As far as overlords, I do jest; there are no robot overlords on the horizon. It’s a common misconception around AI. Indeed, when we refer to it we are simply talking about using machines to do things we consider to be ‘intelligent’.
This can range from using virtual assistants to respond to questions and perform tasks, to using large amounts of data to train machines to learn via algorithms, to more complex deep learning like image recognition and autonomous driving vehicles.
Global technology companies (Google, Amazon, Facebook and Apple) are already investing around 10 per cent of their revenue into intelligent automation, according to McKinsey, achieved up to 50 per cent revenue gains in key business areas as a result.
AI is expected to permanently change the financial services industry in significant ways during the coming years as institutions seek to leverage machines to become more efficient - from the front office to the back end. Estimates for an eventual reduction in back-office staff range from 20 per cent to 30 per cent.
One form of AI being adopted in local banks appears to be Chatbots. In January 2018, Commonwealth Bank of Australia launched its in-house bot Ceba to more than a million customers, performing around 200 tasks. Similar ‘virtual assistant’ functionality has also been developed at NAB.
Fraud Detection is a growing utilisation for AI in financial services. Using machine learning, systems can detect unique activities or behaviours and flag them for security teams. This is effective because of the availability of large volumes of customer data, together with transactional data updated as transactions occur.
At the other end of the complexity scale is the usage of AI to help traders perform more competently. In 2017 UBS debuted two new AI systems on the trading floor, one of which is a system which analyses reams of market data to identify trading patterns and thus formulates new strategies for trading volatility for the bank’s clients.
AI technologies are so complex and fast-paced ethical frameworks need to be considered to tackle what lies ahead. The stigmas around automation, AI and job security will need to be carefully addressed, particular to ensure customers and staff remain engaged and trusting.
Businesses should create room for people to assume more-complex roles, moving from the manual work which dominated the pre-industrial globe to the cognitive labour which characterises strategic and administrative work in a globalized society.
There are three key ethical issues which arise.