Protecting Investor Sentiment by Detecting Financial Fraud With the Help of ML and AI Applications

Abstract

Investors, in spite of their vigilant moves, often are observed to fall victim to financial fraud. There are several machine learning algorithms both supervised and unsupervised which exists and continue to serve the objective of detecting financial fraud like under supervised machine learning random forest, k-nearest neighbours (KNN), logistic regression and support vector machine (SVM) and unsupervised machine learning includes K-means and SOM (self-organizing map).AI will help in mitigating the impact of volatility in the financial market. There is a necessity to adopt new-age machine learning and Artificial Intelligence which will promptly process millions of data and also identify dubious patterns has become very crucial to evade the losses caused by fraudulent activities.