Fraudulent detection model using machine learning techniques for unstructured supplementary service data
The increase in mobile phones accessibility and technological advancement in almost every corner of the world has shaped how banks offer financial service. Such services were extended to low-end customers without a smartphone providing Alternative Banking Channels (ABCs) service, rendering regular f...
Saved in:
Main Author: | Olugbenga, Akinje Ayorinde |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/96376/1/AyoAkinjeMSC2021.pdf.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multiple 2D self organising map network for surface reconstruction of 3D unstructured data
by: Lim, Seng Poh
Published: (2015) -
An adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques
by: Zainal, Anazida
Published: (2011) -
Supervised machine learning approach for detection of malicious executables
by: Ahmed, Yahye Abukar
Published: (2013) -
An Ontology-Driven Methodology To Derive Cases From Structured And Unstructured Sources
by: Manickam, Selvakumar
Published: (2013) -
Classification of cross site scripting web pages using machine learning techniques
by: Al-Aswer, Faisal Saleh Nasser
Published: (2017)