osegabi19/Nigeria-Bank-Complaint-Analytics-Dashboard

Interactive power Bi Dashboard for analyzing Nigeria Bank customers complaints, resolution performance, SLA Compliance, complaints trend, channel of complaint and corresponding department workload # Nigeria-Bank-Complaint-Analytics-Dashboard Interactive power Bi Dashboard for analyzing Nigeria Bank customers complaints, resolution performance, SLA Compliance, complaints trend, channel of complaint and corresponding department workload. ## Project Overview This project contains a synthetic dataset of customer complaints generated to simulate banking service issues across Nigerian in the year 2025. The dataset was created for educational, analytical, and portfolio purposes, enabling data analysis, visualization, business intelligence projects. An interactive Power Bi Dashboard for analyzing Nigeria Bank Customers to identify complaint trends, resolution performance, SLA compliance, and areas requiring operational improvement. ## Objectives - Analyze complaint volumes over time - Compare complaint performance across banks - Monitor resolution rates - Fraud complaint rate - Identify open and unresolved complaints - Measure SLA compliance - Analyze complaint categories - Escalation trend - Identify regional patterns ## Dataset Description * ##### Total Complaints: 4,000 records * ##### Coverage: 10 Nigerian commercial banks * ##### Geographical Scope: 8 states across Nigeria * ##### Period: January 2025 – December 2025 The dataset includes various complaint categories such as: - ATM and POS issues - Mobile and Internet banking failures - Failed transactions - Unauthorized debits - Card-related complaints - Loan and account service issues - Fraud and dispute cases - Customer service complaints ## Tools Used - Power BI - DAX - Power Query - Excel - Data Visualization ## Key KPIs - Total Complaints - Resolved Complaints - Open Complaints - Resolution Rate - Average Resolution Time - SLA Compliance ## Dashboard ## Key Insights It is imperative to know that the data is synthetic data, therefore the finding does not show the realistic bank complaint analysis but a pattern from the generated data as this dataset are confidential and are unavailable for public …