Use of Data Mining Techniques to Detect Fraud in Procurement Sector
| dc.Location | 2022 T 58.6 H36 | |
| dc.Supervisor | Professor Sherief Abdallah | |
| dc.contributor.author | AL HAMMADI, SUMAYYA ABDULLA | |
| dc.date.accessioned | 2022-04-26T08:33:59Z | |
| dc.date.available | 2022-04-26T08:33:59Z | |
| dc.date.issued | 2022-01 | |
| dc.description.abstract | Procurement is an extensive and complex sector in the manufacturing industry, and has attracted an extensive and wide-spreading fraud that directly impacts the operation of an organization and economy at large. These fraudulent activities have contributed to rising problems in the manufacturing industry. Several fraud detection systems are being used in the procurement and logistics sector, and their challenge is incapability of realizing the burden of the money lost and abnormal behaviors in the procurement process. Another major problem with the current system is that having an ever-growing amount of data requires a proportional growing number of staff members to analyze the data. In addition, some of the organizations carry out this task manually using their specialized staff. Despite the implementation of various strategies aiming to fight and reduce fraud in the procurement sector, such as random and periodic audits, whistle-blowing, and many others, most of the UAE's organization still uses the manual approach to do these audits and monitoring of the procurement process. This has continued to be a challenge in most of the businesses in the UAE. This research aims to analyze the reliability and efficiency of data mining techniques in detecting and preventing fraud in the procurement sector in the UAE and globally. The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. From this study I found out that most of the organizations lose quite a huge amount through fraud in their procurement sector. However, unsupervised data mining techniques are reliable in detecting fraud before they happen. For the research, I found out the importance of data mining in detecting fraud in procurement. Data analytics reflects on the structuring of the data to be usable and accessible to teams or individuals who require information about procurement in a company. This essentially makes it easy to detect fraud and thus prevents it from happening. The findings from this study will help implement a system that will significantly reduce fraud in the procurement sector. It will save companies a lot of money which will positively impact. This study concluded that most of the companies lose money due to fraud. They are willing to invest their money in fraud detection and control systems that will curb fraud. Fraud detection is a field that requires dynamic research and periodical upgrades and innovations because fraudsters are many and skilled; they consistently devise new ways to perform fraud in a less detectable way. From this study, I found out that the use of data mining techniques will help discover entirely invisible patterns and alert the fraudsters. There is a need for the companies to acquire new technology devices and ways to mitigate fraud in their procurement sector. | en_US |
| dc.identifier.other | 20206122 | |
| dc.identifier.uri | https://bspace.buid.ac.ae/handle/1234/1994 | |
| dc.language.iso | en | en_US |
| dc.publisher | The British University in Dubai (BUiD) | en_US |
| dc.subject | fraud | en_US |
| dc.subject | data mining | en_US |
| dc.subject | data mining techniques | en_US |
| dc.subject | procurement sector | en_US |
| dc.subject | manufacturing industry | en_US |
| dc.subject | fraud detection systems | en_US |
| dc.subject | procurement process | en_US |
| dc.subject | United Arab Emirates (UAE) | en_US |
| dc.title | Use of Data Mining Techniques to Detect Fraud in Procurement Sector | en_US |
| dc.type | Dissertation | en_US |