Alternative Data Market Overview, Analysis And Forecast To 2030

The global alternative data market size was valued at USD 2.7 billion in 2021 and is expected to expand at a compound annual growth rate (CAGR) of 54.4% from 2022 to 2030.

The global Alternative Data Market size is anticipated to reach USD 143.31 billion by 2030, according to a new report by Grand View Research, Inc. The market is expected to expand at a CAGR of 54.4% from 2022 to 2030. The increasing emphasis on gaining alpha from hedge funds is expected to boost the demand for alternative data. The asset managers from hedge funds, mutual funds, private equity funds, pension funds, unit trusts, life insurance companies, and other BFSI entities are highly inclined to use alternative data to derive predictive insights. Moreover, the use of alternative data for risk management processes is also expected to drive market growth.

Nowadays, data sources are not limited to transactions, and email receipts as companies are finding ways to extract data from various emerging sources. These include social media, web traffic, mobile devices, sensors, IoT-based devices, satellites, and e-commerce portals. The data analysts utilize this data in correlation with each other to derive various hidden patterns and insights. However, the data collected from some of these sources conflict with privacy regulations such as the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR). Thus, the data aggregators and end-users need regulatory compliance, which ensures their datasets are free from Personal Identifiable Information (PII).

North America dominated the market and accounted for a revenue share of more than 67.0% in 2021. The region is estimated to continue its dominance over the forecast period from 2022 to 2030. The emerging presence of numerous alternative data providers in the U.S is the major driving factor. Companies such as Advan, Eagle Alpha, M Science, and YipitData are providing various types of alternative data, including credit and debit card transactions, email receipts, geo-location (foot traffic) records, mobile usage, satellite, weather data, social and sentiment data, and web scraped data. The acquisitions and partnership initiatives from companies such as Nasdaq and S&P Global Platts is further expected to fuel regional market growth.

On the other hand, Asia Pacific is expected to emerge as one of the fastest-growing regional markets over the forecast period. This is due to rising use-cases of alternative data in BFSI, retail, automotive, and telecommunication industries. The use of alternative data for investments and risk assessment, particularly from companies in emerging economies, such as India and China, is expected to boost the regional market growth. 

Related Press Release@ Alternative Data Market Report

Alternative Data Market Report Highlights

• Amidst the coronavirus pandemic, the companies are using alternative data collected from social media, mobile phones, applications, wearables, and other IoT-based devices to assess changes in consumer behavior patterns related to purchases and interests
• The credit and debit card transactions segment is anticipated to exhibit the highest CAGR from 2022 to 2030 owing to the high accuracy of the data type and significant demand from asset managers
• The hedge fund operators segment held the largest revenue share amongst all end-users in 2021 on account of rising demand for data from the investors and firms to identify lucrative investment opportunities and generate alpha
• The BFSI industry segment held the largest market share in 2021 as the entities such as hedge funds, mutual funds, and insurance companies are early adopters of alternative data
• North America dominated the market and accounted for over 67.0% share of revenue in 2021 and is expected to maintain its dominance from 2022 to 2030
• Emerging economies, such as India, Thailand, Singapore, and China, are expected to drive the market in the Asia Pacific owing to the rising use cases of alternative data for predictive risk assessment