XYZ Bank Customer Churn Predictor
AI-Powered Bank Customer Churn Insights, Automated Retention
# Sales AssistantWhat is XYZ Bank Customer Churn Predictor?
Full-stack Bank Churn Predictor analyzing 4,000+ records with SVM/XGBoost (84%+ accuracy), SMOTE-balanced. Features dashboards, LLM-powered churn insights (Mistral Saba 24B), & automated retention emails—built with Python, SQLite, HTML/CSS & Streamlit.
Problem
Bank customers face high churn rates due to manual or basic analysis methods that lack predictive accuracy, real-time insights, and actionable retention strategies.
Solution
AI-powered predictive analytics platform where banks can predict churn with 84%+ accuracy via SVM/XGBoost models, visualize trends via dashboards, and automate retention emails using LLM-generated insights (Mistral Saba 24B).
Customers
Bank managers, customer retention managers, and data analysts at financial institutions seeking data-driven solutions to reduce churn and improve retention.
Unique Features
Integration of SMOTE-balanced ML models with LLM-powered insights, real-time dashboards, and automated email workflows in a single full-stack tool built with Streamlit.
User Comments
High accuracy in predicting churn compared to traditional methods
Automated retention emails save time and improve customer outreach
LLM insights provide actionable recommendations
User-friendly dashboard simplifies data interpretation
Effective for mid-sized banks with limited data teams
Traction
Analyzes 4,000+ records per deployment; no disclosed MRR/user metrics. Built with Python, SQLite, and Streamlit as per ProductHunt description.
Market Size
The global banking customer retention software market is projected to reach $1.2 billion by 2027 (MarketsandMarkets, 2023).
