The AI in Asset Management Market

AI has offered a major impact to the wealth management sector in the past few years. Fintech companies provide their clients a wide array of AI-enabled advisor services to make automated investment decisions. AI-enabled services such as chatbot have helped to enhance customer interactions and services. Rising data volumes, stringent regulations and low-interest rates are promoting asset managers to deploy AI solutions in asset management. Artificial intelligence is used for uses such as customer experience, operational efficiency and investment processes. There has been a huge surge in relocations and deployments of devices and equipment, in the asset management sector which creates opportunities for this AI in asset management market. The ability to purchase, deploy and manage hardware assets manually is getting significantly complicated. This makes a sense of urgency to seek for new product innovations which can deal with huge amounts of data. AI can assist firms in creating actionable insights for connected devices and minimize costs with smart asset management techniques.AI techniques are highly used for the procurement of transactions done online. Machine Learning is majorly been deployed to increase the precision and efficiency of operational workflow, enhance the customer experience and improve the system performance. On the other hand, the huge cost of the solutions lack of awareness among the companies will impede market growth.

Furthermore, the researchers have made enormous strides in developing the ideal human-machine interaction systems in the recent years. Artificial intelligence is utilized to capture audio, text and imagery data from several vendor/internal databases and public sources by applying NLP, computer vision and voice recognition programs. For instance, computer vision and NLP are adopted for data extraction from issuer filings for valuation models and transcription of analyst conference calls. More expansive programs will also process the information collected from several sources to create insights into the investment decision-making process. This generally needs advanced AI techniques, such as machine learning and deep learning.

The global AI in Asset Management Market is segregated on the basis of Type as On Premise and Cloud based. Based on Application the global AI in Asset Management Market is segmented in Portfolio Optimization, Conversational Platform, Risk & Compliance, Data Analysis and Process Automation.

The global AI in Asset Management Market report provides geographic analysis covering regions, such as Europe, North America, Asia Pacific, and Rest of The World. The AI in Asset Management Market for each region is further segmented for major countries including the U.S., Canada, Germany, the U.K., France, Italy, China, India, Japan, Brazil, South Africa, and others.

Competitive Analysis

Amazon Web Services, Inc., BlackRock, Inc., CapitalG, Charles Schwab & Co., Inc, Genpact, Infosys Limited and others are among the major players in the global AI in Asset Management Market. The companies studied in terms of product strategy and various n several growth and expansion strategies to gain a competitive edge in the market. The major players not only follow value chain integration with business operations in multiple stages of the value chain.

• May-2018: Microsoft acquired Semantic Machines, a developer of new approaches for building conversational AI. The companies jointly will develop their work in conversational AI with Microsoft's digital assistant Cortana and social chatbots such as XiaoIce.
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1.      Introduction

1.1.       Key Points

1.2.      Report Description

1.3.      Markets Covered

1.4.      Stakeholders

2.     Research Methodology

2.1.      Research Scope

2.2.     Research Methodology

2.2.1.     Market Research Process

2.2.2.    Research Methodology

2.2.2.1.           Secondary Research

2.2.2.2.          Primary Research

2.2.2.3.          Models for Estimation

2.3.     Market Size Estimation

2.3.1.     Bottom-Up Approach

2.3.2.    Top-Down Approach

3.     Executive Summary

4.    Market Overview

4.1.      Introduction

4.2.     Drivers

4.3.     Restraints

4.4.     Opportunities

4.5.     Challenges

5.     AI in Asset Management Market, By Type

5.1.      Key Points

5.2.  On Premise

5.3.  Cloud based

6.    AI in Asset Management Market, By Application

6.1.      Key Points

6.2. Portfolio Optimization

6.3. Conversational Platform

6.4. Risk & Compliance

6.5.  Data Analysis

6.6. Process Automation

7.     Competitive Landscape

7.1.      Introduction

7.2.     Start-up companies- AI in Asset Management Market

7.3.     Recent Developments

7.3.1.      Mergers & Acquisitions

7.3.2.     New Product Developments

7.3.3.     Portfolio/Production Capacity Expansions

7.3.4.     Joint Ventures, Collaborations, Partnerships & Agreements

7.3.5.     Others

8.    Company Profile

8.1.  Amazon Web Services, Inc.

8.2. BlackRock, Inc.

8.3. CapitalG

8.4. Charles Schwab & Co., Inc

8.5. Genpact

8.6. Infosys Limited

8.7.  International Business Machines Corporation

8.8. IPsoft Inc.

8.9. Lexalytics

8.10.    Microsoft

8.11.     Narrative Science

8.12.    Next IT Corp.

8.13.    S&P Global

8.14.    Salesforce.com, Inc.