Companies that are slow to incorporate alternative data into their R&D, marketing, investment, risk analysis and other key processes expose themselves to extreme opportunity loss at best and operational peril at worst.

As one prime example, active investment management firms—including hedge funds and even private equity funds—incur the strategic risk of being outmaneuvered by competitors leveraging alternative data in their securities valuation and trading signal process. This as alternative data has emerged as an essential tool for investment management firms seeking market outperformance, known as "alpha."

As an ever-evolving methodology, the last decade has ushered in a myriad of new types and sources of alternative data. Unlike traditional data made available by financial exchanges and indexes, SEC filings, financial statements, corporate filings, analyst predictions, press releases, management presentations and other well-entrenched mainstream sources, today's breed of alternative data sets are being compiled from wide ranging and disparate sources. Everything from financial transactions, satellites, sensors and IoT-enabled devices, to e-commerce portals, public records, mobile devices, social media, web traffic and more. However, web scraping and financial transactions are, by far, the most common methods of alternative data procurement.

US Alternative Data Market - Credit GrandViewR.jpgSo lucrative is the economic upside of alternative data assets, the category is experiencing a veritable gold rush mentality that is driving extreme growth worldwide across practically every industry sector. This, as the global alternative data market size is expected to reach USD $143.31 billion by 2030—a staggering increase from $2.7 billion in 2021—with the category forecasted to expand at a compound annual growth rate (CAGR) of 54.4% from 2022 to 2030, according to Grand View Research.

As one industry case in point, investment firms are actively expanding their informational advantage by incorporating alternative data into their investment and risk processes. An EY Global Alternative Fund survey found that the vast majority (a full 70%) of hedge fund managers and over half (56%) of private equity funds currently use, or plan on using, alternative data to support their investment process.  

two-monitors - LO.jpgBeyond banking and financial services and insurance (BFSI), reported to have collectively led the alternative data market in 2021 with a revenue share of more than 15.0% during the period, there are other alternative data early adopters. A few notables making great strides in the space include online retailers, SaaS purveyors and hospitality. These and other such industries are tapping the power of this alt intel for an array of projection activities, with predictive and algorithmic modeling, demand and trend forecasting, lead generation and competitive intelligence among them.

"There are numerous categories of alternative data, and the businesses who fare best are those with the capability to mine insights from the collected data and cross reference and combine it with other types of data, thus enabling investors to identify profitable trends and strategic opportunities," notes Julia Valentine, Managing Partner at professional services firm AlphaMille.

According to the Alternative Data Global Market Report 2022, North America was the largest region in the alternative data market in 2021. The main categories of alternative data—characterized as the non-traditional type from conventional sources that can serve as an indicator of future performance—are credit and debit card transactions, email receipts, geo-location (foot traffic) records, mobile application usage, satellite and weather data, social and sentiment data, web scraped data and web traffic.

"The driver behind this phenomenon is two-fold: investors' appetite for using the data and the providers' willingness to sell credit card transaction data," Valentine says. "Moreover, data providers have been enhancing their capabilities of sorting credit card transaction data by gender, age, seller, geography and other metrics."

Of course, these types of drill down insights can make it much easier to identify and evaluate opportunities, especially when advanced analytics and data science are applied to examining alternative data sets.

According to Valentine, these offerings produce a crucial differentiator generating alpha for buy-side entities like hedge funds, mutual funds, private equity funds, pension funds, unit trusts and life insurance companies.

"It's essential for investors to have curated alternative data to make their teams, innovation and companies more competitive," said Tracy McWilliams, CEO of Inspire Global Ventures, which launched the JASPY single source private company management system. "Machine learning-enabled alternative data analytics assist our clients, mid-market companies and investment firms, make faster and more informed decisions about investments, innovation, M&A and partnerships with early-stage and private placement companies."

The benefits of employing alternative data are seemingly innumerable. "Among the most important is its ability to derive proprietary real-time signals providing alternative viewpoints, unforeseen insights or perhaps both," notes Valentine. "The ability to go beyond standard financial data to understand company performance, market dynamics or consumer behavior is extraordinarily valuable for companies and investors who desire to plan and execute in a calculated, enlightened and intentional way with mitigated risk."

Even amid the extreme upside, a number of challenges plague processes for incorporating alternative data into the investment and risk models. "As compared to the traditional financial data collection, alternative data assets are known to be unstructured, lack specific patterns and, given its high collection frequency, require significant storage and processing resources," says Vita Koreneva, AlphaMille Managing Partner.

"Collecting and analyzing alternative data sets certainly requires navigating any number of difficulties or outright obstacles," Valentine warns. "This includes the procurement of expert personnel and cutting-edge technologies like analytics, fluid data architecture and data science platforms, as well as testing tools to actually leverage meaningful insights gleaned from the data. For example, AI tools such as ML and Natural Language Processing (NLP) are used for analyzing alternative data, unlocking its insights and value and boosting the growth of these assets. ESG (Environmental, Social, Governance) data is an key example of alternative data where multiple providers in the public markets are supplemented with the use of multi-modal AI to collect data used by private markets that is unavailable through existing data providers."

Alt data implementation.pngAccording to Valentine, starting or enhancing an alternative data platform involves multiple steps: design, plan, source data, integrate, transform, use ML, deploy, support and evaluate. A shorter, five-step implementation model is also available for entities that are ready for a fast route to value creation.

With such specialized tools and skillsets involved with mining and distilling alt data, many understandably outsource the function. "A few key considerations for a prospective professional services partner involve their ability to quickly integrate new solutions with existing infrastructure; cost of data feeds; and proving what they deem to be optimal, uncorrelated data sets genuinely add quantifiable value rather than noise," she says.

Valentine further recommends they should also demonstrate an aptitude for key requirements of an alternative data platform, such as rapid and efficient onboarding of data sources; combining structured, semi-structured and unstructured data sets; and data preparation and normalization, among others.

"Data mastering is fundamental to gleaning insight from this seemingly limitless universe of information," notes Christian Robertson, CEO of Datasynthesis.  "It means tracking the data lifecycle from its source—be it real-time or historical, structured or unstructured—through a strict rules-based validation process generating actionable data used to feed the various business intelligence tools used in decision making.  However, to distill meaning from so much information one must adopt an active data mastering approach, which can only be achieved by leveraging the latest open-source technologies with capabilities that far exceed anything possible with existing legacy systems."

Preconditions and complexities aside, AlphaMille Chief Revenue Officer Rick Lutz is keeping an optimistic eye on the big picture. "Alternative data hasn't nearly reached critical mass as of yet and there is tremendous growth ahead in this space," he says. "The big winners will be those that onboard the right 'kind' and caliber of experts who can adeptly navigate this highly specialized and ever-changing field. Done right, the financial upside is stratospheric."

Digital transformation demands agility. That which companies can quickly identify and adapt to ever-fluid business conditions to both survive and thrive. Having the ability to adeptly procure and process alternative data provides a tremendous advantage ... especially for those needing to pivot in the short term. This, whether to reconfigure a strategy, structure, process, team or technology to better assure value-creating—or value-protecting—opportunities. To empower an organization to expand quickly and cost-effectively. To save costs by realizing it is more profitable to outsource non-critical functions to expert providers. To utilize cutting-edge cloud, cybersecurity and data science tools to increase productivity. The profit promoting outcomes are seemingly endless.

No matter the industry in which you operate, now is the time to architect a sound and scalable alternative data plan ensuring your company can keep pace in the 21st Century Digital Age.