Quantifying Risk Analysis at Freddie Mac

Imagine a friend asks to borrow some money. Before you answer, you likely will consider the risks involved with lending the requested amount.

What happens if they don't pay you back when they say will?

What if they don't pay you back at all? 

Those are the types of questions Huadong (Walter) Yang (MSIT '23) confronts on a daily basis, but instead of lending money to a friend, he's focused on single-family home buyers. Yang is a senior quantitative risk analyst at Freddie Mac, the stockholder-owned, government-sponsored enterprise designed to support American homeownership.

Freddie Mac buys loans from mortgage lenders, combines them, and then sells them as mortgage-backed securities.

"How to manage the credit risk is critical for Freddie Mac to operate in this housing financing cycle," Yang said. "My team monitors the credit risk models to make sure these models perform well."

In the past, much of Freddie Mac's analyzing and reporting processes were done manually, Yang said. He helped create several tools to help his team automate those processes — a change that improved efficiency and reduced operational risks.

"In this role, I can see my impact immediately," he said. "If I identify an issue in the current model and provide an improvement accordingly, I can see the model have a better performance next month. This really excites me and pushes me going forward."

Yang analyzes the major drivers for current credit risk trends and provides model improvement advice to his senior management team. "I enjoy working with numbers, and this type of role is a perfect fit for me," he said. "I can apply my technical skills and business knowledge to address issues in the real world.

To do that, Yang relied on lessons learned in Northwestern Engineering's Master of Science in Information Technology (MSIT) program.

Yang's introduction to risk analysis at Freddie Mac came as a student in MSIT. Yang spent four months as a quantitative risk intern with the company. During that time, he collaborated with climate risk colleagues to study the impact of future sea rises on coastal homes.

He also performed global sea level predictions, developed python scripts to collect geospatial data, and designed a Tableau dashboard to monitor sea level rise impact. 

"I am in the center of the US housing market," Yang said. "I can learn a lot about the mortgage industry and experience the latest developments in this space. I have the opportunity to analyze massive datasets and extract useful insights for decision making." 

The combination of technical knowledge and business acumen is what initially drew Yang to MSIT. Once in the program, he learned the basics of data science and discovered an interest in machine learning. He applies those lessons to his work on a daily basis.

"Pursuing a MSIT degree from Northwestern University was a no-brainer for me," he said. "This program taught me how to solve problems in a structured way. I learned how to break down a problem into several steps and deal with them one by one."