Artificial Intelligence in Banking Market Share, Size, Trends, Industry Analysis Report, By Component (Service, Solution); By Technology; By Enterprise Size; By Application; By Region; Segment Forecast, 2024 - 2032
The artificial intelligence in banking market size is expected to reach USD 236.70 Billion by 2032, according to a new study by Polaris Market Research. The report “Artificial Intelligence in Banking Market Share, Size, Trends, Industry Analysis Report, By Component (Service, Solution); By Technology; By Enterprise Size; By Application; By Region; Segment Forecast, 2024 - 2032” gives a detailed insight into current market dynamics and provides analysis on future market growth.
Increasing demand for fraud detection AI software is playing an important role in driving the rapid growth of artificial intelligence (AI) in the banking industry. As the number of financial transactions and digital interactions grows, the banking industry must deal with increasingly sophisticated and diverse types of fraud. In response to the changing threat landscape, banks and financial institutions are relying on advanced AI solutions for fraud detection. These AI-powered systems use machine learning algorithms and predictive analytics to analyze massive amounts of data in real-time, detecting patterns and anomalies that could indicate fraudulent activity. The effectiveness and efficiency of AI-based fraud detection not only improve security measures but also significantly increase operational efficiency.
Artificial intelligence in the banking sector refers to the application of AI technologies within financial institutions. Banks can efficiently analyze large datasets using artificial intelligence, allowing them to predict the latest market trends, currency fluctuations, and equity movements in the financial services industry.
Banks are increasingly integrating AI-powered systems to improve the accuracy, safety, and profitability of their credit and loan assessment processes. Currently, many banks must rely on traditional factors such as credit scores, credit history, and customer references to determine the creditworthiness of both individuals and businesses. A loan and credit system powered by Artificial Intelligence can analyze the behaviors and patterns of customers with limited credit history, resulting in a more accurate assessment of their creditworthiness. Furthermore, the system can proactively notify banks of specific behaviors that may increase the risk of default. To summarize, these technologies will play a critical role in reshaping the consumer lending landscape.
Artificial intelligence is playing a crucial role in improving the security of banking systems. Previously, banks relied heavily on traditional rule-based Anti-Money Laundering (AML) transaction monitoring and name screening systems, which were frequently susceptible to errors. Given the growing number of fraud-related crimes and the dynamic nature of fraud patterns, advanced AI elements are being integrated into the existing systems.
Artificial Intelligence in Banking Market Report Highlights
The large enterprise segment held the largest market share in 2023. They are witnessing growth in the AI banking market owing to their capacity to invest in refined AI technologies.
The services segment witnessed for the fastest market growth in 2023, due to the rising number of software installed in the small, mid, and large sized banks.
Asia-Pacific has witnessed the fastest growth in the artificial intelligence in banking market, due to the adoption of AI technology and rising digitization of the banking sector in region.
The key market players include Amazon Web Services, Inc., Capital One, Cisco Systems, Inc., FAIR ISAAC CORPORATION (FICO), Goldman Sachs, International Business Machines Corporation, JPMorgan Chase & Co., NVIDIA Corporation, RapidMiner, and SAP SE.
Polaris Market Research has segmented the artificial intelligence in banking market report based on component, technology, enterprise size, application, and country:
Artificial Intelligence in Banking, Component Outlook (Revenue - USD Billion, 2019 - 2032)
Service
Solution
Artificial Intelligence in Banking, Technology Outlook (Revenue - USD Billion, 2019 - 2032)
Natural Language Processing (NLP)
Machine Learning & Deep Learning
Computer vision
Others
Artificial Intelligence in Banking, Enterprise Size Outlook (Revenue - USD Billion, 2019 - 2032)
Large Enterprise
SMEs
Artificial Intelligence in Banking, Application Outlook (Revenue - USD Billion, 2019 - 2032)
Risk Management
Customer Service
Virtual Assistant
Financial Advisory
Others
Artificial Intelligence in Banking, Regional Outlook (Revenue - USD Billion, 2019 - 2032)
North America
Europe
Asia-Pacific
Latin America
Middle East Africa