🏦 AI Banking Assistant Overview

AI Banking Assistant is an intelligent chatbot platform designed for modern banking services. It combines React (frontend) and Django (backend) with RAG (Retrieval-Augmented Generation), llm model Mistral served via Ollama, and fine-tuning, to deliver smart, real-time assistance to bank clients.

The system enhances customer support by enabling:

AI-powered smart responses

Ticket reservation and appointment scheduling

Automatic form filling for banking services

Fraud & falsification detection

✨ Features

🤖 Smart Responses: Answer customer queries (balances, services, card issues, FAQs) with context-aware, AI-powered replies.

📚 RAG Integration: Retrieve verified banking knowledge base entries to ensure answers are accurate and compliant.

🧠 Mistral + Ollama: Run models locally for secure, low-latency inference; supports fine-tuning for financial-specific terminology.

🎟 Ticket Reservation: Book banking appointments directly through chat (e.g., "Book me an appointment with a loan officer tomorrow at 10 AM").

📝 Smart Form Filling: Auto-complete loan applications, transfer requests, or account forms by extracting details from conversations.

🔒 Data Privacy First: Local model inference and configurable vector store for sensitive data.

🛠 Tech Stack

Frontend

⚛️ React (modern UI for chatbot & forms)

TailwindCSS (clean styling)

Backend

🐍 Django REST Framework

LangChain + Chroma/FAISS (for RAG and embeddings)

SQLite / PostgreSQL (database)

AI / Models

🧠 Mistral LLM served via Ollama

Fine-tuning support for banking-specific datasets

Retrieval-Augmented Generation for grounded answers

📂 Project Structure

Ai-Banking-Assistant/ │ ├── backend/ # Django backend (chat, APIs, RAG, reservations) │ ├── manage.py │ ├── requirements.txt │ └── apps/... │ ├── frontend/ # React frontend (chat UI, dashboards) │ ├── package.json │ └── src/... │ ├── .gitignore ├── README.md └── requirements.txt

⚙️ Setup & Installation Backend (Django + RAG + Ollama)

cd backend

python -m venv venv

venv\Scripts\activate # Windows

pip install -r requirements.txt

cp .env.example .env

python manage.py migrate

python manage.py runserver

Frontend (React)

cd frontend

npm install

cp .env.example .env

npm start

Ollama + Mistral

ollama pull mistral

ollama serve

🧠 How It Works

Client sends a message → Frontend sends request to Backend API.

Backend retrieves context with RAG from banking knowledge sources.

Mistral model (via Ollama) generates a response.

AI returns:

Smart banking answers

Pre-filled forms

Ticket booking confirmations

Badges

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🏦 AI Banking Assistant Overview

Features

• Client sends a message → Frontend sends request to Backend API.
• Backend retrieves context with RAG from banking knowledge sources.
• Mistral model (via Ollama) generates a response.
• AI returns:

Smart banking answers

Pre-filled form Questions for Auto-filling Forms

Ticket booking confirmations

🚀 Roadmap

• 🌍 Add multilingual support (English, French, Arabic)

• 🔗 Integrate external banking APIs for reservations & transactions

• 📊 Expand fine-tuning with real financial datasets

• 🐳 Dockerize for deployment

License

MIT