Case Study: Fannie Mae improves mortgage forecasting with Wolfram technologies

Fannie Mae cuts mortgage forecasting development time with Wolfram

Fannie Mae financial economist Bernard Gress sought an innovative approach to forecasting mortgage stability, a complex challenge requiring the development of new predictive models. To tackle this, Fannie Mae utilized Wolfram technologies to create a sophisticated genetic algorithm system.

The solution developed with Wolfram technologies simultaneously finds the optimal model structure and the optimal dataset for making final predictions. Gress stated that using Wolfram's expression-based framework saved years of development work by allowing for direct manipulation and easier visualization of data and functions. He concluded that Wolfram technologies are superior for this kind of project development, enabling his team to focus on issues and iterate much more quickly.

Fannie Mae