The Banking Transactions Dataset and its Comparative Analysis with Scale-free Networks

We construct a network of 1.6 million nodes from banking transactions of users of Rabobank. We assign two weights on each edge, which are the aggregate transferred amount and the total number of transactions between the users from the year 2010 to 2020. We present a detailed analysis of the unweight...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Saxena, Akrati, Pei, Yulong, Veldsink, Jan, van Ipenburg, Werner, Fletcher, George, Pechenizkiy, Mykola
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator Saxena, Akrati
Pei, Yulong
Veldsink, Jan
van Ipenburg, Werner
Fletcher, George
Pechenizkiy, Mykola
description We construct a network of 1.6 million nodes from banking transactions of users of Rabobank. We assign two weights on each edge, which are the aggregate transferred amount and the total number of transactions between the users from the year 2010 to 2020. We present a detailed analysis of the unweighted and both weighted networks by examining their degree, strength, and weight distributions, as well as the topological assortativity and weighted assortativity, clustering, and weighted clustering, together with correlations between these quantities. We further study the meso-scale properties of the networks and compare them to a randomized reference system. We also analyze the characteristics of nodes and edges using centrality measures to understand their roles in the money transaction system. This will be the first publicly shared dataset of intra-bank transactions, and this work highlights the unique characteristics of banking transaction networks with other scale-free networks.
doi_str_mv 10.48550/arxiv.2109.10703
format Article
fullrecord <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_2109_10703</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2109_10703</sourcerecordid><originalsourceid>FETCH-LOGICAL-a673-edf83f8a7bc10a768f60060039bb8c6bc0828c4b51cf90dfacfba825343467df3</originalsourceid><addsrcrecordid>eNotz71OwzAYhWEvDKhwAUx8N5Bgx4ntjCX8ShUMRKzRZ8emVlOnsq2W3j3QIh3p3Y70EHLDaFmrpqF3GL_9vqwYbUtGJeWX5LNfW7jHsPHhC_qIIaHJfg4JHjBjshkwjOBzgm7e7jBi9nsLy4DTMfkEB5_X8GFwsoWL1sKbzYc5btIVuXA4JXv93wXpnx777qVYvT-_dstVgULywo5OcadQasMoSqGcoPR3vNVaGaENVZUytW6YcS0dHRqnUVUNr3kt5Oj4gtyeb0-wYRf9FuNx-AMOJyD_AW5BTEY</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>The Banking Transactions Dataset and its Comparative Analysis with Scale-free Networks</title><source>arXiv.org</source><creator>Saxena, Akrati ; Pei, Yulong ; Veldsink, Jan ; van Ipenburg, Werner ; Fletcher, George ; Pechenizkiy, Mykola</creator><creatorcontrib>Saxena, Akrati ; Pei, Yulong ; Veldsink, Jan ; van Ipenburg, Werner ; Fletcher, George ; Pechenizkiy, Mykola</creatorcontrib><description>We construct a network of 1.6 million nodes from banking transactions of users of Rabobank. We assign two weights on each edge, which are the aggregate transferred amount and the total number of transactions between the users from the year 2010 to 2020. We present a detailed analysis of the unweighted and both weighted networks by examining their degree, strength, and weight distributions, as well as the topological assortativity and weighted assortativity, clustering, and weighted clustering, together with correlations between these quantities. We further study the meso-scale properties of the networks and compare them to a randomized reference system. We also analyze the characteristics of nodes and edges using centrality measures to understand their roles in the money transaction system. This will be the first publicly shared dataset of intra-bank transactions, and this work highlights the unique characteristics of banking transaction networks with other scale-free networks.</description><identifier>DOI: 10.48550/arxiv.2109.10703</identifier><language>eng</language><subject>Computer Science - Social and Information Networks ; Physics - Physics and Society</subject><creationdate>2021-09</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2109.10703$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2109.10703$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Saxena, Akrati</creatorcontrib><creatorcontrib>Pei, Yulong</creatorcontrib><creatorcontrib>Veldsink, Jan</creatorcontrib><creatorcontrib>van Ipenburg, Werner</creatorcontrib><creatorcontrib>Fletcher, George</creatorcontrib><creatorcontrib>Pechenizkiy, Mykola</creatorcontrib><title>The Banking Transactions Dataset and its Comparative Analysis with Scale-free Networks</title><description>We construct a network of 1.6 million nodes from banking transactions of users of Rabobank. We assign two weights on each edge, which are the aggregate transferred amount and the total number of transactions between the users from the year 2010 to 2020. We present a detailed analysis of the unweighted and both weighted networks by examining their degree, strength, and weight distributions, as well as the topological assortativity and weighted assortativity, clustering, and weighted clustering, together with correlations between these quantities. We further study the meso-scale properties of the networks and compare them to a randomized reference system. We also analyze the characteristics of nodes and edges using centrality measures to understand their roles in the money transaction system. This will be the first publicly shared dataset of intra-bank transactions, and this work highlights the unique characteristics of banking transaction networks with other scale-free networks.</description><subject>Computer Science - Social and Information Networks</subject><subject>Physics - Physics and Society</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz71OwzAYhWEvDKhwAUx8N5Bgx4ntjCX8ShUMRKzRZ8emVlOnsq2W3j3QIh3p3Y70EHLDaFmrpqF3GL_9vqwYbUtGJeWX5LNfW7jHsPHhC_qIIaHJfg4JHjBjshkwjOBzgm7e7jBi9nsLy4DTMfkEB5_X8GFwsoWL1sKbzYc5btIVuXA4JXv93wXpnx777qVYvT-_dstVgULywo5OcadQasMoSqGcoPR3vNVaGaENVZUytW6YcS0dHRqnUVUNr3kt5Oj4gtyeb0-wYRf9FuNx-AMOJyD_AW5BTEY</recordid><startdate>20210922</startdate><enddate>20210922</enddate><creator>Saxena, Akrati</creator><creator>Pei, Yulong</creator><creator>Veldsink, Jan</creator><creator>van Ipenburg, Werner</creator><creator>Fletcher, George</creator><creator>Pechenizkiy, Mykola</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20210922</creationdate><title>The Banking Transactions Dataset and its Comparative Analysis with Scale-free Networks</title><author>Saxena, Akrati ; Pei, Yulong ; Veldsink, Jan ; van Ipenburg, Werner ; Fletcher, George ; Pechenizkiy, Mykola</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a673-edf83f8a7bc10a768f60060039bb8c6bc0828c4b51cf90dfacfba825343467df3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Computer Science - Social and Information Networks</topic><topic>Physics - Physics and Society</topic><toplevel>online_resources</toplevel><creatorcontrib>Saxena, Akrati</creatorcontrib><creatorcontrib>Pei, Yulong</creatorcontrib><creatorcontrib>Veldsink, Jan</creatorcontrib><creatorcontrib>van Ipenburg, Werner</creatorcontrib><creatorcontrib>Fletcher, George</creatorcontrib><creatorcontrib>Pechenizkiy, Mykola</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Saxena, Akrati</au><au>Pei, Yulong</au><au>Veldsink, Jan</au><au>van Ipenburg, Werner</au><au>Fletcher, George</au><au>Pechenizkiy, Mykola</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Banking Transactions Dataset and its Comparative Analysis with Scale-free Networks</atitle><date>2021-09-22</date><risdate>2021</risdate><abstract>We construct a network of 1.6 million nodes from banking transactions of users of Rabobank. We assign two weights on each edge, which are the aggregate transferred amount and the total number of transactions between the users from the year 2010 to 2020. We present a detailed analysis of the unweighted and both weighted networks by examining their degree, strength, and weight distributions, as well as the topological assortativity and weighted assortativity, clustering, and weighted clustering, together with correlations between these quantities. We further study the meso-scale properties of the networks and compare them to a randomized reference system. We also analyze the characteristics of nodes and edges using centrality measures to understand their roles in the money transaction system. This will be the first publicly shared dataset of intra-bank transactions, and this work highlights the unique characteristics of banking transaction networks with other scale-free networks.</abstract><doi>10.48550/arxiv.2109.10703</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier DOI: 10.48550/arxiv.2109.10703
ispartof
issn
language eng
recordid cdi_arxiv_primary_2109_10703
source arXiv.org
subjects Computer Science - Social and Information Networks
Physics - Physics and Society
title The Banking Transactions Dataset and its Comparative Analysis with Scale-free Networks
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T04%3A05%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-arxiv_GOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20Banking%20Transactions%20Dataset%20and%20its%20Comparative%20Analysis%20with%20Scale-free%20Networks&rft.au=Saxena,%20Akrati&rft.date=2021-09-22&rft_id=info:doi/10.48550/arxiv.2109.10703&rft_dat=%3Carxiv_GOX%3E2109_10703%3C/arxiv_GOX%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true