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6 benefits of data lineage for financial services

IBM Big Data Hub

The financial services industry has been in the process of modernizing its data governance for more than a decade. But as we inch closer to global economic downturn, the need for top-notch governance has become increasingly urgent. The post 6 benefits of data lineage for financial services appeared first on IBM Blog.

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Discover a unified approach to adaptive data and analytics governance

Collibra

Nearly 80% of IT decision-makers agree that the collection and analytics of data has the potential to fundamentally change the way their company does business in the next 1 – 3 years. . > See how adaptive data and analytics governance can help. At Collibra, we believe it’s the next big step forward in data governance.

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The importance of data quality in Financial Services

Collibra

Financial services are highly regulated and maintain a strong focus on compliance and risk management. Considering that major financial organizations handle enormous amounts of data today, they require data accuracy and integrity at all times to minimize risks. What is data quality in financial services?

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Capital Markets, AI, and the need for governance

Collibra

With every financial services organization focused on making better and faster decisions, data professional and business leaders are eager to better understand how AI can facilitate their strategic goals. Financial services orgs, especially those in capital markets, frequently has been on the forefront of generative AI investment.

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Summary – “Industry in One: Financial Services”

ARMA International

The scope of a records and information management (RIM) program in financial services can seem overwhelming. Compared to other industries, the complexities of managing records and information in financial services are arguably some of the toughest to solve, primarily because of the intense regulatory scrutiny.

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AI Governance: Break open the black box

IBM Big Data Hub

Customers, employees and shareholders expect organizations to use AI responsibly, and government entities are demanding it. Failure to meet regulations can lead to government intervention in the form of regulatory audits or fines, damage to the organization’s reputation with shareholders and customers, and revenue loss.

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Automated governance and trustworthy AI

IBM Big Data Hub

Governments and regulatory bodies around the world are working to establish safety standards. The proposed rules aim to govern automated valuation models to protect borrowers. As governments recognize and regulate the growing use of AI for crucial decisions, enterprises should prepare proactively. In the U.S.,