Generative Artificial Intelligence (AI) in Finance Market Report 2025

This Generative Artificial Intelligence (AI) in Finance 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 generative artificial intelligence (AI) in finance market size has grown exponentially in recent years. It will grow from $2.05 billion in 2024 to $2.83 billion in 2025 at a compound annual growth rate (CAGR) of 38.3%. The growth in the historic period can be attributed to digitalization of services, rise in personalized customer responses, rising need for enhancing security and trust in financial services, data privacy and security concerns, and regulatory compliance and governance.

The generative artificial intelligence (AI) in finance market size is expected to see exponential growth in the next few years. It will grow to $10.29 billion in 2029 at a compound annual growth rate (CAGR) of 38.1%. The growth in the forecast period can be attributed to increasing productivity, the application of generative artificial intelligence (AI) in fraud detection and prevention, automation of complex financial tasks through advanced generative artificial intelligence (AI), enhancing customer experience in finance, and operational efficiency and reducing costs. Major trends in the forecast period include developing innovative solutions, data analysis and reporting, artificial intelligence (AI)-driven chatbots, integrating machine learning (ML), and innovations in artificial intelligence tools.

The demand for personalized financial services is anticipated to drive the growth of generative artificial intelligence (AI) in the finance market. Personalized financial services involve creating customized solutions and advice tailored to each client's specific needs, preferences, and circumstances. This demand arises from consumer expectations for better financial management and enhanced risk management. Generative AI combines data from various sources, such as social media, transaction histories, and financial accounts, to provide a more comprehensive and personalized view of a client's financial situation. For example, a May 2024 survey by MX Technologies, which surveyed 150 financial services industry leaders and decision-makers in the U.S. and Canada, found that 81% of data strategy leaders view personalizing experiences based on consumer financial data as crucial for the future. Additionally, 45% of consumers felt that their interactions with finance-related mobile apps were personalized, and 36% preferred to securely share their financial data from all their accounts to receive personalized guidance and insights in one place. Thus, the growing demand for personalized financial services is a key driver of the generative AI market in finance.

Major companies in the generative artificial intelligence (AI) in finance market are focused on developing innovative solutions, such as responsible generative AI, to help banks boost productivity and profitability while adhering to ethical AI practices. Responsible generative AI solutions are designed to ensure the safe and ethical deployment of AI technologies, particularly in critical areas. For example, in May 2024, Temenos AG, a Switzerland-based software company, introduced the first Responsible Generative AI solutions specifically for the core banking and financial sectors. These generative AI capabilities can be used in customer operations and product development, allowing banks to create real-time products based on customer preferences. Temenos Generative AI enables users to perform natural language queries to quickly generate unique insights and reports, significantly speeding up access to crucial data for business stakeholders. For instance, it provides immediate and accessible responses regarding the most profitable customers based on type and demographics.

In July 2024, Nubank, a Brazil-based neobank, acquired Hyperplane for an undisclosed amount. This acquisition is intended to enhance the personalization of financial products and improve decision-making in areas such as risk assessment and marketing. Hyperplane, a US-based data intelligence company, specializes in advancing banking and financial services through sophisticated generative AI technologies.

Major companies operating in the generative artificial intelligence (AI) in finance market are Alphabet Inc., International Business Machines Corporation, The Allstate Corporation, The Goldman Sachs Group Inc., Mastercard Incorporated, Intuit Inc., S&P Global Inc., Plaid Inc., SAS Institute Inc., Klarna Inc., Qlik Technologies Inc., C3.ai Inc., AlphaSense Inc., Marqeta Inc., Upstart Holdings Inc., Hugging Face Inc., ZestFinance Inc., TrueLayer Limited, Featurespace Limited, Numerai Inc.

North America was the largest region in the generative artificial intelligence (AI) in finance market in 2024. Asia-Pacific is expected to be the fastest growing region in the market going forward. The regions covered in the generative artificial intelligence (AI) in finance market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the generative artificial intelligence (AI) in finance market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Generative artificial intelligence (AI) in finance involves AI systems that utilize advanced algorithms and machine learning techniques to produce new data, insights, or financial models. These systems are capable of generating synthetic financial data, simulating market scenarios, developing trading strategies, and producing predictive analytics. By processing and analyzing large volumes of financial information, generative AI in finance enhances decision-making, refines investment strategies, and improves risk management with innovative solutions.

The primary technologies in generative AI for finance include deep learning, natural language processing, computer vision, reinforcement learning, and others. Deep learning, a subset of machine learning, employs neural networks with multiple layers to model complex patterns in extensive datasets, similar to how the human brain processes information. These technologies are implemented through various deployment models such as cloud, on-premises, and hybrid setups. They find applications in areas such as risk management, fraud detection, investment research, and trading algorithms.

The generative artificial intelligence (AI) in finance market research report is one of a series of new reports that provides generative artificial intelligence (AI) in finance market statistics, including generative artificial intelligence (AI) in finance industry global market size, regional shares, competitors with a generative artificial intelligence (AI) in finance market share, detailed generative artificial intelligence (AI) in finance market segments, market trends, and opportunities, and any further data you may need to thrive in the generative artificial intelligence (AI) in finance industry. This generative artificial intelligence (AI) in finance 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 generative artificial intelligence (AI) in finance market consists of revenue earned by entities by services such as algorithmic trading, fraud detection, and management. The market value includes the value of related goods sold by the service provider or included within the service offering. The generative artificial intelligence (AI) in finance market also includes sales of automated tools, risk management tools, and customer relationship tools. 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 3-5 business days.