Predictive Analytics in Banking Market Report 2026

The predictive analytics in banking market size has grown exponentially in recent years. It will grow from $4.62 billion in 2025 to $5.58 billion in 2026 at a compound annual growth rate (CAGR) of 20.6%. The growth in the historic period can be attributed to increasing digitization of banking operations, growth in transactional data volumes, rising adoption of data-driven decision-making, expansion of online banking channels, availability of advanced analytics tools.

The predictive analytics in banking market size is expected to see exponential growth in the next few years. It will grow to $11.67 billion in 2030 at a compound annual growth rate (CAGR) of 20.3%. The growth in the forecast period can be attributed to increasing demand for hyper-personalized banking services, expansion of predictive risk management use cases, growing investments in cloud analytics platforms, rising focus on proactive fraud prevention, increasing adoption of ai-driven banking insights. Major trends in the forecast period include increasing adoption of machine learning-based prediction models, rising use of customer behavior analytics, expansion of real-time data processing capabilities, growing integration with core banking systems, enhanced focus on fraud and risk prediction.

The increasing prevalence of fraudulent activities is expected to drive the growth of predictive analytics in the banking sector. Fraudulent activities involve deliberate schemes designed to deceive or manipulate individuals or organizations for personal or financial gain. In the banking industry, rising cyberattacks and the expansion of digital banking services are contributing to the surge in fraud. Predictive analytics helps combat these threats by using advanced algorithms to detect and flag unusual patterns and behaviors in real time, facilitating proactive fraud detection and prevention. For example, in February 2024, the Federal Trade Commission reported that consumers lost over $10 billion to fraud in 2023, a 14% increase from the previous year. Thus, the growing incidence of fraudulent activities is fueling the demand for predictive analytics in banking.

Leading companies in the predictive analytics in banking market are developing AI-powered data analytics platforms to enhance data analysis and interpretation, enabling faster insights and more informed decision-making. These platforms utilize advanced data processing, predictive modeling, and pattern recognition to improve risk management, personalize customer experiences, detect fraud, streamline operations, and identify new growth opportunities. For example, in March 2024, TransUnion, a US-based information technology firm, introduced OneTru, an AI-driven data analytics platform designed to advance data access and decision-making for financial institutions. This cloud-based platform integrates data analytics, credit risk assessment, and fraud detection into a single portal, using artificial intelligence and machine learning. OneTru consolidates fragmented data sources, providing streamlined access to credit bureau, consumer identity, and marketing data, thereby enhancing the speed and quality of analytics and improving client decision-making processes.

In August 2024, EXL, a US-based technology and operations management firm, acquired ITI Data for an undisclosed sum. This acquisition strengthens EXL's capabilities in managing large-scale data, improving data integration, and delivering advanced analytics solutions. As a result, EXL can provide its clients with enhanced insights, better decision-making, and more efficient operations. ITI Data, based in the US, specializes in data management and predictive analytics within the banking sector.

Major companies operating in the predictive analytics in banking market are Microsoft Corporation, Amazon Web Services Inc., International Business Machines Corporation, Oracle Corporation, SAS Institute Inc., Turing Analytics, Databricks Inc., Alteryx Inc., H2O.ai, EdgeVerve Systems Limited, Google Cloud, Dataiku, Datarobot Inc., Feature Labs, KNIME, Altair Engineering Inc., Rasa, Peltarion, Auger.AI, BigML, Big Squid Inc, dotData Inc., Determined.ai Inc., Turi.

North America was the largest region in the predictive analytics in banking market in 2025. The regions covered in the predictive 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 predictive analytics in banking market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The predictive analytics in banking market consists of revenues earned by entities by providing services such as customer segmentation and profiling, credit risk assessment, and fraud detection and prevention. The market value includes the value of related goods sold by the service provider or included within the service offering. The predictive analytics in banking market also includes sales of workstations, security hardware, and network infrastructure. 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.

This product will be delivered within 1-3 business days.