AI is already being road-tested by City law firms to save time - and could have a future in housing association treasury, writes David Levenson, of Coaching Futures.
Suddenly everyone is talking about artificial intelligence (AI).
Machine learning and robot process automation (RPA) are terms that are tripping off the tongue.
It’s Armageddon out there; If Brexit isn’t coming after our jobs, then the robots will.
So what actually happens when machines take over our jobs?
In 1960s USA, telecommunications companies employed around 1 million switchboard operators. Today, there are fewer than 5,000.
Over 50 years the patterns of employment have changed, and the next 50 years will be no different.
Workers will be doing fewer tasks; instead they will be creating more value.
So how does this all fit into housing?
Well, suppose you are head of treasury with a heap of title deeds, leases, mortgages, valuations, S106 agreements, planning condition schedules and so on, lying somewhere in your head office.
You want to charge security for loan drawdowns or provide information for a portfolio swap as quickly and efficiently as possible.
You know there are proprietary solutions available for warehousing and managing large quantities of non-standard data, but once assembled they will still require you or your lawyers to read through the documents in whatever form they are presented, and then extract, analyse and finally report on the data to your finance director, lenders and auditors.
Now suppose that you have a machine-learning application available to you which can do the same job in 15 per cent of the time.
This is not a scenario pulled from thin air; a leading City law firm has road-tested such an AI application and has concluded that a task which might take an experienced lawyer up to five hours can be completed by the app in less than 45 minutes.
Imagine being up against a completion deadline that allows you just enough time to carry out due diligence on a 15 per cent sample of leases in a portfolio.
The AI application can take care of the whole data-set in the same amount of time.
An efficient future
Machine learning and RPA will be the boon to transactional and compliance-based activity in housing associations over the next five years.
But how will the technology help its users to create more value?
Taking just one business-as-usual example – leasehold management – AI apps can ensure that service charge schedules are accurately produced and interpreted, that S20 notices are correctly prepared and served and that landlords will be able to stem the tide of negative cashflows which currently haemorrhage from their rent accounts because of defective execution of inadequate processes.
Even truly intelligent machines rely on humans to tell them what they need from them.
AI technology can learn how to replicate, re-perform and extend tasks many times faster than we can.
What robots can’t do is identify the problems that need to be solved, and in future this is how housing association employees will increasingly create value for their organisations and save money for their residents.
David Levenson is the founder and managing director of Coaching Futures and a former housing association finance director.