James Dzierzanowski and Susan Lawson
This chapter describes the development and deployment of the credit assistant (CA), a knowledge-based system to support credit operations for Travel-Related Services (TRS) of the American Express Company. ca was developed using art-im, a rule-based programming environment from Inference Corporation. American Express developed this application under a unix environment (sun and rs/6000) and deployed it into a high-volume real-time mainframe environment. ca was designed to be fully cooperative across business operation units with the authorizer’s assistant (aa) and other knowledge-based systems currently under development. ca also reflects advances in technology and general trends in the AI industry that have taken place since aa was implemented in 1989. This chapter also introduces the knowledge highway concept, the design and construction of a series of cooperative knowledge-based systems to support a global operational strategy of authorizations, credit operations, fraud detection, new account processing, and customer service at American Express. CA was designed to support online credit analysis of card members within the credit operations environment of American Express and to synergistically interact with aa (Dzierzanowski et al. 1989). Credit Operations reviews accounts for the Personal, Gold, Platinum, and OPTIMA card products for credit risk and potential fraud situations. The review process is driven by internal American Express risk management statistical models, which set up risky accounts to be reviewed by analysts. Accounts in question could be set up for many reasons, for example, those showing a delinquency or a history of past due balances. When an account is queued to an analyst for inspection, ca is invoked to support the review by denoting interesting features on the card member’s account and recommending actions. Previous to the implementation of ca, a case required, on the average, 22 transactions to achieve resolution. With ca, one transaction can review data, synthesize information, annotate an account, and provide advice and recommendations to a credit analyst. Advice ranges from setting the account up to be reviewed again in several weeks to recommending the cancellation of a card in serious situations. To support continuous training, scripts are also generated if interaction with the card member occurs. In addition, ca ensures that credit policies are consistently enforced. For example, state laws vary on permissible collection activities. Collection procedures allowed in Minnesota might be illegal in Maine. ca takes all the different statutes into account and guarantees that the analyst is in compliance. As scheduled enhancements are rolled out, the system autonomously makes decisions on some cases, composes letters to card members, orders additional information when necessary, and routes accounts into queues for specific actions by analysts. Designed as components in the knowledge highway of cooperative expert systems, ca and aa have been built for compatibility and allow for the real-time exchange of data. Results from one system can be incorporated into the decision process of the other. aa is part of American Express’s front line of service in credit authorization at a point of sale. It interfaces with the TRS credit authorization system (cas), which is based on a transaction-processing facility-based system built for high volume and transaction rates. aa handles transactions referred by cas. Those charges that are not resolved by aa automatically are then sent to an authorizer with supporting advice and recommendations, thus serving as a decision support tool.