Long term property rentals - The Problem - A disconnected market that introduces friction at every step.

The market size of private 'long-term' rental property contracts in the United Kingdom alone was estimated at greater than 5 million tenancy agreements in 2018 – this number is continually and substantially growing as more consumers enter the market unable to raise the substantial capital and income requirements to support a property and a mortgage.

What does this translate to for dif.rent?

Even capturing 20 per cent of this market in the U.K with a fixed fee of 49.99 per contract agreement and 24.99 a month fixed management fee, translates to both a huge cost saving for tenants, and to landlords who are often charged anything up to 10 to 15 per cent commission on their rent.

Fig 1. 20 % @ 49.99 per tenancy agreement of 5M contracts in the United Kingdom.

1 Million contracts at the indicative pricing represents a c. estimated @£350 million p.a recurring revenue stream for UK.– and that’s before you even add the additional revenue opportunities from providing a marketplace for partners to provide everything from home removals, to gardening services, insurance to utilities which in itself has the capacity be a substantial business opportunity once the customers are on board the platform –

"by creating a long-term management relationship that creates genuine value for the consumer in how they find, secure and then manage their rental transaction we have a powerful opportunity to capitalise on time poverty by automating many other related services into the proposition – automatic energy switching to the best tariff based on A.I based analysis of the tenants household composition and historical usage of the rental property, to optimising their route to work from their new home – we will build a compelling user proposition that delivers a real sense of quality of service that benefits both the supplier and the consumer.

This is a global opportunity – the housing market is as broken in many countries as it is in the U.K – and there are huge opportunities to bring better regulation and consumer protection by virtue of market power to emerging markets, where unbanked or undocumented citizens are often preyed upon by unscrupulous property owners.

Fig 2. The steps through a rental process with approximate timelines

The current processes involved for a tenant to first locate the ideal property up to the time the keys are exchanged taken as a whole is far too long (=>21 days), the process involved includes too many manual steps.

By creating an Uber of rentals where the technology enables us to take the best of mobile design thinking, coupled with A.I. + M.L. driven service, to change everything from the way we search and match property, to manage the application process to the on-going payments and maintenance, on a global scale, justifies our strong belief that dif.rent will take its place as the next decacorn opportunity.

The Social Mission

We live in a very different world, social accountability powered by the voice given to the unheard by social media is forcing organisations to address social injustice like never before. It’s not enough to simply come into a market to profit from it, you have to justify consumer trust by representing a product and service that meets the needs of the new generation of highly connected, highly vocal users.

We don’t expect to solve all the world’s housing problems, but what we can do is remove the actual real pain people are suffering that is wholly avoidable when a socially responsible company uses the technology at their disposal to use that technology to enable better outcomes for the consumer.

As an organisation we will be trusted with data on the lives and aspirations of millions of consumers – it is no longer acceptable to simply assume ‘the customer is the product’ and use that data for our own benefit and personal enrichment, but use that data coupled to A.I and Machine Learning to solve the problems those consumers face on every aspect of the transaction – better decision making, removing bias, working always to deliver a positive outcome for both parties, removing expense, risk and victimhood – all these goals are worthy uses of data that help us build a bond of trust with our customers that unlike the legacy industry, we are there to support them, service their needs and above all else treat them with respect.

It is not just empty idealism – the positive benefits in media and community relationships being a company with a strong moral sense of direction and purpose brings far outweighs any costs of delivering on that mission, but the truth is doing good isn’t easy – it’s going to take the brightest minds in our industry to help shape the conversion – people who benefit from the status quo are always resistant to change, and our key challenge is using our capability to deliver tangible improvements in quality of service, tenant covenants and yield on investment to make sure our supplying partners (the property owners) feel the benefits of supporting our ethos and code of conduct is in their own best-interest.

Product - www.dif.rent

The How

To think smarter, you sometimes need to find a smarter person to think for you, and when you exceed their ability to make good decisions, you need to embrace A.I + M.L. to remove the deficiencies in their thinking.

The fundamental problem with the human condition is that regardless of our individual idealism that drives company founders to create great ideas, the person who is most likely to undo that work is the person who is least invested in it, which in our hierarchal corporate world is often the lowest paid, least engaged member of the organisation who is the main consumer touch point. As a company that is a problem because 100 good deeds go un-noticed when 1 bad deed stands out. A lifetime spent serving a multi-cultural population impartially and fairly will be completely undone by one individual who discriminates in the current social media landscape.

Sometimes we have to recognise that humans are not always consistent good decision makers – and the results are self-evident when despite all the vetting and referencing, home-owners still find themselves being stuck in a legal nightmare with toxic tenants, and tenants find themselves at the mercy of unscrupulous property owners, or simply the victim of outright fraud.

Through the correct application of A.I + M.L., we can harness the power of all the data metrics we gather to constantly build and improve our understanding of behaviours and iterate vetting processes to identify patterns and warning flags based on predictive and cognitive behavioural analysis. The closest comparable is the auto-insurance industry where we use pattern matching to identify specific combinations of attributes such as occupation, age, and other factors to better understand and therefore price risk. Removing the decision making process from humans who are prone to unconscious bias, ineptitude or open to corruption ensures that we develop a system rooted in data science, the purpose of which is to accurately match every consumer to an appropriate home rental opportunity, priced for market risk to ensure we develop the kind of risk/reward model that encourages more market participants to seek out additional yield through high risk opportunities.

This needs to be carefully balanced with the very real social responsibility to not exploit the basic human right of people needing a home, but rather allows us to better reward good tenants by allowing proper market price discovery to occur. Coupled to demand-based pricing based on real-time market transactional data, we can optimise yield using compute power in a way no part of the current legacy industry is capable of achieving due to the disconnect between each part of the value chain.

The Details

At the heart of dif.rent’s service is a cloud deployed mobile-first highly integrated platform – robust, and scalable based on micro services and containerised best practices, the primary mechanism of delivery from first touch point to end of service will be our smartphone application, which is built using the latest in dynamic data driven UX creation and will tailor the user experience to renters, property owners, and small business market place suppliers from a single application.

With the majority percentage of Generation Z and Millenials being entirely active on mobile and not utilising traditional web on desktop or laptop, and those generations being the ever growing principal contingent in Generation Rent, we are building an app for consumers who have been brought up using Snapchat, Instagram, Uber and Deliveroo and expect to manage every aspect of their service from a single application, using a user interface that removes out-dated design concept such as username/passwords in favour of biometrics, to changing the entire idea of how we search to a A.I powered match pushing service with a Tinder style search mechanics that removes the slow loading pages of results in favour of a gesture based simplified open interface.

The feature set dif.rent will offer will create a seamless transition through every phase of the rental transaction process both for the consumer and supplier – more than that, it will solve a number of problems from the legacy industry such as enabling payments of rent via card rather than slow and out-dated bank transfers, to a interactive managed inventory check in and check out service, a interactive video tour feature. The benefits for the property owner are equally as impressive – from automating paperwork and compliance, to preparing rental statements and managing payments, the era of chasing agents for cheques will be made obsolete. The biggest pains we will solve will be allowing renters and property owners a direct capability to report, track and deal with problems arising from maintenance, with the landlord able to assign tasks to 3rdparty partners to carry out work and then bill through the platform.

The marketplace feature will allow everything from a complete check-list driven helper function that will automate processes for the home renter – choosing the best priced energy and communications suppliers, organising van hire or booking a movers, cleaners, gardening services – we will enable a single touch-point to reduce the stress of moving by tracking all the little headaches that consume time during a move.

Our investment in A.I + M.L. will give us the opportunity to bake in automated budget predictions and management to help guide affordability decisions, detect potential financial stress and intervene by signposting appropriate agencies before problems become unsolvable.

Managing a rental home can be a complicated process and designing a solution that simplifies it is our key objective – by utilising technology we can reduce the tasks undertaken by both consumers and suppliers through automation, and reduce stress and friction in the transaction process.

We have a great feature roadmap, and thanks to the advances in cloud and mobile we have a genuine opportunity to build an entirely next-generation platform that act as a baseline for a continuous development approach that constantly seeks to advance efficiency of delivery though new technology enablers.

Thank you for reading.

Edwin

email: er@dif.rent