Big Data Technology for the Small Mortgage Company: Guest Li Chang of Recursion Co. Explains
Finding Genius Podcast
Richard Jacobs
4.4 • 1K Ratings
🗓️ 19 November 2020
⏱️ 27 minutes
🧾️ Download transcript
Summary
The mortgage space spits out a seemingly insurmountable level of complex numbers. Accessing clean data from interest rates and housing markets alongside numerous other elements in the mortgage space is no small feat. This podcast presents the CEO of one company that says they can do just that. Listen to hear how big data and its importance meets data democratization.
Listeners will learn
- How Li Chang's career path in big data analytics and housing market economics led her to start Recursion Co. and its new approach to data,
- What big data versus data science means in the context of "cleaning up" data by arranging and normalizing it into usable information, and
- What her company has been able to achieve thus far and what types of customers they are seeking.
Li Chang is the Chief Executive Officer of Recursion Co. After achieving a graduate degree in computer science, she returned to get her PhD in mathematics while working full time at Morningstar. She worked for a hedge fund soon after graduating as a financial engineer and has been working in the mortgage space ever since.
She started Recursion Co. in 2015 when she needed a new challenge and saw a clear need for such a company in the industry. Mortgage data is so immense, she says, that is too big for most companies to handle. Plus, because she knew the capabilities of computer science and data science, she felt Wall Street was not taking advantage of Silicon Valley advancements. Analyzation systems in the mortgage space were very clumsy and "messy."
Li Chang realized that she had the ability, tools, and know-how to put these very complicated numbers together and address the mortgage space data issues in a much more efficient way. She also knew she could make it affordable for a broader audience, calling this effort "data democratization." What exactly does this look like? They rearrange and normalize the chaotic data, bringing it together from many sources in a way that tells the whole story.
Currently, they are looking for smaller companies in the mortgage space as customers. They can help companies who don't have a lot of human resources or technology in-house by providing them with the equivalent resources as if they have a big company behind them.
For more about their work, see their web page, recursionco.com and follow their blog on LinkedIn.
Available on Apple Podcasts: apple.co/2Os0myK
Transcript
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| 0:00.0 | Forget frequently asked questions common sense common knowledge or Google how about advice from a real genius |
| 0:06.8 | 95% of people in any profession are good enough to be qualified and licensed 5% go and beyond. They become very good at what they do, but only 0.1% are real Jesus. |
| 0:18.3 | Richard Jacobs has made it his life's mission to find them for you. He hunts down and interviews geniuses in every |
| 0:24.7 | field, sleep science, cancer, stem cells, ketogenic diets and more. Here come the geniuses. |
| 0:30.1 | This is the Finding Genius Podcast. |
| 0:33.0 | That are Richard Jacobs. |
| 0:35.0 | Hello, this is Richard Jacobs with the Finding Genius Podcast. |
| 0:41.0 | I have my second guest from a company called Recursion Co. |
| 0:45.0 | The website is Recursion Co.com. |
| 0:47.0 | I have Lee Chang, she's the chief executive officer. |
| 0:50.0 | I'm going to talk about how they're using big data to analyze the mortgage and the housing market. |
| 0:54.4 | Lee, thanks for coming. |
| 0:55.4 | Thank you, Richard. |
| 0:56.4 | I'm glad to be here. |
| 0:57.6 | So tell me a little bit about your background and what, how did you come to, you know, to work for or found a recursion co? |
| 1:04.8 | So in 97, I went to Chicago for graduate school. |
| 1:08.8 | After two years, I got two master's degree, |
| 1:11.4 | when in urban planning and the other one is in mathematics and the computer |
| 1:15.4 | finds. And I realize computer science is a lot easier to help me finding a job. So I started to work for a company called Morningstar. |
| 1:25.8 | When I was working there, I found the work there is not challenging enough. I still |
| 1:31.1 | Thursday for interesting things. |
| 1:34.0 | So I enrolled in a PhD program back where the school I attended. |
... |
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