Measuring effectiveness in international financial crime prevention: Can we agree on a performance metric?

The attempts at carrying out terrorist attacks have become more prevalent. As a result, an increasing number of countries have become particularly vigilant against the means by which terrorists raise funds to finance their draconian acts against human life and property. Among the many counter-terrorism agencies in operation, governments have set up financial intelligence units (FIUs) within their borders for the purpose of tracking down terrorists’ funds. By investigating reported suspicious transactions, FIUs attempt to weed out financial criminals who use these illegal funds to finance terrorist activity. The prominent role played by FIUs means that their performance is always under the spotlight. By interviewing experts and conducting surveys of those associated with the fight against financial crime, this study investigated perceptions of FIU performance on a comparative basis between American and non-American FIUs. The target group of experts included financial institution personnel, civilian agents, law enforcement personnel, academicians, and consultants. Questions for the interview and surveys were based on the Kaplan and Norton’s Balanced Scorecard (BSC) methodology. One of the objectives of this study was to help determine the suitability of the BSC to this arena. While FIUs in this study have concentrated on performance by measuring outputs such as the number of suspicious transaction reports investigated, this study calls for a focus on outcomes involving all the parties responsible for financial criminal investigations. It is only through such an integrated approach that these various entities will be able to improve performance in solving financial crime. Experts in financial intelligence strongly believed that the quality and timeliness of intelligence was more important than keeping track of the number of suspicious transaction reports. Finally, this study concluded that the BSC could be appropriately applied to the arena of financial crime prevention even though the emphasis is markedly different from that in the private sector. While priority in the private sector is given to financial outcomes, in this arena employee growth and internal processes were perceived as most important in achieving a satisfactory outcome.

Improving novice analyst performance in modeling the sequence diagram in systems analysis: A cognitive complexity approach

The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.

Improving Novice Analyst Performance in Modeling the Sequence Diagram in Systems Analysis: A Cognitive Complexity Approach

The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.