In recent years, financial institutions have adopted artificial intelligence (AI) technology to manage their financial assets and reduce their operating costs, thereby increasing their 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 voice recognition technologies are in demand and a large number of acquisitions over the past few years have been associated with these technologies, and the same technologies will dominate investment patterns in years to come. coming.
Key areas where AI could be deployed in financial asset management include fraud detection, personal finance 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 analytics. machine learning. This will help organizations automate and improve business processes, which will result in an improved customer experience.
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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 top vendors increasing their global footprint in this space. However, various vendors such as IPsoft and Lexalytics compete with them in the global market by providing competitively priced solutions with customized product offering. Market growth is fueled by leading vendors entering into strategic partnerships with ecosystem vendors and third-party vendors to increase global footprint and customer service capabilities.
Natural language processing (NLP) is the fastest growing technology in the global AI market in financial asset management due to the increasing deployment of chatbots and virtual personal assistants in banking. Moreover, the growing demand for sentiment analysis and management of huge volumes of contracts will boost the NLP segment during the forecast period.
Data analytics holds the largest market share in the application segment of the global AI in financial asset management market, primarily due to the availability of huge volumes of data generated from multiple sources and 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 others.
According to MRH Research, the global AI in Financial Asset Management market is expected to grow at a CAGR of XX% during the forecast period 2022-2030. The objective of this report is to define, describe, segment and forecast AI in Financial Asset Management market based on technology, application and regions. Additionally, the report helps venture capitalists understand the businesses better and make informed decisions. The report is primarily designed to provide business executives with strategically substantial competitor insights, data analysis and market insights, development and implementation of an effective marketing plan.
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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.
Regions include Americas, Europe, APAC, and ROW (ROW includes Middle East and Africa; APAC includes East Asia, South Asia, Southeast Asia and Oceania)
The report includes vendor analysis, which includes financial status, business units, top business priorities, SWOT, business strategies, and opinions.
The report covers the competitive landscape, which includes mergers and acquisitions, joint ventures and collaborations, and competitor benchmarking.
In the vendor profile section, for private companies, segment financial and revenue information will be limited.
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Key players offering AI in financial asset management across the globe include:
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