Name
Abstract | ||
|---|---|---|
The identification of anomalous user behaviour is important in a number of application areas, since it may be indicative of fraudulent activity. In the work presented here, the focus is on the identification and subsequent investigation of suspicious interactions in a network of financial transactions. A network is constructed from data from a peer-to-peer lending system, with links between members representing the initiation of loans. The network is time-sliced to facilitate temporal analysis. Anomalous network structure is sought in the time-sliced network, illustrating the occurrences of unusual behaviour among members. In order to assess the significance of the dense structures returned the enrichment of member attributes within these structures is examined. It seems that dense structures are associated with geographic regions. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-33684-3_4 | MSM/MUSE |
Keywords | Field | DocType |
geographic region,time-sliced network,fraudulent activity,dense structure,financial network data,anomalous network structure,financial transaction,unusual behaviour,anomalous user behaviour,member attribute,application area,anomalous behaviour | Data science,Data mining,Financial transaction,Network data,Geography,Network structure | Conference |
Citations | PageRank | References |
3 | 0.42 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ursula Redmond | 1 | 14 | 1.35 |
| Martin Harrigan | 2 | 59 | 4.74 |
| Pádraig Cunningham | 3 | 3086 | 218.37 |