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This project uses Power BI to analyze banking data, improving risk management, customer insights, and branch efficiency through interactive dashboards and advanced analytics.

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meabhaykr/Financial-Insights-in-Banking-Data-using-PowerBI

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Financial Insights in Banking Data using Power BI


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Project Overview

This project leverages Power BI to provide in-depth financial insights for banking institutions. By analyzing 'Banking Transactions' and 'Customer Account Details' datasets, we aim to help banks make informed decisions about customer relationships, risk assessment, and product offerings.

Key Features

  • Data Cleaning and Standardization: Removed failed transactions and reformatted datasets for consistency and accuracy.
  • Data Relationships: Established and optimized data relationships to ensure high data quality.
  • Branch Efficiency Rating System: Developed a system to rate branch efficiency, enhancing risk assessment and performance metrics.
  • Credit Score Analysis: Identified high-value transactions and analyzed credit scores for better risk management.
  • Interactive Dashboard: Created an interactive dashboard for comprehensive data visualization and insights.

Project Goals

  • Extract meaningful insights from banking data to support strategic decision-making.
  • Improve customer satisfaction through data-driven optimizations in banking services.
  • Identify new growth opportunities and predict future account growth using advanced data analysis techniques.

Datasets Used

  1. Banking Transactions
  2. Customer Account Details

Tools and Technologies

  • Power BI: For data visualization and dashboard creation.
  • DAX (Data Analysis Expressions): For advanced data analysis and calculations.
  • EDA (Exploratory Data Analysis): For initial data exploration and understanding.
  • Data Cleaning: Ensuring data quality and consistency.

Methodology

  1. Data Import and Quality Check: Imported both datasets into Power BI and checked for data quality issues.
  2. Data Cleaning: Removed failed transactions and standardized transaction amounts.
  3. Data Merging: Combined the datasets for comprehensive analysis.
  4. Advanced Analysis using DAX:
    • Analyzed transaction trends over time.
    • Studied customer demographics and employment sectors.
    • Analyzed loan amounts, interest rates, and credit scores.
  5. Predictive Modeling: Developed models to estimate future account growth based on transaction patterns.
  6. Visualization: Created interactive dashboards to present insights clearly and effectively.

Insights and Outcomes

  • Branch Efficiency: The rating system provided insights into branch performance and areas for improvement.
  • Customer Analysis: Detailed understanding of customer demographics and high-value transactions.
  • Risk Assessment: Enhanced risk management through comprehensive credit score analysis.
  • Strategic Decision-Making: Data-driven insights enabled informed strategic decisions, improving overall performance and customer satisfaction.

Power Bi Dashboard Image

Project Link

Access the project files and dashboard

Conclusion

This project demonstrates the power of data analysis and visualization in transforming raw banking data into actionable insights. By leveraging Power BI and advanced analytics, banking institutions can optimize their services, manage risks more effectively, and enhance customer satisfaction.


Feel free to explore the project files and interactive dashboard via the provided link. If you have any questions or feedback, please reach out!

Contact

For any inquiries or support, please contact at meabhaykr@gmail.com


Happy analyzing!

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This project uses Power BI to analyze banking data, improving risk management, customer insights, and branch efficiency through interactive dashboards and advanced analytics.

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