A global banking analytics Portfolio project containig 188 Countries and 1,114 banks with detailed analysis of the top five banks in each country from 2020–2025 alongside country level economic indicators.

Global Banking Intelligence Platform is a banking analytics project covering countries, regions and banks from 2020 to 2025.

The project combines banking financial data and economic indicators to analyze assets, deposits, loans, profitability, growth and risk.

Python

PostgreSQL

Excel

Power BI

DAX

DBeaver

VS Code

Python was used for data extraction, web scraping, cleaning, transformation, validation, financial data processing and synthetic data generation.

Libraries used:

pandas

NumPy

requests

BeautifulSoup 4

Playwright

lxml

PyMuPDF

pdfplumber

fake-useragent

Loguru

Automated bank financial extraction was only possible for a limited number of countries and banks due to differences and limitations in public data availability and source structures.

GBIP uses a hybrid dataset containing official and synthetic data.

Original data was collected from publicly available sources.

Synthetic values were used only where reliable public data was unavailable.

The original bank financial datasets are preserved separately in the Data/Raw/ folder. Unavailable original values are marked as Pending Public Data.

PostgreSQL was used as the main database for storing and analyzing the project data.

SQL was used for:

Data analysis

Data quality checks

Validation

Bank rankings

Country and regional analysis

Growth analysis

Profitability analysis

Risk analysis

SQL views

Summary datasets

The database was developed using pgAdmin and DBeaver.

Power BI was used for the final data model, DAX calculations and interactive dashboard.

The dashboard contains:

Global Overview

Regional Analysis

Country Profile

Bank Profile

Bank Rankings

Risk & Stability

Executive Insights

Overview of global banking scale and key financial indicators.

Comparison of banking performance across regions.

Detailed analysis of a country's banking sector and economic indicators.

Financial performance and key indicators for an individual bank.

Comparison and ranking of banks across major financial metrics.

Analysis of banking risk, capital strength and stability indicators.

Database schema and Power BI model relationship diagrams are also included in the Images/ folder.

Detailed project documentation is available in the Docs/ folder, including:

Data Dictionary

Methodology

SQL Analysis

Data Quality Documentation