“Imagine if you could save through this rent what are you paying for in the future buy property in which you live. At the same time, as landlords, consider getting a higher rent and at the end of your agreement with your tenant, sell it to them, possibly for a higher price than at the beginning of the lease.” With these words, the professor of economics Kostas Zachariadis explains the “K” model that has been implemented by Adjoin Homes since last year (www.adjoinhomes.com), which he founded in London with atomic doctor and quantum physicist Mario Tsatsos.

“In 2020, despite a stable income and a good job as a university professor, I found myself unable to buy my own property after 12 years of renting in London. The amounts we spent on rent were not returned. This is how the idea of ​​​​creating Adjoin Homes in 2022 was born,” says Mr. Zachariadis.

The company is already preparing a stage for its launch in Greece as well, starting in January 2024. But how exactly does the model proposed by the company work?

First, the tenant and the landlord agree on a certain duration and a certain amount of rent, for example. 1000-1200 euros for three years. However, the rental rate is higher than similar properties in the same area. This is the first difference. The higher rent the owner receives is his first incentive to use the service. In return, the tenant will be able to use this additional amount to purchase property after three years at a price below that which will prevail on the market. If, for example, the property at the beginning of the contract is worth 250,000 euros, and after three years the amount has increased to 300,000 euros, the tenant will be able to buy it instead for 275,000 euros. He will make good use of the extra money he has given through rent. In addition, both parties agree at the beginning of the agreement on the minimum amount of the purchase of real estate, for example. in the event that the sale prices decrease in the period of time prior to the expiration of the agreement.

A correct estimate of the future value of a property is the “key” to an agreement between landlords and tenants.

“We believe we can bring the Adjoin model to the Greek market as the benefits for tenants and owners are numerous. Renters, on the other hand, use some of the money they spend on rent for a future purchase, they know the area and property better, and can purchase property at a price below what will prevail in a few years. today,” notes Mr. Zachariadis. Accordingly, owners from the first day receive a higher rental income, as well as potential buyers of their property. This element is especially important as wear can be avoided in this way, which is quite common and increases operating costs for owners.

The model is especially attractive, for example. for people who have bought or rented other property and want to increase their income from a property they do not use. At the same time, they also provide a potential buyer in the long term, without losing capital gains in the future, from a possible price increase. So, if today, for example. the market is not in high demand or the prices are unsatisfactory, the owner can use this model to delay the sale until a later time, securing a higher rent immediately. Accordingly, tenants can start saving money to buy the property they live in.

Artificial intelligence

Adjoin uses artificial intelligence technologies and analytics to select properties suitable for implementing this model. As a rule, objects and areas where prices are expected to rise in the future are selected, since the correct assessment of the future value is “key”.

To date, the experience of England has shown that there is a high demand from interested tenants, mostly young couples, for high-level positions. Without this decision, they would need at least 10 years of savings, paying out amounts in rent that they would not be able to use for any other purpose. “Had I had this solution since 2009 when I started renting an apartment in London, today I would have saved £100,000 which I could use to buy it,” says Mr Zachariadis.