Unwrapping 2019... Part One

Having just exited 2018, and as we step blinking into 2019, the team at Houseprice.AI thought that we should take a look at the year ahead. So to start with, we want to talk about property predictions and their accuracy.


As the Chinese proverb goes, the appropriately named year of the Pig promises to be an interesting time and clearly not just for the property market. All, largely due, to the ever surprising package we call Brexit.
So even though all the presents of 2018 are now unwrapped, one is sitting there and as we give the box a squeeze, we still have no clue what this one marked 'Brexit' will actually look like because the tag still reads 'Only open on March 29th'.

To help us we have reviewed a number of possible outcomes and scenarios and we have combined a number of resources and estimates from the following sources: Bank of England (BOE), Office for Budget Responsibility (OBR), Institute for Fiscal Studies (IFS), Centre for European Reform (CER) , Centre for Economic Policy Research (CEPR) all of which offer current best estimates for the UK’s economy and either explicitly or implicitly, associated potential impacts on the UK's residential property market.

Now many readers will say, 'ahah here's yet another crystal ball, mystic Meg exercise'. However, prediction is actually our business, and we are pretty good at it when it comes to property. By using objective data, paired with Machine Learning (ML), all expressed within a probabilistic framework, we are able to estimate property values to average errors of 2-3%. Our approach is scientific, by this we mean it is expressed as how probably wrong we are, not how absolutely right we are.

However there are three points that need to be stressed.

Firstly, it must be stated that the following are scenarios not forecasts. The scenarios illustrate what could happen, not even necessarily what is most likely to happen under a set of key assumptions. It is therefore a spectrum of outcomes that we worked with.


Secondly, whilst Brexit is clearly the major domestic factor for the UK, the global macro-economic environment is clearly another major concern. We could obviously mention the current fall in global stock markets, the prospect of further trade tensions between the US and China, the start of Quantitative Tightening (QT) and the flattening and inversion of the yield curve. All of the above point to much increased economic downside risks in addition to Brexit. For example, the chart below is reason for concern, since flattening of the yield curve, historically, is more often than not, a pretty good predictor of housing property declines.

Thirdly, whilst real estate is one of the largest asset classes, it is also the most heterogeneous. By comparison, traded stocks, bonds and commodities whilst also very diverse are far more standardised, so a further caveat we must make is that individual properties values can vary very greatly within a single location. Using our ML based algorithms we have high confidence for the predictive accuracy of our appraisal predictions at both a micro and property specific level. The image below links to an interactive map and this example in Stevenage - postcode outer SG4 - shows that HP.AI's average prediction error was 1.10% for 93 Terrace properties that sold and that we predicted over the previous 12 trailing months.

It should be mentioned that this is just one sample postcode area randomly taken from over 2,100 postcode areas that we estimate precise individual property values for, every month, based on our estimates vs actual Land Registry transactions. In fact, if you click on the map image you can see the sample for 12 months up to November 2018 has over 530,000 property valuations. Incidentally why only 530,000? Well we have to calibrate our ML models on the others, so some 700,000 in the last 12 months along with another 15 million from previous years.

Click the image to go to the reactive map

So whilst we are probably wrong, but we are also probably more likely to be less wrong than someone who is authoritatively pointing a finger in the air and citing subjective and anecdotal evidence. The interactive map below shows how accurate our valuations are in every postcode in England & Wales.

Click the image to go to the reactive map



In Part Two we will give our predictions based on 1 macro driver. Until then we hope you have a good week!

Eldred Buck is CEO and Co-Founder of Houseprice.AI Ltd. He has over 25 years experience in capital markets and banking, specialising in quantitative models and derivatives trading across all major asset classes. Previously he founded Eiger Trading Advisors, a leading fintech company.
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Christmas for AI

Vivienne Brooks is the CCO of Houseprice.AI She has a long history as a Technical Software Support Guru, is a graphic artist and also has a strong background in Marketing.
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Did you know that there is more to Houseprice.AI than values?

Do you want to improve your data analytics? Using AI and machine learning we can provide you with the tools to increase your profitability.
Our new  proprietary reports and benchmarks provide fast and objective comparative analyses between residential projects, from single family homes through to large scale developments.
The Insight module within our app,Horizon, distils billions of data points to help you identify emerging areas with steady home appreciation and high rental returns.
Our API delivers our proprietary data into your own applications and business processes and will give you a competitive edge over your competition.

We want to work alongside you and help you every step of the way, as little or as much as you require.

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Robert Marsden talks about the application of Houseprice.AI technology

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Artificial intelligence

Artificial intelligence is very much a buzz word right now and quite rightly so. However, to me what’s most important is the application of the technology.

How Houseprice.AI uses this technology

We provide a transparent and objective solution to help people to make some of the very large and important decisions. In the case of home owners probably the largest, most important decision they make in their lives. And, in the case of investors, clearly objective repeatable process is all important.

Why Houseprice.AI?

I have known the founders for many years. In the case of Eldred, over 20 years. He has a good track record of getting businesses off the launchpad, and in the case of Houseprice.AI, it really is in a peer group of one in Europe.

Providing an objective, repeatable and transparent methodology really is transformational in one of the largest asset classes in the world.

Robert Marsden is COO of Houseprice AI. Previously Investment Director with Fidelity Worldwide Investment, he is experienced in all the major asset classes and provides insight with a view to the perspective of users of pricing mortgage backed securities and RMBS style assets. During a 30 year career, he has been with Coal Pension Trustees Services, BlueCrest Capital Management, LLP, Mercer Investment Consulting, NCB and Lombard Odier.
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The Top 10 Property market benefits from the Budget

Philip Hammond has delivered his third Budget as chancellor.
These are the top ten benefits to the UK property market announced in the Autumn Budget yesterday:

  • £1bn of funding to the British Business Bank for smaller house-builders
  • £653m to finance strategic partnerships with biggest housing associations to deliver over 13,000 new homes
  • Additional £500m to take the Housing Infrastructure Fund to £5.5bn & unlock 650,000 homes
  • Funding provided for local areas to deliver homes at a discount in perpetuity through parishes and neighbourhoods encouraged to set up Community Land Trusts to build homes for sale
  • New Permitted Development Rights for upward extensions & to allow commercial buildings to be converted to housing
  • Help to Buy extended by 2 years until March 2023. Encouragement for a ‘new wave’ of shared ownership homes
  • Retailers with a rateable value of £51,000 or less will have bill cut by 1/3 for the next two years up to revaluation·
  • A Future High Streets Fund of £675 million to invest in infrastructure etc
  • Proposals for business led development
  • corporations
Philip Challinor is the Chairman of Houseprice.AI and was part of the architects team at Denning Male Polisano who helped convert Highbury, the former home of Arsenal FC into 700 homes for local people.



If you would like to know more information about Houseprice.AI , Horizon, or access to our API please feel free to contact us at info@houseprice.ai.


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Eldred Buck talks about Data sets and AI

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How important are data sets

One of the intriguing facts about Houseprice.AI is the fact that our data sets are very vast and that means that we are able to accurately estimate the appraisal value of a property by virtue of these data sets and that means that for the 22.5 million properties in the UK we can arrive at a valuation in 10 seconds provided that we put the correct data in, most of which we actually have.

Who can makes use this data

The market place that we’re serving is everybody from home buyers though to, essentially, all the intermediaries involved in that process and all the professionals involved with the industry and sector. Bearing in mind that we have a residential market of 6.2 trillion pounds, in the order of 3 times the GDP of the country. It’s a very substantial market that we are looking to apply our technology to, and there are a myriad number of applications that come from being able to value property on an objective set of criteria which are universally applied across the geographies that we are involved in. Which in this case is England and Wales.

Why did you start Houseprice.AI

The reason that we started Houseprice.AI was in order to meet the need for objective information in the residential market. We saw that actually with the application of Machine Learning and the use of supervised learning sets as part of Artificial Intelligence that we would be able to provide consumers with a far better set of objective criteria in terms of valuing their property.

Eldred Buck is CEO and Co-Founder of Houseprice.AI Ltd and a Non Executive Director at Sequant Capital. He has over 25 years experience in capital markets and banking, specialising in quantitative models and derivatives trading across all major asset classes. Previously he founded Eiger Trading Advisors, a leading fintech company.
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Eldred Buck interview, RICS Modus magazine

Eldred has been featured in the October issue of the Royal Institute of Chartered Surveyors monthly publication, Modus.

The article came out on the 10th, so it is "fresh off the press". You can read it here, or click the link to download a pdf copy.


Example fallback content: This browser does not support PDFs. Please download the PDF to view it: Modus Article.

Eldred Buck is CEO and Co-Founder of Houseprice.AI Ltd and a Non Executive Director at Sequant Capital. He has over 25 years experience in capital markets and banking, specialising in quantitative models and derivatives trading across all major asset classes. Previously he founded Eiger Trading Advisors, a leading fintech company.



If you would like to know more information about Houseprice.AI , Horizon, or access to our proprietary API please feel free to contact us at info@houseprice.ai.


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Gio Miano talks about Insight

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Why Houseprice.AI created Insight

We created Houseprice Insight, which is part of our offering, and is essentially a way to allow our users to provide their customers with much more granularity, data analysis and insight on a specific area.

How does Insight help the user?

We created the ability for someone to show that they effectively know their area. For example, what’s going to happen if a new Waitrose down the street opens up, what’s going to happen if the school kids are doing better at school, what’s going to happen if the NHS push more money to improve their service in the area. How that is going to affect the value of the area has to affect the value of a property. And how you can actually extrapolate this to have a meaningful forecast.

The significance of using AI and Machine Learning

I think that the problem that we now have is because we value things based on the past, and what we want to do, is we want to try to extrapolate with the ability to do a meaningful prediction in the future. Which is not just drawing a straight line between points and know that is the future value.

What Insight can demonstrate

We want to understand why and what impact each single amenity has. The little park that they are planning to build and how that is going to affect the area, as a community project. Where is going to be the best place to open a park. Where is it going to affect the value of an area. How is it is going to affect the value of an area.

We are helping to create sustainable projects, that also have the minimum impact on peoples life, and also on their most important asset. Their house.

Giovanni Miano is Co-founder and CTO of Houseprice AI. Gio has been involved with HFT projects across the globe and is experienced in designing and implementing highly complex IT solutions. Previously he has served as technical consultant for several global firms such as BP, Trafigura, Morgan Stanley and Goldman Sachs.
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