Predictive Analytics with Machine Learning for Fraud Detection of Online Marketing Transactions

Project Code :TCMAPY434

Objective

Introducing different advance technologies used to deal with frauds and threats which are happening while transaction becoming through online. feature engineering and its feature selection are including to show the better performance of the advance technologies .

Abstract

With digital strategies coping up with online marketing system, enormous data passed to these sectors, online transactions are becoming more prone to frauds and threats resulting in data leakage and personal details exposed to fraudsters leading to huge loss to customers. This makes online marketing systems adapt to high-level security and data handling technology solutions like machine learning, deep learning and predictive analytics which are efficient enough to deal with highly sensitive data, predict frauds and unwanted behavioral patterns in this data. This paper reviews the different advance technologies commonly used to deal with this type of data forms a comparison among them and suggests the most efficient and informative method to use in this sector. Through the end of the review, feature engineering and its selection of parameters for achieving better performance are discussed.

KEYWORDS: Machine Learning, online transactions,predictive analytics

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