Dublin, June 21, 2019 (GLOBE NEWSWIRE) – The “Global AI in Financial Asset Management Market – Drivers, Constraints, Opportunities, Trends and Forecasts to 2025” the report was added to ResearchAndMarkets.com offer.
Global AI in Financial Asset Management Market Expected to Experience a CAGR of 33.84% to Reach $ 11.39 Billion in Revenue by 2025
In recent years, financial institutions have adopted artificial intelligence (AI) technology to manage their financial assets and reduce operating costs, thereby increasing revenues. 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 a large number of acquisitions in recent years have been associated with these technologies, and the same technologies will dominate investment models in the years to come. future
The main areas where AI could be deployed in financial asset management include fraud detection, personal financial management, and investment banking. With the implementation of financial asset management, financial institutions can effectively manage their financial assets and meet the expectations of changing customer behavior by leveraging technologies including AI, predictive analytics and l machine learning. This will help organizations automate and improve business processes, thereby improving the customer experience.
The global AI in financial asset management market is categorized based on the presence of diverse small and large vendors. Genpact, IBM, Infosys and Synechron are among the main suppliers increasing their global footprint in this space. However, various vendors such as IPsoft and Lexalytics compete with them in the global market by offering competitively priced solutions with customized product offering. Market growth is fueled by leading vendors entering into strategic partnerships with vendors and third-party ecosystem vendors to increase global footprint and customer service capabilities.
Natural Language Processing (NLP) is the fastest growing technology in the global financial asset management AI market due to the growing deployment of chatbots and virtual personal assistants in the banking industry. In addition, the growing demand for sentiment analysis and handling huge contract volumes will boost the NLP segment during the forecast period.
Data analytics holds the largest market share in the application segment of the global financial asset management AI market mainly due to the availability of huge volumes of data generated from multiple sources and of the need to analyze these data sets for decision making. Investment banks are implementing AI in areas such as investment decisions, alternative investment strategies, hedge fund management, and more.
The global AI in financial asset management market is categorized into three segments: technology, application, and regions.
- Technology includes predictive analytics, machine learning, NLP and others
- The app includes conversational platforms, data analytics, risk and compliance, portfolio optimization, process automation and more
- The regions include the Americas, Europe, APAC and the ROW (the ROW includes the Middle East and Africa; the APAC includes East Asia, South Asia, l ‘Southeast Asia and Oceania)
- The report includes vendor analysis, which includes financial status, business units, key business priorities, SWOT, business strategies, and views.
- The report covers the competitive landscape, which includes mergers and acquisitions, joint ventures and collaborations, and competitor benchmarking.
- In the Supplier Profile section, for private companies, financial information and segment revenue will be limited.
The main players offering AI in financial asset management around the world are:
- Next computer
- Narrative science
Main topics covered:
2 Industry outlook
2.1 Industry overview
2.1.1 Industry Overview
2.1.2 Industry Trends
3 Market overview
3.1 Total addressable market
3.2 Addressable market segment
3.2.1 PEST analysis
3.2.2 Porter’s five forces analysis
3.3 Related markets
3.4 Market segmentation
3.5 Market dynamics
18.104.22.168 Adoption of smart systems in the data-driven financial sector
22.214.171.124 Rapid proliferation of new investment vehicles
126.96.36.199 Changing customer behavior and expectations
188.8.131.52 Reluctance of financial institutions to deploy fully autonomous systems
184.108.40.206 Inability of the workforce to respond to AI outcomes while managing financial assets
220.127.116.11 Implementing AI for Merger and Acquisition
18.104.22.168 Adoption of cognitive systems in basic banking operations
3.5.4 Scrutineer – Impact assessment
4 AI in the FAM market, by technology
4.2 Predictive analysis
4.3 Machine learning
5 AIs in the FAM market, by application
5.2 Conversation platform
5.3 Data analysis
5.4 Risk and compliance
5.5 Portfolio optimization
5.6 Process automation
6 AI in the FAM market, by geography
7 Competitive landscape
7.1 Competitor analysis
7.2 Analysis of the product / offer portfolio
7.3 SWOT analysis
7.4 Market development
7.4.1 Mergers & Acquisitions (M&A)
7.4.3 Product launches and exhibitions
8 supplier profiles
For more information on this report, visit https://www.researchandmarkets.com/r/5s1hqk
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