Unlocking real-time credit scoring with Django and Google Vertex AI. In this project, I build a full pipeline that reads an M-Pesa PDF statement, extracts transactions, analyzes financial patterns, and generates a credit score using a custom Python scoring engine — enhanced with Gemini for AI-driven insights. This walkthrough covers: 🔹 Parsing M-Pesa statements using PDFPlumber 🔹 Extracting transactions into clean JSON 🔹 Running a rule-based credit scoring model 🔹 Using Vertex AI Gemini to generate financial summaries 🔹 Building a Django dashboard for score visualization 🔹 Integrating AI securely using API keys / service accounts What you get is a practical, end-to-end fintech workflow showing how AI can support digital lending, risk analysis, and real-time financial insights. Perfect for developers exploring: ✔ Fintech engineering ✔ Django + AI integrations ✔ Google Vertex AI ✔ PDF automation ✔ Loan decision systems ✔ Server-side AI workflows 🌐 Website: 🎙️ Podcast: 🌎 Find Me Here: 🌐 Website: 🐦 Twitter: [ /bryan_oginga ] 📲 WhatsApp: 👨‍💻 Developers WhatsApp Community: