Alternative Data Market to surpass USD 42.3 Billion by 2032
As per a recent research report, Alternative Data Market surpass USD 42.3 Billion by 2032.
The growing
prominence of internet, social media, e-commerce, and the IoT beyond
traditional financial and economic indicators will drive the market growth. Rising
advancements in technology, including big data analytics and AI, have made it
feasible to process and extract valuable insights from massive volumes of data.
The granular and real-time nature of alternative data offers deeper
understanding of various industries and markets to offer competitive advantages.
The surging focus of major industry players on innovative product developments to
cater to the rising need for alternative data solutions is also expected to
fuel the segment growth.
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Alternative data
market from the IT and telecom industry vertical segment accounted for
considerable revenue share in 2022 and is likely to propel at notable CAGR from
2023 to 2032. The increasing reliance on cloud services, IoT devices, and
mobile technologies has led to the proliferation of data sources. Moreover, as investors
are leveraging IT and telecom data to make informed decisions, especially in
technology-related investments, market players are introducing innovative
solutions, further boosting the segment growth. For instance, in April 2023,
Finastra, a global financial software tool provider, collaborated with Alygne,
a platform that delivers customized ESG alternative data, to assist asset
managers worldwide in making informed ESG investments.
Alternative data market from the credit and
debit card transactions type segment is set to witness substantial expansion
through 2032. The growth can be attributed to the increasing inclination of customers
towards cashless transaction options, including credit and debit cards. For
instance, in 2022, 54.8 billion credit card transactions were made in the U.S. With
businesses and investors increasingly seeking more comprehensive insights into
consumer behavior and economic trends, credit and debit card transaction data
have emerged as valuable sources of information. Additionally, the advancements
in data analytics and AI have enabled businesses to extract actionable
intelligence from these data sources, thereby driving segment growth.
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Asia Pacific alternative data market size is
estimated to be worth USD 11.4 billion by the end of 2032 attributed to the
strong growth of e-commerce and rising digital transactions in the region. The rapid digital
transformation has led to the surge in online consumer activities and adoption
of emerging technologies, such as IoT and mobile payment systems. For instance,
in 2021, the highest number of real-time transactions were conducted in India,
reaching 48 billion. Additionally, investors and businesses in Asia Pacific are
increasingly recognizing the value of alternative data in forming investment
strategies, market expansion, and risk assessment, further offering potential
growth opportunities to the regional industry players. To cite an instance, in
May 2023, ExtractAlpha, a Hong Kong-based provider of investment research and
data analytics, unveiled new alternative datasets to assist investors in
making more informed decisions while increasing alpha creation.
Partial chapters of report table of contents
(TOC):
Chapter 2 Executive Summary
2.1
Alternative data market 360º synopsis, 2018 - 2032
2.2 Regional
trends
2.3 Data type
trends
2.4 Industry
vertical trends
2.5 End-use
trends
Chapter 3 Alternative Data Market
Industry Insights
3.1 Impact on
COVID-19
3.2 Russia-
Ukraine war impact
3.3 Industry
ecosystem analysis
3.4 Vendor
matrix
3.5 Profit
margin analysis
3.6
Technology & innovation landscape
3.7 Patent
analysis
3.8 Key news
and initiatives
3.9
Regulatory landscape
3.10 Impact
forces
3.10.1 Growth
drivers
3.10.1.1
Rising need for data-driven decision making
3.10.1.2 The
rapidly evolving technologies
3.10.1.3
Rising adoption of data analytics for data excavation
3.10.2
Industry pitfalls & challenges
3.10.2.1 Data
privacy and compliance
3.10.2.2 Data
bias and representativeness
3.11 Profit
margin analysis
3.12 Vendor
matrix analysis
3.13 Growth
potential analysis
3.14 Porter’s
analysis
3.15 PESTEL
analysis
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