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What is Model Risk and Why Does it Matter?

DataRobot Blog

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses.

Risk 111
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Financial services firms turn to automated, data-driven processes for new products and services

CIO Business Intelligence

Transitioning to automated, data-driven processes is the best way for these companies to not only cope with change but also take advantage of it. Consumer banks can use digital interactions to gather more customer data and apply real-time analytics to expand services and speed up processes.

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How to implement zero trust device security

CIO Business Intelligence

The added demand for remote access to corporate applications driven by business continuity, customer reach, and newfound employee satisfaction comes with a heightened concern over data security. Zero Trust principles are aimed at improving cybersecurity and have been mandated in the federal arena since 2022.

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Understanding New Data-Driven Methodologies In Software Development

Smart Data Collective

Big data has turned the software industry on its head. The relationship between software development and big data is a two-way street. While many software developers are looking to create new applications that use big data, they are also using big data to streamline development.

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Selling the C-suite on preemptive IT investments

CIO Business Intelligence

Others include preparation for zero-day attacks, almost anything having to do with data stewardship, as well as IT training and social engineering audits. When this happens, corporate risk is heightened as preemptive projects get delayed — sometimes for indefinite periods of time. The average cost of a data breach is $4.64

ROI 117
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Generative AI’s potential as a force multiplier in defense

CIO Business Intelligence

First, there is the need to properly handle the critical data that fuels defense decisions and enables data-driven generative AI. Organizations need novel storage capabilities to handle the massive, real-time, unstructured data required to build, train and use generative AI. billion by 2032.

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The Future of RegTech for AI Governance

IBM Big Data Hub

The adoption of AI is driven by its utility and the improvements in efficiency it creates. Beyond these common uses of AI, there are also uses that regulators are beginning to identify as areas where there may be a higher risk. The use of artificial intelligence (AI) is now commonplace throughout society.

Risk 98