论文标题
FICO信用评分问题的二次编程解决方案
A Quadratic Programming Solution to the FICO Credit Scoring Problem
论文作者
论文摘要
经过数十年的发展信用评分经验，FICO公司已经提出了FICO信用评分问题，如下所示：找到具有组件步骤功能的广义加性模型（GAM），从而最大程度地提高了差异（可容纳，可容纳性，解释性，法律，解释性）约束。桩约束也称为形状约束，满足它们称为得分工程。在2003年之前，FICO使用基于线性编程的算法大致解决了FICO信用评分问题。在本文中，我为FICO信用评分问题提供了精确的解决方案。找到确切的解决方案已经避开了FICO多年。差异是得分权重的二次函数的比率。我表明最大差异问题可以转变为二次程序。二次编程公式使人们可以很容易地处理桩约束。 FICO目前使用该技术的各个方面来开发著名的FICO信用评分。
After decades of experience in developing credit scores, the FICO corporation has formulated the FICO Credit Scoring Problem as follows: Find the Generalized Additive Model (GAM), with component step functions, that maximizes divergence subject to the PILE (Palatability, Interpretability, Legal, Explain-ability) constraints. The PILE constraints are also called shape constraints, and satisfying them is called score engineering. Before 2003, FICO used an algorithm, based on Linear Programing, to approximately solve the FICO Credit Scoring Problem. In this paper, I develop an exact solution to the FICO Credit Scoring Problem. Finding the exact solution has eluded FICO for years. Divergence is a ratio of quadratic functions of the score weights. I show that the max divergence problem can be transformed into a quadratic program. The quadratic programming formulation allows one to handle the PILE constraints very easily. FICO currently uses aspects of this technology to develop the famous FICO Credit Score.
