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Ai And Advance Machine Learning In Bfsi Market

AI and Advance Machine Learning in BFSI Market By Component (Solution and Services), Deployment Model (On-premise and Cloud), Enterprise Size (Large Enterprises and SMEs), and Application (Fraud & Risk Management, Customer Segmentation, Sales & Marketing, Digital Assistance and Others): Global Opportunity Analysis and Industry Forecast, 2021–2030

A03986
Pages: 321
Sep 2021 | 6519 Views
   
Author(s) : Pramod Borasi, Shadaab Khan , Vineet Kumar
Tables: 168
Charts: 75
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COVID-19

Pandemic disrupted the entire world and affected many industries.

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AI and Advance Machine Learning in BFSI Market outlook - 2030

The global AI and advance machine learning in BFSI market size was valued at $7.66 billion in 2020, and is projected to reach $61.24 billion by 2030, growing at a CAGR of 23.1% from 2021 to 2030. Artificial intelligence in finance is transforming the BFSI industry as AI is helping the financial industry to streamline and optimize processes ranging from credit decisions to quantitative trading and financial risk management. In addition, advanced machine learning technology is used to help organizations to improve customer experience, services, and to optimize budgets. Furthermore, it provides solutions to process automation to replace routine manual work in most cases. In addition, AI and advanced machine learning help in reducing the credit default frauds by monitoring transactions to detect suspicious transactions with compliance concerns.

COVID-19 pandemic is expected to positively impact the growth rate of the artificial intelligence and machine learning in BFSI market, owing to increased shift towards work from home culture across banks & fintech agencies and rapid adoption of artificial intelligence and machine learning tools in banks and fintech organizations for performing critical jobs across the globe.

Improvement in data collection technology among the banks and financial institutions positively impacts the AI and advance machine learning in BFSI market growth. In addition, rise in investment by BFSI companies in AI and machine learning and customer preferences for personalized financial services are some of the important factors that boost growth of the AI and advance machine learning in BFSI market across the globe. However, factors such as higher deployment cost of AI & advance machine learning and lack of skilled labor are limiting the growth of the AI and advance machine learning in BFSI market. Conversely, surge in adoption of modern applications in BFSI sector is expected to offer remunerative opportunities for the expansion of the market during the forecast period.

Artificial-Intelligence--Advance-Machine-Learning-in-BFSI-Market-2021-2030

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Segment Review

The global AI and advance machine learning in BFSI market is segmented into component, deployment model, enterprise size, application and region. Depending on component, the AI and advanced machine learning in BFSI market is segregated into solution and services. On the basis of deployment model, it is categorized into on-premise and cloud. Depending on enterprise size, it is fragmented into large enterprises and SMEs.  Based on application, the market is divided into fraud & risk management, customer segmentation, sales & marketing, digital assistance and others. Region wise, the AI and advance machine learning in BFSI market is studied across North America, Europe, Asia-Pacific, and LAMEA.

The fraud & risk management segment is expected to garner a significant AI and advance machine learning in BFSI market share in 2020, owing to surge in need for machine learning technologies by banks and financial institution in their fraud detection system and implementing of an AI-driven verification model across the fintech and banks. However, the digital assistance segment is expected to grow at the highest rate during the forecast period, owing to growing need of digital assistance in banks and fintech to solve critical customer queries.

Region wise, North America region is contributed largest market share in 2020, owing to early adoption of machine learning solutions among the banking sector and various government initiatives for supporting SMEs to adopt artificial intelligence solution. However the Asia-Pacific region is expected provides lucrative opportunity to boost the growth of the AI and advanced machine learning in BFSI market owing to rapid adoption of analytics solutions by banks across China, Japan and India to analyze their customer behavior and prevent online frauds.

The report focuses on the growth prospects, restraints, and trends of global AI and advance machine learning in BFSI market analysis. The study provides Porter’s five forces analysis to understand the impact of various factors such as bargaining power of suppliers, competitive intensity of competitors, threat of new entrants, threat of substitutes, and bargaining power of buyers on global AI and advanced machine learning in BFSI market.

Competitive Analysis 

The key players operating in the global AI and advanced machine learning in BFSI industry include Amazon Web Services Inc., BigML, Inc, Cisco Systems, Inc., Fair Isaac Corporation, Hewlett Packard Enterprise Development LP, International Business Machines Corporation, Microsoft Corporation, RapidMiner, Inc., SAP SE and SAS Institute Inc. These players have adopted various strategies to increase their market penetration and strengthen their foothold in the competitive AI & advance machine learning in BFSI industry. 

COVID-19 Impact Analysis

With alarming increase in COVID-19 patients, various governments have implemented lockdown, which, in turn, increased the number of digital banking and access of premiums. Furthermore, with rise in digitization among both financial institutes & end users and surge in demand for advanced machine learning technology among fintech, transaction delays & need to increase the speed of payment processing drive the growth of the AI and advance machine learning in BFSI analysis in the pandemic situation. 

AI and Advance Machine Learning in BFSI Market
By Component

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Solution Segment holds a dominant position throughout the forecast period

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For instance, according to a survey of Prudential Regulation Authority (PRA) by Bank of England in August 2020, around 40% of respondents reported an increase in the importance of machine learning and data science for future operations, and a further 10% of banks reported a large increase. In addition, none of the banks reported a decrease in the importance of machine learning and data science. Furthermore, around 35% of banks reported that machine learning and data science had a positive impact on technologies that support remote working among employees and on their overall security provided for ML projects. In addition, the pandemic has accelerated the use of ML-powered tools to manage a sudden increase in customer enquiries. Thus, number of such development across the globe are anticipated to provide lucrative opportunity for the expansion of the AI and advance machine learning in BFSI market. 

Top Impacting Factors

Increase in Investment by BFSI Companies in AI and Machine Learning

BFSI companies are increasing investment in machine learning and AI solutions to transform the management process of fintech and to provide better services to end users. In addition, with incase in complexity and competition in the BFSI sector, the demand for industry-specific solutions increased to meet its goals. Thus, to meet the requirement of customers, various banking institutes and fintech are investing in AI solution, which, in turn, drives the growth of the market. Furthermore, AI and machine learning can assist financial institutes at various stages of risk management process ranging from identifying risk exposure, measuring, estimating, and assessing its effects. In addition, BFSI companies are adopting and developing machine learning techniques to analyze large volume of data and to deliver valuable insights to customers. Moreover, increase in investments in AI and advanced machine learning by fintech & banks to enhance the automation process and to offer more streamlined and personalized customer experience propels the growth of the market. In addition, major financial institutes such as Bank of America, JPMorgan, and Morgan Stanley are investing heavily in machine learning technology to develop automated investment advisors and train systems to detect flags such as money laundering techniques, which can be prevented by financial monitoring, thus augmenting the growth of the market.

AI and Advance Machine Learning in BFSI Market
By Deployment Model

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Cloud segment will grow at a highest CAGR of 23.9% during 2021 - 2030

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Rise in Preference for Personalized Financial Services

End users are increasingly preferring personalized financial services, owing to surge in adoption of chatbots among banks and increase in competition among the BFSI companies for garnering maximum market share. Various BFSI companies are providing budget management apps powered by machine learning, which help customers to achieve their financial targets and improve their money management process, thus driving the growth of the market. 

Furthermore, robo-advisors are one of the other rapidly emerging trends in personalized financial services, as they specifically target investors with limited resources such as individuals and small- to medium-sized businesses for managing their funds. In addition, machine learning-based robo-advisors can apply traditional data processing techniques to create financial portfolios and solutions such as trading, investments, and retirement plans for their users. Moreover, with rise of usage-based insurance machine learning and AI technologies are helping to calculate the premium suitable for each individual, which, in turn, propels the growth of the AI and advanced machine learning in BFSI market. 

AI and Advance Machine Learning in BFSI Market
By Region

2030
North America 
Europe
Asia-pacific
Lamea

Asia-Pacific would exhibit the highest CAGR of 24.6% during 2021-2030.

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Key Benefits For Stakeholders     

  • The study provides an in-depth analysis of global AI and advanced machine learning in BFSI market forecast along with the current trends and future estimations to elucidate the imminent investment pockets.
  • Information about key drivers, restraints, and opportunities and their impact analysis on global AI and advance machine learning in BFSI market trends is provided in the report.
  • Porter’s five forces analysis illustrates the potency of the buyers and suppliers operating in the industry.
  • The quantitative analysis of the market from 2021 to 2030 is provided to determine the market potential.

Key Market Segments

By Component

  • Solution
  • Services
  • Implementation & Integration Service
  • Training & Support Service
  • Consulting Service

By Deployment Model 

  • On-premise
  • Cloud 

By Enterprise Size

  • Large Enterprises
  • SMEs  

By Application

  • Fraud & Risk Management
  • Customer Segmentation
  • Sales & Marketing
  • Digital Assistance
  • Others

By Region

  • North America
    • U.S.
    • Canada
  • Europe 
    • UK
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Rest of Europe
  • Asia-Pacific 
    • China
    • Japan
    • India
    • Australia 
    • South Korea
  • Rest of Asia-Pacific
    • LAMEA
    • Latin America 
    • Middle East 
    • Africa

Key Market Players

  • Amazon Web Services Inc.
  • BigML, Inc
  • Cisco Systems, Inc.
  • Fair Isaac Corporation
  • Hewlett Packard Enterprise Development LP
  • International Business Machines Corporation
  • Microsoft Corporation
  • RapidMiner, Inc.
  • SAP SE
  • SAS Institute Inc.
 

CHAPTER 1:INTRODUCTION

1.1.Report description
1.2.Key benefits for stakeholders
1.3.Key market segments
1.4.Research methodology

1.4.1.Secondary research
1.4.2.Primary research
1.4.3.Analyst tools & models

CHAPTER 2:EXECUTIVE SUMMARY

2.1.Key findings

2.1.1.Top impacting factors
2.1.2.Top investment pockets

2.2.CXO perspective

CHAPTER 3:MARKET OVERVIEW

3.1.Market definition and scope
3.2.Key forces shaping global artificial intelligence and advanced machine learning in BFSI market
3.3.Case studies

3.3.1.CargoSmart adopted Tibco advance analytics solution for improving its decision-making capability by using real-time analysis
3.3.2.Honeywell International Inc. adopted data and business analytics platform of Expedien Inc. to increase productivity, lower risk costs, accelerate growth, and lower risk of organizations

3.4.Market dynamics

3.4.1.Drivers

3.4.1.1.Increase in investment by BFSI companies in AI and machine learning
3.4.1.2.Increasing preferences for personalized financial services
3.4.1.3.Increase in collaboration between financial institutes and AI & machine learning solution company

3.4.2.Restraint

3.4.2.1.Higher deployment cost of AI and advanced machine learning
3.4.2.2.Lack of skilled labor

3.4.3.Opportunity

3.4.3.1.Increase in government initiatives and growth in investments to leverage the AI technology

3.5.Market evolution/industry roadmap
3.6.Impact of government regulations on the global artificial intelligence and advanced machine learning in BFSI market
3.7.COVID-19 impact analysis on AI and Advanced Machine Learning in BFSI market

3.7.1.Impact on market size
3.7.2.Consumer trends, preferences, and budget impact
3.7.3.Economic impact
3.7.4.Strategies to tackle negative impact
3.7.5.Opportunity window

3.8.Key future initiatives

3.8.1.Product launches

CHAPTER 4:GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET, BY COMPONENT

4.1.Overview
4.2.Solution

4.2.1.Key market trends, growth factors, and opportunities
4.2.2.Market size and forecast, by region
4.2.3.Market analysis, by country

4.3.Service

4.3.1.Key market trends, growth factors, and opportunities
4.3.2.Market size and forecast, by region
4.3.3.Market analysis, by country

CHAPTER 5:GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET, BY DEPLOYMENT MODEL

5.1.Overview
5.2.On-premise

5.2.1.Key market trends, growth factors, and opportunities
5.2.2.Market size and forecast, by region
5.2.3.Market analysis, by country

5.3.Cloud-based

5.3.1.Key market trends, growth factors, and opportunities
5.3.2.Market size and forecast, by region
5.3.3.Market analysis, by country

CHAPTER 6:GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET, BY ENTERPRISE SIZE

6.1.Overview
6.2.Large enterprise

6.2.1.Key market trends, growth factors, and opportunities
6.2.2.Market size and forecast, by region
6.2.3.Market analysis, by country

6.3.SMEs

6.3.1.Key market trends, growth factors, and opportunities
6.3.2.Market size and forecast, by region
6.3.3.Market analysis, by country

CHAPTER 7:GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET, BY APPLICATION

7.1.Overview
7.2.Fraud & Risk Management

7.2.1.Key market trends, growth factors, and opportunities
7.2.2.Market size and forecast, by region
7.2.3.Market analysis, by country

7.3.Customer Segmentation

7.3.1.Key market trends, growth factors, and opportunities
7.3.2.Market size and forecast, by region
7.3.3.Market analysis, by country

7.4.Sales & Marketing

7.4.1.Key market trends, growth factors, and opportunities
7.4.2.Market size and forecast, by region
7.4.3.Market analysis, by country

7.5.Digital Assistance

7.5.1.Key market trends, growth factors, and opportunities
7.5.2.Market size and forecast, by region
7.5.3.Market analysis, by country

7.6.Others

7.6.1.Key market trends, growth factors, and opportunities
7.6.2.Market size and forecast, by region
7.6.3.Market analysis, by country

CHAPTER 8:GOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET, BY REGION

8.1.Overview

8.1.1.Market size and forecast, by region

8.2.North America

8.2.1.Key market trends, growth factors, and opportunities
8.2.2.Market size and forecast, by component
8.2.3.Market size and forecast, by service type
8.2.4.Market size and forecast, by deployment model
8.2.5.Market size and forecast, by enterprise size
8.2.6.Market size and forecast, by application
8.2.7.Market size and forecast, by country

8.2.7.1.U.S.

8.2.7.1.1.Market size and forecast, by component
8.2.7.1.2.Market size and forecast, by service type
8.2.7.1.3.Market size and forecast, by deployment model
8.2.7.1.4.Market size and forecast, by enterprise size
8.2.7.1.5.Market size and forecast, by application

8.2.7.2.Canada

8.2.7.2.1.Market size and forecast, by component
8.2.7.2.2.Market size and forecast, by service type
8.2.7.2.3.Market size and forecast, by deployment model
8.2.7.2.4.Market size and forecast, by enterprise size
8.2.7.2.5.Market size and forecast, by application

8.3.Europe

8.3.1.Key market trends, growth factors, and opportunities
8.3.2.Market size and forecast, by component
8.3.3.Market size and forecast, by service type
8.3.4.Market size and forecast, by deployment model
8.3.5.Market size and forecast, by enterprise size
8.3.6.Market size and forecast, by application
8.3.7.Market size and forecast, by country

8.3.7.1.UK

8.3.7.1.1.Market size and forecast, by component
8.3.7.1.2.Market size and forecast, by service type
8.3.7.1.3.Market size and forecast, by deployment model
8.3.7.1.4.Market size and forecast, by enterprise size
8.3.7.1.5.Market size and forecast, by application

8.3.7.2.Germany

8.3.7.2.1.Market size and forecast, by component
8.3.7.2.2.Market size and forecast, by service type
8.3.7.2.3.Market size and forecast, by deployment model
8.3.7.2.4.Market size and forecast, by enterprise size
8.3.7.2.5.Market size and forecast, by application

8.3.7.3.France

8.3.7.3.1.Market size and forecast, by component
8.3.7.3.2.Market size and forecast, by service type
8.3.7.3.3.Market size and forecast, by deployment model
8.3.7.3.4.Market size and forecast, by enterprise size
8.3.7.3.5.Market size and forecast, by application

8.3.7.4.Italy

8.3.7.4.1.Market size and forecast, by component
8.3.7.4.2.Market size and forecast, by service type
8.3.7.4.3.Market size and forecast, by deployment model
8.3.7.4.4.Market size and forecast, by enterprise size
8.3.7.4.5.Market size and forecast, by application

8.3.7.5.Spain

8.3.7.5.1.Market size and forecast, by component
8.3.7.5.2.Market size and forecast, by service type
8.3.7.5.3.Market size and forecast, by deployment model
8.3.7.5.4.Market size and forecast, by enterprise size
8.3.7.5.5.Market size and forecast, by application

8.3.7.6.Netherlands

8.3.7.6.1.Market size and forecast, by component
8.3.7.6.2.Market size and forecast, by service type
8.3.7.6.3.Market size and forecast, by deployment model
8.3.7.6.4.Market size and forecast, by enterprise size
8.3.7.6.5.Market size and forecast, by application

8.3.7.7.Rest of Europe

8.3.7.7.1.Market size and forecast, by component
8.3.7.7.2.Market size and forecast, by service type
8.3.7.7.3.Market size and forecast, by deployment model
8.3.7.7.4.Market size and forecast, by enterprise size
8.3.7.7.5.Market size and forecast, by application

8.4.Asia-Pacific

8.4.1.Key market trends, growth factors, and opportunities
8.4.2.Market size and forecast, by component
8.4.3.Market size and forecast, by service type
8.4.4.Market size and forecast, by deployment model
8.4.5.Market size and forecast, by enterprise size
8.4.6.Market size and forecast, by application
8.4.7.Market size and forecast, by country

8.4.7.1.China

8.4.7.1.1.Market size and forecast, by component
8.4.7.1.2.Market size and forecast, by service type
8.4.7.1.3.Market size and forecast, by deployment model
8.4.7.1.4.Market size and forecast, by enterprise size
8.4.7.1.5.Market size and forecast, by application

8.4.7.2.Japan

8.4.7.2.1.Market size and forecast, by component
8.4.7.2.2.Market size and forecast, by service type
8.4.7.2.3.Market size and forecast, by deployment model
8.4.7.2.4.Market size and forecast, by enterprise size
8.4.7.2.5.Market size and forecast, by application

8.4.7.3.India

8.4.7.3.1.Market size and forecast, by component
8.4.7.3.2.Market size and forecast, by service type
8.4.7.3.3.Market size and forecast, by deployment model
8.4.7.3.4.Market size and forecast, by enterprise size
8.4.7.3.5.Market size and forecast, by application

8.4.7.4.Australia

8.4.7.4.1.Market size and forecast, by component
8.4.7.4.2.Market size and forecast, by service type
8.4.7.4.3.Market size and forecast, by deployment model
8.4.7.4.4.Market size and forecast, by enterprise size
8.4.7.4.5.Market size and forecast, by application

8.4.7.5.South Korea

8.4.7.5.1.Market size and forecast, by component
8.4.7.5.2.Market size and forecast, by service type
8.4.7.5.3.Market size and forecast, by deployment model
8.4.7.5.4.Market size and forecast, by enterprise size
8.4.7.5.5.Market size and forecast, by application

8.4.7.6.Rest of Asia-Pacific

8.4.7.6.1.Market size and forecast, by component
8.4.7.6.2.Market size and forecast, by service type
8.4.7.6.3.Market size and forecast, by deployment model
8.4.7.6.4.Market size and forecast, by enterprise size
8.4.7.6.5.Market size and forecast, by application

8.5.LAMEA

8.5.1.Key market trends, growth factors, and opportunities
8.5.2.Market size and forecast, by component
8.5.3.Market size and forecast, by service type
8.5.4.Market size and forecast, by deployment model
8.5.5.Market size and forecast, by enterprise size
8.5.6.Market size and forecast, by application
8.5.7.Market size and forecast, by country

8.5.7.1.Latin America

8.5.7.1.1.Market size and forecast, by component
8.5.7.1.2.Market size and forecast, by service type
8.5.7.1.3.Market size and forecast, by deployment model
8.5.7.1.4.Market size and forecast, by enterprise size
8.5.7.1.5.Market size and forecast, by application

8.5.7.2.Middle East

8.5.7.2.1.Market size and forecast, by component
8.5.7.2.2.Market size and forecast, by service type
8.5.7.2.3.Market size and forecast, by deployment model
8.5.7.2.4.Market size and forecast, by enterprise size
8.5.7.2.5.Market size and forecast, by application

8.5.7.3.Africa

8.5.7.3.1.Market size and forecast, by component
8.5.7.3.2.Market size and forecast, by service type
8.5.7.3.3.Market size and forecast, by deployment model
8.5.7.3.4.Market size and forecast, by enterprise size
8.5.7.3.5.Market size and forecast, by application

CHAPTER 9:COMPETITIVE LANDSCAPE

9.1.Key players positioning analysis, 2020
9.2.Competitive dashboard
9.3.Top winning strategies

CHAPTER 10:COMPANY PROFILE

10.1.Amazon Web Services, Inc.

10.1.1.Company overview
10.1.2.Key Executives
10.1.3.Company snapshot
10.1.4.Product portfolio
10.1.5.Business performance
10.1.6.Key strategic moves and developments

10.2.BigML, Inc.

10.2.1.Company overview
10.2.2.Key Executives
10.2.3.Company snapshot
10.2.4.Product portfolio

10.3.Cisco System Inc.

10.3.1.Company overview
10.3.2.Key Executives
10.3.3.Company snapshot
10.3.4.Operating business segments
10.3.5.Product portfolio
10.3.6.R&D Expenditure
10.3.7.Business performance

10.4.FAIR ISAAC CORPORATION

10.4.1.Company overview
10.4.2.Key Executives
10.4.3.Company snapshot
10.4.4.Operating business segments
10.4.5.Product portfolio
10.4.6.R&D Expenditure
10.4.7.Business performance

10.5.HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

10.5.1.Company overview
10.5.2.Key executives
10.5.3.Company snapshot
10.5.4.Operating business segments
10.5.5.Product portfolio
10.5.6.R&D expenditure
10.5.7.Business performance
10.5.8.Key strategic moves and developments

10.6.INTERNATIONAL BUSINESS MACHINES CORPORATION

10.6.1.Company overview
10.6.2.Key executives
10.6.3.Company snapshot
10.6.4.Operating business segments
10.6.5.Product portfolio
10.6.6.R&D expenditure
10.6.7.Business performance
10.6.8.Key strategic moves and developments

10.8.MICROSOFT CORPORATION

10.8.1.Company overview
10.8.2.Key executives
10.8.3.Company snapshot
10.8.4.Operating business segments
10.8.5.Product portfolio
10.8.6.R&D expenditure
10.8.7.Business performance

10.9.RapidMiner, Inc.

10.9.1.Company overview
10.9.2.Key Executives
10.9.3.Company snapshot
10.9.4.Product portfolio
10.9.5.Key strategic moves and developments

10.10.SAP SE

10.10.1.Company overview
10.10.2.Key Executives
10.10.3.Company snapshot
10.10.4.Operating business segments
10.10.5.Product portfolio
10.10.6.R&D Expenditure
10.10.7.Business performance
10.10.8.Key strategic moves and developments

10.11.SAS INSTITUTE INC.

10.11.1.Company overview
10.11.2.Key Executives
10.11.3.Company snapshot
10.11.4.Product portfolio
10.11.5.Key strategic moves and developments

LIST OF TABLES

TABLE 01.KEY NEW PRODUCT LAUNCHES (2018-2020)
TABLE 02.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 03.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE FOR SOLUTION, BY REGION, 2020–2030 ($MILLION)
TABLE 04.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE FOR SERVICE, BY REGION, 2020–2030 ($MILLION)
TABLE 05.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 06.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE FOR ON-PREMISE, BY REGION, 2020–2030 ($MILLION)
TABLE 07.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE FOR CLOUD-BASED, BY REGION, 2020–2030 ($MILLION)
TABLE 08.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 09.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE LARGE ENTERPRISE, BY REGION, 2020–2030 ($MILLION)
TABLE 10.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE FOR SMES, BY REGION, 2020–2030 ($MILLION)
TABLE 11.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 12.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE FOR FRAUD & RISK MANAGEMENT, BY REGION, 2020–2030 ($MILLION)
TABLE 13.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE FOR CUSTOMER SEGMENTATION, BY REGION, 2020–2030 ($MILLION)
TABLE 14.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE FOR SALES & MARKETING, BY REGION, 2020–2030 ($MILLION)
TABLE 15.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE FOR DIGITAL ASSISTANCE, BY REGION, 2020–2030 ($MILLION)
TABLE 16.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE FOR OTHERS, BY REGION, 2020–2030 ($MILLION)
TABLE 17.ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY REGION, 2020–2030 ($MILLION)
TABLE 18.NORTH AMERICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 19.NORTH AMERICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 20.NORTH AMERICA WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 21.NORTH AMERICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 22.NORTH AMERICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 23.NORTH AMERICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COUNTRY, 2020–2028 ($MILLION)
TABLE 24.U.S. ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 25.U.S. ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 26.U.S. WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 27.U.S. ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 28.U.S. ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 29.CANADA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 30.CANADA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 31.CANADA WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 32.CANADA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 33.CANADA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 34.EUROPE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 35.EUROPE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 36.EUROPE WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 37.EUROPE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 38.EUROPE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 39.EUROPE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COUNTRY, 2020–2028 ($MILLION)
TABLE 40.UK ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 41.UK ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 42.UK WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 43.UK ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 44.UK ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 45.GERMANY ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 46.GERMANY ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 47.GERMANY WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 48.GERMANY ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 49.GERMANY ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 50.FRANCE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 51.FRANCE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 52.FRANCE WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 53.FRANCE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 54.FRANCE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 55.ITALY ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 56.ITALY ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 57.ITALY WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 58.ITALY ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 59.ITALY ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 60.SPAIN ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 61.SPAIN ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 62.SPAIN WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 63.SPAIN ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 64.SPAIN ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 65.NETHERLANDS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 66.NETHERLANDS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 67.NETHERLANDS WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 68.NETHERLANDS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 69.NETHERLANDS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 70.REST OF EUROPE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 71.REST OF EUROPE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 72.REST OF EUROPE WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 73.REST OF EUROPE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 74.REST OF EUROPE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 75.ASIA-PACIFIC ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 76.ASIA-PACIFIC ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 77.ASIA-PACIFIC WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 78.ASIA-PACIFIC ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 79.ASIA-PACIFIC ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 80.ASIA-PACIFIC ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COUNTRY, 2020–2028 ($MILLION)
TABLE 81.CHINA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 82.CHINA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 83.CHINA WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 84.CHINA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 85.CHINA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 86.JAPAN ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 87.JAPAN ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 88.JAPAN WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 89.JAPAN ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 90.JAPAN ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 91.INDIA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 92.INDIA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 93.INDIA WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 94.INDIA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 95.INDIA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 96.AUSTRALIA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 97.AUSTRALIA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 98.AUSTRALIA WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 99.AUSTRALIA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 100.AUSTRALIA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 101.SOUTH KOREA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 102.SOUTH KOREA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 103.SOUTH KOREA WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 104.SOUTH KOREA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 105.SOUTH KOREA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 106.REST OF ASIA-PACIFIC ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 107.REST OF ASIA-PACIFIC ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 108.REST OF ASIA-PACIFIC WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 109.REST OF ASIA-PACIFIC ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 110.REST OF ASIA-PACIFIC ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 111.LAMEA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 112.LAMEA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 113.LAMEA WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 114.LAMEA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 115.LAMEA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 116.LAMEA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COUNTRY, 2020–2028 ($MILLION)
TABLE 117.LATIN AMERICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 118.LATIN AMERICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 119.LATIN AMERICA WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 120.LATIN AMERICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 121.LATIN AMERICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 122.MIDDLE EAST ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 123.MIDDLE EAST ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 124.MIDDLE EAST WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 125.MIDDLE EAST ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 126.MIDDLE EAST ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 127.AFRICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
TABLE 128.AFRICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI SERVICE MARKET REVENUE, BY TYPE, 2020–2030 ($MILLION)
TABLE 129.AFRICA WIRELESS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
TABLE 130.AFRICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
TABLE 131.AFRICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
TABLE 132.AMAZON WEB SERVICES, INC.: KEY EXECUTIVES
TABLE 133.AMAZON WEB SERVICES, INC.: COMPANY SNAPSHOT
TABLE 134.AMAZON WEB SERVICES, INC.: PRODUCT PORTFOLIO
TABLE 135.AMAZON WEB SERVICES, INC.: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 136.BIGML, INC.: KEY EXECUTIVES
TABLE 137.BIGML, INC.: COMPANY SNAPSHOT
TABLE 138.BIGML, INC.: PRODUCT PORTFOLIO
TABLE 139.CISCO SYSTEM INC.: KEY EXECUTIVES
TABLE 140.CISCO SYSTEM INC.: COMPANY SNAPSHOT
TABLE 141.CISCO SYSTEM INC.: OPERATING SEGMENTS
TABLE 142.CISCO SYSTEM INC.: PRODUCT PORTFOLIO
TABLE 143.FAIR ISAAC CORPORATION: KEY EXECUTIVES
TABLE 144.FAIR ISAAC CORPORATION: COMPANY SNAPSHOT
TABLE 145.FAIR ISAAC CORPORATION: OPERATING SEGMENTS
TABLE 146.FAIR ISAAC CORPORATION: PRODUCT PORTFOLIO
TABLE 147.HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP: KEY EXECUTIVES
TABLE 148.HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP: COMPANY SNAPSHOT
TABLE 149.HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP: OPERATING SEGMENTS
TABLE 150.HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP: PRODUCT PORTFOLIO
TABLE 151.INTERNATIONAL BUSINESS MACHINES CORPORATION: KEY EXECUTIVES
TABLE 152.INTERNATIONAL BUSINESS MACHINES CORPORATION: COMPANY SNAPSHOT
TABLE 153.INTERNATIONAL BUSINESS MACHINES CORPORATION: OPERATING SEGMENTS
TABLE 154.IBM CORPORATION: PRODUCT PORTFOLIO
TABLE 155.MICROSOFT CORPORATION: KEY EXECUTIVES
TABLE 156.MICROSOFT CORPORATION: COMPANY SNAPSHOT
TABLE 157.MICROSOFT CORPORATION: OPERATING SEGMENTS
TABLE 158.MICROSOFT CORPORATION: PRODUCT PORTFOLIO
TABLE 159.RAPIDMINER, INC.: KEY EXECUTIVES
TABLE 160.RAPIDMINER, INC.: COMPANY SNAPSHOT
TABLE 161.RAPIDMINER, INC.: PRODUCT PORTFOLIO
TABLE 162.SAP SE: KEY EXECUTIVES
TABLE 163.SAP SE: COMPANY SNAPSHOT
TABLE 164.SAP SE: OPERATING SEGMENTS
TABLE 165.SAP SE: PRODUCT PORTFOLIO
TABLE 166.SAS INSTITUTE INC.: KEY EXECUTIVES
TABLE 167.SAS INSTITUTE INC.: COMPANY SNAPSHOT
TABLE 168.SAS INSTITUTE INC.: PRODUCT PORTFOLIO

LIST OF FIGURES

FIGURE 01.KEY MARKET SEGMENTS
FIGURE 02.GLOBAL ARTIFICIAL INTELLIGENCE AND ADVANCED MACHINE LEARNING IN BFSI MARKET SNAPSHOT, BY SEGMENTATION, 2020–2030
FIGURE 03.ARTIFICIAL INTELLIGENCE AND ADVANCED MACHINE LEARNING IN BFSI MARKET SNAPSHOT, BY REGION, 2020–2030
FIGURE 04.ARTIFICIAL INTELLIGENCE AND ADVANCED MACHINE LEARNING IN BFSI MARKET: TOP IMPACTING FACTOR
FIGURE 05.TOP INVESTMENT POCKETS
FIGURE 06.LOW-TO-HIGH BARGAINING POWER OF SUPPLIERS
FIGURE 07.LOW-TO-HIGH BARGAINING POWER OF BUYERS
FIGURE 08.LOW-TO-MODERATE THREAT OF SUBSTITUTES
FIGURE 09.MODERATE-TO-HIGH THREAT OF NEW ENTRANTS
FIGURE 10.LOW-TO-HIGH COMPETITIVE RIVALRY
FIGURE 11.MARKET EVOLUTION/INDUSTRY ROADMAP
FIGURE 12.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY COMPONENT, 2020–2030 ($MILLION)
FIGURE 13.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR SOLUTION, BY COUNTRY, 2020 & 2030(%)
FIGURE 14.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR SERVICE, BY COUNTRY, 2020 & 2030(%)
FIGURE 15.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY DEPLOYMENT MODEL, 2020–2030 ($MILLION)
FIGURE 16.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR ON-PREMISE, BY COUNTRY, 2020 & 2030(%)
FIGURE 17.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR CLOUD-BASED,  BY COUNTRY, 2020 & 2030(%)
FIGURE 18.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY ENTERPRISE SIZE, 2020–2030 ($MILLION)
FIGURE 19.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR LARGE ENTERPRISE, BY COUNTRY,  2020 & 2030(%)
FIGURE 20.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR SMES, BY COUNTRY, 2020 & 2030(%)
FIGURE 21.GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, BY APPLICATION, 2020–2030 ($MILLION)
FIGURE 22.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR FRAUD & RISK MANAGEMENT, BY COUNTRY, 2020 & 2030(%)
FIGURE 23.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR CUSTOMER SEGMENTATION, BY COUNTRY, 2020 & 2030(%)
FIGURE 24.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR SALES & MARKETING, BY COUNTRY, 2020 & 2030(%)
FIGURE 25.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR DIGITAL ASSISTANCE, BY COUNTRY, 2020 & 2030(%)
FIGURE 26.COMPARATIVE SHARE ANALYSIS OF GLOBAL ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET FOR OTHERS, BY COUNTRY, 2020 & 2030(%)
FIGURE 27.U.S. ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 28.CANADA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 29.UK ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 30.GERMANY ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 31.FRANCE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 32.ITALY ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 33.SPAIN ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 34.NETHERLANDS ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 35.REST OF EUROPE ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 36.CHINA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 37.JAPAN ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 38.INDIA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 39.AUSTRALIA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 40.SOUTH KOREA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 41.REST OF ASIA-PACIFIC ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 42.LATIN AMERICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 43.MIDDLE EAST ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 44.AFRICA ARTIFICIAL INTELLIGENCE & ADVANCE MACHINE LEARNING IN BFSI MARKET REVENUE, 2020–2030 ($MILLION)
FIGURE 45.KEY PLAYER POSITIONING ANALYSIS: GLOBAL AI AND ADVANCE MACHINE LEARNING IN BFSI MARKET
FIGURE 46.COMPETITIVE DASHBOARD
FIGURE 47.COMPETITIVE DASHBOARD
FIGURE 48.COMPETITIVE HEATMAP OF KEY PLAYERS
FIGURE 49.TOP WINNING STRATEGIES, BY YEAR, 2020-2021
FIGURE 50.TOP WINNING STRATEGIES, BY DEVELOPMENT, 2019-2021
FIGURE 51.TOP WINNING STRATEGIES, BY COMPANY, 2020-2021
FIGURE 52.AMAZON WEB SERVICES, INC.: REVENUE, 2018–2020 ($MILLION)
FIGURE 53.AMAZON WEB SERVICES, INC.: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 54.R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 55.CISCO SYSTEM INC.: REVENUE, 2018–2020 ($MILLION)
FIGURE 56.CISCO SYSTEM INC.: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 57.CISCO SYSTEM INC.: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 58.R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 59.FAIR ISAAC CORPORATION: REVENUE, 2018–2020 ($MILLION)
FIGURE 60.FAIR ISAAC CORPORATION: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 61.R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 62.HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP: REVENUE, 2018–2020 ($MILLION)
FIGURE 63.HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 64.R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 65.INTERNATIONAL BUSINESS MACHINES CORPORATION: REVENUE, 2018–2020 ($MILLION)
FIGURE 66.INTERNATIONAL BUSINESS MACHINES CORPORATION: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 67.INTERNATIONAL BUSINESS MACHINES CORPORATION: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 68.R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 69.MICROSOFT CORPORATION: REVENUE, 2019–2020 ($MILLION)
FIGURE 70.MICROSOFT CORPORATION: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 71.MICROSOFT CORPORATION: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 72.R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 73.SAP SE: REVENUE, 2018–2020 ($MILLION)
FIGURE 74.SAP SE: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 75.SAP SE: REVENUE SHARE BY REGION, 2020 (%)

 
 

The adoption of AI and advance machine learning in BFSI solutions has increased over the years to help organizations monitor production processes and to provide enhanced customer services. In addition, AI and advance machine learning in BFSI technology is being used across a number of applications to help drive productivity, improve efficiency, and save people time and organizational funds. Furthermore, AI and advance machine learning in BFSI tools is used to clean data sets, give predictions, improve decision-making, and to respond to customer service needs, which are expected to fuel the market growth. In addition, surge in adoption of cloud as well as mobile applications is expected to drive the growth of the market.

Key providers of AI and advance machine learning in BFSI market such as SAP SE, International Business Machines Corporation, and Microsoft Corporation account for a significant share in the market. For instance, Saxo Bank, a leading Danish investment bank, managed to drastically reduce the time it takes to onboard new customers and get them trading on its platform, owing to investments in data science and advanced machine learning technologies by automating repeating and time-consuming tasks and provide better time management of workers.

Furthermore, financial institutes are collaborating with AI and machine learning companies to enhance their existing AI system for better and secure systems. For instance, in August 2021, RBL Bank partnered with Amazon Web Services (AWS) to strengthen its AI-powered banking solutions and drive digital transformation at the bank, adding significant value to the bank’s innovative offerings, saving costs, and tightening risk controls. In addition, it is leveraging Amazon Textract, a machine learning service that automatically extracts text, handwriting, and data from scanned documents, across the bank’s risk and operations divisions to analyze documents such as financial statements, stock statements, and stock audit reports to predict default risk.

Moreover, many open banking platforms are leveraging solutions from financial technology providers to improve their management technology. For instance, in September 2020, Open banking platform, Tink leveraged open banking technology from Enel to develop digital financial solutions for its clients in Italy and Europe. With the agreement, Tink will be able to support its clients in the daily management of their finances, with an innovative and engaging solution that uses machine learning to provide tailored and personalized advice. Thus, such developments across the globe drive the growth of the market.

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A. The AI and advance machine learning in BFSI Market is estimated to grow at a CAGR of 23.1% from 2021 to 2030.

A. The AI and advance machine learning in BFSI Market is projected to reach $61.24 billion by 2030.

A. To get the latest version of sample report

A. Factors such as increase in investments in AI and advanced machine learning by fintech & banks to enhance the automation process and to offer more streamlined and personalized customer experience drives the growth of the AI and advance machine learning in BFSI market

A. The key players profiled in the report include Amazon Web Services Inc., BigML, Inc, Cisco Systems, Inc., Fair Isaac Corporation, Hewlett Packard Enterprise Development LP, International Business Machines Corporation, Microsoft Corporation, RapidMiner, Inc., SAP SE and SAS Institute Inc and many more.

A. On the basis of top growing big corporations, we select top 10 players.

A. The AI and advance machine learning in BFSI Market is segmented on the basis of component, deployment model, enterprise size, application and region.

A. The key growth strategies of AI and advance machine learning in BFSI market players include product portfolio expansion, mergers & acquisitions, agreements, geographical expansion, and collaborations.

A. Solution Segment holds a dominant position throughout the forecast period.

A. Cloud segment will grow at a highest CAGR of 23.9% during 2021 - 2030.

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