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Data Management
Sam Munoz 0
Series: BCBS 239 - Principle 4

Principle 4: Completeness – A bank should be able to capture and aggregate all material risk data across the banking group. Data should be available by business line, legal entity, asset type, industry, region and other groupings, as relevant for the risk in question, that permit identifying and reporting risk

Analytics
Leo Sadovy 2
Agility and the Analytic Sandbox

Analytics gives us not just the ability but the imperative to separate our planning activities into two distinct segments – detailed planning that leads to budgets in support of execution, and high-level, analytic-enabled business/scenario planning. My critique of Control Towers in this blog last time led me not only to

Data Management
Sam Munoz 0
Series: BCBS 239 – Principle 3

Principle 3: Accuracy and Integrity – A bank should be able to generate accurate and reliable risk data to meet normal and stress/crisis reporting accuracy requirements. Data should be aggregated on a largely automated basis so as to minimize the probability of errors. It seems logical that banks would want

Data Management
Sam Munoz 0
Series: BCBS 239 - Principle 2

Principle 2: Data architecture and IT infrastructure – A bank should design, build and maintain data architecture and IT infrastructure which fully supports its risk data aggregation capabilities and risk reporting practices not only in normal times but also during times of stress or crisis, while still meeting the other

Data Management
Brooke Upton 0
Series: BCBS 239 - Principle 1

Principle 1: Governance – A bank’s risk data aggregation capabilities and risk reporting practices should be subject to strong governance arrangements consistent with other principles and guidance established by the Basel Committee. My colleagues and I have written a series of posts on the principles of BCBS 239. In this

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