Data Analytics in Financial Market Report 2025

The data analytics in financial market size has grown rapidly in recent years. It will grow from $13.89 billion in 2024 to $16.05 billion in 2025 at a compound annual growth rate (CAGR) of 15.5%. The growth during the historic period can be attributed to increasing regulatory requirements, the rise of digital banking, the expansion of big data, growing demand for real-time decision-making, and the emergence of fintech companies.

The data analytics in financial market size is expected to see rapid growth in the next few years. It will grow to $28.17 billion in 2029 at a compound annual growth rate (CAGR) of 15.1%. In the forecast period, growth is expected to be driven by the expansion of cloud-based analytics, rising demand for personalized financial services, increased adoption of blockchain technology, a surge in mobile banking usage, heightened need for advanced fraud detection, and a stronger focus on customer experience. Key trends anticipated include advancements in quantum-safe cryptography, development of explainable AI models, innovations in federated learning systems, adoption of synthetic data generation, and the use of emotion AI for customer analytics.

The rising number of fraud cases in the finance sector is expected to drive growth in the data analytics market for financial services in the coming years. Financial fraud involves deceptive activities such as unauthorized access to funds, data manipulation, or falsification of transactions within banking, investment, or insurance systems. These fraudulent acts can occur through both digital and traditional methods, undermining institutional integrity and eroding consumer trust. The increase in fraud is largely due to the rapid digitization of banking services without equivalent enhancements in security, creating vulnerabilities that sophisticated cybercriminals exploit. Data analytics in finance combats fraud by using advanced algorithms to identify suspicious patterns and anomalies in real time. These tools enable quicker detection of fraudulent activities, reducing financial losses and strengthening security measures. Additionally, they improve compliance and support better decision-making, thereby reinforcing trust in financial institutions. For example, in March 2025, the US Federal Trade Commission (FTC) reported that 38% of fraud cases involved financial loss in 2024, up from 27% in 2023. Consequently, the increasing incidence of fraud is fueling the expansion of data analytics in the financial sector.

Leading companies in the financial data analytics market are developing innovative solutions such as AI-powered predictive analytics platforms to improve real-time decision-making, risk management, and fraud detection. These platforms combine machine learning algorithms, integration of alternative data sources, and cloud-based processing to analyze vast financial datasets for forecasting market trends, detecting irregularities, and optimizing investment strategies with high accuracy. For instance, in July 2025, Anthropic PBC, a US-based AI research company, launched Claude for Financial Services - an enterprise-grade language model featuring constitutional AI safeguards designed to prevent harmful outputs while delivering precise financial analysis. This product addresses critical compliance challenges within banking and investment sectors and reduces the risk of AI hallucinations by 80% compared to traditional large language models (LLMs).

In May 2024, S&P Global Inc., a US-based financial information and analytics provider, acquired Visible Alpha LLC for an undisclosed sum. This acquisition is intended to enhance S&P Global’s investment research capabilities by integrating Visible Alpha’s detailed consensus data and analytics tools into its platforms, thereby increasing value for institutional investors. Visible Alpha LLC is a US-based company specializing in financial data analytics and investment research tools.

Major players in the data analytics in financial market are International Business Machines Corporation, The Bank of New York Mellon Corporation, S&P Global Inc., London Stock Exchange Group plc, Intercontinental Exchange Inc., Nasdaq Inc., LexisNexis Risk Solutions Inc., Dun & Bradstreet Holdings Inc., Morningstar Inc., FactSet Research Systems Inc., EXL Service Holdings Inc., Moody’s Investors Service Inc., Bloomberg Finance L.P., QlikTech International AB, Clearwater Analytics Holdings Inc., Sisense Ltd., Board International SA, Macrobond Financial AB, AlphaSense Inc., and QuantConnect LLC.

North America was the largest region in the data analytics in financial market in 2024. Aisa-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in data analytics in financial report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the data analytics in financial market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s recommendations and conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the financial sector, particularly in investment strategies and risk management. Heightened tariffs have fueled market volatility, prompting cautious behavior among institutional investors and increasing demand for hedging instruments. Banks and asset managers are facing higher costs associated with cross-border transactions, as tariffs disrupt global supply chains and dampen corporate earnings, key drivers of equity market performance. Insurance companies, meanwhile, are grappling with increased claims risks tied to supply chain disruptions and trade-related business losses. Additionally, reduced consumer spending and weakened export demand are constraining credit growth and investment appetite. The sector must now prioritize diversification, digital transformation, and robust scenario planning to navigate the heightened economic uncertainty and protect profitability.

Data analytics in finance involves the application of advanced analytical tools and techniques - such as statistical models, machine learning, and data mining - to examine financial data and support better decision-making. Its primary goals are to identify trends, evaluate risks, optimize investment strategies, and enhance overall financial performance and forecasting.

The main components of financial data analytics include software and services. Software encompasses advanced computational tools and methods used to collect, process, and analyze financial data for improved decision-making, risk management, compliance, and strategic planning. These solutions are utilized by organizations of various sizes, including small and medium-sized enterprises (SMEs) and large corporations, and are implemented via different deployment models such as on-premises and cloud-based platforms. Data analytics is applied across multiple areas, including risk management, fraud detection and prevention, customer management, compliance and security management, among others. Key end-users span sectors such as banking, insurance, investment management, and others.

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

The data analytics in financial market consist of revenues earned by entities by providing services such as portfolio optimization,sentiment analysis, trade surveillance, financial forecasting, and liquidity analysis. The market value includes the value of related goods sold by the service provider or included within the service offering. Data analytics in financial market also includes sales of data visualization tools, alternative data feeds, predictive analytics models, risk scoring systems, and real-time analytics dashboards. 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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