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    Home > Top Stories > Artificial Intelligence and Human intelligence: better together
    Top Stories

    Artificial Intelligence and Human intelligence: better together

    Artificial Intelligence and Human intelligence: better together

    Published by Gbaf News

    Posted on May 21, 2019

    Featured image for article about Top Stories
    Tags:Artificial IntelligenceEmerging technologyEmploys algorithmsHuman intelligence

    By Jonathan Barrett, Managing Director, Dataminr

    There are few industries that will be left unaffected by artificial intelligence (AI). AI has the ability to fundamentally change the way that people work and open up new frontiers, roles and careers that are unimaginable today.

    And the financial industry is not exempt from this. To fully appreciate the challenges of AI and machine learning, and the benefits it can bring to financial professionals, it’s necessary to first define these two terms and how they are related to each other.

    AI is an umbrella term that encompasses many subfields. For the sake of simplicity, most of what people think of as AI currently — embedded in computing services we use everyday, when we search the web or review social media posts, for example — has machine learning at its core. AI aims to emulate or supercede human intelligence, while machine learning establishes and employs algorithms that learn models from data.

    With the variety and volume of data sources in finance expanding, greater demands are placed on a wide variety of professionals in the industry, who must extract what is most relevant to make timely and effective decisions.  That is why organisations are turning to AI-enabled solutions to distill and catalogue data to drive efficiency and provide situational awareness that can make a real difference to their clients and businesses.

    In fact, a recent survey by the Financial Times of 30 leading banks about their use of AI revealed an industry excited about the prospects of a technology that can help cut costs, drive innovation and boost returns.

    Businesses and individuals need to willingly embrace new models and new skills that will enhance their ways of working, enable them to make informed and better calculated business decisions, and in doing so, ensure that they remain ahead of their competitors.

    The shift to higher value work

    McKinsey estimates that up to 50% of tasks currently performed by humans could be automated by 2055, creating an important opportunity for businesses to thoughtfully prepare their teams for new frontiers of work that we can’t imagine today.  With the automation of certain tasks, especially those that are time-consuming and repetitive, we can realise the real benefit that machine learning can have on optimising business performance and improving operations in the long term.

    By eliminating time spent on the monotonous aspects of jobs, machine learning is enabling a range of financial industry professionals to focus on creating strategies for growth, doing more with the enterprise and customer data they have, and learning more about the market-impacting events around them so that they can make more informed decisions.

    Room for growth

    Any emerging technology comes with limitations, and machine learning, especially within finance, is no exception. The financial markets are fluid, formed by an intricate network of parts both outside and inside the sector. An alteration in the market mechanism can be caused by anything from a natural disaster to regulatory shifts. As such, the data the financial markets create, like the markets themselves, are complex and constantly changing.

    Although machine learning platforms have made significant strides in identifying trends and accounting for particular risk factors, they can fall short when faced with unpredictable changes and fluctuations in the financial markets. Particularly when making financial decisions such as adjusting investment strategies, machine learning tools cannot be exclusively relied upon to provide completely reliable or precise information. While machine learning can certainly be advantageous and ease the process, it must be used in tandem with human intelligence to avoid hidden risks.

    Human capabilities to form opinions, use emotional intelligence, and drive creativity remain essential to running any business — and can be greatly enhanced when coupled with machine learning.  Such technology can give financial professionals the time, methods, and multi-dimensional information required to be more innovative, productive and valuable to their organisations.

    This is a unique time for the industry to understand how the combined power of human and artificial intelligence can transform business, while ensuring that industry professionals now and in the future can evolve their skills and reach new levels of performance.

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