DUBLIN--(BUSINESS WIRE)--The "Global AI in Financial Asset Management Market - Drivers, Restraints, Opportunities, Trends, and Forecast up to 2025" report has been added to ResearchAndMarkets.com's offering.
The Global AI in Financial Asset Management Market is Expected to Witness a CAGR of 33.84% to Reach Revenue of $11.39 Billion by 2025
In recent years, financial institutions are adopting the artificial intelligence (AI) technology for managing their financial assets and reducing operating cost, thereby increasing the revenue. Several fintech companies and banks are rapidly deploying voice assistants and chatbots to manage customer interactions and resolve issues (queries) with minimal human involvement. Machine learning, computer vision, and speech recognition technologies are in demand and major number of acquisitions in the recent years were associated with these technologies, and the same technologies will dominate the investment patterns in the coming years.
Major areas where AI could be deployed in managing financial assets include fraud detection, personal financial management, and investment banking. With the implementation of financial asset management, the financial institutions can effectively manage their financial assets and meet expectations of the changing customer behaviour by leveraging technologies, including AI, predictive analytics, and machine learning. This will assist organizations in automation and improves business processes, thus resulting in enhanced customers experience.
The global AI in financial asset management market is categorized based on the presence of diversified small and large vendors. Genpact, IBM, Infosys, and Synechron are among the key vendors increasing their global footprint in this space. However, various vendors such as IPsoft and Lexalytics are competing with them in the global market by providing solutions at a competitive price with the customized product offering. The market growth is fuelled by key vendors entering into strategic partnerships with suppliers and third-party vendors in the ecosystem to increase the global footprint and customer service capabilities.
Natural language processing (NLP) is the fastest growing technology in the global AI in financial asset management market owing to the increasing deployment of chatbots and virtual personal assistants in the banking sector. Additionally, increasing demand for sentiment analysis and management of huge volumes of contracts will drive the NLP segment during the forecasted period.
Data analysis is having the largest market share in the application segment of the global AI in financial asset management market primarily due to availability of huge volumes of data being generated from multiple sources and need to analyse these datasets for decision making. Investment banks are implementing AI in areas such as investment decisions, alternative investment strategies, managing hedge funds and others.
The global AI in financial asset management market is categorized based on three segments - technology, application, and regions.
- Technology includes Predictive Analytics, Machine Learning, NLP, and Others
- Application includes Conversational Platforms, Data Analysis, Risk & Compliance, Portfolio Optimization, Process Automation, and Others
- Regions include the Americas, Europe, APAC, and RoW (RoW includes the Middle East and Africa; APAC includes East Asia, South Asia, South-East Asia, and Oceania)
- The report comprises an analysis of vendors, which includes financial status, business units, key business priorities, SWOT, business strategies, and views.
- The report covers the competitive landscape, which includes mergers & acquisitions, joint ventures & collaborations, and competitor comparison analysis.
- In the vendor's profile section, for the companies that are privately held, the financial information and revenue of segments will be limited.
The key players offering AI in financial asset management across the globe include:
- Genpact
- IBM
- Infosys
- Synechron
- Next IT
- IPsoft
- Lexalytics
- Narrative Science
Key Topics Covered:
1 Executive Summary
2 Industry Outlook
2.1 Industry Snapshot
2.1.1 Industry Overview
2.1.2 Industry Trends
3 Market Snapshot
3.1 Total Addressable Market
3.2 Segment Addressable Market
3.2.1 PEST Analysis
3.2.2 Porter's Five Force Analysis
3.3 Related Markets
3.4 Market Segmentation
3.5 Market Dynamics
3.5.1 Drivers
3.5.1.1 Adoption of intelligent systems in the data-driven financial sector
3.5.1.2 Rapid proliferation of new investment vehicles
3.5.1.3 Changing customer behaviour and expectation
3.5.2 Restraints
3.5.2.1 Reluctance among financial institutions to deploy fully autonomous systems
3.5.2.2 Workforce inability to react to AI outcomes while managing financial assets
3.5.3 Opportunities
3.5.3.1 Implementation of AI for Merger & Acquisition
3.5.3.2 Adoption of cognitive systems in core banking operations
3.5.4 DRO - Impact Analysis
4 AI in FAM Market, By Technology
4.1 Overview
4.2 Predictive Analytics
4.3 Machine Learning
4.4 NLP
4.5 Others
5 AI in FAM Market, By Application
5.1 Overview
5.2 Conversational Platform
5.3 Data Analysis
5.4 Risk & Compliance
5.5 Portfolio Optimization
5.6 Process Automation
5.7 Others
6 AI in FAM Market, By Geography
6.1 Overview
6.2 Americas
6.3 Europe
6.4 APAC
6.5 ROW
7 Competitive Landscape
7.1 Competitor Analysis
7.2 Product/Offerings Portfolio Analysis
7.3 SWOT Analysis
7.4 Market Developments
7.4.1 Mergers & Acquisitions (M&A)
7.4.2 Expansions
7.4.3 Product Launches & Exhibitions
8 Vendor Profiles
For more information about this report visit https://www.researchandmarkets.com/r/obzp6f
