Project Overview
FinTech Corp, a financial services platform, wanted to predict customer churn and optimize investment recommendations using AI and machine learning. They approached SOFTLEOAI to develop a predictive analytics engine.
Challenges
- Manual analysis of customer data led to delayed insights
- Difficulty in identifying high-risk accounts and potential churn
- Inefficient investment recommendation system
Our Solution
- Built a Python-based machine learning pipeline using scikit-learn and XGBoost to predict customer churn
- Integrated real-time data processing with Apache Kafka for immediate insights
- Developed a dashboard using React and Dash to visualize predictions and actionable metrics
- Implemented AI-driven investment recommendation engine personalized for each customer
Results / Impact
- Reduced customer churn by 25% within 3 months
- Automated data analysis cut processing time by 60%
- Improved investment conversion rate by 18%
- Management gained real-time insights for strategic decisions
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