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The chase is on for more alternative data within financial services

The chase is on for more alternative data within financial services

The chase is on for more alternative data within financial services 45

Amidst a backdrop of global economic uncertainty and sharp and accelerated market shifts, Omri Orgad, Regional Managing Director at Bright Data (formerly Luminati Networks), highlights the rising importance of external data sources, or alternative data, within the financial services industry as a tool for mission-critical decision-making.

With 4 billion webpages and 1.2 million terabytes (TB) of data, the Internet is the largest source of alternative data (alt-data). Web data, social sentiment, geolocation markers, point of sale (POS) transactions, and weather satellite imagery are just some of the real-time, fast, and up-to-date public data streams that allow business leaders to get near-live insights with which to better understand and act on the latest decision-making factors. Naturally, the more data we generate and process as a society, the more we stand to understand trends and forecasts for the future. This is a win-win for companies and their customers.

During the past year, stakeholders across financial services firms have increasingly realised the game-changing nature of alt-data and have been trying to get their hands on quality sources that can remove the guesswork from their investment and strategy-led decisions. A recent survey gathered in cooperation with leading market research experts Vanson Bourne highlighted that nearly a quarter (24%) of financial services professionals who work for organisations that collect alt-data use it daily to aid their work. Furthermore, respondents from financial services sectors, including insurance, banking, and hedge funds, found a clear dependence on external data sources, with 95% of financial services organisations relying on outside information to contribute towards business success in the past year.

In addition, a PwC survey of more than 1,000 senior executives showcased that highly data-driven organisations are three times more likely to report significant improvements in decision-making compared to those who rely less on data.

What is alt-data and how is it generated?

In its most conventional form, the term ‘alt-data’ refers to any information about a financial instrument gained from non-traditional sources. To portray this using a real-life example, just look at how financial analysts complement their insights with information from other sources that include sentiment, expert networks, qualitative data from social media, and so on. Alt-data helps provide an indication of the future performance of a company outside of traditional ways of sourcing data, such as SEC filings, broker forecasts, financial records, press releases, and media reports.

The bigger question here is who generates this alt-data. There are three streams that predominantly generate this type of data, and these include:

Omri Orgad

Omri Orgad

  • Individuals: Your average Joe, like you and me. Every time someone posts a comment on a blog or social media site, or reviews an item on eBay/Amazon, or searches for something on Google, that data is indicative of a behaviour or a pattern. And when you multiply it by a factor of a million or more, you get a trend. It’s this factor that influences decision-making at the highest levels.
  • Companies: They leave a trail of data in their wake, following customer purchases / transactional data, or bulk buys on items, cars leased, houses put up for rent, and so on. This type of alt-data stream creates a more structured pattern that is easier to analyse and can provide even deeper insights into market shifts and trends. Data from government agencies, taxes, and so on is also included in this group.
  • Internet of Things (IoT): Data generated from IoT devices, like the sensors on cars, buildings and inside the house, will power some game-changing insights. For instance, with this type of alt-data, we can better understand the frequency at which people pass a certain street or how often a supermarket is visited. IoT-generated alt-data has the potential to revolutionise this market and is likely going to be the future.

The emergence of alt-data within financial services

Investors and big players within the hedge fund sector are often referred to as ‘quants’, and many of them are increasingly making decisions driven in part by insights discovered using AI and bots. Those have largely been the innovators within the financial services industry when it comes to adopting technologies that allow them to gather alt-data on a mass scale. Those within investment management were also early adopters, with most trading and asset management firms predicted to have exceeded $7 billion investment in alt-data platforms and technology by 2020. This again includes qualitative data drawn from insights within social media and other sites, satellite imagery, web traffic, patent-filling data, and other relevant data points. These serve as forward-looking trading signals and are increasingly seen as a must-have commodity to help asset managers, bankers, and other financial types avoid competition.

According to research from Greenwich Associates in 2017, around 75% of hedge funds already use social media and social-driven news feeds to inform investing decisions. More recently, research from Vanson Bourne has pointed out that 64% of organisations that rely on alt-data sources when building business strategies say that alt-data impacts their investing strategy, and 59% say it impacts their customer experience strategy. Furthermore, 80% of those surveyed expressed they require more competitive insights from alt-data, and 79% hoped to get information on customer behaviour from the data.

There is a vast treasure trove of additional alt-data sources that can be combined with social and news media to offer traders near-live predictive insights. Financial analysts can similarly use these alt-data sources to gain invaluable foresight with which to anticipate and predict specific sector trends. It’s no wonder, then, why alt-data is generating such a good reputation.

What’s next for alt-data?

Estimations from the likes of those at AIMA and others claim that there will be over 5,000 different alternative datasets available by 2024. These vary in quality, breadth, type, and countless other factors, but the figures are a real representation of the market’s growing appetite for alt-data. We will see more hedge funds seeking alpha using alt-data to guide their predictive insights. Banks, fintech players, and other consumer-facing financial instruments that underwrite loans will keep alt-data in their pockets to sharply guide their decision-making risks and increase confidence in their future underwriting processes.

There will be more focus on assessments within the financial services sector towards all types of risks, especially as risk drivers continue to emerge from more and more directions. Investors and banks alike will leverage all the data available and will combine their own financial methodologies with data science techniques to ultimately find the right solutions, reduce risks, and gain competitive advantage.

Without a doubt, alt-data has transformed the financial services industry and will continue to do so over the coming years. Now, increasingly available technology removes the complexity from the equation and simplifies the process of getting your hands on the most trustworthy alt-data. Therefore, seeking alpha or remaining one step ahead of the market no longer seems like a mission-impossible operation. The data is out there to guide the most ground-breaking or comprehensive moves with certainty. During the past year, alt-data has definitely shown us that it can become the financial sector’s well-established, all-knowing, trusted adviser.

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