FinTech & Data Analytics
FinTech & Data Analytics focuses on building applications that analyze financial data, visualize insights, and help users make smarter financial decisions. Projects in this domain involve data processing, financial dashboards, transaction analysis, and interactive visualizations using tools like Python, Pandas, and Plotly.
Skills
Technical competencies and proficiency levels in this domain.
Analytics
Data Processing
Visualization
Framework
Programming
Projects
Work completed in the FinTech & Data Analytics discipline.
Kapido – Ride Demand & Supply Analysis Platform
Kapido is a full-stack data analytics platform that identifies and explains demand–supply mismatches in ride-sharing systems. It uses machine learning models trained in Python to predict ride demand, estimate driver availability, and compute real-time gaps. The platform provides time-based and location-based insights, highlights shortage zones on a map, and offers actionable recommendations to improve driver allocation and operational efficiency.
MoneyMind – Personal Finance Dashboard
MoneyMind is a production-ready personal finance analysis dashboard built entirely in Python. The application allows users to upload bank transaction CSV files and automatically cleans, categorizes, and analyzes the financial data. It provides an interactive dashboard with real-time visualizations, spending trends, category breakdowns, and personalized savings recommendations. The system supports multiple bank export formats, automatically detects column aliases, merges debit/credit fields, and performs intelligent transaction categorization. The dashboard includes dynamic charts, heatmaps, spending insights, and theme customization (dark/light mode). MoneyMind helps users better understand their financial behavior, identify overspending patterns, and improve savings through data-driven insights.