Скачать или смотреть Paisabazaar Banking Fraud Analysis in Python | AlmaBetter Project (Module 2) | EDA & Visualization

Welcome to my Paisabazaar Banking Fraud Analysis Project — a complete data analysis and visualization project built using Python.
This is my Capstone Project for Module 2 of the AlmaBetter Data Science Course.

In this project, I explore and analyze Paisabazaar’s financial dataset to detect potential fraud patterns, assess customer credit behavior, and derive meaningful business insights using Python libraries such as Pandas, Matplotlib, and Seaborn.

🔍 What’s covered in this video:

Introduction to the Paisabazaar dataset

Data cleaning, preprocessing & handling missing values

Exploratory Data Analysis (EDA)

Detecting anomalies and fraud indicators

Creating data visualizations to understand customer behavior

Deriving actionable business insights

📊 Key Skills Demonstrated:

Python (Pandas, NumPy, Matplotlib, Seaborn)

Data Wrangling & EDA

Data Visualization & Insight Generation

Fraud Detection Analysis

💡 Outcome:

Gained clear insights into customer credit patterns, income-debt relationships, and behavioral indicators that help in detecting potential frauds and improving financial decision-making.

🎓 Project Type: AlmaBetter Capstone Project (Module 2)
🧠 Domain: Banking Fraud / Credit Risk Analysis
📈 Tools Used: Python, Pandas, Matplotlib, Seaborn

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