Financial Loan Demand Forecasting
The Challenge
A financial service company wanted to offer better loan choices to its customers by forecasting their demand for different loan options. However, using traditional methods, it was difficult to account for the complex factors that influence customer behavior and preferences.
The Solution
We used big data and machine learning techniques to build a predictive model that estimates the demand for each loan choice based on contract level offer and historical purchase data. Our model can help the company adjust its loan pricing strategy according to customer demand and market conditions.
The Results
Our solution delivered impressive results. Here are some highlights:
- We improved the forecasting accuracy by 7% compared to the benchmark method.
- We used stratified sampling and feature selection to reduce the computational cost and complexity of the model.
- We provided actionable insights and recommendations for the company to optimize its loan pricing and increase its profitability.