A new commodity spawns a lucrative, fast-growing industry. In the 20th century, the resource in question was oil. Now, whichever way you look, it is data and information, the oil of the digital era.
Over the past few years, 90 percent of the data in the world has been a result of 2.5 quintillion bytes of data created on a daily basis. This rapid growth generates opportunities for collecting, processing and analyzing, or what is commonly referred to as big data.
In fact, the usage of big data by enterprises has significantly increased in the last years, from 17% in 2015 to 53% in 2017. In 2018, 97.2% of companies indicated that they were investing in big data and artificial intelligence, especially companies in the Telecommunications, Financial Services, and Healthcare industries.
Big data in finance
Big data technology has become a fundamental part of the financial services industry and will continue to lead innovation in the future. Nowadays, banks and insurance companies use big data to become more efficient and optimize revenues through targeted pricing, and to provide better services to customers.
Furthermore, big data analytics is needed in the investment industry for better investment decisions, capital allocation, outperformance, improvement of services, and increase in market efficiency. For instance, algorithmic trading uses considerable historical data with complex mathematical models to optimize portfolio returns.
Evolution and innovation
Given that, the volume of available data has grown exponentially over the last years, triggering 33 trillion of gigabytes in 2018, and expecting to grow to 175 trillion by 2025[1]. In this context, more sophisticated algorithms have been developed, and computational power and storage have steadily improved. The convergence of these trends is fuelling rapid technological advances and business disruptions.
One example is the development of machine learning, a new data processing algorithm that creates relationships between known data points and uses those relationships to make predictions on new data. Systems enabled by machine learning can allow companies to optimize costs, improve customer experiences, and scale-up services. In general, companies agree that artificial intelligence and machine learning are relevant components of their data platform and analytics projects [2] to improve their business decisions making.
Challenges
Despite the financial services industry increasing embrace of big data, significant challenges still exist in the field:
· Most importantly, the collection of unstructured data carries concerns over privacy. For instance, personal information based on individuals’ decisions can be gathered easily through social media, emails and health records.
· Along with vast historical data, banking and capital markets also need to actively manage real-time data. Likewise, investment banks and asset management firms deal with huge amounts of data to gain informational advantage and make sounded investment decisions.
· Another challenge is attracting and retaining the right talent — not only data scientists but business translators who combine data knowledge with industry and functional expertise.
Data changing the Investment Industry: From Big Data to Fast Data
There are three characteristics that define the quality of data: volume, variety, and velocity. In a context of increasing competition, regulatory constraints and customer needs, financial firms are seeking new ways to leverage technology to gain efficiency.
Data itself is worthless unless it can lead to timely and informed action. Therefore, deriving greater value and insight requires ‘Fast Data’ — the rapid gathering and analysis of data in real-time. Unlike big data, which focuses on storage, Fast data is a consumption orientated view and provides a richer context in terms of analysis and decision making. In fact, companies value mostly managing data in real-time (70%) and accessing relevant data rapidly (68%)[3].
At BITA, we believe in a future where passive investments keep growing, where the ability to analyze massive amounts of data quickly will drive performance, and sounded investment decisions. Our view is that the effective use of data requires judgment and careful oversight and that the union of human judgement with technology produces the best results.
For this reason, we set out to tackle some of these issues by developing the world’s most advanced technology infrastructure. Our solutions include BITA ACE, a real-time and high-performance index calculation engine, and BITACORE, a cloud-based backtesting software for flexible construction of indexes and quantitative investment strategies. For more information go to https://www.bitadata.com/
Authors:
Alejandra Olivares, BITA’s Index Product Development Associate
Oana Barabula, Content Collaborator
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Additional sources used: Investopedia.com, Bloomberg.com, Scotsman.com, Raconteur.net
[1] IDC Digital Universe Study (2012), IDC DataAge 2025 Study (2017). Available online: https://www.seagate.com/files/www-content/our-story/trends/files/Seagate-WP-DataAge2025-March2017.pdf
[2] 451 Research’s Voice of the Enterprise: Data and Analytics, IBM, 1H 2019
[3] IDC/Dell EMC Big Data: Turning Promise into Reality
