Customer lifetime value goes a step further than churn rate prediction. It uses retention (i.e. the inverse of churn) and a “discount” factor, which accounts for the decreasing value of future money to predict the expected monetary value that a customer will generate over the entire period of the relationship with your company.
In this blog, we will cover a broad spectrum of topics in Finance that relate to predicting trends and outliers on both the small and large scales. We will cover
- Commercial Growth Predictions by Monitoring Parking Lots
- Stock Predictions with Weather Forecasts
- Anomaly Detection use to find Fraud
- Market Forecasts with Sentiment Analysis
We introduce the concept of Reinforcement Learning and discuss how such an algorithm can be used to solve portfolio optimizations that extract the most value from raw market data. Over time, such algorithms learn the strategies to deploy that will generate the maximum possible value and consequently the maximum possible profit.