Online Financial Company Analysis Using AI-Driven KPIs

Online Financial Company Analysis Using AI-Driven KPIs

This project leverages AI-powered Key Performance Indicators (KPIs) to analyze the performance of an online financial company. Using Power BI, Excel, and AI-driven insights, the project provides data-driven recommendations to optimize business growth, customer engagement, and financial stability.

Project Objectives:

Revenue & Profitability Analysis:

Track total revenue, net profit, and growth trends.

Identify high-value financial products and services.

Measure ROI and customer lifetime value (CLV).

Customer Behavior & Retention:

Analyze customer acquisition cost (CAC) vs. revenue per user.

Predict churn rate and customer retention using AI models.

Identify high-value customers and segmentation strategies.

Risk & Fraud Detection:

AI-based anomaly detection for fraudulent transactions.

Risk scoring models for customer financial behavior.

Operational Efficiency:

AI-driven employee performance metrics.

Cost optimization and efficiency tracking.

AI-Driven KPIs Used:

Financial KPIs: Revenue Growth Rate, Gross Profit Margin, Net Profit Margin, Return on Assets (ROA).

Customer KPIs: Customer Acquisition Cost (CAC), Customer Lifetime Value (CLV), Churn Rate Prediction.

Risk KPIs: Fraud Detection Accuracy, Risk Score, Compliance Adherence.

Operational KPIs: AI-Driven Employee Productivity, Cost-to-Revenue Ratio.

Tools & Technologies Used:

Excel: Data preprocessing, pivot tables, and trend analysis.

Power BI: Interactive dashboards with AI-powered insights.

AI Models: Machine Learning algorithms for churn prediction and fraud detection.

Final Deliverables:

AI-Powered Financial Dashboard with real-time KPIs.

Customer Segmentation & Churn Prediction Report.

Fraud Detection & Risk Assessment Visualizations.

Strategic Recommendations for Business Growth.