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4 strategic sourcing use cases to strengthen your supply chain

IBM Big Data Hub

It also can help optimize transportation costs and service-level agreements as well as improve inventory management and visibility. Sign up for a 30-day free trial here Risk management Supply chains are under tremendous stress, facing challenges from supply, demand, logistics and shifting industry landscapes.

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COVID-19 Effects on Financial Services & Managing Risk

bridgei2i

They will also need recalibrated scorecards post-COVID as the existing models will not hold. They will need to evolve new scorecards considering the pandemic factor for early default detection. AI can assess quantitative data, as well as unstructured data systems, for better risk management of financial and reputational losses.

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Automating Model Risk Compliance: Model Monitoring

DataRobot Blog

Combined, telemetry on accuracy and data drift empowers the modeler to manage model risk for their organization, and thereby minimize the potential adverse impacts of a deployed ML model. While having such telemetry is crucial for sound model risk management principles, it is not, by itself, sufficient. Conclusion.

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