The Future Proptech conference will showcase the very latest ideas and technologies that the industry has to offer to a diverse set of users.
2nd May at the
Business Design Centre
‘Housing Crisis’ are two words that appears on the conference website and that are all too often coupled, as indeed are; ‘greedy and housebuilders’ along with ‘planning and delays’ and not forgetting ‘special and interests’. Everyone is calling for less rhetoric and more action, however this is not easy since the Housing Crisis is clearly not a simple problem to solve and there are always myriad and competing opinions on how to address the issues that underpin this deep seated problem.
Consequently Houseprice.AI are delighted to be selected as one of the participants in the ‘Innovation’ stream at Future Proptech and we will specifically be looking to address some of the challenges that have been set out by MHCLG by applying Big Data, Machine Learning (ML) and Artificial Intelligence (AI) to help better inform all participants and stakeholders involved with, planning, delivery and sales of housing.
We at Houseprice.AI are driven by the belief that transparency, clarity and consistency can be achieved through better data and leading edge technology and this combination allows for a more holistic approach to the housing problem. We want to show that adoption of a more data based approach, which objectively uses as many quantifiable drivers as possible, will naturally lead to more optimised and transparent solutions for all participants.
By incorporating better data and AI - everything from asset price and mix through to local, socio economic and environmental impacts - planning, construction and property demand and sales can be far better modeled and analysed; both more objectively and much faster. Ultimately this improvement to existing processes, project evaluations and decision making, then leads directly to lower costs and greater efficiencies. Here are just a few examples.
AI as a Facilitator of Sustainable Regeneration
Multiple variables, socio-economic, demographic, access to green spaces, transportation, educational, recreational can be measured modeled and visualized, thereby allowing better and more objective decisions to be made with more confidence than ever before. More importantly these can then be modeled with forward looking factors leading to a whole new level of reliability based on predominantly ‘objective’ data.
This ensures that the number, size, mix of units, building types, tenure, phasing, etc all match the actual and future demands of local neighbourhoods adding value, vibrancy and vitality to existing communities. We believe that even aesthetics, such as building heights and design issues can also be modelled and optimised to create the ideal solution for each scenario.
Rethinking the Planning Process
Currently only a few local authorities succeed in hitting their government set targets for determining Planning Applications. We are confident that using AI and Big Data will allow users an opportunity to completely re-think the Planning Process. Just one example is to introduce site specific planning policy and townscape principles within a 3 dimensional planning framework that is coordinated on a GIS mapping system; the pre-Planning phase can be reduced. By allowing more objective analysis of Town Planning criteria and better engagement of local stakeholders, the whole preconstruction phase can start to be measured in months rather than years.
Creating new housing models fit for the future
Housing solutions are now so wide ranging that to simply continue to roll out the same old formula will inevitably be a wasted opportunity. There are now a range of options in the rental sector alone which, according to the Joseph Rowntree Foundation, 1.6m in London are currently locked into now for life. These options include:
Private Rental Sector-PRS.
This product is a hybrid aimed at these who wish to spend their moderate incomes on stylish living rather than a mortgage. Theirs is a discretionary, almost hedonistic philosophy as far divorced from the’ my home is my castle’ as its is possible to be. They will change their home almost as often as they will change their car. There is also a new class of investor as crowdfunding and even multiple small investor clubs create funds which are far less specific about risk and returns, but want to invest in creating more diverse and vibrant cities.
Post Grad Housing
Most University cities struggle to retain the graduates that were nurtured there, often due to the high cost of appropriate housing located near employment opportunities. An emerging model is flatted accommodation suitable for singles or couples in the pre-family face of their lives. These units typically feature flats clustered around a shared kitchen which preserves the ‘sharing, community feel that is a step or two up from student housing but retains the comfort and excitement of communal living. Each flat has its own ‘kitchenette’ for making drinks and breakfasts within their own private living room. There may also be a guest room in each cluster to accommodate the occasional visitor as most flats will only have one bedroom. Build costs can be as low as £75,000 for a one bed unit and the model is perfect for prefabricated solutions,
Mixed Tenure Housing
As couples plan for a family, a range of tenures tailored to the security needs of the occupiers is being introduced by a number of enlightened developers. This is a variance on the shared ownership scheme, allowing tenants to secure a five, ten or even longer term lease, fixing their overheads and meaning that they can invest in better quality fittings and decoration.
There may also be an element of self-build, reducing homeowners costs even further.
Private shared ownership housing.
This used to be the preserve of the social housing providers, but a model aimed at the aspirational middle income young family allows for an element of equity building that reduces the pain of jumping onto the property ladder. The first rung is normally set at 10% and similar tranches or more can be purchased at the owners obtain funding. So after ten years a family could own their own property outright without the painful process of finding big deposits and satisfying earnings hurdles to qualify for mortgages. Crowdfunding investors are ideally suited to this investment opportunity as building voids are virtually eliminated and investments can be withdrawn on an annual basis with a ten year maximum horizon.
It is clear that better more objective and therefore more creative solutions can arise by using better data and technology. Ultimately the Housing Crisis, which at first glance appears almost Gordian in complexity and scale, can be unpicked and solved by using clean data, consistent methods and transparent objective processes. The housing crisis is a problem that everyone acknowledges, but it will never be fixed by opinions, only by rational decisions based on real data and through objective planning, delivery and action.
We look forward to seeing you at the Business Design Centre, Islington on May 2nd 2018.
|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 firstname.lastname@example.org.