Knowledge-based Exception Handling in Securities Transactions* Minhong Wang, Huaiqing Wang, Kwok Kit Wan and Dongming Xu Department of Information Systems, City University of Hong Kong, Hong Kong {iswmh, iswang, iskk, isxu}@cityu.edu.hk Abstract * With rising trading volumes and increasing risks in securities transactions, the securities industry is making an effort to achieve straight through processing to shorten the trade lifecycle and minimize transaction risk. While attempting to shorten the settlement cycle, the trade information must be passed within the trade lifecycle in a timely and accurate fashion. Exception handling is critical to make sure trades that give rise to exceptions or trades containing errors need to be detected and reconciled in compressed timescales. In order for a knowledge level solution for exception handling, the technology of intelligent agents is applied in this research. Intelligent agents with their knowledge base and properties of autonomy, activity and pro- activity are well suited for business exception handling. Based on analysis on exceptions occurred in securities transactions and process of exception reconciliation, several types of intelligent agents are proposed and a multi-agent framework is presented for exception handling in securities trading. Furthermore, business knowledge such as business rules and strategies are extracted from securities trading and settlement practice, and applied to the design of individual agents to make them act autonomously and collaboratively to fulfil the goal of exception reconciliation. By separating business logic from business model, such business rules approach can enhance the flexibility and adaptability of our agent-based exception handling system. 1. Introduction In today’s fast moving market the financial institutions are facing what many consider being its great challenge - the planned transition to shortened settlement cycle and much-desired capability for Straight Through Processing (STP) of securities trades [1]. However, the prospect of a compressed settlement cycle also has a fundamental impact on * This research is supported by a Strategic Research Grant (7001309) from City University of Hong Kong. operations risk management. This has led to some considerable attention not merely on the processing of fully automated trade and settlement cycle, but also on the automation of all processes required for identifying and fixing any exceptions reported in the cycle [2]. It requires participants to enable an exception-based process to achieve some level of STP, which embodies early identification of errors for timely resolution. Efforts are attempted to make in some STP systems to deliver operations risk management and competitive advantages as they seek to achieve shortened settlement cycle. However, the major issue of such risk management has not been adequately addressed, and the mechanism of automating exception handling is still under investigation. In this paper we focus on exception handling in securities transactions, which aims to automate the identification and resolution of exceptions to assist securities industry to gain quicker competitive advantage. With a view to providing a knowledge- based solution for exception handling in securities trading, we propose to apply the technology of intelligent agents to deal with the representative abnormal transactions throughout the trade lifecycle. Given specific knowledge and capabilities, intelligent agents are capable of dealing with complex problems and vast amounts of information collaboratively in dynamic and unpredictable environment. Moreover, based on previous research and experimental results, some properties of intelligent agents, such as reactive and proactive behaviors, are directly applicable for tracking abnormal transactions in a systematic and goal-driven manner [3, 4, 5]. After the analysis on possible exceptions in securities transactions and resolution to such problems, a society of intelligent agent is proposed for the STP environment. Data acquisition agents are responsible for collecting data of securities transactions. Based on such data, monitoring agents may keep track on the transaction processes. When an exception is detected, a diagnostic agent will be initiated and attempt to identify the problems. According to the output from the diagnostic agent, a resolution agent will take some initiatives to resolve problems. In order for a Proceedings of the 37th Hawaii International Conference on System Sciences - 2004 0-7695-2056-1/04 $17.00 (C) 2004 IEEE 1