"Interactive Bank Loan Dashboard in Power BI"

Did you know that Excel can help you predict how much interest you’ll really pay on a loan—before you even visit the bank? Using the PMT function in Excel, I analyzed a $1,200 loan at an 8% annual interest rate, repaid over 2 years. The monthly payment came to $54.27, meaning about $102.48 will be paid in total interest. 📊 Key Insights: • Always compare loan options—some banks offer lower rates or longer repayment terms. • Paying slightly more monthly can significantly reduce total interest. • Excel’s financial formulas like PMT, FV, and RATE are powerful tools for smarter financial decisions. As a Data Entry and Spreadsheet Specialist, I use Excel not just for data management but for creating clear, actionable insights that support financial planning and decision-making. #DataEntry #Excel #RemoteWork #VirtualAssistant #DataAnalysis

From Raw Data to Insight: My Bank Loan Report Project One of my recent projects involved transforming a large set of raw bank loan data into a meaningful Bank Loan Report Dashboard, created entirely in Microsoft Excel. Initially, the dataset appeared daunting, containing thousands of loan records with details on applications, funding, and repayment statuses. However, I viewed it as an opportunity to enhance my data analysis skills. I undertook the following steps: - Cleaned and organized the data - Built pivot tables - Visualized key metrics, including: - 38.6K total loan applications - 86% good loans versus 14% bad loans - $473.1M total funded amount - Average interest rate: 13.33% The most rewarding aspect was seeing the dashboard come to life, illustrating trends across Current, Fully Paid, and Charged Off loans. It was gratifying to witness how a few Excel formulas and clear visualizations could convey a compelling story about financial performance. This project reaffirmed my passion for working with data: the ability to find clarity in complexity and transform numbers into valuable insights. #Excel #DataAnalysis #DashboardDesign #DataVisualization #LearningJourney #FinancialAnalytics #BankLoanReport #PortfolioProject

💼 Bank Loan & Delinquency Dashboard | Power BI | Excel | MySQL I’m excited to share my Bank Loan and Delinquency Analysis Dashboard, designed to provide comprehensive insights into loan disbursement, collection trends, and delinquency performance. 📊 Project Highlights: Developed an interactive Power BI dashboard integrating data from Excel and MySQL for seamless reporting. Conducted in-depth analysis of loan portfolio performance, including total funded amount, principal, and interest income. Performed Year-over-Year (YoY) trend analysis to identify growth patterns and areas of improvement. Delivered regional and state-level insights, highlighting top-performing and underperforming branches. Built a delinquency monitoring module to analyze default behavior by bank, region, and customer segment. 📈 Impact: Enabled stakeholders to make data-driven lending and collection decisions, optimize portfolio performance, and reduce delinquency risks through actionable insights. #PowerBi #DataAnalytics #LoanAnalysis #FinanceAnalytics #BusinessIntelligence #DataVisualization #DashboardDesign #SQL #Excel #BankAnalytics

Bank-Loan-Report In this project I’ve built an interactive dashboard using Power BI to dive deep into bank loan data — dealing with applications, funded amounts, repayments, and borrower profiles. Process: 1). Processed and cleaned a large loan dataset to ensure accurate insights (removing duplicates, standardising formats, defining “good” vs “bad” loans) 2). Built data models and calculated key metrics (KPIs) like total applications, funded amount, average interest rate. 3). Designed a multi-page Power BI dashboard (Summary, Overview, Details) featuring maps, bar charts, slicers by state, loan purpose, home ownership etc. Derived insights such as: - 38.6K loan applications processed, with ~$435.8M funded and ~$473.1M received . - Good loans ≈ 86.2% of portfolio, bad loans ≈ 13.8% — highlighting credit risk and portfolio performance  - Average interest rate ~12% Visual Preview Below: https://lnkd.in/gJTkcAn5

Tableau project dashboard following: #Bank_loan_analysis To analyze the overall performance of bank loans — tracking loan amounts, payments, loan purposes, verification status, and geographic trends. The goal is to gain insights into loan distribution, repayment behavior, and approval trends.

📊 Bank Loan Report Dashboard | Power BI Project 💡 I built this interactive Power BI dashboard to analyze and visualize key banking metrics related to loan performance and portfolio quality. ✅ Key KPIs & Insights: >📄 Total Loan Applications: 38.6K >💰 Total Funded Amount: $435.8M >💵 Total Amount Received: $473.1M >📊 Average Interest Rate: 12.0% >📉 Average DTI (Debt-to-Income): 13.3% >✅ Good Loan Ratio: 86.2% | ❌ Bad Loan Ratio: 13.8% 📈 Dashboard Sections: 1️⃣ Summary View – Overall loan performance, funding, and repayment metrics 2️⃣ Overview View – Applicant analysis by month, state, term, purpose, and employment length 3️⃣ Details View – Transaction-level data with funding, interest rate, and repayment details 🛠️ Tools Used: Power BI | DAX | Data Modeling | Data Cleaning This project helped me strengthen my data analytics and visualization skills while gaining insights into loan performance trends. GitHub Link : https://lnkd.in/g5JCJKfh #PowerBI #DataAnalytics #DashboardDesign #BankingAnalytics #LoanPerformance #DataVisualization #FinanceAnalytics

Just completed a Dynamic Bank Loan Dashboard using Power BI! 🎯 Problem Statement: Banks often face challenges analyzing loan data efficiently — understanding which loan types perform best, tracking repayments, and identifying potential defaulters. Approach: Imported and transformed raw data in Power BI Built data relationships and calculated KPIs using DAX Created visualizations for loan amount trends, repayment status, and customer segments Designed an interactive dashboard with slicers and filters for better insights Thanks to Data Tutorials for their clear guidance and step-by-step explanation! 🙏 #PowerBI #DataAnalytics #Dashboard #LearningByDoing #DataVisualization #DataTutorials

Just launched my latest Power BI project: Bank Loan Performance & Risk Analysis! In the world of finance, knowing your risk is everything. My goal was to take a massive dataset of loan information and create a single, interactive dashboard that helps a bank answer two critical questions: Where is our highest risk of default ? Which borrower segments are performing the best? Here's a snapshot of the insights I delivered: ✅ Risk Identification: Visualized loan status by Credit Grade and Verification Status to pinpoint high-risk segments quickly. ✅ Financial Pulse Check: Tracked the total Revolving Balance and Total Payment across various borrower categories. ✅Geographic Trends: Mapped out loan performance by state to uncover regional lending patterns. ✅Technical Skills Showcase: Used Power Query for advanced data shaping and wrote robust DAX measures to power the core financial metrics (like Year-wise Loan Amount statistics). This project was a great exercise in data modeling and transforming complex financial data into a clear, actionable 360-degree view of the bank’s lending portfolio. Take a look at the attached dashboard image! I'd appreciate any thoughts or feedback on the visualization and insights.  #PowerBI #DataAnalytics #FinancialData #CreditRisk #BusinessIntelligence #DataVisualization #PowerBIProject #Dashboard #PBIreport

🚀 Just wrapped up a full Financial Loan Analysis Dashboard — and the insights are INSANE. What started as a dataset full of numbers turned into a story: ✅ 50,000+ loan clients ✅ $581M+ total loan disbursed ✅ Highest loan demand occurs in December ($167M!) ✅ Grade G loans carry the highest interest rate (20.91%) ✅ SME applications dominate loan disbursement (84.09%) But here’s what shocked me the most: ➡️ Despite a massive loan disbursement, loan repayment ($598M) exceeded the total loan amount. ➡️ Clients with employment history 1–3 years received the highest total loan ($209M). This dashboard helps decision makers answer key questions instantly: 🔹 Which customer segments are most profitable? 🔹 Which loan grades carry the highest risks based on interest rates? 🔹 When should marketing push for new loan applications? 💡 The goal isn’t just to visualize data — it’s to reveal opportunities. The right dashboard turns confusion into clarity. Numbers into strategy. Data into decisions. 📊 Tools used: Power BI | Data Modeling | DAX #PowerBI #DataAnalysis #DashboardDesign #BusinessIntelligence #DataStorytelling #Loans #Finance #Analytics

📊 Bank Analytics Dashboard – Excel Project 💼 I created this interactive Bank Analytics Dashboard using Microsoft Excel to analyze and visualize key financial metrics like loan disbursement, collections, and revenue. 💡 Dashboard Insights: Total Loan Amount: ₹347,701.60K Total Accounts: 31,309 Total Collection: ₹74,577.30K Total Revenue: ₹422,278.90M Total Interest: ₹73,993.07K 📈 Key Analysis Areas: State-wise and Religion-wise loan payments Loan status overview (Active, Closed, Cancelled, etc.) Grade-wise and Branch-wise loan performance Year-wise loan disbursement trends 🧰 Tools & Techniques Used: Excel | Pivot Tables | Charts | Slicers | Data Cleaning This project helped me improve my data visualization and analytical thinking by turning raw data into meaningful business insights. 💬 Always exploring new ways to make data more insightful and interactive! #ExcelDashboard #DataAnalytics #BankAnalytics #ExcelProject #DataVisualization #BusinessAnalytics #DataAnalyst