Detection of fraudulent financial papers by picking a collection of characteristics using optimization algorithms and classification techniques based on squirrels

To produce important investment decisions, investors require financial records and economic information. However, most companies manipulate investors and financial institutions by inflating their financial statements. Fraudulent Financial Activities exist in any monetary or financial transaction scenario, whether physical or electronic. A challenging problem that arises in this domain is the issue that affects and troubles individuals and institutions. This problem has attracted more attention in the field in part owing to the prevalence of financial fraud and the paucity of previous research. For this purpose, in this study, the main approach to solve this problem, an anomaly detection-based approach based on a combination of feature selection based on squirrel optimization pattern and classification methods have been used. The aim is to develop this method to provide a model for detecting anomalies in financial statements using a combination of selected features with the nearest neighbor classifications, neural networks, support vector machine, and Bayesian. Anomaly samples are then analyzed and compared to recommended techniques using assessment criteria. Squirrel optimization's meta-exploratory capability, along with the approach's ability to identify abnormalities in financial data, has been shown to be effective in implementing the suggested strategy. They discovered fake financial statements because of their expertise

Un primer acercamiento a un modelo predictivo ajustable por umbrales para detección de fraudes financieros

El fraude en el sector financiero en transacciones con tarjetas de crédito y débito es un fenómeno que ha recibido el estudio de la comunidad científica por su impacto económico, tanto en individuos como en instituciones. Analizar este problema desde la perspectiva de machine learning es un gran desafío por la poca disponibilidad de transacciones etiquetadas y el desbalanceo en la proporción de clases. En este trabajo exploramos un enfoque alternativo basado en el ajuste del umbral de probabilidad del algoritmo de fraude. A través de experimentaciones mostramos que este abordaje es eficiente y constituye una alternativa válida para detectar fraude de forma efectiva.Sociedad Argentina de Informátic

Exploring the Perceptions of Accountants on Academic Preparations Related to Occupational Fraud and Internal Control Weaknesses

Occupational fraud and internal control material weaknesses (ICMWs) have become global issues due to the strong correlation between internal control (IC) and fraud revelation. However, academic education (AE) has a positive influence on deliberative reasoning and ethical decisions. Nevertheless, little is known of how accountants perceive their AE prepared them to detect fraud and respond to ICMWs. Thus, there is a need to explore how accountants perceive the strengths and weaknesses in their AE regarding fraud and ICMWs. The study contains a comprehensive review of articles published by peer-reviewed journals, particularly in the last five years. The conceptual framework included the Agency Theory, the Fraud Triangle Theory, the COSO Model, and the Experiential Learning Model (ELM). The method of the research is qualitative with exploratory multiple-case study design. A guarantee of data saturation appeared by conducting thirteen semi-structured, face-to-face interviews with accountants who encountered fraud or ICMWs in work environments. The participants were recruited through a combination of purposive snowball sampling and criterion sampling techniques. Data analysis techniques included open coding, axial coding, content analysis, and cross-case synthesis. Also, data was triangulated by corroborating the findings with evidence from other sources. There are twenty-eight minor themes under eight main themes. Six unique sub-minor themes provided profound findings regarding: (a) educational topics related to anti-fraud, (b) educational methods associated with anti-fraud, (c) educational topics related to IC, (d) educational methods related to IC, and (d) competencies of accounting students (Ass) related to fraud and ICMWs