Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Fraud Detection within Mobile Money: A mathematical statistics approach
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Context: Today it is easy to do banking transaction digitally, both on a computer or by using a mobile phone. As the banking-services increases and gets implemented to multi-platforms it makes it easier for a fraudster to commit financial fraud. This thesis will focus on investigating log-files from a Mobile Money system that makes it possible to do banking transactions with a mobile phone. 

Objectives: The objectives in this thesis is to evaluate if it is possible to combine two statistical methods, Benford's law together with statistical quantiles, to find a statistical way to find fraudsters within a Mobile Money system.

Methods: Rules was extracted from a case study with focus on a Mobile Money system and limits was calculated by using quantiles. A fraud detector was implemented that use these rules together with limits and Benford's law in order to detect fraud.The fraud detector used the methods both independently and combined.The performance was then evaluated.

Results: The results show that it is possible to use the Benford's law and statistical quantiles within the studied Mobile Money system. It is also shown that there is only a very small difference when the two methods are combined or not both in detection rate and accuracy precision.

Conclusions: We conclude that by combining the chosen methods it is possible to get a medium-high true positive rates and very low false positive rates. The most effective method to find fraudsters is by only using quantiles. However, combining Benford's law with quantiles gives the second best result.

Place, publisher, year, edition, pages
2015. , 45 p.
Keyword [en]
Fraud detection, Benford's law, quantiles, Mobile Money
National Category
Computer Science
Identifiers
URN: urn:nbn:se:bth-10898OAI: oai:DiVA.org:bth-10898DiVA: diva2:865559
Subject / course
DV2524 Degree Project in Computer Science for Engineers
Educational program
DVACD Master of Science in Computer Security
Supervisors
Examiners
Available from: 2015-11-06 Created: 2015-10-28 Last updated: 2015-11-06Bibliographically approved

Open Access in DiVA

fulltext(767 kB)331 downloads
File information
File name FULLTEXT02.pdfFile size 767 kBChecksum SHA-512
15b481f65c58b99ce69450b1ae6d66f2abc030c8e4e72cdf5cca2a34cafb15b425d91cc958f699bc9530b45ee8b0a19072bb0742a89edbf36003b590e1ac4d66
Type fulltextMimetype application/pdf

By organisation
Department of Computer Science and Engineering
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 331 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 443 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf