PUBLISHER: The Business Research Company | PRODUCT CODE: 1710318
PUBLISHER: The Business Research Company | PRODUCT CODE: 1710318
Generative artificial intelligence (AI) in banking and finance involves applying AI technologies to create new content, insights, or solutions based on existing data and patterns within the financial sector. This includes utilizing advanced machine learning models, such as generative adversarial networks (GANs) and transformer models, to perform various tasks.
Key technologies in generative AI for banking and finance include natural language processing, deep learning, reinforcement learning, generative adversarial networks, computer vision, and predictive analytics. Natural language processing (NLP) enables AI systems to understand and interact with human language. Deployment models for these technologies include both on-premises and cloud-based solutions, catering to applications such as fraud detection, customer service, risk assessment, compliance, trading, and portfolio management. These technologies are used by a range of end-users, including banks, insurance companies, investment firms, and fintech companies.
The generative artificial intelligence (AI) in banking and finance market research report is one of a series of new reports from The Business Research Company that provides generative artificial intelligence (AI) in banking and finance market statistics, including generative artificial intelligence (AI) in banking and finance industry global market size, regional shares, competitors with a generative artificial intelligence (AI) in banking and finance market share, detailed generative artificial intelligence (AI) in banking and finance market segments, market trends and opportunities, and any further data you may need to thrive in the generative artificial intelligence (AI) in banking and finance industry. This generative artificial intelligence (AI) in banking and finance market research report delivers a complete perspective on everything you need, with an in-depth analysis of the current and future scenarios of the industry.
The generative artificial intelligence (AI) in banking and finance market size has grown exponentially in recent years. It will grow from $1.3 $ billion in 2024 to $1.75 $ billion in 2025 at a compound annual growth rate (CAGR) of 34.9%. The growth in the historic period can be attributed to the digital transformation of financial services, the need for enhanced customer experiences, the rise of data analytics capabilities, increasing regulatory compliance demands, the necessity for fraud detection and risk management, growing importance of operational efficiency and cost reduction.
The generative artificial intelligence (AI) in banking and finance market size is expected to see exponential growth in the next few years. It will grow to $5.74 $ billion in 2029 at a compound annual growth rate (CAGR) of 34.6%. The growth in the forecast period can be attributed to the demand for personalized financial services, integration of AI with existing banking systems for streamlined operations, need for predictive analytics in risk management, focus on enhancing customer trust and transparency, urgency to address data privacy concerns, rapid evolution of workforce skills to support AI initiatives, competitive pressure to leverage advanced AI technologies for maintaining market advantage. Major trends in the forecast period include the integration of generative AI into risk management and fraud detection systems, expansion of AI capabilities in algorithmic trading and investment strategies, enhancement of regulatory compliance through automated reporting, the rise of AI-powered virtual assistants for customer service, development of advanced predictive analytics for market forecasting, growing emphasis on ethical AI practices to ensure transparency and fairness in AI applications.
The growing emphasis on data security is expected to drive the expansion of generative artificial intelligence (AI) in the banking and finance sector. Data security involves protecting digital information from unauthorized access, corruption, or theft throughout its lifecycle, with measures in place to ensure confidentiality, integrity, and availability. This heightened focus on data security stems from the rise in cyber threats, stringent regulatory requirements, and the need to safeguard sensitive data from breaches and loss. Generative AI plays a key role in enhancing data security in banking and finance by identifying unusual patterns, predicting potential risks, and automating security protocols to better protect sensitive financial data. For example, in April 2024, a report by the Department for Science, Innovation, and Technology, a US-based law enforcement agency, highlighted that 22% of businesses and 14% of charities had experienced cybercrime in the past year. The figures were even higher for medium-sized businesses (45%), large businesses (58%), and high-income charities (37%). As a result, the increasing focus on data security is fueling the growth of generative AI in the banking and finance market.
Key players in the generative AI market for banking and finance are focusing on cutting-edge technologies, such as cloud-based AI platforms, to boost operational efficiency, automate complex financial processes, enhance customer service through personalized interactions, and provide advanced analytics for improved decision-making and risk management. Cloud-based AI platforms are online services offering AI capabilities, allowing organizations and developers to create, deploy, and manage AI models and applications without investing in or maintaining physical hardware or managing intricate infrastructure. For instance, in September 2023, Ally Financial Inc., a US-based financial services firm, introduced Ally.ai, a proprietary cloud-based AI platform. Ally.ai aims to enhance financial services with advanced machine learning algorithms and natural language processing, improving customer interactions with personalized financial advice, automating routine tasks, and providing predictive analytics to optimize decision-making and operational efficiency.
In July 2024, Sparq, a US-based digital engineering firm, acquired Kingsmen Software for an undisclosed amount. This acquisition is intended to provide Sparq's clients with advanced technological insights and solutions by integrating Kingsmen's expertise in generative AI, custom software delivery, and financial sector services. Kingsmen Software, also based in the US, specializes in generative AI strategies for the financial industry.
Major companies operating in the generative artificial intelligence (AI) in banking and finance market are Microsoft Corporation, Wells Fargo & Co, Amazon Web Services Inc., HSBC Holdings plc, International Business Machines Corporation, American Express, Morgan Stanley & Co LLC, Goldman Sachs Group Inc., ING Group, Oracle Corporation, SAP SE, Nvidia Corporation, Salesforce Inc., NatWest Group plc., Lloyds Banking Group, Oversea-Chinese Banking, SAS Institute Inc., SymphonyAI LLC, DataRobot Inc., Rasa Technologies Inc.
North America was the largest region in the generative artificial intelligence (AI) in banking and finance market in 2023.Asia Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the generative artificial intelligence (AI) in banking and 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 banking and finance market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
The generative artificial intelligence (AI) in banking and finance includes revenues earned by entities through the sale of cloud services, consulting and implementation services, and data and analytics services. 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) market in banking and finance also includes sales of fraud detection systems, portfolio management systems, and personalized financial planning 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.
Generative Artificial Intelligence (AI) In Banking And Finance Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.
This report focuses on generative artificial intelligence (ai) in banking and finance market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
Where is the largest and fastest growing market for generative artificial intelligence (ai) in banking and finance ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The generative artificial intelligence (ai) in banking and finance market global report from the Business Research Company answers all these questions and many more.
The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.
The forecasts are made after considering the major factors currently impacting the market. These include the Russia-Ukraine war, rising inflation, higher interest rates, and the legacy of the COVID-19 pandemic.