e-værdi gives accurate property valuations

PR photo: Jørn Knudsen, CEO, e-nettet Fold sammen
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Kære læser. Artiklen her er en del af det engelske magasin Copenhagen Fintech. Indholdet er udformet på engelsk, da det også henvender sig til en udenlandsk læserskare, som deltager på eventen Money2020, hvor Berlingske Media er mediapartner. Magasinet er udformet af Berlingske Medias kommercielle redaktion i samarbejde med Copenhagen Fintech. God læselyst.

Sponsored by E-nettet

For ten years e-nettet has been working with statistical property valuations and has created a model that can be adjusted to the individual financial institutions and form the basis for positive customer experiences.

The financial sector uses statistical property valuations to ensure solvency both for portfolio management of property values and for credit evaluation of homeowners who want to take out new mortgages. Statistical property valuations, which are based on carefully prepared data, are essential for homeowners and homebuyers: for example, if one wants to sell one’s home or buy a new one.

With the e-værdi product, e-nettet has developed a model to calculate the current property value of homes whose high quality can be documented. And this is a valuable tool for employees in the financial sector.

”The tool is based on a regression analysis, with a number of explanatory variables that have significance for the property value as input. For example, it has data about prices in the local area within a given radius from the property in question,” says Steen Høy Hansen, a consultant at e-nettet’s Property Data Solutions.

”We examine the properties that have been sold in the area. I mean the properties that have been for sale “on the free market,” where they have been visible at an estate agent’s. This is important, because if you only base things on what is registered on the public registers as free sales, this can include things like transfers within families, where the price is often lower. We crosscheck with properties that have been on offer, and therefore we can say with certainty that they have been in free sale. This increases the quality of our data,” he points out.

Steen Høy Hansen, consultant at Property Data Solutions, e-nettet

e-værdi streamlines work in the financial sector
Since the model automates the process of estimating the value of properties, a fair amount of time can be saved at the mortgage and financial institutions. This time can be spent on giving better advice to bank customers.

Several financial institutions have developed their own solutions based on e-værdi, which have reduced the number of physical valuations carried out by consultants.

”In the financial institutions, you have a streamlined work process, where, in many cases, you can get a good idea of the property right at your desk, without having to go out and look at all the properties in a valuation. Accordingly, it is important for us to be able to demonstrate that our model has a high performance,” Steen Høy Hansen says.

”Our overall statistics reveal how accurate our evaluations are: our performance measurement shows that 90% of our city property valuations deviate less than 20% from the actual sales price, and that figure is even slightly lower on a national basis,” he adds.

The optimal circle
These high performance numbers are due to the long series of disparate data that are taken in and refined by the regression model. Some of that data include asking prices and reduced prices, as well as amenity values such as the size and age of the property and its location in relation to a motorway or a lake, which can influence the valuation in diverse ways.

”As well as that, the idea is to include properties that are close to the property you are valuing, and which have been sold within the shortest possible period of time. This is what we call the optimal circle. Less recent sales over a larger geographical area provide less certain data,” Steen Høy Hansen explains.

Jørn Knudsen, CEO, e-nettet

Tailor-made solutions
e-nettet is in possession of a considerable amount of diverse data, which can be supplemented with one’s own valuation data or other property data products. By doing this, a financial institution can get a tailor-made solution that meets the exact need that it has in relation to property valuations.

“We have made an additional standard solution that we call rating. We supplement the model value with some rating figures that can give the user a feeling of how safe the basis of e-værdi’s calculations is. This means that we can give an exact indication of when it makes sense to look more closely at the model-estimated property valuation made by e-værdi,” Steen Høy Hansen says.

e-værdi was launched in the financial sector back in 2012. It is merely one of many examples of how e-nettet is working with data and data quality, and, by collaborating with the financial sector, how it is generating the benefits of digitisation for bank customers.


This article is part of the commercial publication 'Copenhagen Fintech'. Click here to view all articles