THE USE OF GRAPH DATABASES TO IDENTIFY FRAUDULENT SCHEMES IN THE FINANCIAL SECTOR

A. Tyunina; D. Kukueva; V. Kondusova

doi:doi:10.58168/PPSPM2025_192-198

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THE USE OF GRAPH DATABASES TO IDENTIFY FRAUDULENT SCHEMES IN THE FINANCIAL SECTOR

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THE USE OF GRAPH DATABASES TO IDENTIFY FRAUDULENT SCHEMES IN THE FINANCIAL SECTOR

Section: SECTION 1. SYSTEMS ANALYSIS, MANAGEMENT, INFORMATION PROCESSING

Proceedings: PROBLEMS AND PROSPECTS IN SYSTEMS AND PROCESS MODELING : MATERIALS OF THE ALL-RUSSIAN SCIENTIFIC AND PRACTICAL CONFERENCE, VORONEZH, OCTOBER 14, 2025

UDC 004.9

A. Tyunina ¹

D. Kukueva ²

V. Kondusova ³

Author and publication information

Authors:

1. Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation

2. Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation

3. Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation

Type:

Сonference article

DOI:

https://doi.org/10.58168/PPSPM2025_192-198

Pages:

from 192 to 198

Published:

30.12.2025

Subject area:

UDC 004.9

Language:

Russian

Keywords:

graph databases, Neo4j, financial fraud, social network analysis, PageRank, mediation centrality, community discovery, Cypher, linked data, proactive security

Abstract and keywords

Abstract:
The article discusses the use of Neo4j graph databases to detect and analyze complex fraudulent schemes in financial transactions. The study demonstrates the advantages of the graph approach over traditional relational databases in the analysis of related data. The key graph analysis algorithms are described in detail: PageRank to identify influential nodes, Betweenness Centrality to detect intermediary elements, and community detection algorithms to identify organized groups. Practical examples of queries in the Cypher language and schemes for organizing typical fraudulent operations are given. The results of the study show that graph analysis makes it possible to move from a reactive to a proactive approach in the fight against financial fraud, ensuring the identification of complex relationships and the preventive blocking of illegal schemes.

Keywords:
graph databases, Neo4j, financial fraud, social network analysis, PageRank, mediation centrality, community discovery, Cypher, linked data, proactive security

References

1. Robinson Ya., Vebber D., Ayfrem E. Grafovye bazy dannyh. Novye tehnologii dlya raboty s svyazannymi dannymi. - 2-e izd. - Moskva: Dialektika, 2023. - 382 s.

2. Vnukov A.A. Zaschita informacii v bankovskih sistemah: ucheb. posobie dlya bakalavriata i magistratury. - 2-e izd., pererab. i dop. - Moskva: Yurayt, 2017. - 246 s. EDN: https://elibrary.ru/ZTAVOZ

3. Balanov A.N. Kompleksnaya informacionnaya bezopasnost'. Polnyy spravochnik specialista: Prakticheskoe posobie. - Moskva: Infra-Inzheneriya, 2024. - 156 s.

4. Miller Dzh. Dzh. Vvedenie v analiz grafov s ispol'zovaniem Neo4j: obnaruzhenie moshennichestva i analiz finansovyh shem. - Moskva: DMK Press, 2021. - 254 s.

5. Vnukov A.A. Zaschita informacii v bankovskih sistemah: ucheb. posobie dlya bakalavriata i magistratury. - 2-e izd., pererab. i dop. - Moskva: Yurayt, 2017. - 246 s. EDN: https://elibrary.ru/ZTAVOZ

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