BUS2002 Business Analysis: Fraudulent Mobile Wallet Transactions

BUS2002 Business Analysis: Fraudulent Mobile Wallet Transactions


Objective: Fraudulent mobile wallet transactions prediction using Machine learning

Brief outline:

Mobile wallet or money is a recent and growing medium of financial transactions in the world. It allows mobile network subscribers to receive, save and spend money using their mobile phone. This financial scheme is widely used as an alternative to monies in cash and in bank accounts. Although the technology is used in most countries in the world, it is particularly popular in Africa, Asia and Latin America. Like other forms of financial transactions, money is vulnerable to fraud since more people have access to mobiles than are bank accounts.

This project aims to investigate effective models for predicting fraudulent mobile wallet transactions using supervised machine learning algorithms. Due to the private nature of financial datasets, the project will be implemented using a publicly available synthetic dataset or a dataset is simulated using various software. about mobile wallet transactions.

These models help real life companies to detect fraudulent transactions and help them prevent consequences by taking necessary measures

Dataset can be found in the following link https://www.kaggle.com/ealaxi/paysim1 python code need to used and should be included in the appendix example of analysis to be done are included in the python file attached word count 15000 excluding appendix chapters to included are introduction, background, literature review, data description and methodology, analysis and results, comparisons and discussion , conclusion and recommendations, references, appendix.
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