Rsquare, a leading domestic commercial real estate integrated service corporations, marked the first anniversary of launching its data platform RA (Rsquare Analytics) and unveiled the test-run results of its commercial real estate data solution and its expansion strategy based on artificial intelligence (AI).
On the 2nd, Rsquare Chief Executive Lee Yong-gyun said at the company's first inaugural briefing held at the Plaza Hotel in Jung-gu, Seoul, that "with the advent of RA, we opened a new era in the commercial real estate market—one that is based on data infrastructure rather than personal networks," adding, "we plan to advance services by integrating AI based on the insights we have accumulated."
RA, now in its first year since launch, achieved meaningful results both quantitatively and qualitatively. It currently provides data on more than 7,000 commercial real estate assets nationwide, and detailed data averaging 10,000 cases per month and totaling more than 100,000 cases have been used in transaction and valuation work. Within eight months of launch, RA was also introduced to more than 50 institutions, including Singapore's GIC, Germany's DWS, and PAG.
Now, one year after launch, the number of clients has grown to 150. They include the financial sector, asset managers, and investment institutions such as Woori Bank, the first among the four major domestic commercial banks to adopt RA, Samsung Securities, IGIS Asset Management, Koramco REITs Management and Trust, and Hyundai Commercial.
An Rsquare official said, "The fact that large domestic and overseas investment institutions refer to RA data for investment evaluation and use it for key decision-making is proof that it has achieved global-level consistency and completeness," adding, "based on the trust as a 'solution used by top-tier financial and investment firms,' the adoption by major corporations across various fields is gaining momentum."
According to Rsquare, until RA appeared, Korea's commercial real estate data market lacked an optimized infrastructure. Overseas services such as RCA (Real Capital Analytics) or CoStar focused on transaction case statistics or country-level data, limiting their ability to reflect the micro characteristics of the domestic market. In contrast, RA fills this gap with precision data tailored to the domestic market, the company said.
Lee Yong-gyun said, "For large building transactions, RA is the only tool that can comprehensively view such detailed information," explaining, "this is why financial companies and institutional investors, who value reliability and accuracy, are adopting it one after another."
The RA solution provides real-time micro and macro comparative information, including lease status and profitability indicators of individual assets, long-term market trends, and benchmark data by region. Users can easily obtain information that previously could only be identified through personal networks or separate service engagements. It also incorporates field due diligence-based data and reflects lease terms and building operations information that existing third-party solutions cannot provide.
In practice, the financial sector, including banks, reviews the lease status of collateral real estate, the latest transaction cases, and market price changes when assessing credit and making loan decisions. Securities analysts and investment managers cite lease histories and market indicators provided by RA to prepare investment reports and research materials and to establish portfolio strategies. Asset managers verify through RA's vast market price database whether the cap rate of an office building under acquisition review is appropriate compared to the market average. In addition, during the investment review process, they can use RA's benchmarks for rent levels and vacancy trends of comparable assets.
Based on its accumulated vast data, RA plans to sequentially introduce next-generation features incorporating AI to enhance the solution's value. First, it is preparing AI services that automatically calculate the current value of individual properties and future rent growth by developing an automated valuation model (AVM) and a rent forecasting model. Users will be able to more easily gauge the future profitability of target assets or appropriate purchase prices. Through this, RA will move beyond past data analysis to provide predictive value that supports future decision-making.
In addition, RA will upgrade its existing geospatial, location-analysis function so that its AI algorithm presents an investment suitability index by comprehensively analyzing location conditions and surrounding commercial district data. When selecting locations or establishing development strategies, the data will automatically capture patterns and variables that people tend to miss. It is expected to offer new insights for real estate development and investment decisions.
Moreover, Rsquare will continue strengthening services such as RA's automated customized report function and the enhancement of its English interface. Depending on investor needs, AI will generate tailored reports, and an authoritative English service with glossaries of technical terms and real-time translation will be provided so global investors can use it easily.
Finally, RA will expand its data coverage beyond logistics and office to various industry domains such as residential and retail, where institutional investors are seeking to expand. Through this, RA plans to evolve into a comprehensive data solution across the entire real estate asset class.
RA currently has time-series databases built for information on more than 7,000 commercial real estate assets nationwide. Among them, about 1,600 major office buildings and more than 1,100 logistics centers are visited and verified monthly by a specialized research team of more than 60 people to update the latest information on rents, tenants, and vacancies. By directly confirming and reflecting detailed elements that are difficult to grasp with official documents such as building ledgers—such as actual rent levels, current vacancy status, temperature ranges of logistics facilities, and whether truck docking is possible—the precision of the data is enhanced.
Lee Yong-gyun said, "RA is a precision commercial real estate analysis solution that has dramatically lowered the information barrier in the domestic market," adding, "through constant improvements in data quality and practicality, we will establish a unique position as the 'Bloomberg' of the real estate industry. Furthermore, we will stand shoulder to shoulder with global real estate analytics services such as CoStar and RCA."