세계의 은행 업무용 빅데이터 분석 시장 규모 조사 및 예측 : 유형별(온프레미스, 클라우드), 용도별(피드백 관리, 고객 분석, 소셜 미디어 분석, 부정 감지와 관리, 기타), 지역별 분석(2023-2030년)

Global Big Data Analytics in the Banking Market is valued at approximately USD 5.1 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 10.8% over the forecast period 2023-2030. The market of big data analytics in the banking industry refers to utilizing advanced analytics techniques and technology to extract valuable insights and make data-driven decisions making in the banking industry. Big data analytics includes the collection, storage, processing and the analysis on large amount of structured and unstructured data from various sources of banks ecosystem. The driving factors of the market are the increasing adoption of cloud services and the increasing need for fraud detection and prevention systems.

The study done by the Bank of England suggests that migrating in 2021 to the cloud has the potential to reduce technology infrastructure costs by 30 to 50 per cent, including the expenses associated with maintaining physical equipment. In addition to the growth of new technology such as AI and ML. By using technology banks can enhance their customer engagement and retention creating a lucrative opportunity for market growth. However, issues associated with installation and integration among banks and financial institutions is hinder the growth of the market.

The key regions considered for the Global Big Data Analytics in the Banking Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to factors such as rising adoption of big data applications by major American banks and rising investments on advance analytics technology solutions. Whereas, Asia Pacific is emerging as the fastest growing region due to the increasing volume of data generated by banks and the large customer base in the region and this region also consists with the highest smartphone users.

Major market players included in this report are:

• Oracle Corporation
• SAP SE
• International Business Machine Corporation
• Alteryx Inc.
• Aspire Systems Inc.
• Adobe Systems Incorporated
• Microstrategy Inc.
• Mayato GmbH
• Mastercard Inc.
• ThetaRay Ltd

Recent Developments in the Market:

• January 2022 - RBL Bank and Google announced a collaboration to boost the lender's customer experience strategy and enhance its value proposition to serve its rapidly growing customer base through its digital platform, Abacus 2.0. This partnership will help offer more better customer data management and analytics, enabling effective cross-selling within the Bank's large customer base and significantly reducing customer acquisition costs.
• On February 2020 - Oracle Financial Crime and Compliance Management suite of products now include an integrated analytics workbench, 300-plus customer risk indicators, and embedded graph analytics visualizations. These capabilities build on Oracle's strategy to help financial institutions fight money laundering and achieve compliance.

Global Big Data Analytics in the Banking Market Report Scope:

• Historical Data: 2020 - 2021
• Base Year for Estimation: 2022
• Forecast period: 2023-2030
• Report Coverage: Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
• Segments Covered: Type, application, region
• Regional Scope: North America; Europe; Asia Pacific; Latin America; Middle East & Africa
• Customization Scope: Free report customization (equivalent up to 8 analyst's working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Type:

• On-premise
• Cloud

By Application:

• Feedback Management
• Customer Analytics
• Social Media Analytics
• Fraud Detection and Management
• Other

By Region:

• North America
• U.S.
• Canada
• Europe
• UK
• Germany
• France
• Spain
• Italy
• ROE
• Asia Pacific
• China
• India
• Japan
• Australia
• South Korea
• RoAPAC
• Latin America
• Brazil
• Mexico
• Middle East & Africa
• Saudi Arabia
• South Africa
• Rest of Middle East & Africa

Table of Contents

Chapter 1. Executive Summary

• 1.1. Market Snapshot
• 1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
  • 1.2.1. Big Data Analytics in the Banking Market, by Region, 2020-2030 (USD Billion)
  • 1.2.2. Big Data Analytics in the Banking Market, by Type, 2020-2030 (USD Billion)
  • 1.2.3. Big Data Analytics in the Banking Market, by Application, 2020-2030 (USD Billion)
• 1.3. Key Trends
• 1.4. Estimation Methodology
• 1.5. Research Assumption

Chapter 2. Global Big Data Analytics in the Banking Market Definition and Scope

• 2.1. Objective of the Study
• 2.2. Market Definition & Scope
  • 2.2.1. Industry Evolution
  • 2.2.2. Scope of the Study
• 2.3. Years Considered for the Study
• 2.4. Currency Conversion Rates

Chapter 3. Global Big Data Analytics in the Banking Market Dynamics

• 3.1. Big Data Analytics in the Banking Market Impact Analysis (2020-2030)
  • 3.1.1. Market Drivers
    • 3.1.1.1. Increasing adoption of cloud service
    • 3.1.1.2. Increasing need of fraud detection and prevention
  • 3.1.2. Market Challenges
    • 3.1.2.1. Difficult to implementation and integration
  • 3.1.3. Market Opportunities
    • 3.1.3.1. Growth of new technology
    • 3.1.3.2. Banks can enhance their customer engagement and retention

Chapter 4. Global Big Data Analytics in the Banking Market Industry Analysis

• 4.1. Porter's 5 Force Model
  • 4.1.1. Bargaining Power of Suppliers
  • 4.1.2. Bargaining Power of Buyers
  • 4.1.3. Threat of New Entrants
  • 4.1.4. Threat of Substitutes
  • 4.1.5. Competitive Rivalry
• 4.2. Porter's 5 Force Impact Analysis
• 4.3. PEST Analysis
  • 4.3.1. Political
  • 4.3.2. Economical
  • 4.3.3. Social
  • 4.3.4. Technological
  • 4.3.5. Environmental
  • 4.3.6. Legal
• 4.4. Top investment opportunity
• 4.5. Top winning strategies
• 4.6. COVID-19 Impact Analysis
• 4.7. Disruptive Trends
• 4.8. Industry Expert Perspective
• 4.9. Analyst Recommendation & Conclusion

Chapter 5. Global Big Data Analytics in the Banking Market, by Type

• 5.1. Market Snapshot
• 5.2. Global Big Data Analytics in the Banking Market by Type, Performance - Potential Analysis
• 5.3. Global Big Data Analytics in the Banking Market Estimates & Forecasts by Type2020-2030 (USD Billion)
• 5.4. Big Data Analytics in the Banking Market, Sub Segment Analysis
  • 5.4.1. On-premise
  • 5.4.2. Cloud

Chapter 6. Global Big Data Analytics in the Banking Market, by Application

• 6.1. Market Snapshot
• 6.2. Global Big Data Analytics in the Banking Market by Application, Performance - Potential Analysis
• 6.3. Global Big Data Analytics in the Banking Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
• 6.4. Big Data Analytics in the Banking Market, Sub Segment Analysis
  • 6.4.1. Feedback Management
  • 6.4.2. Customer Analytics
  • 6.4.3. Social Media Analytics
  • 6.4.4. Fraud Detection and Management
  • 6.4.5. Other

Chapter 7. Global Big Data Analytics in the Banking Market, Regional Analysis

• 7.1. Top Leading Countries
• 7.2. Top Emerging Countries
• 7.3. Big Data Analytics in the Banking Market, Regional Market Snapshot
• 7.4. North America Big Data Analytics in the Banking Market
  • 7.4.1. U.S. Big Data Analytics in the Banking Market
    • 7.4.1.1. Typebreakdown estimates & forecasts, 2020-2030
    • 7.4.1.2. Application breakdown estimates & forecasts, 2020-2030
  • 7.4.2. Canada Big Data Analytics in the Banking Market
• 7.5. Europe Big Data Analytics in the Banking Market Snapshot
  • 7.5.1. U.K. Big Data Analytics in the Banking Market
  • 7.5.2. Germany Big Data Analytics in the Banking Market
  • 7.5.3. France Big Data Analytics in the Banking Market
  • 7.5.4. Spain Big Data Analytics in the Banking Market
  • 7.5.5. Italy Big Data Analytics in the Banking Market
  • 7.5.6. Rest of Europe Big Data Analytics in the Banking Market
• 7.6. Asia-Pacific Big Data Analytics in the Banking Market Snapshot
  • 7.6.1. China Big Data Analytics in the Banking Market
  • 7.6.2. India Big Data Analytics in the Banking Market
  • 7.6.3. Japan Big Data Analytics in the Banking Market
  • 7.6.4. Australia Big Data Analytics in the Banking Market
  • 7.6.5. South Korea Big Data Analytics in the Banking Market
  • 7.6.6. Rest of Asia Pacific Big Data Analytics in the Banking Market
• 7.7. Latin America Big Data Analytics in the Banking Market Snapshot
  • 7.7.1. Brazil Big Data Analytics in the Banking Market
  • 7.7.2. Mexico Big Data Analytics in the Banking Market
• 7.8. Middle East & Africa Big Data Analytics in the Banking Market
  • 7.8.1. Saudi Arabia Big Data Analytics in the Banking Market
  • 7.8.2. South Africa Big Data Analytics in the Banking Market
  • 7.8.3. Rest of Middle East & Africa Big Data Analytics in the Banking Market

Chapter 8. Competitive Intelligence

• 8.1. Key Company SWOT Analysis
  • 8.1.1. Company 1
  • 8.1.2. Company 2
  • 8.1.3. Company 3
• 8.2. Top Market Strategies
• 8.3. Company Profiles
  • 8.3.1. Oracle Corporation
    • 8.3.1.1. Key Information
    • 8.3.1.2. Overview
    • 8.3.1.3. Financial (Subject to Data Availability)
    • 8.3.1.4. Product Summary
    • 8.3.1.5. Recent Developments
  • 8.3.2. SAP SE
  • 8.3.3. International Business Machine Corporation
  • 8.3.4. Alteryx Inc.
  • 8.3.5. Asphire Systems Inc.
  • 8.3.6. Adobe Systems Incorporation
  • 8.3.7. Microstrategy Inc.
  • 8.3.8. Mayato Gmbh
  • 8.3.9. Mastercard Inc.
  • 8.3.10. Thetaray Ltd

Chapter 9. Research Process

• 9.1. Research Process
  • 9.1.1. Data Mining
  • 9.1.2. Analysis
  • 9.1.3. Market Estimation
  • 9.1.4. Validation
  • 9.1.5. Publishing
• 9.2. Research Attributes
• 9.3. Research Assumption