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The Need For Personalized Data Journeys for Your Data Consumers

DataKitchen

While this is a technically demanding task, the advent of ‘Payload’ Data Journeys (DJs) offers a targeted approach to meet the increasingly specific demands of Data Consumers. Payload DJs facilitate capturing metadata, lineage, and test results at each phase, enhancing tracking efficiency and reducing the risk of data loss.

Insurance 169
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5 Sure-Fire Tips How AI Is Going to Improve Fintech in 2021

Smart Data Collective

AI (Artificial Intelligence) and ML (Machine Learning) will bring improvement in Fintech in 2021 as the accuracy and personalization of payment, lending, and insurance services while also assisting in the discovery of new client pools. Client Risk Profile Categorization. A crucial decision is needed in many financial sectors.

Insurance 137
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Proposals for model vulnerability and security

O'Reilly on Data

Like many others, I’ve known for some time that machine learning models themselves could pose security risks. Forcing your model to make a false prediction for the attacker’s benefit is sometimes called a violation of your model’s “integrity”.) Sometimes also known as an “exploratory integrity” attack.)

Modeling 278
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How Financial Services and Insurance Streamline AI Initiatives with a Hybrid Data Platform

Cloudera

With AI, financial institutions and insurance companies now have the ability to automate or augment complex decision-making processes, deliver highly personalized client experiences, create individualized customer education materials, and match the appropriate financial and investment products to each customer’s needs.

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Back to the Financial Regulatory Future

Cloudera

While there are clear reasons SVB collapsed, which can be reviewed here , my purpose in this post isn’t to rehash the past but to present some of the regulatory and compliance challenges financial (and to some degree insurance) institutions face and how data plays a role in mitigating and managing risk.

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Don’t Fear Artificial Intelligence; Embrace it Through Data Governance

CIO Business Intelligence

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. era is upon us.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

It is frequently used for risk analysis. Factor analysis: Factor analysis is a statistical method for taking a massive data set and reducing it to a smaller, more manageable one. Time series analysis: StatisticsSolutions defines time series analysis as “a statistical technique that deals with time series data, or trend analysis.