Real Estate Analytics (R.E.A.): Delivering Unique Intelligence for Real Estate

Jean-Michel Paul, CEO, Real Estate Analytics (R.E.A.)Jean-Michel Paul, CEO
Headquartered in Singapore, Real Estate Analytics (R.E.A.) is driven by the mission of providing the best-in-class property analytics and solutions with a transparent data-driven approach. While the company is today well-recognized in the real estate market, its history entails years of dedication and perseverance. It all started when Jean-Michel Paul, the current CEO at R.E.A., was doing his PhD at the Berkeley Haas University. For a young Paul, the university’s dedicated library used to be the most interesting part to visit. “By all accounts, it was fascinating—but at the same time, useless. Doing my dissertation, I used data mining algorithms for the first, or one of the first times, in the field, but was consternated to see how unusable real estate data was,” he said. In the later phase, Paul progressed in his career but couldn’t get this fact out of his mind. After business successes in fund management and fintech in the UK, he revisited this challenge and came back to Singapore with the idea of solving it.

Soon enough, with two bright co-founders possessing exceptional skills—Patrick Yan as CTO and Jiajia Yao as Head Quant—Paul set the foundation of R.E.A. from a simple one-room office in 2019.
“Equipped with cutting-edge technology and a data-driven statistical approach, we believed that everyone can be empowered to make smart, holistic property decisions in their life,” mentions Paul. Today, the company harnesses the power of proptech without the constraint of physical boundaries by organizing the world’s information and making it universally accessible and useful.

At its core, R.E.A.’s mission is to provide Accessible Organized Property Data with Empowering Tailored Solutions, starting with Asia. This is then complemented progressively by a wide array of images, listings, energy, and building characteristics. “We joke that if there is a black cat in the neighbourhood our database needs to know it,” smiles Paul. The company developed a set of unique algorithms to derive more data (extraction or extrapolation) and intricate ‘tools’ that can be assembled to offer a tailored solution with a specific set of users in mind. The data and tools are then put together to be accessible in unique ways. “You can zoom in or delimit any universe you deem useful according to any criteria. This enable outputs that were simply not possible before, such as an index for a specific neighbourhood,” states Paul. The company’s unique data set can be used in an array of smart cities applications, from considering an acquisition to exploring, renovating, and many more.

We aim to become the global reference for the real estate industry

Paul believes that R.E.A. is perfectly placed to be the PropTech 3.0 torchbearers. “Proptech 1.0 was about putting on the net what previously existed on paper format and Proptech 2.0 is about smart applications in the traditional real estate functions. What is enabling Proptech 3.0 is the quantification of real estate related data in unprecedented ways. This digitalization enables the discovery of new and better ways of doing things in previously impossible ways,” he said. To this end, R.E.A. is rolling out its first dedicated AI applications in the traditional real estate markets and specific tailored segments, such as sustainability, tokenization, and investment. The company is also expanding geographically to cover 500 million people in Asia within 18 months, and its public data explorer will be made available in three countries by year-end. “We aim to become the global reference for the real estate industry,” concludes Paul.
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Company
Real Estate Analytics (R.E.A.)

Headquarters
Suntec Tower Two, Singapore

Management
Jean-Michel Paul, CEO and Patrick Yan, CTO and Jiajia Yao, Head Quant

Description
R.E.A.’s mission is to provide Accessible Organized Property Data with Empowering Tailored Solutions, starting with Asia. This is then complemented progressively by a wide array of images, listings, energy, and building characteristics. The company developed a set of unique algorithms to derive more data (extraction or extrapolation) and intricate ‘tools’ that can be assembled to offer a tailored solution with a specific set of users in mind. The data and tools are then put together to be accessible in unique ways.

"We aim to become the global reference for the real estate industry"

- Jean-Michel Paul, CEO