The global alternative data market size was valued at $2.7 billion in 2021, according to Grand View Research.

Alternative Data is expected to grow at a compound annual growth rate of 54.4% from 2022 to 2030.

Over the last decade, we have seen multiple new types of alternative data emerge. Common alternative data sources include web scraping, financial transactions, mobile devices, social media, satellites, sensors and IoT-enabled devices.

Investment firms are actively expanding their informational advantage by incorporating alternative data into their investment and risk processes. Over 70% of asset managers in the U.S. are inclined to use alternative data in their investment process.

The Difference between Traditional and Alternative Data

Traditional data sources include financial data available through sources like Bloomberg, S&P and similar data providers. It contains data made available by exchanges, SEC filings, financial statements, press releases and management presentations.

An alternative data set is compiled from various sources, including social media, web traffic, e-commerce portals, public records, financial transactions, mobile devices, sensors, and satellites.

Web scraping and financial transactions remain the most common sources of alternative data.

More About Alternative Data

The main categories of alternative data include credit & debit card transactions, email receipts, geo-location (foot traffic) records, mobile application usage, satellite & weather data, social & sentiment data, web scraped data, web traffic, and other data types.

According to Grand View Research, the credit & debit card transactions led the market and accounted for more than 14% of global alternative data revenue in 2019. The driver behind this phenomenon is two-fold: investors’ appetite for using the data, and the providers’ willingness to sell credit card transaction data. Moreover, data providers have been enhancing their capabilities of sorting credit card transaction data by gender, age, seller, geography, and other metrics. AlphaMille has the capability to mine insights from this data with other types of data, thus enabling investors to identify profitable trends and businesses.

The Benefits of Alternative Data

When advanced analytics and data science are applied to alternative data, the process yields additional insights into evaluating investment opportunities. These insights produce a crucial differentiator generating alpha (market outperformance) for the buy-side entities including hedge funds, mutual funds, private equity funds, pension funds, unit trusts, and life insurance companies.

According to Grand View Research, hedge funds, including Blackrock Advisors, AQR Capital Management, and Bridgewater Associates accounted for over 70% of the global alternative data revenue in 2020. Asset managers use alternative data to derive predictive insights and enhance risk management.

How to Leverage Alternative Data

Alternative data has become one of the key drivers of alpha (market outperformance). The process of incorporating alternative data into the investment and risk processes, however, is challenging. Compared to the traditional financial data sources, alternative data is often unstructured, lacks specific patterns, and is “big” - collected often, thus creating storage and processing challenges. This requires expert personnel and cutting-edge technologies, including analytics platforms, fluid data architecture, data science, and testing tools in order to leverage meaningful insights from this data. AI tools such as ML and Natural Language Processing (NLP) are used for analyzing data, unlocking its insights and value, and boosting the growth of alternative data.