Data Mining for Financial Fraud Detection: Techniques, Case Studies and Challenges

Afiz Adewale Lawal, Enuma Ezeife, Jamiu Olamilekan Akande, Ajibola Olapade, Aishat Oluwatoyin Olatunji

Open source

DOI: 10.56557/ajomcor/2025/v32i29127
Published: 2025-02-24
Container: Asian Journal of Mathematics and Computer Research
Publisher: IK Press
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.56557/ajomcor/2025/v32i29127,
  title = {Data Mining for Financial Fraud Detection: Techniques, Case Studies and Challenges},
  author = {Afiz Adewale Lawal and Enuma Ezeife and Jamiu Olamilekan Akande and Ajibola Olapade and Aishat Oluwatoyin Olatunji},
  year = {2025},
  journal = {Asian Journal of Mathematics and Computer Research},
  doi = {10.56557/ajomcor/2025/v32i29127},
  url = {https://doi.org/10.56557/ajomcor/2025/v32i29127}
}

RIS

TY  - JOUR
TI  - Data Mining for Financial Fraud Detection: Techniques, Case Studies and Challenges
AU  - Afiz Adewale Lawal
AU  - Enuma Ezeife
AU  - Jamiu Olamilekan Akande
AU  - Ajibola Olapade
AU  - Aishat Oluwatoyin Olatunji
PY  - 2025
JO  - Asian Journal of Mathematics and Computer Research
DO  - 10.56557/ajomcor/2025/v32i29127
UR  - https://doi.org/10.56557/ajomcor/2025/v32i29127
ER  -

APA

Lawal, A. A., Ezeife, E., Akande, J. O., Olapade, A., & Olatunji, A. O. (2025). Data Mining for Financial Fraud Detection: Techniques, Case Studies and Challenges. Asian Journal of Mathematics and Computer Research. https://doi.org/10.56557/ajomcor/2025/v32i29127

Source records

crossref · retrieved 2026-11-05T01:15:32.322Z