EstateGuru, like most other companies in the financial sector, is concentrating on data. Data and the quality of this data is the key to successfully building the ecosystem for universal global real estate financing and investing.
“This year’s focus has been on building a more data-driven organization for which we have created a data science team within the risk department. I’m happy to announce that, as of October, we’ve got our own data scientist, Ms. Nesma Almoazamy from Egypt, as well. Besides this appointment, we are also integrating more external data providers, including borrower and real estate data, into our systems. This move will lead to more automatic models for credit scoring, lead generation and marketing analysis. Consequently, we are changing how crowdfunding uses data, and we are building a data platform which will eventually also be suitable for machine learning “, says Andres Luts, Baltic Risk Manager, of recent developments at the company.
EstateGuru’s journey started in 2014 when the first loan was issued through the platform. Infrastructure for data gathering has been built from scratch by EstateGuru’s IT department and it takes into account the long-term growth vision of the business as well as best practices in the market. This tailor-made IT solution for data has helped EstateGuru not just to gather and save data, but also to analyze and extract the most value from it.
EstateGuru’s goal is to offer more value to investors and borrowers who use its services. It is impossible to maximize shareholder value without increasing customer value first. The key goals regarding data science are automatic data handling to make faster decisions for borrowers, the creation of more investment opportunities for investors, and maximizing investor value, not model complexity. Last but not least is the importance of scalability.
“I believe that, with the support of our team members, these goals are achievable in the coming years. The implementation of a data-driven culture at EstateGuru has not been difficult as we are flexible by nature, and we do not have to overcome a rigid legacy. Therefore we can continue disrupting the financial sector and data science scene in the future “, added Luts.