Λέσχη Φίλων Στατιστικής - GrStats forum
AI@AUEB 23/5/2023 (*** Change of DAY, TIME ,ROOM! ***): A machine learning and network approach to Value Added Tax fraud detection by Angelos Alexopoulos (Dept. of Economics, AUEB) Forumgrstats

Join the forum, it's quick and easy

Λέσχη Φίλων Στατιστικής - GrStats forum
AI@AUEB 23/5/2023 (*** Change of DAY, TIME ,ROOM! ***): A machine learning and network approach to Value Added Tax fraud detection by Angelos Alexopoulos (Dept. of Economics, AUEB) Forumgrstats
Λέσχη Φίλων Στατιστικής - GrStats forum
Would you like to react to this message? Create an account in a few clicks or log in to continue.
Για προβλήματα εγγραφής και άλλες πληροφορίες επικοινωνήστε με : grstats.forum@gmail.com ή grstats@stat-athens.aueb.gr

Go down
avatar
GRStats2
Posts : 46
Join date : 2022-11-19

AI@AUEB 23/5/2023 (*** Change of DAY, TIME ,ROOM! ***): A machine learning and network approach to Value Added Tax fraud detection by Angelos Alexopoulos (Dept. of Economics, AUEB) Empty AI@AUEB 23/5/2023 (*** Change of DAY, TIME ,ROOM! ***): A machine learning and network approach to Value Added Tax fraud detection by Angelos Alexopoulos (Dept. of Economics, AUEB)

Sat 13 May 2023 - 14:40
AI@AUEB
*** Change of DAY, TIME ,ROOM! ***

Angelos Alexopoulos
Department of Economics, AUEB

Title: A machine learning and network approach to Value Added Tax fraud detection

TUESDAY 23/5/2023
16:15-17.30 (hybrid presentation, Greek time)

T105, New AUEB Building (Trias 2),
and virtually via MS Teams:

https://teams.microsoft.com/l/meetup-join/19%3aOiYUJgd5vTDTv9p0FnXvTdZ9TTZxIBRHwZzEpD02P-Y1%40thread.tacv2/1683621333082?context=%7b%22Tid%22%3a%22ad5ba4a2-7857-4ea1-895e-b3d5207a174f%22%2c%22Oid%22%3a%225b49c8b5-6801-409c-a8f8-6e18215b3a08%22%7d

Abstract:

Value Added Tax (VAT) fraud erodes tax revenues and puts legitimate businesses at a disadvantaged position thereby impacting inequality. Identifying and combating VAT fraud before it occurs is therefore important for welfare. This paper proposes suitably flexible machine learning algorithms for detection of VAT fraudulent transactions. The innovation of the algorithms is in utilising the information provided by their VAT structure. Making use of the universe of Bulgarian VAT data the fraud detection algorithms detect around 50 percent of the VAT fraud and outperform well-known techniques that ignore the network of VAT transactions. Importantly, the proposed methods are automated, and can be implemented following the taxpayers' submission of their VAT returns, enabling tax revenue authorities, in the EU and elsewhere, to prevent large losses of tax revenues through performing early identification of fraud between business-to-business transactions within the VAT system. The approach developed can be applied to similar problems where network interactions exist and can be quantified, such as fraud in online transactions, in insurance and social security systems as well as in telecommunication systems.

To subscribe to the mailing list of AI@AUEB, send a message (with any subject and body) to ai_meetings-subscribe@lists.aueb.gr.

More info: https://www.aueb.gr/el/content/aiaueb-talk-machine-learning-and-network-approach-value-added-tax-fraud-detection-angelos
Back to top
Permissions in this forum:
You cannot reply to topics in this forum