Artificial Intelligence (AI) in Asset Management Market Size, By Technology (Machine Learning, Natural Language Processing (NLP)), By Deployment (On-Premise, Cloud), By End Use (BFSI, Retail & E-Commerce, Healthcare, Energy & Utilities), Application & Global Forecast, 2023 - 2032

AI in Asset Management Market Size

AI in Asset Management Market size valued at USD 2.5 billion in 2022 and is anticipated to grow at a CAGR of 24% between 2023 and 2032. Exponentially growing data volumes, tight regulations, and low interest rates are forcing asset managers to rethink their traditional business strategies. In addition, the latest technological developments have paved the way for specialization in asset management. Many fintech companies are using knowledge-based & domain-rich machine learning and Natural Language Processing (NLP) techniques to provide financial & investment services.
 

For example, in February 2023, Morningstar, Inc. partnered with TIFIN Group to provide TIFIN Asset Manager Platform (AMP) with aggregated insights from its products to strengthen the asset manager platform’s algorithmic models for distribution intelligence. The new AMP platform combines the expertise in distribution, marketing, and sales operations into a single software platform, helping asset managers in arranging distribution for non-residents, organization, and stores in a timely manner.
 

AI in asset management encompasses the use of AI algorithms, machine learning, natural language processing, and big data analytics to automate & enhance various aspects of asset management. This includes data analysis, investment decision-making, risk management, portfolio optimization, compliance monitoring, and personalized investment solutions.
 

Regulatory and compliance concerns can hinder AI in asset management market growth. Asset management is subject to strict regulations and compliance standards. The use of digital technology presents additional challenges as algorithms and models must adhere to rules of investor protection, risk management, privacy, and ethical thinking. Introducing the regulatory environment and ensuring compliance with changing regulations can present challenges in the adoption of AI in asset management.
 

COVID-19 Impact

The COVID-19 pandemic had positive impacts on the global market as it accelerated the adoption of AI in asset management as firms sought to navigate market volatility, optimize operations, and adapt to the new normal of remote work & digital interactions. This crisis reinforced the importance of data-driven insights, automation, and agility, driving the increased reliance on AI technologies in the asset management industry.
 

AI in Asset Management Market Trends

The increasing adoption of machine learning and deep learning will drive market growth. Machine learning and deep learning algorithms excel at processing and analyzing large amounts of data. Companies can use this technology to extract valuable insights from various data sources such as financial data, business metrics, company announcements, and newspapers. The ability to analyze complex data in real time enables asset managers to make more informed investment decisions. In addition, the use of machine learning and deep learning in asset management stems from their ability to process complex data, build better understanding, improve risk management, improve evidence, and provide personalized recommendations.
 

AI in Asset Management Market Analysis

The AI in asset management market from machine learning segment was reached USD 1.5 billion in 2022. Machine learning techniques are widely used in quantitative modeling and alpha generation techniques. These algorithms can be trained on historical trading data to identify events or indicators that can result in excessive returns. With the use of machine learning algorithms, asset managers can build quantitative models to capture market inefficiencies, generate alpha, and increase investments.
 

The portfolio optimization segment accounted for 25% of AI in asset management market share in 2022. Portfolio optimization algorithms use historical data and risk returns of different assets to establish optimum ranges. The optimal limit represents the set of information that provides the maximum expected return for a given level of risk or the lowest risk for a given level of expected return. Artificial intelligence, such as machine learning and optimization, can analyze large amounts of data and identify the best information of interest. In addition, rapid advancements in AI and machine learning technologies have significantly enhanced the capabilities of portfolio optimization algorithms. These technologies enable asset managers to process large volumes of data, extract valuable insights, and optimize portfolios with greater precision.
 

North America AI in asset management market held over 30% revenue share in 2022, due to the increasing adoption of advanced technologies in North America. The region has a strong ecosystem of technology companies, research centers, and financial institutions that actively explore & use artificial intelligence for real estate management. The availability of technology & skills along with expertise in the market. The increasing cyber-crimes in BFSI sector is expected to grow the North America market demand. Artificial intelligence plays an important role in fraud detection and prevention in the BFSI industry.
 

Machine learning algorithms can analyze large amounts of transaction data in real time to identify fraudulent patterns, anomalies, and suspicious activities. AI-driven fraud detection enables financial institutions to increase security, reduce financial losses, and protect their customers. Artificial intelligence technology enables the BFSI division to provide personalized financial services based on the client needs.
 

AI in Asset Management Market Share

Some of the major companies operating in the AI in asset management market are

• Amazon Web Services, Inc.
• BlackRock, Inc.
• CapitalG
• Charles Schwab & Co., Inc.
• Genpact
• Intel
• Infosys Limited
• International Business Machines Corporation
• IPsoft Inc.
• Lexalytics
• Microsoft
• TABLEAU SOFTWARE LLC
• Next IT Corp.
• S&P Global
• Salesforce, Inc.

These companies focus on strategic partnerships and new service launches & commercialization for market expansion. Furthermore, these companies are heavily investing in research to introduce innovative services and garner maximum revenue in the market.
 

AI in Asset Management Industry News:

• In February 2023, EagleView Technologies, Inc., a prominent provider of aerial imagery, software & analytics, released new asset management solutions. By integrating Machine Learning (ML) with high-resolution aerial imagery, the company aims to solve various asset management problems for commercial organizations and local governments.
   

The Artificial Intelligence (AI) in asset management market research report includes in-depth coverage of the industry with estimates & forecast in terms of revenue (USD Million) from 2018 to 2032 for the following segments:

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Market, By Technology

• Machine Learning
• Natural Language Processing (NLP)

Market, By Deployment Model

• On-premise
• Cloud

Market, By Application

• Portfolio Optimization
• Conversational Platform
• Risk & Compliance
• Data Analysis
• Process Automation
• Others

Market, By End Use

• BFSI
• Retail & E-commerce
• Healthcare
• Energy & Utilities 
• Others

The above information has been provided for the following regions and countries:

• North America
  • U.S.
  • Canada
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Netherlands
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • ANZ
  • Singapore 
• Latin America
  • Brazil
  • Mexico
  • Argentina
• MEA
  • UAE
  • Saudi Arabia
  • South Africa