Unlike our parents and grandparents, we live and breathe in the digital world. Initially, it was discussions on online forums, then chats and emails, and now most of our entire life and financial transactions are executed in digital mode.

As the stakes are getting higher, it is not enough to detect fraud after the event. Imagine someone with a few confidential information about your bank or credit card details, able to execute a fraudulent transaction. Banks and insurance companies need tools and techniques to detect frauds in real-time to take appropriate actions.

We humans lose the sense of interpretation and visualisation as we move beyond three-dimensional space.

Today a financial transaction involves hundreds of parameters like transaction amount, past transaction trends, GPS location of the transaction, transaction time, merchant name etc. We need to consider many parameters to detect an anomaly and fraud in realtime.

Isolation forest algorithm implemented in Scikit-Learn can help to identify the frauds in realtime and avoid financial loss. In this article, I will discuss step by step process of a fraudulent transaction with machine learning.

#data-science #python #programming #machine-learning #cybersecurity