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.