International Journal of Information Management 26 (2006) 81–88 Case study Improving debt collection processes using rule-based decision engines: A case study of Capital One Amita Goyal Chin à , Hiren Kotak Virginia Commonwealth University, USA Abstract This case assesses the plethora of issues related to rule-based decision engine technology, and in particular, its role in complex and dynamic organizational processes. This paper argues rule-based engines can effectively be implemented for good organizational decision making, even in environments consisting of large volumes of volatile data. Further, this case argues for the necessity of the successful integration of such rule-based technology for effectual management, improved information quality and superior decision making. This argument is conducted by analyzing the pre and post implementation situation at Capital One, a leading credit card and financial services company which has successfully implemented a large-scale rule-based decision engine system, as a component of its core debt collections processes, to achieve a hallmark competitive edge. r 2005 Elsevier Ltd. All rights reserved. Keywords: Rule-based decision; Rule-based engine; Debt collection; Capital One; Project Edison 1. Introduction We have been witnessing an ever-increasing trend of organizations storing enormous quantities of volatile data and needing to intelligently analyze that data using enterprise knowledge and rules. A rule is ‘‘[a] formal and implementable expression of some user requirement’’ (eForce, 2005). A rule may also be thought of as ‘‘[a] statement that defines or constrains some aspect of the business which is intended to assert business structure or to control or influence the behaviour of the business’’ (eForce, 2005). While numerous business rules are transcribed in operating and procedure manuals, many business rules remain unspoken, unclear, and undocumented, yet are crucial to the successful workings of the business. Capturing and incorporating all of these written and unwritten rules, together with enterprise data and processes (Charfi & Mezini, 2004), into organizational information systems, especially those housing enormous volumes of dynamic data, has proven vitally important. Rule-based decision engine technology allows organizations to specify and manage business rules, and to sift through reams of data and easily highlight the extreme or outlier cases. ‘‘Rule engines are used when you need to work with large sets of rapidly changing data in ways that would be too complex or cost-prohibitive to do manually,’’ and are ‘‘usually designed to allow a constant and flexible addition of rules and data, to centralize rules and make them easy to manage, and to reduce the difficulty of modelling extremely complex ARTICLE IN PRESS www.elsevier.com/locate/ijinfomgt 0268-4012/$ - see front matter r 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijinfomgt.2005.10.002 à Corresponding author. Tel.: +1 804 828 7131; fax: +1 804 828 3199. E-mail addresses: amita@saturn.vcu.edu (A.G. Chin), hiren.kotak@capitalone.com (H. Kotak).