Invoice combines auction prices for art with reasoned catalogs – ARTnews.com



Not so long ago it was possible to attend a prestigious art fair in a world capital where you might find two very similar works of art displayed on the stands of two different dealers who could have placed very different asking prices for the works. How wild? Try a million dollar difference or a work for twice the price of its near-twin.

This was not supposed to happen in a world where the art market would have achieved some form of price transparency. Although auction price databases were the first – and for a long time the only – form of transparency and innovation in the art market, this data was not widely or easily accessible. The databases that housed the information, either in the auction houses themselves or in the aggregators, were built with archaic technology. In an increasingly interconnected world, price data has remained in silos that are difficult to access.

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In recent years, auction houses have made their data easier to discover through research. This allowed buyers to guess at a fair price for a work of art in a gallery or at an art fair a more accessible independent point of reference. It was fine, but there’s a lot more to understanding the importance and appeal of a work of art than a few random prices at public auctions.

“Relying on auction prices alone will never give you half the truth,” says Christian Huhnt who, along with Dimitris Hermann, has spent the last five years building Facture. “To identify the right price for a work, it must be placed in the context of other works by the artist. You have to understand the distribution of works in public and private collections and assess the likelihood of these works entering the market. Only by connecting catalog raisonné data to auction data can you get this powerful 360-degree overview.

To deal with the fragmentation of reasoned catalogs and auction prices, Huhnt and Hermann tried to anticipate. What do dealers and auctioneers need to do their jobs better that can also be of value to art advisers and their clients, and even to the larger institutional community around museums and public galleries?

The response is in the form of an Invoice, a new service launched this month. Today Invoice combines data from the reasoned catalogs of over 60 of the most traded artists with millions of images and auction prices, museum inventory and gallery listing sites. This reconciled data can show not only what price a work of art has sold at auction, but also who owns similar works which, as everyone knows, has a big effect on the value of a painting, a sculpture or other type of work of art.

Bill can be searched manually by entering relevant information about an artist or work of art. But it can also be searched by image. Upload a photo of a work of interest to you and Invoice will return the catalogs or auction data to you. Invoice will also allow you to submit a photo from your phone via Whatsapp or Telegram. Invoice’s chatbot responds by identifying the work and providing its data. This feature is already in use by major auction houses in the United States and Europe and by the Hermitage Museum in St. Petersburg, Russia.

The objective of Huhnt and Hermann is not simply to cross the prices of existing exchanges and auctions. Their sight stretches towards the distant horizon. The information and data surrounding works of art and the artists who created them are abundant and diverse. Combining auction prices and catalog raisonné data is only the first step in what Huhnt and Hermann hope will be a larger project. Value in art is underpinned by scholarship. They hope to rethink and reinvent the way catalogs reasoned are published, edited and used. Artistic data is notoriously difficult to come by. But making it accessible is only the first step in building a platform that sparks interest in art, educates the market, and serves all stakeholders in the art world beyond the marketplace. to collectively build a better system for the historical heritage of art.

Bill is in beta, for now. Users are prompted to sign up and provide a credit card (which will not be charged without the customer’s permission.) Once the service exits beta and switches to a subscription model, users will be prompted to choose a subscription plan based on their early user status.


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