InvesFinder Real Estate Valuation and Analysis
We analyse demographic, economic and specific property data to make decisions on buy to let investments. At any one time, we have 120,000 properties are systems of which around 400 are profitable by to let investments. Of those 400 possible investments, at least 250 are outstanding deals which we believe will rent out within one month.
How does Invesmore PropTech work?
We help you make property buying decisions led by data and experience.
Source housing and demographic related data
We aggregate, process and ingest millions of pieces of raw data from 26+ different sources.
Make sense of property markets
Using custom weighted algorithms and machine learning we prioritise, visualise, filter and isolate areas and properties of interest.
Buy profitable residential investments
As a result of our people, systems and processes, we find more deals and buy with more confidence to out compete other investors.
We make sense of data
We source data from the Office of National Statistics, The Land Registry, Police.uk, Ofstead, Propertydata and some of the property portals. Our raw data includes information on 1,700,000 postcodes, 34,000 local neighbourhoods and 60,000 relevant properties at any one time. Overall, for any given property, we have roughly 8000 different pieces of data.
Identify the right properties
We have developed weighted scoring algorithms which combine and prioritise different relevant metrics. We then organise all this information within a system called Elastic Search. It allows us to combine different datasets for deeper insights and easy information retrieval. For even more accurate insights, we use machine learning to understand nuanced correlations between various data points.
Do deep analysis
With all this data crunching from a typical list of 50,000 properties, we will flag up 200 properties as outstanding deals. We analyse rental yield, net profitability, mortgageability & LTV ratios, refurbishment costs, probable capital growth and overall cost of purchase. We also look at demographics, income, population and crime changes to identify the right cities, neighbourhoods and roads to buy in.
What are the benefits of a data driven approach?
We’ve turned years of property knowledge into powerful algorithms which find deals instantly.
Computers are fast at processing data. Humans are slow.
By filtering out noisy information, our analysts and negotiators focus on the right deals.
Combine scale with focus and we find more contender property deals than any other consultancy.
We don’t directly sell our data. It’s not our business model. If you want organised data on the UK property market, head over to our friends at PropertyData.co.uk
We do sell are the benefits of this data i.e. locating properties which we know make attractive solid buy to let deals. We also offer renovation services through Invesmore Renovations and financial services through our partner Charles Louis Mortgages
We’ll show you…
At the moment for copyright reasons related to some of the data we use, we can’t publicly expose all of our information. But, if you are serious investor and you want some proof, then fill in the fact finder here, book in a free 30 minute consultation and we’ll show you what we’ve got.
If you don’t want to speak to us directly, then have a look in our insight section, where Nick Garner talks about some of the data, the findings and methodologies used by Invesmore.
We get data from the same places you can… And most of it is free. For partially processed data we rely on PropertyData.co.uk who do a great job at organising and structuring property information.
For demographic, house price, economic, schools and crime data we use information collected and collated by the UK government. This includes the Office of National statistics, OFSTED, Land Registry, numerous UK police forces and local councils.
The secret to our success is not getting hold of the data, it’s how we’ve organised the information to emulate the kinds of insights only long-time property professionals would have.
For us, data is a servant to experience and depth of knowledge. Before launching Invesmore, the co-founders spent nine months pulling together millions of pieces of data.
Over about 110 hours of meetings, we prioritised, organised and created sets of rules which give us so much useful information today.
A typical meeting would involve one of the data team doing a show and tell of the system.
We have a set of specimen areas which we use for referencing. So the data person would show the latest algorithm or system changes and the property pros would assess those changes against the specimen areas they have worked in for decades.
If the proposed changes correlate with our property pros experience of an area or particular properties, then we roll those changesout across the whole of the UK dataset.
As of writing, we analyse on these levels:
Local authority: effectively a whole city or part of a large city. Were looking at high level economic and population trends. For each local authority we have 2,896 pieces of data.
MSOA: A middle layer super output area usually consists of an area with 5,000 to 15,000 inhabitants. There are 7,201 MSOA’s in England and Wales, with approximately another 1,235 equivalent areas in Scotland and a few hundred in Northern Ireland. For each of these areas we have 2,515 pieces of data.
LSOA: A lower layer super output area usually has between 700 and 1400 inhabitants. There are 34,753 LSOA’s in the UK. For each of these areas we have 893 pieces of data.
Postcodes: there are 1,755,005 live postcodes in the UK, for each of these we have 121 pieces of data.
Properties: As of writing we have 40,000 live properties on systems and historic data on another 92,000 properties. This data set is constantly growing. Every day we process between 1000 and 3000 new properties.
When you add all of this information together and then combine different metrics at different levels, there are billions of data combinations we use. That’s why the clever part is not how much data we get a hold of, but it’s how we we make it useful.
As of writing we have 51 Golden rules for buying the right property which have moulded our algorithms and steered our property analysts.
Without getting too detailed, all our algorithms and processes centre around a few big ideas:
- Where there’s more demand than supply + an ability to pay more, prices go up and the opposite is true.
- ‘Human’ factors i.e. people like to be near other people similar to themselves. This influences demand from economically productive people.
- Economic factors i.e. looking at economic indicators which guide us towards areas that are robust and can handle a downturn.
- People want to be close to employment, amenities and services.
- People don’t like crime, except for those causing it.
- People want to live in nice environments in nice properties
As a result, we typically only manually review 1 in 150 properties that our systems process. We will write up a comprehensive document explaining all the different rules.