This white paper outlines the necessity for effective and efficient credit risk modeling and decision-making in enhancing customer experience. It discusses the drawbacks of traditional credit risk models, such as long development times, cumbersome processes, high outsourcing costs, incomplete risk views, data management issues, and loss of corporate knowledge. The paper emphasizes the urgency to adopt modern approaches due to competitive pressures from non-bank lenders and the evolving market demands. It introduces four key components of contemporary credit risk modeling: robust data management utilizing both traditional and alternative data, advanced analytics for deeper insights, automated decision-making processes, and an agile, integrated platform for seamless operation.

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