Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Olamieee/Financial-Services-Churn

Domain:

digital infrastructure

Record type:

softwaremodel
Creator:
Ola
Host:
ChurnGuard AI is a machine learning-powered web application that predicts customer churn risk for financial institutions in Nigeria. # ChurnGuard AI 🎯 **Predictive Customer Intelligence for Nigerian Banks** ChurnGuard AI is a machine learning-powered web application that predicts customer churn risk for financial institutions in Nigeria. Built with Flask and scikit-learn, it provides real-time predictions to help banks retain valuable customers. ## 📋 Features - **Real-time Predictions**: Get churn probability in under 3 seconds - **Batch Processing**: Upload CSV/Excel files for bulk predictions - **High Accuracy**: 95.2% prediction accuracy - **Nigerian Market Focus**: Tailored for Nigerian banking customers across all 36 states - **User-Friendly Interface**: Clean, responsive design that works on all devices - **Actionable Insights**: Get retention recommendations based on risk levels - **Risk Categorization**: Automatic classification into High, Medium, or Low risk - **Template Download**: Sample file provided for easy batch uploads ## 🚀 Quick Start ### Prerequisites - Python 3.8 or higher - pip package manager ### Installation 1. **Clone the repository** ```bash git clone github.com cd churnguard-ai ``` 2. **Create a virtual environment** ```bash python -m venv venv # On Windows venv\Scripts\activate # On macOS/Linux source venv/bin/activate ``` 3. **Install dependencies** ```bash pip install -r requirements.txt ``` 4. **Run the application** ```bash python app.py ``` 5. **Open your browser** Navigate to `127.0.0.1` ## 📦 Project Structure ``` churnguard-ai/ ├── app.py # Flask application ├── templates/ │ └── index.html # Frontend template ├── financial_churn_model.pkl # Trained ML model ├── encoder.pkl # Label encoders for categorical features ├── scaler.pkl # Feature scaler ├── requirements.txt # Python dependencies ├── README.md # Project documentation └── .gitignore # Gi …

Visit

github.com

Similar

Olamieee/PolySentOlamieee/yoruba-emotionOlamieee/yoruba-emotion-modelOlamieee/Kinyarwanda-Hatespeech-DetectionOlamieee/yoruba-emotion-tokenizerCustomers Churn Prediction in Financial Institution Using Artificial Neural Network

Olamieee/PolySent

Multilingual sentiment analysis and content moderation for English, Yoruba, Nigerian Pidgin, Kinyarw

Olamieee/yoruba-emotion

Fine-tuning AfroXLMR on SemEval-2025 Task 11 for multilabel emotion detection in Yorùbá, a low-resou

Olamieee/yoruba-emotion-model

Olamieee/Kinyarwanda-Hatespeech-Detection

# Kinyarwanda Hate Speech Detection App A machine learning app to detect **hate**, **normal**, or *

Olamieee/yoruba-emotion-tokenizer

Customers Churn Prediction in Financial Institution Using Artificial Neural Network

In this study, a predictive model using Multi-layer Perceptron of Artificial Neural Network architec