Most of the wealthiest people in South Korea own real estate. Real estate investing in Korea is considered one of the top long-term investments people can make. In addition, unlike stocks, with real estate, plenty of deals can be found if you do your research. The truth is real estate all around the world is not priced perfectly. Therefore people can find great deals. However, most buyers don’t have the time to do proper research.
XAI Land is a real estate startup that uses big data and AI to offer the most accurate and comprehensive automated valuation models (AVM) that value residential and commercial uses. An AVM is an estimated value for any kind of property. However, AVMs have been prone to be highly significant to residential properties. In Korea, AVMs that have been developed are proven to be not as accurate as AVMs used in the United States and other countries.
AI is being used in the financial sector. There are hundreds of AI Robo-advisors out there. However, few platforms use AI when dealing with real estate. Real estate is significantly more complicated than buying stock. Therefore it requires a lot of your time. In addition, you need to understand concepts such as leverage and short/long-term financing.
Therefore XAI Land created its own AVM service based on AI, big data, and machine learning technologies. Users can discover the current instantly and predict the future market value of any property in Korea. Best of all, users can do this right from the comfort of their homes. Their AVM tool is being well-received by real estate service providers. The strong team at XAI Land consists of data science, real estate, and software developers.
“I believe our database and proprietary AVMs and software can contribute to making the real estate market in Korea more transparent, which can eventually bring it to the attention of an increasing number of global investors,” said the CEO of XAI Land, Raymond Chetti
Koreans rely heavily on realtors for market information when looking to buy a home or office. However, being able to sit down and talk to a broker about the value of a property can be a daunting experience. Especially if the realtor is not equipped with any data, market reports, or insight. Data such as this is critical in understanding why a property’s value is what it is.
On the other hand, sellers must pay additional costs to appraise their property.
AI has evolved to a point over the last decade where it can analyze data, draw conclusions, and produce authoritative reports. These reports allow stakeholders such as real estate brokers, buyers, and sellers to more confidently and easily see eye-to-eye when understanding a property’s true market value.
Several real estate firms in the United States are already integrating AI to estimate real estate and supplement their human appraisal work.
The key is not only about having the right amount of data. It is about how you process, analyze, and feature engineer it. Not just numerical data such as transaction values, but other factors that make each property unique. Everyone in Korea has access to the same data sets provided by the government’s open data portal. However, it is about the knowledge and experience of the team to make that open data valuable.
The best way to think about XAI Land’s work and related results is to think of them as a superstar team of chefs. You can think of “data sources” like “supermarkets and other local food markets,” “data” like “ingredients necessary for a recipe”, and their “start-up team” as the “team of chefs” in the same kitchen who are working together to cook the best meal. Just because a chef knows where an Emart is located does not mean they know how to cook the most amazing Samgyetang (Ginseng Chicken Soup).
XAI Land uses machine learning for data-driven property valuations in South Korea as the company currently has a database for 3.2 million villa units in Seoul and is working to expand its database to Seoul’s surrounding suburbs, Gyeonggi-do, which composes over a quarter of the country’s total population (13.53 million people spread out over 10,171 km2 of land).
Machine learning is a form of AI that allows people to understand the impact of large amounts of data. XAI Land analyzes large amounts of data to cluster together properties in the country with similar attributes and features. We are talking about hundreds of thousands of prior real estate transactions and listings by large amounts of data. In addition, XAI Land can consider some of a property’s key attributes or features. This includes factors that might be driving up or lowering their value. Some of these features include supply/demand (number of transactions over time), socio-demographics, and infrastructure.
XAI Land reports will contain data and analysis that allows users to understand property details. Details include similar comparable properties, historical price growth, and surrounding real estate market conditions. They offer reliable data for those looking to make the smartest decision possible. XAI Land has the most comprehensive real estate data/analytics database and APIs.
The company aims to allow users to upload their own Excel files to their system. This will allow companies to download data directly to perform their own analysis. As well as integrate XAI land’s APIs into internal systems.
Feel free to try XAI Land by scheduling a demo through their site.
XAI Land recently signed an MOU with WeFunding, an online real estate investment company. The MOU agreement will be for WeFunding to use XAI Land’s automated valuation models (AVM) for their mortgage review system. XAI Land will provide the data necessary for WeFunding’s screening process for real estate investment. In addition, XAI Land will provide a future valuation model based on machine learning.
“Through this business alliance with XAI Land, WeFunding’s review system has been further advanced and refined to provide more stable investment products to investors,” said the CEO of WeFunding, Jisoo Lee.
WeFunding has a patented system that diversifies and designs product portfolios tailored to suit the customer’s asset structure and goals. For example, it analyzes the correlation, profitability, and stability of the office market in China, the logistics center market in Seoul, and the hotel market in New York, and allocates the investment stake in each product group according to each individual investor.
Therefore, if you are single and in your 30s, the risk is higher than that of a married person in their 50s. So the portfolio will be composed mainly of short-term investment products with high returns but higher risk.
“The agreement with WeFunding, the first patented technology-based real estate investment company in the industry, will contribute to resolving the asymmetry of real estate information that exists between ordinary and professional real estate investors,” said the CEO of XAI Land, Raymond Chetti.
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