential of enterprise AI

CIO Business Intelligence

Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs. [1] Reliability and security is paramount.

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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. Technological riskdata confidentiality The chief technological risk is the matter of data confidentiality.

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Optimizing Risk and Exposure Management – Roundtable Highlights

Cloudera

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. .

Risk 100