Machine Learning in the Financial Services Market Report 2025

The machine learning in the financial services market size has grown exponentially in recent years. It will grow from $3.85 billion in 2024 to $5.24 billion in 2025 at a compound annual growth rate (CAGR) of 36.2%. The growth in the historic period was driven by the rising need for fraud detection, greater adoption of automation in financial operations, growing demand for personalized banking experiences, the expanding volume of financial data, and the increasing use of digital payment platforms.

The machine learning in the financial services market size is expected to see exponential growth in the next few years. It will grow to $17.83 billion in 2029 at a compound annual growth rate (CAGR) of 35.8%. In the forecast period, growth is expected to stem from the growing preference for cloud-based solutions, increased use of predictive analytics in finance, rising demand for real-time customer insights, wider adoption of robo-advisors, and a stronger focus on regulatory compliance through automation. Key trends anticipated include advancements in explainable artificial intelligence models, enhanced application of machine learning in credit scoring, the emergence of autonomous financial advisors, innovations in fraud detection algorithms, and progress in real-time risk management systems.

The growing preference for cloud-based solutions is expected to drive the expansion of machine learning in the financial services market. Cloud-based solutions are internet-delivered services or tools that eliminate the need for local installation or management. Their rising adoption is largely due to the demand for remote access, enabling individuals and businesses to access essential tools and data from any location. In financial services, cloud-based solutions provide flexible and scalable infrastructure, allowing institutions to process vast amounts of data in real time, deploy machine learning models more quickly, and seamlessly integrate analytics into operations for improved decision-making and risk management. For example, in December 2023, Eurostat, a Luxembourg-based governmental statistical agency, reported that 42.5% of EU enterprises used cloud computing services in 2023 - primarily for email, file storage, and office software - marking a 4.2% increase from 2021. This trend is fueling the growth of machine learning applications in the financial services sector.

Companies in the machine learning in financial services market are increasingly forming strategic partnerships to strengthen technological capabilities and broaden market presence. Such partnerships involve collaboration between organizations to leverage combined resources and expertise for mutual growth. For instance, in December 2022, Deutsche Bank AG, a Germany-based investment banking company, partnered with Nvidia Corporation, a US-based technology company, to expand the use of artificial intelligence (AI) and machine learning (ML) in financial services. The partnership focuses on improving operational efficiency, enhancing risk management, and developing AI-powered applications that comply with regulatory requirements. It also supports Deutsche Bank’s transition to cloud-based infrastructure and fosters innovation through initiatives such as virtual avatars and financial language models, aimed at delivering smarter, faster, and more personalized banking services.

In December 2024, Mastercard Inc., a US-based credit card company, acquired Recorded Future for an undisclosed amount. This acquisition seeks to strengthen Mastercard’s cybersecurity and fraud detection capabilities by incorporating Recorded Future’s machine learning-powered threat intelligence platform. The integration enables financial institutions and digital businesses to proactively detect, evaluate, and address cyber threats, thereby enhancing trust and security across Mastercard’s global payment ecosystem. Recorded Future Inc., based in the US, specializes in cybersecurity and threat intelligence solutions designed for the financial services industry.

Major players in the machine learning in the financial services market are Amazon Web Services Inc., Microsoft Corporation, Intel Corporation, Accenture Public Limited Company, International Business Machines Corporation, Oracle Corporation, SAP Societas Europaea, Salesforce Inc., NVIDIA Corporation, SAS Institute Inc., Palantir Technologies Inc., Fair Isaac Corporation, HighRadius Corporation, Upstart Holdings Inc., DataRobot Inc., Ocrolus Inc., Feedzai Inc., H2O.ai Inc., ZestFinance Inc., and Overbond Ltd.

North America was the largest region in the machine learning in the financial services market in 2024. The regions covered in machine learning in the financial services report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the machine learning in the financial services 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.

Machine learning in financial services involves the application of advanced algorithms and statistical models that allow systems to learn from historical data and make predictions or decisions without explicit programming. It enables financial institutions to enhance efficiency, accuracy, and decision-making by detecting patterns, automating tasks, and delivering personalized services.

The core components of machine learning in financial services are software and services. Software comprises platforms and tools for building, deploying, and managing machine learning models, available through both cloud-based and on-premises deployment. These solutions support a wide range of applications, such as fraud detection and prevention, risk management, customer analytics, portfolio management, algorithmic trading, regulatory compliance, chatbots and virtual assistants, loan underwriting, and insurance claim processing. The technology serves diverse end users, including banks, insurance providers, investment firms, and others.

The machine learning in the financial services market research report is one of a series of new reports that provides machine learning in the financial services market statistics, including machine learning in the financial services industry's global market size, regional shares, competitors with a machine learning in the financial services market share, detailed machine learning in the financial services market segments, market trends and opportunities, and any further data you may need to thrive in the machine learning in the financial services industry. This machine learning in the financial services 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 machine learning in the financial services market consists of revenues earned by entities by providing services such as financial forecasting, regulatory compliance support, portfolio optimization, and transaction monitoring. 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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