Remove Examples Remove Financial Services Remove Insurance Remove IoT
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How insurers drive success in the digital transformation race with modern data management

Reltio

The insurance industry is facing unprecedented disruption. Insurance carriers have been called to transform customer experience, business offerings, and operations. As an insurer, your current business models are being challenged by new thinking, new competitors, and new ways of working.

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Conversational AI use cases for enterprises

IBM Big Data Hub

For example, natural language understanding (NLU) focuses on comprehension, enabling systems to grasp the context, sentiment and intent behind user messages. For example, a chat bubble might inquire if a user needs assistance while browsing a brand’s website frequently asked questions (FAQs) section.

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Ransomware Protection in 2021

eSecurity Planet

Screenshot example. Expanding on what a ransomware attack looks like, here is an example of how Locky would appear on your desktop. Healthcare and financial services are the most attacked industries. Increased attacks on individuals with high net value and Internet of Things (IoT) devices ( McAfee ).

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A consumer perspective on FinTech disruption (part 3)

CGI

As FinTech firms aggressively and innovatively push their way into the financial services space, established banks are increasingly focused on effectively responding to the competitive threat. Get deep customer input early and often: Successful FinTechs aren’t just launching new services. Recommendations for banks.

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Best Practices for Building a Data-Driven Business Model

Information Matters

Many of the devices which make up the Internet of Things (IoT) and the apps we use on our phones are throwing off data at increasing speed and volume. This is leading to insurance product offerings being developed for very precise groups rather than the more traditional “one size fits all” approach. New Sources of Data.

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#ModernDataMasters: Sarit Bose, Cognizant

Reltio

There were certain limitations of doing things on an RDBMS and traditional storage – for example being dependent on storage, not being able to get the funds to continuously scale up processing, not being able to incorporate macroeconomic and social factors that impact decisions etc. . People are not going to remember you for that.”.

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#ModernDataMasters: Henrik Liliendahl, Chairman & CTO, Product Data Lake

Reltio

Could you also please share an example of where things have not gone so well and what you learned from the experience? As far as specific examples go, I could share a few stories but it’s probably better if I don’t! We will see scope-creep from IoT into data management – it will have a huge impact.

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