Covolution: financial services’ new reality
By Alex Foster, head of insurance, finance, payments and post trade at BT
Artificial Intelligence’s (AI) transformative power is impacting business both large and small across a multitude of industries. Financial services firms are no exception. Given the huge amount of data financial services produces and its hunger for statistical analysis it is an industry that is ripe for disruption. In fact, AI promises to fundamentally change the nature of financial services. It will demand that humans adapt and treat it as an opportunity for cross-disciplinary growth. Once this is realised, the question should no longer be whether AI will affect our jobs, but how and when?
The rise of AI has forged a broad debate among financial services and technology experts alike that has raised a myriad of questions about job security and the automation of the workforce. Some of the world’s top thinkers are even more concerned. Stephen Hawking has warned that its full development “could spell the end of the human race” by bringing conflict to humanity, while Elon Musk cites it as our “biggest existential threat”.
While concerns resonate among many, others relish the opportunity for covolution: humans embracing the increasing usage of AI. Technology giants such as Microsoft, Amazon, Apple and Google have been quick to develop AI technology. In fact, their digital assistants are so widely used that the number of active AI-powered devices could surpass 7.5 billion by 2021, almost exceeding the world’s current human population.
In some ways, the revolutionising effects of AI have been a long time coming. The term itself has been around for over sixty years. In 1951, Alan Turing published an article titled “Computing Machinery and Intelligence” in which he proposed the “imitation game,” now known as the “Turing Test”. The official birth of AI as a science was in 1956 when John McCarthy of the Dartmouth Summer Research Project on Artificial Intelligence set out to understand how machines could simulate aspects of intelligence. This progress continued through the 1960s and ‘70s, recognising images, translating between languages, and learning instructions.
Today, the UK’s AI sector is thriving: Google and Microsoft’s respective acquisitions of DeepMind and SwiftKey are examples of how the world’s largest technology companies have bought into the concept of AI in recent years. Accenture has estimated that AI could add £654bn to the UK economy by 2035. In addition, the government’s spring budget introduced a £270m investment fund for disruptive technologies such as AI and robotics. Some proponents of AI advocate that it will become a vital driver of the UK’s competitiveness in the global market.
AI is already causing upheaval in financial services. It has permeated sectors from trading, financial advice and risk management to portfolio optimisation, customer service and regulation. In fact, AI has become vital to the industry’s operation because of firms’ all-consuming appetite for data. With advances in big data and cloud computing, more companies rely on cognitive computing and machine learning to analyse patterns or trends, cutting costs and increasing efficiency. This trend will only become more widespread as technologies improve and possibilities increase, raising the question that has dominated the AI debate in financial services: if more and more data and regulatory functions are being performed by AI, what will happen to jobs?
Disruption is now inevitable and the role of human intervention will almost certainly change, but this does not mean that all jobs will be automated. Instead, we will see a shift in the nature of jobs that financial institutions demand. There is a growing need for people with cross-disciplinary skills to bridge the gap between technology and business. Those who can build the programmes and business models that surround them stand to gain the most. As a result, strong partnerships between engineering, computing and business faculties around the globe are being built.
Contrary to what many sceptics fear, machines won’t take over just yet. The more likely, near-term outcome is that augmented intelligence and cognification, in which machines and AI assist humans, will allow humans to use AI for processes which require very specific decisions.
A key discussion among senior political and business leaders is how to manage this shift to ensure a smooth transition. For this to occur, humans will need to adapt and respond to these demands as new skills are required in the workforce to implement changes brought about by technology.
Any new technology or innovation will always bring challenges, and rather than swimming against the tide, we need to recognise the need for balance. Regardless of whether you are a sceptic or a believer, one thing is certain: AI has arrived and cooperating with it is a necessity and not a choice. So, ask yourself: are you ready for covolution?
The bank can access data science, artificial intelligence and machine learning for new products.
AiPEX with Watson simulates a team of analysts and traders to identify potential investments.
Machine learning models systematically scan newly arriving, anonymized data to identify anomalies.
The Cobalt programme launched in 2018 to help fintechs collaborate with the asset manager.
Users with different skill levels will be able to undertake machine learning and advanced analytics.