Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/24C702E4-59C6-480D-B219-121AA23C3351 | ||
| Year | 2022 | ||
| Type of Item | Master Thesis | ||
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| Bibliographic Citation | Panagiotis Digenakis, "Artificial intelligence methodologies for the identication of financial Fraud: A literature review ", Master Thesis, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2022 https://doi.org/10.26233/heallink.tuc.92649 | ||
| Appears in Collections |
Fraud is linked to both organized crime and terrorism and causes significant economic damage. Among the most common forms of fraud is financial fraud, which can be distinguished into categories such as falsification of financial statements, tax evasion and tax fraud, credit card fraud, money laundering, etc. Those who commit fraud play a dynamic game of cat. with the mouse with those who try to block them. Preventing a particular type of fraud doesn't mean the fraudsters give up, they just distance themselves until they develop a new tactic. Specifically, they are constantly on the lookout for new avenues for fraud, for new weaknesses in the system. So given that economic systems are constantly developing, there are always new opportunities to exploit. Detecting financial fraud is becoming an increasingly pressing issue, various methods have been developed from time to time to detect it. In this paper, artificial intelligence methods and some statistical techniques will be analyzed.
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