Westminster Business School Blog Academic Minds | Can FinTech and big data transform a post COVID-19 landscape?

Academic Minds | Can FinTech and big data transform a post COVID-19 landscape?

June 10, 2020
Academic Minds
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The SARS-CoV-2 virus epidemic has generated widespread strife and conflict in economies across the globe. Virtually overnight, consumers shifted their activities online. There is an evolution underway in the FinTech industry, with the potential to transform financial services forever. Machines with infinite cloud-based memories together with Artificial Intelligence (AI) capabilities have entered a brave new world. Fund managers face an enticing prospect to generate money with this new technology. Is COVID-19 a perfect storm, heralding the dawn of a new tech era in wealth management, or another disaster-in-waiting?

A time of great change

Evidence shows that few investment professionals have been exploiting FinTech for competitive advantage. As with the game-changing industrial revolution of the 1760s and the coming of the steam engine: humans were not replaced. In this fourth industrial revolution, our expected use of AI in FinTech will not replace humans either. Big data is not knowledge, but AI can help to automate routine processes and efficiently retrieve vast amounts of data and information that is buried in time. AI algorithms and data management provide this information in an ordered format for us to make intelligent, efficient and timely decisions. Wealth managers will be able to achieve profitable investments by creating and managing even more smarter investment portfolios.

The building blocks of success

Artificial Intelligence (AI), Blockchain (B), Cloud Computing (C) and Data (D), ABCD form the building blocks of an evolving financial ecosystem. B & C form the backbone of this technology infrastructure. More interesting are the A & D elements that spark our imaginations to create smart investment portfolios.

The challenge in education is to understand and develop novel applications of AI. Experts use predictive analytics and complex algorithms to extract valuable financial insights from a variety of big data sources. This data, sized in terms of petabytes and exabytes, exists in a variety of forms, namely: alternative, unstructured and structured. It is gathered from multiple devices (voice, text, image) and processed systematically to be available as business insights.

Invest, develop and enjoy the rewards

Although FinTech offers great potential, only 10% of fund managers are adopters. The allure of exceptional returns from investments is offset by the additional cost, complexity of data management and expertise of applying FinTech. Data and financial analysts are in high demand. Those who develop effective Machine Learning algorithms, to discern patterns and signals from the big data reap the benefits.

Hedge funds have used ML since the early 2010s to examine securities traded daily. To ensure that trades are cost effective, the models can find cheap sources for executing trades via the best brokers and exchanges. In Asset Allocation applications, predictive analytics tools are used to gauge opportunities from the buy and sell signals across markets and securities. They are effectively used in Debt markets to process and generate credit alerts on issuers as well as signals for stock picking.

Clearly, Covid-19 is a perfect storm bringing in a new Tech-era in financial services.

This thought piece was authored by Ann Thapar and originally appeared in the online edition of Business & Industry 2 June 2020. The final edit for the WBS Blog version was carried out by Joseph Coote-Cowling. Read more blog posts published under our Academic Minds column.

Ann Thapar lectures as Course Leader on our new postgraduate programme the MSc in FinTech with Business Analytics which holds its inaugural in-take this coming Academic Year 2020/21. Applications are still open for September.