By Gordon Graylish, Programme Director of the AI & Machine Learning in Financial Services virtual programme at Imperial College Business School
Steam, electricity and computing. These three industrial revolutions have completely transformed the way in which we manufacture and work, and the efficiency of this process too. All three revolutions were met with great fear, despite proving to be the catalyst for massive innovation. We are currently living through what experts describe as the fourth industrial revolution, and the situation is exactly the same – mass innovation mixed with fear too.
The 4th industrial revolution is set to completely change the job landscape, just as the previous ones did. In the 1800’s, for example, Primary jobs based around farming, fishing and mining accounted for over 80% of roles, now they are just 1.3% of the UK workforce. On the other hand, Tertiary jobs including transport retail and services moved from less than 15% to 84%, which as a result of, we see a massive increase in societal wealth.
In this fourth industrial revolution, labelled as “cyber-physical systems” by the World Economic Forum, the main driver is the growth of intelligence in our digital systems – and in finance in particular the lead vehicle is Artificial Intelligence.
AI’s competitive edge
Today, digital technologies such as AI, distributed ledger, and ubiquitous computers are massively increasing competition in all aspects of finance, from digital onboarding, compliance and fraud detection, to loans, investments and to a radical increase in efficiency.
These technologies have two imperatives, reduce costs and initiate new offerings – both of which can give a company a real competitive edge. Unfortunately, CEOs and finance executives just cannot ignore the benefits any longer. They cannot say they do not need to understand these technologies, or say knowledge of technology is not necessary for a finance role – the two are increasingly becoming intertwined, and the most successful finance leaders for the future will get ahead of the curve in this space.
AI is completely changing the information that we use. In the past, 80% of information was internal to the organization, within five years, that will reverse with 80% being external – it just simply cannot be ignored by finance professionals anymore. All major financial firms have multiple efforts underway with AI and it is of course a huge focus of the startup and disruptor community.
Semiconductor firms, such as Intel and Nvidia, list AI as their prime focus, as have Microsoft, Amazon web services and IBM. The focus has shifted from CPUs to GPUs to neuromorphic computing with an astounding increase in capability. This has had a disruptive impact on cost and capability.
The statistics simply prove this further. From 2017, the costs of training a common image algorithm has dropped from $1000 to $10, the costs to classify a billion images is even more radical, a drop from $10000 to .03 – it’s clear they have a disruptive impact on costs.
AI has its challenges
In many cases the AI application is a black box – its process can be unknown, which of course means its application is susceptible to risks. For instance, levels of bias from historic data points have been seen in the adoption of AI in both mortgage lending to minorities and credit card lending to women – something that certainly needs re-addressing and correcting. Whilst in a non-finance setting, we’ve seen the recent A-level debacle, where students faced historical bias in their results because of previous school results.
The implications of this bias, both in terms of bad publicity and customer dissatisfaction, act as a stark warning for CEOs and finance leaders who think they can implement AI without understanding it fully. These black box algorithms have huge challenges and rosks, hence the extreme focus now been paid on explainable AI, the ethical use of AI and tools based approaches made to assist in testing and challenges algorithms.
Like all revolutions, it is at times messy, but progress will come, and the pace of change and the massive changes in storage and communications magnifies this. Artificial Intelligence will massively impact insurance, banking and investment, but the benefits of this impact will only be there for those who are implementing it are knowledgeable and have the expertise. Simply not engaging in investment in AI is no longer possible for CEOs and finance executives, they’ll be left behind and beaten by the competition if they don’t invest.
Leaders and executives have to learn the inside out of AI in their industry, or incur competitive impacts and unacceptable risk. Programmes like the Imperial College Business School online AI & Machine Learning in Financial Services are there to educate leaders about these AI applications in their industry and are vitally important for leaders in understanding the realm of the possible and also its risks. Without understanding AI, the future of their companies could be in doubt, and blind investment without understanding how to utilize the technologies will bring about just as much risk to brand and the survival of the business.
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