Applications of artificial intelligence have been growing rapidly in the financial sector including assets management. Major areas where AI is gaining traction in financial assets management include investment banking, personal financial management, and fraud detection. With the help of technologies such as AI, machine learning, and predictive analytics, financial institutes can manage their financial assets effectively and meet their consumer’s changing behaviour. This will help organizations to enhance their business operations and process automation, which further results in improved customer experience.
Increasing demand for automation in financial products
Changing customer behaviour and rising demand for automation in financial products are the major factors contributing to the growth of artificial intelligence (AI) in assets management market. AI is primarily dependant on digital data that are generated from various sources such as customer service and business process. Investment banks and other financial institutes are leveraging artificial intelligence in order to identify and analyse the hidden patterns from collected data to enhance the capabilities of asset management. With the adoption of these technologies, companies can deal with constantly changing compliance and regulatory environment related to market risks.
AI helps in providing automated investment solutions
Artificial intelligence (AI) is widely observed as an innovation driver, and in the wealth management sector, the adoption of AI has led to the development of digital wealth management platforms and services. With the help of automation solutions, the process of wealth allocation can be executed and customized. This constantly monitors the possible portfolio, which in turn reduces the time required in the traditional wealth allocation process. Automated investment solutions are currently limited to bonds, mutual funds, shares, and exchange-traded funds. However, looking at the AI growth in every financial sector, it is expected to see automation will help structured investments in real-time.
Furthermore, the increasing trend of data-driven financial decisions has become the significant factors driving the global AI in assets management market. Moreover, the rising adoption of technologies such as blockchain, big data analytics, etc. in financial services is another factor contributing to the growth of AI in assets management market in the given analysis period.
The data analysis application holds a significant market share
Data analysis, risk & compliance, portfolio optimization, process automation, and others are some of the applications analysed in this market. Among these, the data analysis segment is expected to hold a significant share during the analysis period. The availability of a huge amount of digital data and the need for analyse these data sets are becoming major factors driving the segment in global AI in assets management market over the forecasted period.
North America holds the largest share in the global market
Geographic regions included in the global AI in assets management market study are North America, Europe, Asia Pacific, South America, and Middle East & Africa along with its major countries. Among these, North America is expected to hold the largest share in the global AI in assets management market in a given forecasted period. This can be attributed due to the increasing development of AI and machine learning solutions in financial services and products especially in personal financial management, fraud detection, and investment banking. Furthermore, rising investments in US-based fintech start-ups are expected to drive the AI in the assets management market in the region. It is recorded that, till the third quarter of 2019, the funding in US fintech start-ups has reached USD 12.9 billion compared to USD 12.5 billion in 2018.
Key Market Players
• Lexalytics
• Narrative Science
• Next IT
• IPsoft
• Genpact
• IBM
• Infosys
• Synechron
• Others
Market Segments: AI in Assets Management Market
- By Technology
- Machine Learning
- Predictive Analytics
- NLP
- Others
- By Application
- Data Analysis
- Risk & Compliance
- Portfolio Optimization
- Process Automation
- Others
- By Region (tentative)
- North America
- US
- Canada
- Mexico
- Europe
- Germany
- France
- UK
- Russia
- Asia Pacific
- China
- India
- South Korea
- Japan
- South-East Asia
- The Middle East and Africa
- Saudi Arabia
- South America
- Brazil
- North America
Key Sources
• Industry Associations
• Patent Websites
• Company Annual Reports
• Company Websites
• Key industry leaders
• Technology consultants
• Others
Key Questions Answered
• What are the key growth regions and countries?
• What are the important types and technologies being used?
• What are the market players doing, in terms of research and development?
• Which are the new applications for this market?
• What are the integrations happening?
• What are the recent news, developments, mergers, or large value deals?
Key Stakeholders
• Fintech Companies
• Financial Institutes
• Technology Support Providers
• Software Service Providers
• Regulatory Authorities
• Research and Innovation Organizations
• Technocrats
• Suppliers and Distributors
• Other Channel Partners
• Quality Control Organizations
• Environmental Authorities