AI in Banking Comprehensive Study by Application (Back Office/Operation, Customer Service, Compliance & Security, Others), Service (Professional Service, Managed Service), Technology (Machine Learning, Natural Language Processing (NLP), Computer Vision), Solution (Chatbot Customer Behavior Analytics, Customer Relationship Management (CRM), Data Analytics & Visualization, Fraud Detection, Others), End User (Public Sector Bank, Government Bank, Others) Players and Region - Global Market Outlook to 2024

Edison, NJ -- (SBWire) -- 02/03/2020 --This intelligence report provides a comprehensive analysis of the "Global AI in Banking Market. This includes Investigation of past progress, ongoing market scenarios, and future prospects. Data True to market on the products, strategies and market share of leading companies of this particular market are mentioned. It's a 360-degree overview of the global market's competitive landscape. The report further predicts the size and valuation of the global market during the forecast period.Some of the key players profiled in the study are Google Inc. (United States), Microsoft Corporation (United States), Intel (United States), NVidia Corporation (United States), AWS (United States), IBM (United States), SAP (Germany), Cognizant (United States), Oracle (United States), Salesforce (United States), Accenture (Ireland), IPsoft Inc. (United States) and Micro Strategy Incorporated (United States).

AI in banking refers to the process of operating banking operations by highly automatic techniques. Banking industries especially implementing artificial intelligence to offer personalized banking, customer support services, enhance security and back-end process and others. According to a study conducted by CMR and NASSCOM, 74% top Indian IT decision makers support the need for artificial intelligence in the BFSI sector. Further, emphasizing on technological advancement such as Chatbot enables banking solutions and process automation expected to drive the AI in the banking market.

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Market Drivers
- Rising Demand of Customized IT Solutions in Banking Sector
- Integration of AI and Autonomous Operational Processes

Market Trend
- Increasing Adoption of Chatbot Enabled Banking Applications

Restraints
- High Initial Capital Investment

Opportunities
- Emphasizing on Intelligent Applications for Banking Operations
- Growing Demand of Process Automation

Challenges
- Continuously Changing Technical Landscape
- Maintaining Authenticity and Privacy of the Data

Each segment and sub-segment is analyzed in the research report. The competitive landscape of the market has been elaborated by studying a number of factors such as the best manufacturers, prices and revenues. Global AI in Banking Market is accessible to readers in a logical, wise format. Driving and restraining factors are listed in this study report to help you understand the positive and negative aspects in front of your business.

This study mainly helps understand which market segments or Region or Country they should focus in coming years to channelize their efforts and investments to maximize growth and profitability. The report presents the market competitive landscape and a consistent in depth analysis of the major vendor/key players in the market.

Furthermore, the years considered for the study are as follows:
Historical year – 2013-2017
Base year – 2018
Forecast period** – 2019 to 2025 [** unless otherwise stated]

**Moreover, it will also include the opportunities available in micro markets for stakeholders to invest, detailed analysis of competitive landscape and product services of key players.

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The titled segments and Market Data Break Down are illuminated below:
Application (Back Office/Operation, Customer Service, Compliance & Security, Others), Service (Professional Service, Managed Service), Technology (Machine Learning, Natural Language Processing (NLP), Computer Vision), Solution (Chatbot Customer Behavior Analytics, Customer Relationship Management (CRM), Data Analytics & Visualization, Fraud Detection, Others), End User (Public Sector Bank, Government Bank, Others)

Top Players in the Market are: Google Inc. (United States), Microsoft Corporation (United States), Intel (United States), NVidia Corporation (United States), AWS (United States), IBM (United States), SAP (Germany), Cognizant (United States), Oracle (United States), Salesforce (United States), Accenture (Ireland), IPsoft Inc. (United States) and Micro Strategy Incorporated (United States).

Region Included are: North America, Europe, Asia Pacific, Oceania, South America, Middle East & Africa

Country Level Break-Up: United States, Canada, Mexico, Brazil, Argentina, Colombia, Chile, South Africa, Nigeria, Tunisia, Morocco, Germany, United Kingdom (UK), the Netherlands, Spain, Italy, Belgium, Austria, Turkey, Russia, France, Poland, Israel, United Arab Emirates, Qatar, Saudi Arabia, China, Japan, Taiwan, South Korea, Singapore, India, Australia and New Zealand etc.

Objectives of the Study
- To Define, Describe, and Segment The Global AI in Banking Market On The Basis Of Type, Function, Application, And Region.
- To provide detailed information regarding the major factors influencing the market growth (drivers, restraints, opportunities, and industry-specific challenges)
- To estimate the size of the Global AI in Banking Market in terms of value.
- To study the individual growth trends of the providers of Global AI in Banking Market, their future expansions, and analyze their contributions to the market
- To strategically analyze micro-markets with respect to individual growth trends, future prospects, and contribution to the total market, covered by Global AI in Banking Market and various regions.
- To track and analyze competitive developments such as joint ventures, mergers & acquisitions, and new product launches, in Global AI in Banking Market.
- To strategically profile key market players and comprehensively analyze their market position and core competencies

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Strategic Points Covered in Table of Content of Global AI in Banking Market:
Chapter 1: Introduction, market driving force product Objective of Study and Research Scope the Global AI in Banking market
Chapter 2: Exclusive Summary – the basic information of the Global AI in Banking Market.
Chapter 3: Displaying the Market Dynamics- Drivers, Trends and Challenges of the Global AI in Banking
Chapter 4: Presenting the Global AI in Banking Market Factor Analysis Porters Five Forces, Supply/Value Chain, PESTEL analysis, Market Entropy, Patent/Trademark Analysis.
Chapter 5: Displaying the by Type, End User and Region 2013-2018
Chapter 6: Evaluating the leading manufacturers of the Global AI in Banking market which consists of its Competitive Landscape, Peer Group Analysis, BCG Matrix & Company Profile
Chapter 7: To evaluate the market by segments, by countries and by manufacturers with revenue share and sales by key countries in these various regions.
Chapter 8& 9: Displaying the Appendix, Methodology and Data Source

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Key questions answered
- Who are the Leading key players and what are their Key Business plans in the Global AI in Banking market?
- What are the key concerns of the five forces analysis of the Global AI in Banking market?
- What are different prospects and threats faced by the dealers in the Global AI in Banking market?
- What are the strengths and weaknesses of the key vendors?

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