Samuel has 14 years of experience and leadership in all SDLC phases. As a member of the SAS Americas Risk Practice he is tasked with requirements, design, development and deployment of enterprise risk management systems and assets that are globally leveraged for customer engagements.
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
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
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
