| Autor: |
David Jesenko, Štefan Kohek, Borut Žalik, Matej Brumen, Domen Kavran, Niko Lukač, Andrej Živec, Aleksander Pur |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Applied Sciences, Vol 12, Iss 23, p 12492 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2076-3417 |
| DOI: |
10.3390/app122312492 |
| Popis: |
Acts of fraud have become much more prevalent in the financial industry with the rise of technology and the continued economic growth in modern society. Fraudsters are evolving their approaches continuously to exploit the vulnerabilities of the current prevention measures in place, many of whom are targeting the financial sector. To overcome and investigate financial frauds, this paper presents STALITA, which is an innovative platform for the analysis of bank transactions. STALITA enables graph-based data analysis using a powerful Neo4j graph database and the Cypher query language. Additionally, a diversity of other supporting tools, such as support for heterogeneous data sources, force-based graph visualisation, pivot tables, and time charts, enable in-depth investigation of the available data. In the Results section, we present the usability of the platform through real-world case scenarios. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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