NEW
YORK, July 16, 2024 /PRNewswire/ -- The global
artificial intelligence in asset management market size is
estimated to grow by USD 10.37
billion from 2023-2027, according to Technavio. The
market is estimated to grow at a CAGR of 37.88% during
the forecast period. Rapid adoption of artificial intelligence in
asset management and growing importance of asset tracking is
driving market growth, with a trend towards growing
adoption of cloud-based artificial intelligence services in asset
management. However, rising number of data privacy and
cybersecurity poses a challenge. Key market players include
Amazon.com Inc., AXOVISION GmbH, BlackRock Inc., Deloitte Touche
Tohmatsu Ltd., Genpact Ltd., Infosys Ltd., International Business
Machines Corp., Lexalytics Inc., Microsoft Corp., New Narrative
Ltd., Salesforce Inc., and The Charles Schwab Corp..
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Artificial
Intelligence In Asset Management Market Scope
|
Report
Coverage
|
Details
|
Base year
|
2022
|
Historic
period
|
2017 - 2021
|
Forecast
period
|
2023-2027
|
Growth momentum &
CAGR
|
Accelerate at a CAGR of
37.88%
|
Market growth
2023-2027
|
USD 10373.18
million
|
Market
structure
|
Concentrated
|
YoY growth 2022-2023
(%)
|
35.12
|
Regional
analysis
|
North America, Europe,
APAC, Middle East and Africa, and South America
|
Performing market
contribution
|
North America at
49%
|
Key
countries
|
US, China, Germany, UK,
and France
|
Key companies
profiled
|
Amazon.com Inc.,
AXOVISION GmbH, BlackRock Inc., Deloitte Touche Tohmatsu Ltd.,
Genpact Ltd., Infosys Ltd., International Business Machines Corp.,
Lexalytics Inc., Microsoft Corp., New Narrative Ltd., Salesforce
Inc., and The Charles Schwab Corp.
|
Market Driver
Asset management is a vital business function, and the
integration of cloud-based artificial intelligence (AI) services is
revolutionizing its operations. AI's cost-effectiveness and
scalability make it an attractive option for asset managers seeking
to enhance their efficiency and decision-making capabilities. These
services enable asset managers to process vast amounts of data,
recognize trends, and make decisions based on real-time
information. AI models can analyze economic data, market trends,
and other investment variables, optimizing portfolios by
identifying profitable investments. In risk management, AI plays a
significant role, allowing early identification and mitigation of
potential risks, minimizing losses, and safeguarding client
investments. Customizable AI models cater to unique investment
strategies, risk profiles, and firm requirements, providing a
competitive edge. The abundance of available data is another factor
fueling AI adoption in asset management. Cloud-based AI services
expeditiously process this data, offering real-time insights for
informed investment decisions. These factors are anticipated to
fuel the growth of the cloud-based AI market in asset management
during the forecast period.
Artificial Intelligence (AI) is revolutionizing the Asset
Management industry by enhancing quantitative modeling and alpha
generation techniques. AI models use historical trading data to
identify market inefficiencies, providing valuable insights for
asset managers. Wealth management firms are leveraging AI to
improve operational efficiency, streamline investment processes,
and ensure data quality for better client retention. Technology
companies like EagleView, an analytics provider, use AI to analyze
aerial imagery and news articles for investment opportunities.
Human-machine interaction systems, such as chatbots and
conversational platforms, offer personalized services to both
business-to-consumer and business-to-business clients. AI's ability
to learn from large datasets through deep learning algorithms
enables more accurate predictions and faster response times. Low
interest rates and strict regulations necessitate the need for AI
to generate alpha and optimize financial transactions. Natural
language processing (NLP) and voice recognition programs improve
human-machine interaction, while computer vision and virtual
assistants offer operational advantages in a work-from-home (WFH)
environment. AI's role in asset management continues to grow, with
applications ranging from portfolio management to risk assessment
and regulatory compliance.
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Market Challenges
- The artificial intelligence (AI) in asset management market has
experienced substantial growth in recent years, offering benefits
such as improved decision-making and increased efficiency for asset
management firms. However, the use of AI technology raises concerns
regarding data privacy and cybersecurity. Asset managers rely on
large data sets to function, but ensuring their privacy and
protection is crucial. Advanced AI algorithms require access to
detailed personal and financial information, making it a prime
target for cybercriminals. External data sources also pose
challenges, as ownership and data processing become difficult to
manage and audit. Furthermore, automation of tasks through AI can
lead to job losses, necessitating firms to address employment
concerns. Lastly, regulatory compliance is a significant challenge
due to varying laws and regulations governing data protection,
cybersecurity, and AI use. These factors may increase the risk of
cyberattacks and data breaches, potentially hindering market
growth.
- Artificial Intelligence (AI) is revolutionizing the Asset
Management industry, with conversational platforms like chatbots
becoming essential for Business-to-Consumer and
Business-to-Business interactions. However, challenges persist,
such as strict regulations and low-interest rates. AI tools like
Natural Language Processing (NLP), computer vision, and voice
recognition programs are transforming investment services. With the
shift to Work From Home (WFH), digital technology is increasingly
important. TIFIN Group's Scotia Smart Investor uses AI algorithms
and machine learning for data analysis, decision making, risk
management, and portfolio optimization. Compliance monitoring,
investor protection, privacy, ethical thinking, and market
volatility are addressed through AI. Data sources include financial
data, company announcements, and business metrics. AI's role in
asset management is crucial, but it must navigate regulations,
interest rates, and ethical considerations.
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Segment Overview
This artificial intelligence in asset management market report
extensively covers market segmentation by
- Deployment
- 1.1 On-premises
- 1.2 Cloud
- Industry Application
- 2.1 BFSI
- 2.2 Retail and e-commerce
- 2.3 Healthcare
- 2.4 Energy and utilities
- 2.5 Others
- Geography
- 3.1 North America
- 3.2 Europe
- 3.3 APAC
- 3.4 Middle East and
Africa
- 3.5 South America
1.1 On-premises- The on-premise segment of the
global artificial intelligence (AI) in asset management market is
projected to experience substantial growth in the upcoming years.
On-premise AI solutions offer organizations more control and
flexibility over their data compared to cloud-based alternatives.
Installed locally on organizations' servers, these solutions cater
to unique business requirements. On-premise AI solutions provide
complete ownership and control over data, enabling customization
that is not possible with cloud-based options. Additionally, they
offer enhanced security, as data is stored within the
organization's premises instead of on a remote cloud server,
reducing the risk of data breaches. Furthermore, on-premise
solutions deliver superior performance and faster response times,
resulting in more accurate and actionable insights for better
decision-making. Financial institutions, particularly banks and
other financial organizations, are increasingly adopting on-premise
AI solutions for asset management due to their need for
customization and security in handling large volumes of sensitive
data daily. The continuous addition of features and advancements in
on-premise AI solutions is expected to fuel the expansion of the
global AI in asset management market throughout the forecast
period.
For more information on market segmentation with
geographical analysis including forecast (2023-2027) and historic
data (2017-2021) - Download a Sample Report
Learn and explore more about Technavio's in-depth research
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efficiency and processing power.
The global Aerospace Artificial Intelligence market is also
expanding, with AI technologies revolutionizing aircraft
operations, maintenance, and safety protocols. Major aerospace
companies are investing in AI for predictive maintenance,
autonomous flight systems, and enhanced passenger experience,
propelling the market's growth.
Research Analysis
Artificial Intelligence (AI) is revolutionizing the asset
management industry by automating various tasks, from portfolio
management to customer service. Conversational platforms, such as
chatbots, are a key application of AI in business-to-consumer and
business-to-business asset management. These systems use Natural
Language Processing (NLP) and deep learning to understand and
respond to customer queries, providing personalized investment
advice and improving operational efficiency. However, the
implementation of AI in asset management is not without challenges.
Strict regulations and low-interest rates pose significant hurdles
for asset managers looking to adopt AI models. FinTech companies
are leading the charge in this space, offering software platforms
that use algorithmic models to analyze financial transactions and
provide data-driven investment recommendations. The TIFIN AMP, a
resourceful AI model from TIFIN Group, is an example of how AI is
transforming investment services. It uses deep learning to
understand client needs and preferences, providing customized
investment solutions while ensuring data quality and client
retention. The human-machine interaction systems also enable
seamless communication between clients and asset managers,
enhancing the overall customer experience. Despite the benefits,
the implementation of AI in asset management also raises concerns
around data security and privacy. Non-residents and other
stakeholders must ensure that regulations are in place to protect
sensitive financial information and maintain transparency in
financial transactions.
Market Research Overview
Artificial Intelligence (AI) is revolutionizing the Asset
Management industry by automating various tasks and enhancing
business strategies. Conversational platforms and chatbots are
being integrated into Business-to-Consumer (B2C) and
Business-to-Business (B2B) models for efficient communication and
customer service. AI technologies like Natural Language Processing
(NLP), computer vision, and voice recognition programs are being
used to analyze vast data volumes and make informed decisions.
However, strict regulations and low-interest rates pose challenges
to the adoption of AI in the industry. AI algorithms and machine
learning models are being used for portfolio optimization, risk
management, compliance monitoring, and decision making. Digital
technology is enabling asset managers to analyze financial data,
business metrics, company announcements, and other data sources for
alpha generation techniques. Wealth management and investment
services are leveraging AI models for operational efficiency,
investment processes, and client retention. Deep learning and
chatbots are being used for human-machine interaction systems,
while virtual assistants are being integrated into software
platforms for non-residents. Technology Insights and analytics
providers like TIFIN Group are offering AI-powered solutions for
asset managers to stay competitive in the digital age. The use of
AI in asset management is also enabling the analysis of aerial
imagery, market volatility, and financial transactions for
investment opportunities. Ethical thinking, investor protection,
privacy, and regulatory compliance are essential considerations in
the implementation of AI models. The asset management industry is
embracing digital technology to stay ahead of the curve and provide
better services to clients.
Table of Contents:
1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation
- Deployment
-
- Industry Application
-
- BFSI
- Retail And E-commerce
- Healthcare
- Energy And Utilities
- Others
- Geography
-
- North America
- Europe
- APAC
- Middle East And Africa
- South America
7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix
About Technavio
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Contacts
Technavio Research
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UK: +44 203 893 3200
Email: media@technavio.com
Website: www.technavio.com/
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