Peningkatan Akurasi Pembobotan Attribute Importance Weights pada Deteksi Fraud

Kerugian miliaran dollar setiap tahunnya dialami oleh bank yang disebabkan oleh Fraud. Salah satu solusi untuk mengatasi kasus fraud yang dialami dunia perbankan dapat dilakukan dengan proses deteksi fraud. Pada proses deteksi Fraud, terdapat berbagai atribut PBF (Process Based Fraud) yang setiap atributnya memiliki dampak yang berbeda dalam mendeteksi fraud. Untuk menentukan bobot setiap atribut PBF digunakan metode MDL (Modified Digital Logic). Metode MDL menghasilkan attribute importance weights yang sesuai dengan dampak atribut PBF. Namun peran pakar masih sangat signifikan dalam menilai setiap attribute importance weights. Penelitian ini bertujuan untuk mengubah prosedur penentuan bobot  attribute importance weights dalam metode MDL dengan menambahkan metode Multiple Linear Regression (MLR). Dengan mengganti inputan yang sebelumnya diberikan oleh pakar menjadi perbandingan bobot atribut secara otomatis. Kemudian hasil dari kedua metode dievaluasi menggunakan confusion matrix. Berdasarkan hasil eksperimen, metode MLR menunjukkan persentase klasifikasi menggunakan semua attribute importance weights menunjukkan hasil yang lebih baik dengan akurasi sebesar 99,5%

Methodological contributions for the fightind fraud: A multidisciplinary challenge

State of the art scientific methods can be used against financial fraud, mainly of a technical nature (computer, economic, mathematical). Although some of the scientific areas involved are not related to technology, such as sociology, it is important that all disciplines provide useful tools to detect fraud. The detection and prevention of financial fraud is a multidisciplinary task, so the solution to this urgent problem needs to be provided by multidisciplinary teams

Computational intelligent hybrid model for detecting disruptive trading activity

The term “disruptive trading behaviour” was first proposed by the U.S. Commodity Futures Trading Commission and is now widely used by US and EU regulation (MiFID II) to describe activities that create a misleading appearance of market liquidity or depth or an artificial price movement upward or downward according to their own purposes. Such activities, identified as a new form of financial fraud in EU regulations, damage the proper functioning and integrity of capital markets and are hence extremely harmful. While existing studies have explored this issue, they have, in most cases, either focused on empirical analysis of such cases or proposed detection models based on certain assumptions of the market. Effective methods that can analyse and detect such disruptive activities based on direct studies of trading behaviours have not been studied to date. There exists, accordingly, a knowledge gap in the literature. This paper seeks to address that gap and provides a hybrid model composed of two data-mining-based detection modules that effectively identify disruptive trading behaviours. The hybrid model is designed to work in an on-line scheme. The limit order stream is transformed, calculated and extracted as a feature stream. One detection module, “Single Order Detection,” detects disruptive behaviours by identifying abnormal patterns of every single trading order. Another module, “Order Sequence Detection,” approaches the problem by examining the contextual relationships of a sequence of trading orders using an extended hidden Markov model, which identifies whether sequential changes from the extracted features are manipulative activities (or not). Both models were evaluated using huge volumes of real tick data from the NASDAQ, which demonstrated that both are able to identify a range of disruptive trading behaviours and, furthermore, that they outperform the selected traditional benchmark models. Thus, this hybrid model is shown to make a substantial contribution to the literature on financial market surveillance and to offer a practical and effective approach for the identification of disruptive trading behaviour

SENTIMENT AND BEHAVIORAL ANALYSIS IN EDISCOVERY

A suspect or person-of-interest during legal case review or forensic evidence review can exhibit signs of their individual personality through the digital evidence collected for the case. Such personality traits of interest can be analytically harvested for case investigators or case reviewers. However, manual review of evidence for such flags can take time and contribute to increased costs. This study focuses on certain use-case scenarios of behavior and sentiment analysis as a critical requirement for a legal case’s success. This study aims to quicken the review and analysis phase and offers a software prototype as a proof-of-concept. The study starts with the build and storage of Electronic Stored Information (ESI) datasets for three separate fictitious legal cases using publicly available data such as emails, Facebook posts, tweets, text messages and a few custom MS Word documents. The next step of this study leverages statistical algorithms and automation to propose approaches towards identifying human sentiments, behavior such as, evidence of financial fraud behavior, and evidence of sexual harassment behavior of a suspect or person-of-interest from the case ESI. The last stage of the study automates these approaches via a custom software and presents a user interface for eDiscovery teams and digital forensic investigators

The Impact of Information and Communication Technology on Internal Control’s Prevention and Detection of Fraud

This study explores the Impact of Information and Communication Technology (ICT) on internal control effectiveness in preventing and detecting fraud within the financial sector of a developing economy – Nigeria. Using a triangulation of questionnaire and interview techniques to investigate the internal control activities of Nigerian Internal Auditors in relation to their use of ICT in fraud prevention and detection, the study made use of cross-tabulations, correlation coefficients and one-way ANOVAs for the analysis of quantitative data, while thematic analysis was adopted for the qualitative aspects. The Technology Acceptance Model (TAM) and Omoteso et al.’s Three-Layered Model (TLM) were used to underpin the study in order to provide theoretical considerations of the issues involved. The study’s findings show that Nigerian Internal Auditors are increasingly adopting IT-based tools and techniques in their internal control activities. Secondly, the use of ICT-based tools and techniques in internal control positively impacts on Internal Auditors’ independence and objectivity. Also, the study’s findings indicate that Internal Auditors’ use of ICT-based tools and techniques has the potential of preventing electronic fraud, and such ICT-based tools and techniques are effective in detecting electronic fraud. However, continuous online auditing was found to be effective in preventing fraud, but not suited for fraud detection in financial businesses. This exploratory study sheds light on the impact of ICT usage on internal control’s effectiveness and on internal auditors’ independence. The study contributes to the debate on the significance of ICT adoption in accounting disciplines by identifying perceived benefits, organisational readiness, trust and external pressure as variables that could affect Internal Auditors’ use of ICT. Above all, this research was able to produce a new model: the Technology Effectiveness Planning and Evaluation Model (TEPEM), for the study of ICT adoption in internal control effectiveness for prevention and detection of fraud. As a result of its planning capability for external contingencies, the model is useful for the explanation of studies involving ICT in a unique macro environment of developing economies such as Nigeria, where electricity generation is in short supply and regulatory activities unpredictable. The model proposes that technology effectiveness (in the prevention and the detection of fraud) is a function of TAM variables (such as perceived benefits, organisational readiness, trust, external pressures), contingent factors (size of organisation, set-up and maintenance cost, staff training and infrastructural readiness), and an optimal mix of human and technological capabilitie

Mapping (Dis-)Information Flow about the MH17 Plane Crash

Digital media enables not only fast sharing of information, but also disinformation. One prominent case of an event leading to circulation of disinformation on social media is the MH17 plane crash. Studies analysing the spread of information about this event on Twitter have focused on small, manually annotated datasets, or used proxys for data annotation. In this work, we examine to what extent text classifiers can be used to label data for subsequent content analysis, in particular we focus on predicting pro-Russian and pro-Ukrainian Twitter content related to the MH17 plane crash. Even though we find that a neural classifier improves over a hashtag based baseline, labeling pro-Russian and pro-Ukrainian content with high precision remains a challenging problem. We provide an error analysis underlining the difficulty of the task and identify factors that might help improve classification in future work. Finally, we show how the classifier can facilitate the annotation task for human annotators

Essays on the Rationality of Online Romance Scammers

The rapid development of the internet has served an essential role in providing communication platforms for people to choose to have personal interactions. One manifestation is using social media platforms and dating services to establish social relationships. The use of online platforms has also provided unscrupulous individuals with malicious intent the ability to target vulnerable victims using bogus romantic intent to obtain money from them. This type of newly evolved cybercrime is called an online romance scamming. To date, online romance scams have spread to every part of the world (i.e., mainly in the United States, China, Canada, Australia, and the UK) and caused considerable financial and emotional damage to victims. Prior research on online romance fraudsters provides a preliminary understanding of the operational features (stages and persuasive techniques) and their modus operandi. However, the objectivity and relevance of the victimization data in explaining offenders\u27 behaviors may render those studies may represent significant drawbacks. To overcome the limitations, it is important to use actual offender data to generate meaningful analyses of romance fraudsters\u27 behaviors. Consequently, this dissertation aims to use experimental data similar to that applied in my previous work (Wang et al., 2021), combined with existing criminological and communication theories, to promote a better understanding of romance fraudsters\u27 behaviors in the online world. This dissertation begins with a scoping review of the current online romance scam literature, intending to use a scientific strategy to address the existing scholarly gap in this field of research. Derived from rational choice theory, the criminal events perspective, interpersonal deception theory, and neutralization theory, the second and third paper uses an experimental approach to assess the influence of rewards on romance fraudsters\u27 behaviors. The three papers\u27 results demonstrate the rationality of online romance fraudsters when facing rewards. Moreover, such rationality can be explicitly seen from their uses of different linguistic cues. Finally, the outcomes provided in the current project also provide policymakers the information about the rationality and modus operandi of fraudsters which can be used to identify the behavioral patterns at an early phase to prevent significant harm to the victim

The Impact of the contextual factors on the success of e-government in Lebanon: Context-System Gap

Purpose: The relationship between context and e-governance has been gaining a significant momentum in academic circles due its social and technical complexities. There are many challenges posed by the disparity between the context and the system when it comes to e-governance in developing countries. This research aims to reveal more successful adoption of e-governance initiatives and exposes factors that hinder its implementation. We develop a conceptual framework showing the reciprocity between the context and the system or what is termed “Context-System Gap”. Therefore, this research will study the appropriateness of the context and its influence on the system and the influence of the system on the context. The purpose of this research is to explore the factors that enable successful e-government adoption in Lebanon, where e-governance is still at its initial stage. Most empirical research and theories on the implementation of e-governance in developing countries remain at the macro-level and miss out on the complexities of the context of deployment and the role of the gap between the citizens and the government. The purpose of this thesis is to provide an empirical model differentiating between the electronic context and the electronic system and shed a light over a new gap, government-citizen gap, in the adoption of e-government. Design/methodology/approach: Following previous research on e-government services adoption, this study uses several technology use and acceptance models and literature to examine the elements behind the adoption and use of e-government services in Lebanon from citizen and government perspectives. The research strategy is a quantitative method approach employing questionnaire. Quantitative data will be collected from e-government users (citizens) and statistical tests will be conducted in order to examine the relation between variables. Practical implications: The findings are useful for policy-makers and decision-makers to develop a better understanding of citizens' needs. The proposed model can be used as a guideline for the implementation of e-government services in developing countries. Originality/value: This study is the only one to examine the dimensions influencing citizens’ adoption of e-government technologies in developing countries using a unified model merging context and system elements