Predictive Analytics in Banking Market Report 2025

This Predictive Analytics in Banking market report delivers an in-depth analysis of the market’s key characteristics, including size, growth potential, and segmentation. It provides a detailed breakdown of the market across major regions and leading countries, highlighting historical data and future growth projections. The report also examines the competitive landscape, market share insights, emerging trends, and strategic developments shaping the market.

The predictive analytics in banking market size has grown exponentially in recent years. It will grow from $3.84 billion in 2024 to $4.64 billion in 2025 at a compound annual growth rate (CAGR) of 21%. The growth in the historic period can be attributed to credit risk assessment, fraud detection and prevention, customer segmentation and personalization, regulatory compliance and operational efficiency.

The predictive analytics in banking market size is expected to see exponential growth in the next few years. It will grow to $9.85 billion in 2029 at a compound annual growth rate (CAGR) of 20.7%. The growth in the forecast period can be attributed to artificial intelligence and machine learning, big data and real-time analytics, regulatory pressure and compliance, customer expectations for personalization and cybersecurity and fraud prevention. Major trends in the forecast period include enhanced customer experience through personalization, integration of AI and machine learning for advanced predictive models, real-time predictive analytics for instant decision-making, increased focus on cybersecurity and fraud prevention and regulatory compliance and risk management.

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 2024. The regions covered in the predictive analytics in banking market report are Asia-Pacific, 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, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Predictive analytics in banking involves using advanced techniques such as statistical analysis, machine learning, and data mining to examine historical and current data in order to forecast future trends and behaviors. This approach helps financial institutions make informed decisions by predicting customer behavior, market conditions, and potential risks.

Key areas of predictive analytics in banking include marketing, sales, finance, human resources, and operations. In marketing, predictive analytics focuses on strategic activities and functions designed to meet customer needs and improve services. This encompasses various solutions and services, with deployment models that include both on-premise and cloud options. Applications of predictive analytics extend to small and medium enterprises (SMEs) as well as large enterprises.

The predictive analytics in banking market research report is one of a series of new reports that provides predictive analytics in banking market statistics, including predictive analytics in banking industry global market size, regional shares, competitors with a predictive analytics in banking market share, detailed predictive analytics in banking market segments, market trends, and opportunities, and any further data you may need to thrive in the predictive analytics in banking industry. This predictive analytics in banking market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

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.

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