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Designing the Infrastructure for Credit Risk Model Development

About this paper

As more organizations globally realize the value of analytics and credit scoring, there’s growing interest in setting up analytics and modeling disciplines in-house. But to realize expected value, your organization needs a comprehensive plan and long-term vision for analytics and modeling. This paper explores the most common problems organizations face when setting up infrastructure for analytics – and credit risk modeling specifically – and suggests ways to increase productivity and reduce problems through better planning and design. The discussion focuses on building, using and monitoring predictive models, including scorecards. 

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