Big Data Analytics in Banking Market Report 2026

The big data analytics in banking market size has grown rapidly in recent years. It will grow from $39.86 billion in 2025 to $44.6 billion in 2026 at a compound annual growth rate (CAGR) of 11.9%. The growth in the historic period can be attributed to increasing digitization of banking operations, growth in online and mobile banking usage, rising volumes of transactional data, adoption of data warehousing technologies, early implementation of fraud analytics tools.

The big data analytics in banking market size is expected to see rapid growth in the next few years. It will grow to $69.2 billion in 2030 at a compound annual growth rate (CAGR) of 11.6%. The growth in the forecast period can be attributed to increasing use of AI-driven analytics models, rising investments in cloud-native banking platforms, growing demand for personalized banking services, expansion of advanced compliance analytics, increasing integration of analytics with core banking systems. Major trends in the forecast period include increasing adoption of predictive analytics for risk management, rising deployment of real-time fraud detection systems, growing use of customer behavior analytics platforms, expansion of cloud-based analytics solutions, enhanced focus on data-driven decision making.

The increasing adoption of digital banking platforms is expected to drive growth in the big data analytics in banking market. Digital banking platforms are online or mobile services that allow customers to access accounts, perform transactions, and manage finances without visiting branches. Adoption is rising due to demand for convenience, real-time services, and remote banking capabilities. Big data analytics supports digital banking by providing insights into customer behavior, detecting fraud, optimizing personalized services, and enhancing operational efficiency. For example, in September 2025, Open Banking Limited reported that over 15.16 million individuals and businesses were using technology-powered services, with transactions reaching 2.04 billion, a 3.5% increase from June. Therefore, digital banking adoption is driving growth in big data analytics.

Major companies in the big data analytics in banking market are adopting cloud-based analytics platforms, such as fully managed data lakes and AI-enabled cloud services, to improve scalability, flexibility, and operational efficiency. Cloud-based analytics platforms are centralized internet-hosted systems that allow banks to store, process, and analyze large volumes of financial and customer data without on-premises infrastructure, supporting real-time insights and regulatory compliance. In October 2025, Oracle Corporation, a US-based cloud computing company, introduced Oracle Financial Services Analytics Cloud, offering integrated data management, AI-driven predictive models, and seamless API connectivity for core banking systems. The platform allows banks to scale analytics operations rapidly, reduce IT overhead, and improve customer experience with personalized financial services.

In April 2025, Kinective, a US-based provider of banking operations platforms, acquired Datava for an undisclosed amount. The acquisition enables Kinective to integrate advanced, end-to-end data intelligence within its operations suite, allowing financial institutions to unify transactional and customer data and leverage predictive analytics for operational efficiency. Datava is a US-based provider of data aggregation, machine learning dashboards, and predictive banking analytics tools.

Major companies operating in the big data analytics in banking market are Microsoft Corporation, Oracle Corporation, KPMG International Cooperative, NTT DATA Corporation, Capgemini Societas Europaea (Capgemini SE), International Business Machines Corporation (IBM), Wipro Limited, HCL Technologies Limited, Tata Consultancy Services Limited, Accenture Public Limited Company (Accenture plc), Sopra Steria Group, Infosys Limited, Databricks Inc., Experian Public Limited Company (Experian plc), DXC Technology Company, SAS Institute Inc., Palantir Technologies Inc., Equifax Inc., Mphasis Limited, FICO (Fair Isaac Corporation), ThoughtWorks Inc., Cognizant Technology Solutions Corporation, Deloitte Touche Tohmatsu Limited, Neptune Intelligence Computer Engineering Ltd. (NICE), Alteryx Inc., MicroStrategy Incorporated, Teradata Corporation, Snowflake Inc., PricewaterhouseCoopers LLP (PwC), and Ernst & Young Global Limited (EY).

North America was the largest region in the big data analytics in banking market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the big data analytics in banking market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the big data analytics in banking market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The big data analytics in banking market consists of revenues earned by entities by providing services such as data mining, predictive analytics, regulatory compliance monitoring, credit scoring, portfolio optimization, market trend forecasting, data visualization and real-time transaction analysis. The market value includes the value of related goods sold by the service provider or included within the service offering. The big data analytics in banking market also includes sales of analytics software platforms, data management tools, cloud-based analytics systems, business intelligence (BI) dashboards, backup devices, and security hardware systems. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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