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Real Estate

Automated Valuation Model for UK Residential Property

Challenge
Property valuation is a service of huge demand, and especially in London UK, where hundreds real estate deals are being performed every day. Properties can be considered not just as homes, but rather an investment or even a collateral for financial activities. Automated Valuation Models are seen as complementary to traditional appraisals and there is an opinion that systematic and fast quantitative methods might reduce the inaccuracies due to reliance on human judgement. Several companies across UK provide property valuations and some even have their own online tools for this service.

ENBISYS developed AVM with very high accuracy (MdAPE 7.29 across UK and 6.46 for Greater London) for property valuation companies in United Kingdom. The more accurate the model the higher Companies may charge for such services.
Approach
We aimed to train our neural network to get as accurate valuation as possible, considering open data available. So, the first task was to mine different types of data from various sources, clean the data and set it up for practical use. During this R&D project we developed proprietary methods for Feature Engineering, thus we can calculate the feature' influence on overall AVM accuracy before implementing all the required work to add it.
ENBISYS performed R&D where the most sophisticated technology of modern time, Deep Learning, has been implemented to its fullest. Unique architecture of neural network, state-of-the-art algorithms, data cleaning methods and feature extracting/engineering have become ENBISYS exclusive competencies that can be translated to other projects in the field of property valuation. This proprietary development will bring the certainty to property purchasers, investors and loan institutions.

Solution
AVM from ENBISYS is a completely developed online platform which allows to get property valuations across the whole territory of the UK. The Artificial Intelligence algorithms ask for address, property type, number of rooms and total area of the property. Based on these parameters the customer gets approximate property price and the result is provided with certain confidence each time. The logic of underlying Artificial Intelligence considers more than 30 different parameters like proximity to bus/train stations, types of construction materials, number of schools around, crime rates in the area and many other.

AVM development let ENBISYS to attain very sophisticated competencies in Feature Engineering and testing as well as in Data cleaning. We collected large amounts of different types of data and have own methods how to make almost any data work for particular valuation task. Thus, with more data available it will be possible to increase the AVM' accuracy even further.

Automated Valuation Model for UK Residential Property

Challenge
Property valuation is a service of huge demand, and especially in London UK, where hundreds real estate deals are being performed every day. Properties can be considered not just as homes, but rather an investment or even a collateral for financial activities. Automated Valuation Models are seen as complementary to traditional appraisals and there is an opinion that systematic and fast quantitative methods might reduce the inaccuracies due to reliance on human judgement. Several companies across UK provide property valuations and some even have their own online tools for this service.

ENBISYS developed AVM with very high accuracy (MdAPE 7.29 across UK and 6.46 for Greater London) for property valuation companies in United Kingdom. The more accurate the model the higher Companies may charge for such services.
Approach
We aimed to train our neural network to get as accurate valuation as possible, considering open data available. So, the first task was to mine different types of data from various sources, clean the data and set it up for practical use. During this R&D project we developed proprietary methods for Feature Engineering, thus we can calculate the feature' influence on overall AVM accuracy before implementing all the required work to add it.
ENBISYS performed R&D where the most sophisticated technology of modern time, Deep Learning, has been implemented to its fullest. Unique architecture of neural network, state-of-the-art algorithms, data cleaning methods and feature extracting/engineering have become ENBISYS exclusive competencies that can be translated to other projects in the field of property valuation. This proprietary development will bring the certainty to property purchasers, investors and loan institutions.
Solution
AVM from ENBISYS is a completely developed online platform which allows to get property valuations across the whole territory of the UK. The Artificial Intelligence algorithms ask for address, property type, number of rooms and total area of the property. Based on these parameters the customer gets approximate property price and the result is provided with certain confidence each time. The logic of underlying Artificial Intelligence considers more than 30 different parameters like proximity to bus/train stations, types of construction materials, number of schools around, crime rates in the area and many other.

AVM development let ENBISYS to attain very sophisticated competencies in Feature Engineering and testing as well as in Data cleaning. We collected large amounts of different types of data and have own methods how to make almost any data work for particular valuation task. Thus, with more data available it will be possible to increase the AVM' accuracy even further.

Automated Valuation Model for UK Residential Property

Challenge
Property valuation is a service of huge demand, and especially in London UK, where hundreds real estate deals are being performed every day. Properties can be considered not just as homes, but rather an investment or even a collateral for financial activities. Automated Valuation Models are seen as complementary to traditional appraisals and there is an opinion that systematic and fast quantitative methods might reduce the inaccuracies due to reliance on human judgement. Several companies across UK provide property valuations and some even have their own online tools for this service.

ENBISYS developed AVM with very high accuracy (MdAPE 7.29 across UK and 6.46 for Greater London) for property valuation companies in United Kingdom. The more accurate the model the higher Companies may charge for such services.
Approach
We aimed to train our neural network to get as accurate valuation as possible, considering open data available. So, the first task was to mine different types of data from various sources, clean the data and set it up for practical use. During this R&D project we developed proprietary methods for Feature Engineering, thus we can calculate the feature' influence on overall AVM accuracy before implementing all the required work to add it.
ENBISYS performed R&D where the most sophisticated technology of modern time, Deep Learning, has been implemented to its fullest. Unique architecture of neural network, state-of-the-art algorithms, data cleaning methods and feature extracting/engineering have become ENBISYS exclusive competencies that can be translated to other projects in the field of property valuation. This proprietary development will bring the certainty to property purchasers, investors and loan institutions.
Solution
WAVM from ENBISYS is a completely developed online platform which allows to get property valuations across the whole territory of the UK. The Artificial Intelligence algorithms ask for address, property type, number of rooms and total area of the property. Based on these parameters the customer gets approximate property price and the result is provided with certain confidence each time. The logic of underlying Artificial Intelligence considers more than 30 different parameters like proximity to bus/train stations, types of construction materials, number of schools around, crime rates in the area and many other.

AVM development let ENBISYS to attain very sophisticated competencies in Feature Engineering and testing as well as in Data cleaning. We collected large amounts of different types of data and have own methods how to make almost any data work for particular valuation task. Thus, with more data available it will be possible to increase the AVM' accuracy even further.

Let's discuss your Case!
Let's discuss your Case!
Let's discuss your Case!