Big Data Analytics in Banking Market Size
| Study Period | 2019 - 2029 |
| Market Size (2024) | USD 8.58 Million |
| Market Size (2029) | USD 24.28 Million |
| CAGR (2024 - 2029) | 23.11 % |
| Fastest Growing Market | Asia Pacific |
| Largest Market | North America |
Major Players
*Disclaimer: Major Players sorted in no particular order |
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Big Data Analytics in Banking Market Analysis
The Big Data Analytics In Banking Market size is estimated at USD 8.58 million in 2024, and is expected to reach USD 24.28 million by 2029, growing at a CAGR of 23.11% during the forecast period (2024-2029).
Based on the inputs obtained from numerous insights, such as investment patterns, shopping trends, investment motivation, and personal or financial background, big data analytics can help banks understand client behavior.
- The considerable increase in the volume of data generated and governmental requirements are the main forces behind adopting Big Data analytics in the banking sector. With the development of technology, consumers are using more and more devices to start transactions (such as smartphones), which impacts the volume of transactions. Given the current data growth rate, better data collection, organization, integration, and analysis are necessary.
- Government rules and considerable data gathering are affecting the banking industry. As technology develops, more consumers are using more devices to start transactions (such as smartphones), which boosts the volume of transactions. This motivates big data analytics, which gives data analysts a single location to see and quickly locate all data points. Thanks to this consolidated picture, team members can exchange insights that could enhance the banking industry.
- A Big Data Analytics solution offers the processing, persistence, and analytic capabilities necessary to unearth fresh business insights while enabling a company to store all its data in a flexible, affordable environment. An analytics tool for big data gathers and keeps track of structured and unstructured data and techniques for arranging enormous amounts of wildly different data from various sources.
- The majority of legacy systems are unable to handle the rising burden. The entire system's stability may be compromised if the necessary amounts of data are gathered, stored, and analyzed utilizing an obsolete infrastructure. Organizations must either improve their processing capacity or entirely redesign their systems to tackle the issue.
- Due to the rise in usage and adoption in banking sectors to analyze and research consumer data and implement efficient strategies, the COVID-19 pandemic has significantly impacted data analytics in the banking industry. Because of the rapid evolution of technology, data analytics in banking has seen tremendous growth.
Big Data Analytics in Banking Market Trends
Risk Management and Internal Controls Across the Bank to Witness the Growth
- With the use of cutting-edge technologies, banks can reduce credit risk and make better decisions based on a variety of risk criteria. Banks can control credit risk and avert default circumstances thanks to the big data and analytics platform.
- Additionally, a blatant indicator is the retail bank's use of Big Data analytics for credit risk management. It has been demonstrated that applying credit risk indicators based on behavioral patterns in payment transactions allows for the detection of credit events much sooner than conventional indicators based on overdrawn accounts and late payments.
- Real-time fraud detection using data and analytics tools helps reduce credit and liquidity risk by enabling close monitoring of debtors and the ability to foresee loan default.
- Big data can be used to identify high-risk accounts, as demonstrated by The Bank of America. For 9.5 million mortgages, the Corporate Investment Group is responsible for calculating the likelihood of default, which helped Bank of America forecast losses from loan defaults. By cutting the time needed to calculate loan defaults from 96 to 4 hours, the bank was able to increase its efficiency.
Understand The Key Trends Shaping This Market
Europe to Expected to Witness Significant Growth
- The most well-known rule governing how financial organizations exchange and safeguard customers' private information continues to be the General Data Protection Rule of the European Union.
- Moreover, data exchange was made possible through open application programming interfaces (APIs) as a result of the Payment Services Directive (PSD2) by the European Union. Due to an environment where data can be shared freely, the capacity to collect, handle, and analyze data has grown in importance.
- Additionally, it is anticipated that both the number of customers and regulatory revisions will rise shortly. The demand for customer analytics and intelligence technologies should consequently increase.
- The UK-based Lloyds Banking Group employed data analytics to meet the needs of diverse client categories while optimizing growth in targeted segments.
- European retail banks are using Big Data analytics solutions due to the "open banking" trend, which addresses problems that traditional financial institutions have faced for decades.
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Big Data Analytics in Banking Industry Overview
Big Data Analytics In Banking Market is quite fragmented due to the existence of numerous global firms that provide a range of big data analytics solutions for banks for diverse applications, such as fraud detection and management, customer analytics, social media analytics, etc. Oracle Corporation, IBM Corporation, and SAP SE are some of the major market participants.
- February 2023 - Alteryx announced new self-service and enterprise-grade capabilities to its Alteryx Inc cloud-based analytics tool to support clients in making quicker and more informed decisions. With full access to Designer Cloud now included, the platform has been improved to provide employees of all skill levels with an approachable, simple-to-use drag-and-drop interface without compromising data governance or security standards.
- August 2022 - Aspire Systems launches the holistic approach to accelerate implementation. This innovation is powered by AI and drives implementation speeds. With this new autonomous application implementation methodology, Aspire Systems is geared to help businesses derive maximum value out of their Oracle Cloud ERP Application implementation.
Big Data Analytics in Banking Market Leaders
IBM Corporation
SAP SE
Oracle Corporation
Aspire Systems Inc.
Alteryx Inc.
*Disclaimer: Major Players sorted in no particular order
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Big Data Analytics in Banking Market News
- March 2023 - Alteryx has declared that it had successfully earned the Google Cloud Ready - AlloyDB Designation. Customers may access data from various databases using Alteryx's growing library of connectors, enabling them to use more data than ever before. Cloud Ready - AlloyDB is a new moniker for the products offered by Google Cloud's technology partners that interact with AlloyDB. By receiving this recognition, Alteryx has worked closely with Google Cloud to incorporate support for AlloyDB into its solutions and fine-tune its current capabilities for the best results.
- January 2023 - Aspire Systems has announced its rise to the AWS Advanced Consulting Partner tier, where partnership lets Aspire bolster its cloud solutions with AWS resources to support government and space agencies, leaders in education, and nonprofits. Using the resources gleaned from the much sought-after APN Immersion Days, Aspire provides exclusive, state-of-the-art AWS solutions to its customers.
Big Data Analytics in Banking Market Report - Table of Contents
1. INTRODUCTION
1.1 Study Assumptions & Market Definition
1.2 Scope of the Study
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Attractiveness - Porter's Five Force Analysis
4.2.1 Threat of New Entrants
4.2.2 Bargaining Power of Buyers/Consumers
4.2.3 Bargaining Power of Suppliers
4.2.4 Threat of Substitute Products
4.2.5 Intensity of Competitive Rivalry
4.3 Industry Value Chain Analysis
4.4 Impact of COVID-19 on the Market
5. MARKET DYNAMICS
5.1 Market Drivers
5.1.1 Enforcement of Government Initiatives
5.1.2 Risk Management and Internal Controls Across the Bank to Witness the Growth
5.1.3 Increasing Volume of Data Generated by Banks
5.2 Market Challenges
5.2.1 Lack of Data Privacy and Security
6. RELEVANT CASE STUDIES AND USE CASES
7. MARKET SEGMENTATION
7.1 By Solution Type
7.1.1 Data Discovery and Visualization (DDV)
7.1.2 Advanced Analytics (AA)
7.2 By Geography
7.2.1 North America
7.2.2 Europe
7.2.3 Asia-Pacific
7.2.4 Latin America
7.2.5 Middle East and Africa
8. COMPETITIVE LANDSCAPE
8.1 Company Profiles
8.1.1 IBM Corporation
8.1.2 SAP SE
8.1.3 Oracle Corporation
8.1.4 Aspire Systems Inc.
8.1.5 Adobe Systems Incorporated
8.1.6 Alteryx Inc.
8.1.7 Microstrategy Inc.
8.1.8 Mayato GmbH
8.1.9 Mastercard Inc.
8.1.10 ThetaRay Ltd
- *List Not Exhaustive
9. INVESTMENT ANALYSIS
10. FUTURE OF THE MARKET
Big Data Analytics in Banking Industry Segmentation
Big data analytics can help banks understand customer behavior based on the inputs received from various insights, including investment patterns, shopping trends, motivation to invest, and personal or financial background. With the improvement in big data analytics, banks can analyze market trends and form decisions related to lowering or increasing interest rates for individuals across various regions. With the help of big data analytics, financial services are actively using it to store data, derive business insights, and improve scalability as the number of electronic records grows.
The big data analytics in the banking market is segmented by Type of Solutions (Data Discovery and Visualization (DDV) and Advanced Analytics (AA)) and Geography (North America, Europe, Asia Pacific, Latin America, Middle East and Africa). The market sizes and forecasts are provided in terms of value (USD million) for all the above segments.
| By Solution Type | |
| Data Discovery and Visualization (DDV) | |
| Advanced Analytics (AA) |
| By Geography | |
| North America | |
| Europe | |
| Asia-Pacific | |
| Latin America | |
| Middle East and Africa |
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Big Data Analytics in Banking Market Research FAQs
How big is the Big Data Analytics In Banking Market?
The Big Data Analytics In Banking Market size is expected to reach USD 8.58 million in 2024 and grow at a CAGR of 23.11% to reach USD 24.28 million by 2029.
What is the current Big Data Analytics In Banking Market size?
In 2024, the Big Data Analytics In Banking Market size is expected to reach USD 8.58 million.
Who are the key players in Big Data Analytics In Banking Market?
IBM Corporation, SAP SE, Oracle Corporation, Aspire Systems Inc. and Alteryx Inc. are the major companies operating in the Big Data Analytics In Banking Market.
Which is the fastest growing region in Big Data Analytics In Banking Market?
Asia Pacific is estimated to grow at the highest CAGR over the forecast period (2024-2029).
Which region has the biggest share in Big Data Analytics In Banking Market?
In 2024, the North America accounts for the largest market share in Big Data Analytics In Banking Market.
What years does this Big Data Analytics In Banking Market cover, and what was the market size in 2023?
In 2023, the Big Data Analytics In Banking Market size was estimated at USD 6.97 million. The report covers the Big Data Analytics In Banking Market historical market size for years: 2019, 2020, 2021, 2022 and 2023. The report also forecasts the Big Data Analytics In Banking Market size for years: 2024, 2025, 2026, 2027, 2028 and 2029.
Big Data Analytics in Banking Industry Report
Banking analytics, particularly banking big data, is gaining significance due to the rise in data production and regulatory requirements. This technology enables banks to comprehend customer patterns and tendencies, leading to more insightful decision-making. The adoption of data analytics in banking is propelled by the necessity for improved data gathering, organization, integration, and examination. However, many traditional systems find it challenging to manage the escalating data load, requiring either an enhancement in processing capacity or a total system revamp. Banking data analytics solutions provide the required processing, persistence, and analytic capabilities to reveal new business insights. These tools can monitor and arrange both structured and unstructured data from various sources. The market is divided by type of solutions and geography, with solutions encompassing data discovery and visualization and advanced analytics. Big data in banking is also being utilized for risk management and internal controls across banks, aiding in minimizing credit risk and detecting fraud in real-time. For a more comprehensive understanding of these trends, a free PDF download of the report is available.
Big Data Analytics In Banking Market Report Snapshots
