More than a quarter (27%) of organisations surveyed by Gartner expect to adopt some form of artificial intelligence or machine learning in their finance department by 2020. With so much data, from so many sources, machine learning is often the only real way financial professionals can successfully sift through the noise in a world of information chaos. Jonathan Barrett, Managing Director of Dataminr tells us more about it.
Before delving into the details of exactly how machine learning can benefit financial professionals, it’s important to have a clear understanding of exactly what artificial intelligence (AI) is, what machine learning is, and how the two fit together. As stated by Oxford University, AI is concerned with getting computers to perform tasks that currently are only feasible for humans. Simply, it is human intelligence manifested by a machine. Within AI exists machine learning. This is when a computer is programmed to make decisions, learn from outcomes and adjust, in a way of self-improving, according to their environment.
As an industry that needs to remain at the forefront of adopting new, and better, methods of working, financial professionals, in particular, are seeing a huge surge in the use of this technology. By bringing together multiple data sets, machine learning can take on the process of sifting through vast amounts of data and provide people working in the financial sector with greater insight to inform critical decisions. In doing so, machine learning is proving to be invaluable.
Embracing the new
A recent report from McKinsey revealed that up to 50% of tasks we tackle at work today could be automated by 2055. But this is not a reason for worry. Machine learning on its own, with no human supervision or influence, is not where the future of finance is heading. And rightly so. Rather, this new technology opens up previously untapped opportunities for a wide range of finance professionals to prepare for and excel in roles of the future — roles that we have not yet even imagined.
More than a quarter (27%) of organisations surveyed by Gartner expect to adopt some form of artificial intelligence or machine learning in their finance department by 2020.
Machine learning is already making its mark on industries that for decades have depended on technology to automate tasks and drive efficiency. Furthermore, we are beginning to understand the true value of how this technology can be used to reduce workloads, particularly in relation to the necessary but repetitive types of work we face in many roles. When used in this way, machine learning has the real power to free up time for strategic thinking and research. It can empower better decision-making by allowing financial professionals to focus on more valuable tasks, such as business growth and retaining vital talent. In this way, machine learning technologies can prove to be the crucial advantage against competitors.
As with most technologies, there still remains limitations with machine learning, especially within finance. The financial markets — and the data they produce — are complex and can change within a split second. They form a web of moving parts, influenced by factors both inside and outside of the financial sectors. Anything from changes in regulation to unpredictable world events, such as political risks or natural disasters, can cause a shift in market mechanisms.
Machine learning models are perfectly capable of predicting and taking certain risk elements into account but can fall short when it comes to these kinds of uncertainties. This makes it difficult to rely solely on machine learning to provide accurate or wholly reliable information when making financial decisions, especially within the context of investment strategies. In this instance, if there is no human input, machine learning could create unwanted and unseen risks.
When used in the right way, machine learning can complement human expertise. We need the creativity, emotions and the ability to form a point of view that only humans possess. But machine learning can mitigate the more repetitive and time-consuming elements of work, enabling people to be more productive, innovative and add new value. So we shouldn’t fret that machines will take over the role of humans in the financial workplace. We instead need to look at the opportunities to enhance the power of both.
Evolving skills, evolving opportunities
For example, hedge funds are hotbeds of new methods and platforms. Traders in this area are often turning to the quantamental approach, blending algorithmic-based and human-based decision-making to generate better results. Artificial intelligence is increasingly being used to reduce unnecessary information while at the same time draw relevant data together, with alternative and unstructured data playing a prominent role.
Machine learning models are perfectly capable of predicting and taking certain risk elements into account but can fall short when it comes to these kinds of uncertainties.
In turn, financial professionals are in a stronger position to give an insightful and accurate analysis. This means they can better understand the investments they are making and the strategies they are employing.
Other financial professionals, such as traders and investors, are increasingly relying on real-time information from alternative data sources to gain new insights, assess situations quicker and enhance their decision-making. The sheer amount of data that traders are faced with is vast and overwhelming. Utilising machine learning systems that can make sense of the information chaos and at a rate simply unachievable by humans allows traders and investors to stay ahead of the game.
Machine Learning and humans: a coexistence
Machine learning is revolutionising the finance industry. On its own, it is not enough to provide an entirely accurate and reliable picture upon which pivotal financial decisions can be made. But, used in tandem with human oversight, insight, and expertise, machine learning empowers businesses and individuals across the financial sector to make faster, smarter decisions that can generate new business value or drive revenue.
About Jonathan Barrett:
Jonathan Barrett is European Managing Director at Dataminr, an AI-enabled platform that discovers, distills and alerts on activity across publicly available data sources, enabling professionals to know and act on high impact events earlier. Jonathan has over 25 years of experience in the tech industry and is passionate about transforming businesses that have the potential to change the world.