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Munich (dpa) - The idea sounds good: If you are looking for a property, you simply enter an address on a map and get an overview of the property prices on site.

This can be an advantage for buyers.

Because with the knowledge of the price level, you may be able to get something out of negotiations with a provider.

This, in turn, can help sellers create an offer.

"So far there is hardly any information for this part of the market," says Scoperty managing director Michael Kasch.

"This is why prospective buyers and sellers often find it so difficult to find a fair price for a property."

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With his new company, Kasch wants to change that.

The start-up, which has been on the market since mid-November 2020, uses data from market research institutes such as Infas 360 GmbH or the real estate appraiser Sprengnetter to feed an algorithm that can use it to provide estimates for more than 35 million residential properties in Germany.

For example, previous transaction data in the area are included in the assessment, as well as offer prices and location information as well as data from land registry offices, for example: the address, estimated size of the residential and property, the year of construction and the property type.

The estimated prices are then displayed on a map for each street and for each house number.

But does such data really offer added value?

"If it is promised that Big Data can offer more price transparency than before, that makes me skeptical," says Steffen Sebastian, economist at the University of Regensburg.

The reason: "Properties are heterogeneous goods."

This means that houses and apartments differ and are only interchangeable to a limited extent.

"In order to make valid statements, you need in-depth information."

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“Take row houses, for example,” explains the holder of the Chair of Real Estate Financing.

“They are all similar, but they differ in terms of equipment and condition.

All of this has an impact on the value of the property. "

The price can vary considerably from one house to the next, depending on its condition.

"Even the question of who an apartment or house is rented to can play a role."

Scoperty founder Kasch knows that too.

“This means that owners can also set specific data for their property,” he explains.

The value for an object can thus be specified more precisely.

If you want to sell, you can mark your house or apartment as open to bids.

If interested, buyers can contact the owner via the platform.

On this marketplace, however, data from properties that are not for sale at all also appear.

"A price tag for a property that is not for sale does not lead to more transparency, but to more misunderstandings," criticizes Matthias zu Eicken from the owners' association Haus & Grund.

Kasch counters: "If you don't want your property's data to appear, you can have it deleted."

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To Eicken, however, there is another catch: In his view, the price ranges given leave too much leeway.

For apartments in an apartment building in a sought-after Frankfurt location, for example, estimated areas of 57 to 105 square meters and prices of around 435,000 to 808,000 euros are displayed on the portal.

Detached houses in the north of Hamburg range between 1.1 and 1.6 million euros.

There is a great risk that the tool's assumptions will sometimes be wrong.

The broker association IVD is also still suspicious of the start-up.

“Scoperty is not much help at the moment, it confuses more than it helps,” writes Stephan Kippes, head of market research at IVD Süd in Munich, in a recently published article.

Kippes doubts whether a reasonable algorithm can be developed in view of the many variables involved in the assessment and the relatively poor access to the initial data.

Owners intending to sell should consult an expert, says Haus & Grund.

The value of a property depends on many factors.

Economist Sebastian, on the other hand, at least emphasizes that an offer like Scoperty's can be a rough guide for buyers or sellers.

"In the end, however, you have to go to the market with a realistic asking price."

© dpa-infocom, dpa: 210301-99-635302 / 2

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