The document provides an overview of a 67-page report on the AI in financial asset management market from 2019 to 2025. It discusses key trends such as the growing adoption of AI technologies like machine learning by financial institutions to manage assets and customer interactions. The global market is expected to grow at a CAGR of 33.84% during the forecast period, with technologies like natural language processing seeing increased use. The report segments the market by technology, applications, and regions to provide an in-depth analysis of industry trends, competitive landscape, and growth opportunities.

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AI in Financial Asset Management Market – Notable Developments, Upcoming Trends & Future
Applications 2030
[67 Report Pages ] 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 an d 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 technologie s will dominate the investment
patterns in the coming years
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Major areas where AI could be deployed in manging 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 me et expectations of the changing
customer behavior by leveraging technologies, including AI, predictive analytics, and machine learning. This will assist orga nizations in automation and improves
business processes, thus resulting in enhanced customer’s experience.
The global AI in financial asset management market is categorized based on the presence of diversified small and large vendors. Gen pact, IBM, Infosys, and
Synechron are among the key vendors increasing their global footprint in this space. However, various vendo rs 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 grow th 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 owi ng to the increasing deployment of
chatbots and virtual personal assistants in the banking sector. Additionally, increasing demand for sentiment analysis and ma nagement 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 theses datasets for decision makin g. Investment banks are implementing AI in
the areas such as investment decisions, alternative investment strategies, managing hedge funds and others.
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According to Infoholic Research, the global AI in financial asset management market is expected to grow at a CAGR of 33.84% d uring the forecast period 2019–
2025. The aim of this report is to define, describe, segment, and forecast the AI in financial asset management market on the basis of technology, application,
and regions. In addition, the report helps the venture capitalists in understanding the companies better and make well-informed decisions. The report is primarily
designed to provide the company’s executives with strategically substantial competitor information, data analysis, and insigh ts about the market, development,
and implementation for an effective marketing plan.
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 Americas, Europe, APAC, and RoW (RoW includes Middle East and Africa; APAC includes East Asia, South Asia, So uth-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 vendors 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
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1.1 Primary Research
 The global Digital Advertising Market is derived using a mix of bottom up and top down approach. To derive the global number for 2015 to
2019, the country wise revenue has been analyzed and summed up to Resources the regional market, which were further added up to
Resources global market. Thus, each region has been considered as the separate market and validated using data triangulation
 Historic estimation is an iterative process triangulated by multiple factors which include and not limited to adoption of Titanium 3D Printing
Medical Devices, regulatory policies, prices of Titanium 3D Printing Medical Devices, and economic development of each country
 Growth rate of the market has been determined by analyzing the trend of the parent and ancillary markets. Moreover, other factors such as
research initiatives, funding overview, and regulatory framework in various countries have also been taken into consideration to derive the
market growth rate
 Pricing data was collected via actual quotes from manufacturers and company press releases on regional level. To avoid discrepancies in the
pricing of various countries, regional prices have been considered for market estimation
For forecasting, the following parameters were considered:
 The base year considered for Digital Advertising Market is 2019. Market size from 2015-2019 are the actual revenues with forecasts from
2020 to 2026
 As a part of company policy, we do not investigate publicly available reports, as these reports are not always coherent, sometimes even
contradicting in their declarations of value. Also, we don’t have access to their reports
 Manufacturers do not generally specify clientele, as it constitutes critical strategic information
 Major players in the market were identified through primary as well as secondary research
 Market drivers and restraints along with their current and expected impact has been taken into consideration
 Inflation has not been taken into consideration while estimating the market

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 Financial data has been only provided for publicly listed companies. The information for privately held companies is sourced from the company
websites and other reliable paid data sources
1.2 Secondary data sources
List of secondary sources includes but is not limited to:
 Hoover’s
 Factiva
 Investor Presentations
 Company Annual Reports
 Many Others