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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.

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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.

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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.

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For more about their work, see their web page, and follow their blog on LinkedIn.

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