List of Articles fraud detection

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  1 - Comparison of three different methods for detection of corn and sunflower oils in adulterated sesame oil
  Peyman Mahasti Shotorbani Hassan Hamedi Melika Zandi Maryam Fahimdanesh
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  2 - Employing unsupervised learning to detect fraudulent claims in auto insurance (isolation forest)
  farbod khanizadeh Farzan Khamesian Maryam Esna-Ashari
  10.30495/jma.2022.20585
  For insurance companies, fraud detection strategies are of significant importance. Lack of such a plan to prevent insurance fraud and making payments quickly to insured in order to compensate for losses will lead to customer satisfaction and increase companies’ po More

  For insurance companies, fraud detection strategies are of significant importance. Lack of such a plan to prevent insurance fraud and making payments quickly to insured in order to compensate for losses will lead to customer satisfaction and increase companies’ portfolio in short term. However in the long run, it will have dire consequences for the insurance industry. In other words, the cost of fraudulent claims would be transferred indirectly to insured in the form of a rise in premiums. The purpose of this study is to provide insurers with a mechanism to detect fraudulent claims. This goal is achieved through an unsupervised algorithm to detect anomalies in the data set. The use of this algorithm, as it is an ensemble learning, increases the accuracy in detecting suspicious cases and reduces false positives. According to the results, the damage to the culprit, the type and use of the vehicle, and the sex of the victim are among the most important indicators in the detection of fraudulent cases. Manuscript profile
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  3 - Molecular Identification of Gelatin Origin in Pastilles and Jelly Products Collected from Tehran Markets
  N. Kamandi M. Ghobadi Dana M. Ghavami
  10.30495/jfbt.2022.18965
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  4 - Provide a new approach to identify and detect credit card fraud using ANN - ICA
  Javad Balaee kodehi Mohammad Tahghighi Sharabyan
  Introduction: The imperialistic competition algorithm is a method in the field of evolutionary computing that deals with finding the optimal answer to various optimization problems. This algorithm provides an algorithm for solving mathematical optimization problems by m More

  Introduction: The imperialistic competition algorithm is a method in the field of evolutionary computing that deals with finding the optimal answer to various optimization problems. This algorithm provides an algorithm for solving mathematical optimization problems by mathematical modeling the socio-political evolution process. The imperialistic competition algorithm forms an initial set of possible answers. These initial answers are known as chromosomes in the genetic algorithm, particles in the particle swarm algorithm, and countries in the imperialistic competition algorithm. The imperialistic competition algorithm gradually improves these initial solutions (countries) with a special process that follows and finally provides the appropriate solution to the optimization problem. By imitating the process of the social, economic, and political evolution of countries and by mathematically modeling parts of this process, this algorithm presents operators in a regular form as an algorithm that can help solve complex optimization problems. In fact, this algorithm looks at the solutions of the optimization problem in the form of countries and tries to gradually improve these solutions during an iterative process and finally reach the optimal solution of the problem.Method: The proposed algorithm of this article (combined algorithm of neural network and colonial competition) has used the social-political process of the imperialistic competition algorithm with mathematical modeling in order to provide a strong and efficient algorithm in the field of diagnosis optimization.Findings: Our experiments proved that neural data classification using the transaction rejection option can lead us to a very low error rate, while we are looking for a very high detection rate. In this study, we reached an accuracy rate of 98.54, which is a higher accuracy rate compared to previous methods.Discussion: In this research, credit card fraud detection has been done with the aim of identifying the fraud rate, increasing the accuracy, and applying the lowest system error rate using neural networks and combining it with the colonial competition algorithm. Also, effective features were extracted in the evaluation of fraud detection. It can be concluded that the proposed classification system can have a very high detection performance in credit card financial transactions. Manuscript profile
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  5 - Presenting a Model for Financial Reporting Fraud Detection using Genetic Algorithm
  Mahmood Mohammadi Shohreh Yazdani Mohammadhamed Khanmohammadi
  10.22034/amfa.2019.1872783.1252
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  6 - Fraud Detection of Credit Cards Using Neuro-fuzzy Approach Based on TLBO and PSO Algorithms
  Maryam Ghodsi Mohammad Saniee Abadeh
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  7 - A hybrid model based on machine learning and genetic algorithm for detecting fraud in financial statements
  Akbar Javadian Kootanaee Abbas ali Poor Aghajan Mirsaeid Hosseini Shirvani
  10.22094/joie.2020.1877455.1685
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  8 - The Effect of Personality Type and Professional ethics on Auditors' Ability to Detect Fraud Using the Theory of Planned Behavior by theRole of Professional Skepticism
  Leyla Alizadegan Mahmoud SamadiLargani Mohsen Imeni
  10.30495/faar.2022.693669
  AbstractThe purpose of this study was to investigate the effect of personality type and professional ethics on the ability of auditors' to detect financial reporting fraud using the theory of planned behavior with respect to the mediating role of professional skepticism More

  AbstractThe purpose of this study was to investigate the effect of personality type and professional ethics on the ability of auditors' to detect financial reporting fraud using the theory of planned behavior with respect to the mediating role of professional skepticism. The statistical population of the study includes auditors working in the auditing organization and auditing firms that are members of the Iranian Society of Certified Public Accountants. Using Morgan table, 302 people were selected as the research sample. The method of the present study is descriptive-survey and the tool used in the research is a questionnaire. The structural equation Modeling (SEM) was used to investigate the effect of variables and the partial least squares (PLS) approach was used to analyze the patterns. The results showed that the types of auditors' personality types, professional ethics and professional skepticism, have a positive and significant relationship directly on the auditors' ability to detect financial statements fraud. Also, personality type and professional ethics have an indirect and positive relationship with respect to the mediating role of professional skepticism on the detection of fraud in financial statements.According to the research findings, the more professional skeptics auditors are during the audit, the more willing they are to seek information about the signs of fraud and hence the greater their ability to detect fraud. Manuscript profile
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  9 - An Analysis of Auditors Capability on Fraud Detection Using the Planned Behavior Theory Perspective: the Impact of Auditors Experience and Personality Type with Respect to the Role of Professional Skepticism
  Leila Alizadegan Mahmoud Samadi Largani Mohsen Imeni
  10.30495/faar.2023.699788
  AbstractThe purpose of this study was to investigate to an analysis of auditors capability on fraud detection using the planned behavior theory perspective and the impact of auditors experience and personality type with respect to the mediating role of professional skep More

  AbstractThe purpose of this study was to investigate to an analysis of auditors capability on fraud detection using the planned behavior theory perspective and the impact of auditors experience and personality type with respect to the mediating role of professional skepticism in Iran by referring to opinion of professional accounting including auditors working in the auditing organization and auditing firms that are members of the Iranian Society of Certified Public Accountants. The impacts of auditors experience and personality type were obtained through a questionnaire on a five-option Likert scale. The designed questionnaire was distributed among 333 members of ICPA  of which 302 were suitable for use in this study. Structural equation method (SEM) was used to investigate the effects of specific variables, and partial least squares (PLS) approach was used to analyze the model. The results showed that the types of auditors' personality types,auditors experience, and professional skepticism, have a positive and significant relationship directly on the auditors' ability to detect financial statements fraud. Also, personality type and auditors experience have an indirect and positive relationship with respect to the mediating role of professional skepticism on the detection of fraud in financial statements. According to the research findings, Auditors increase the ability to detect fraud by identifying and eliminating the constraints caused by the factors that lead to fraud  regarding the effective role of occupational experience and personality type with respect to the mediatating role of professional skeptic. the more professional skeptics auditors are during the audit, the more willing they are to seek information about the signs of fraud and hence the greater their ability to detect fraud. Manuscript profile
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  10 - A Machine Learning Approach to Detect Energy Fraud in Smart Distribution Network
  Mahdi Emadaleslami Mahmoud-Reza Haghifam
  10.30495/ijsee.2021.683248
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