The Financial Fraud Detection System using the Fraud Triangle Theory (FTT)

2021 ◽  
Vol 9 (1) ◽  
pp. 767-771
Author(s):  
Bobby K Simon
Keyword(s):  
Detection System ◽  
Fraud Detection ◽  
Financial Fraud ◽  
Fraud Triangle ◽  
Triangle Theory

scholarly journals Kecurangan Dalam Laporan Keuangan “Menguji Teori Froud Triangle”

2018 ◽  
Vol 19 (1) ◽  
pp. 77
Author(s):  
Langgeng Prayitno Utomo
Keyword(s):  
Logistic Regression ◽  
Fraud Detection ◽  
Financial Statements ◽  
External Pressure ◽  
Fraud Triangle ◽  
Triangle Theory ◽  
Fraudulent Financial Statements

This study aims to examine the factors that affect the fraudulent financial statements of the company. Fraud detection of financial statements using fraud triangle theory. Based on the theory of fraud triangle there are three factors: pressure, opportunity, and rationalization are used as parameters to detect fraud. The sample of this study used 44 companies in 3 years of observation, where the company is divided into companies that are indications of fraud and not by doing the analysis using the calculation of the underlying M-score, this study used logistic regression, the result that the indication of fraud in this study only can be obtained from external pressure factors on pressure variables and the effectiveness of monitoring on the opportunity variables, this study fails to establish influence in three factors at once ie pressure, opportunity, and rational

scholarly journals A Relative Investigation of Various Algorithms for Online Financial Fraud Detection Techniques

2021 ◽  
Author(s):  
C Pallavi ◽  
Girija R ◽  
Vedhapriyavadhana R ◽  
Barnali Dey ◽  
Rajiv Vincent
Keyword(s):  
Credit Card ◽  
Detection System ◽  
Geographical Area ◽  
Fraud Detection ◽  
Location Analysis ◽  
Financial Fraud ◽  
Detection Techniques ◽  
Spending Patterns ◽  
Efficient Data ◽  
Financial Transactions

Online financial transactions play a crucial role in today’s economy. It becomes an unavoidable part of the business and global activities. Transaction fraud executes thoughtful intimidations to e-commerce spending. Now-a-days, the online contract or business is fetching additional sound by knowing the types of online transaction frauds associated with, these are raising which disturbs the currency accompanying business. It has the capability to confine and encumber the contract accomplished by the intruder from an honest consumer’s credit card information. In order to avoid such a problem, the proposed system is established transaction limit for the customers. Efficient data is only considered for detecting fraudulent user action and it happens only at the time of registration. Transaction which is happening for any individual is not at all known to any FDS (Fraud Detection System) consecutively at the bank which mainly issues credit cards to customers. To speak out this problem, BLA (Behaviour and Location Analysis) is executed. The FDS tracks at a credit card provided by bank. All the inbound business is directed to the FDS aimed at confirmation, authentication and verification. FDS catches the card particulars and matter to confirm that the operation is fake or genuine. The pick-up merchandises are unknown to Fraud Detection System. If the transaction is assumed to be fraud, then the corresponding bank declines it. In order to verify the individuality, uniqueness or originality, it uses spending patterns and geographical area. In case, if any suspicious pattern is identified or detected, the FDS system needs verification. The information which is already registered by the user, the system identifies infrequent outlines in the disbursement method. After three invalid attempts, the system will hinder the user. In this proposed system, most of the algorithms are checked and investigated for online financial fraud detection techniques.

scholarly journals Human behavior scoring in credit card fraud detection

2021 ◽  
Vol 10 (3) ◽  
pp. 698
Author(s):  
Imane Sadgali ◽  
Nawal Sael ◽  
Faouzia Benabbou
Keyword(s):  
Rough Set ◽  
Credit Card ◽  
Rough Set Theory ◽  
Detection System ◽  
Hybrid Approach ◽  
Score Function ◽  
Fraud Detection ◽  
Financial Fraud ◽  
Electronic Payment ◽  
Financial Systems

<span lang="EN-US">Now days, the analysis of the behavior of cardholders is one of the important fields in electronic payment. This kind of analysis helps to extract behavioral and transaction profile patterns that can help financial systems to better protect their customers. In this paper, we propose an intelligent machine learning (ML) system for rules generation. It is based on a hybrid approach using rough set theory for feature selection, fuzzy logic and association rules for rules generation. A score function is defined and computed for each transaction based on the number of rules, that make this transaction suspicious. This score is kind of risk factor used to measure the level of awareness of the transaction and to improve a card fraud detection system in general. The behavior analysis level is a part of a whole financial fraud detection system where it is combined to intelligent classification to improve the fraud detection. In this work, we also propose an implementation of this system integrating the behavioral layer. The system results obtained are very convincing and the consumed time by our system, per transaction was 6 ms, which prove that our system is able to handle real time process.</span>

scholarly journals An Xgboost based system for financial fraud detection

2020 ◽  
Vol 214 ◽  
pp. 02042
Author(s):  
Shimin LEI ◽  
Ke XU ◽  
YiZhe HUANG ◽  
Xinye SHA
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Credit Card ◽  
Detection System ◽  
Fraud Detection ◽  
Financial Fraud ◽  
Credit Card Fraud

Credit card fraud leads to billions of losses in online transaction. Many corporations like Alibaba, Amazon and Paypal invest billions of dollars to build a safe transaction system. There are some studies in this area having tried to use machine learning or data mining to solve these problems. This paper proposed our fraud detection system for e- commerce merchant. Unlike many other works, this system combines manual and automatic classifications. This paper can inspire researchers and engineers to design and deploy online transaction systems.

scholarly journals Analysis and Countermeasures of Financial Fraud of Listed Companies—Taking Greencool Incident as an Example

2020 ◽  
Vol 5 (4) ◽  
pp. 286
Author(s):  
Shumin Ge
Keyword(s):  
Sustainable Development ◽  
Economic Development ◽  
Listed Companies ◽  
Financial Fraud ◽  
Fraud Triangle ◽  
Continuous Increase ◽  
The Sustainable Development ◽  
Triangle Theory ◽  
Cover Up ◽  
China’S Economy

<p>The sustainable development of China’s economy stimulates the continuous increase in the number of listed companies, and the competition among them is also intensifying. Financial fraud is used to cover up the real operation of the company, which has a serious impact on the order of economic development. So, it is necessary to analyze the causes of financial fraud of listed companies, and we need to deal with the behavior from the root. Therefore, this article selects one of the typical cases in this field, Greencool incident, and combines with the fraud triangle theory to explore the essential causes of financial fraud, and puts forward relevant governance countermeasures, so as to reduce the occurrence of financial fraud.</p>

Financial Statement Fraud Detection Using Published Data Based on Fraud Triangle Theory

2017 ◽  
Vol 23 (8) ◽  
pp. 7054-7058 ◽  
Author(s):  
Ricardo Parlindungan ◽  
Fernando Africano ◽  
P. Sri Megawati Elizabeth
Keyword(s):  
Fraud Detection ◽  
Financial Statement ◽  
Published Data ◽  
Fraud Triangle ◽  
Financial Statement Fraud ◽  
Triangle Theory

scholarly journals An intelligent payment card fraud detection system

2021 ◽  
Author(s):  
Manjeevan Seera ◽  
Chee Peng Lim ◽  
Ajay Kumar ◽  
Lalitha Dhamotharan ◽  
Kim Hua Tan
Keyword(s):  
Detection System ◽  
Fraud Detection ◽  
Payment Card
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