Generative Artificial Intelligence (AI) In Banking Market Size
How Will the Generative Artificial Intelligence (AI) In Banking Market Grow, and What Is the Projected Market Size?
The banking sector has witnessed a substantial increase in the size of the generative artificial intelligence (AI) market in the past few years. The market size is projected to expand from $1.16 billion in 2024 to $1.44 billion in 2025, growing at a compound annual growth rate (CAGR) of 24.1%. This significant growth during the historical period is the result of factors like growing data availability, the adoption of cloud computing, the demand for personalized customer services, regulatory compliance pressures, and the emergence of fintech disruptors.
The market size for generative artificial intelligence (AI) in banking is on track for a significant surge over the coming years, with prospective growth estimated at $3.39 billion by 2029, representing an impressive compound annual growth rate (CAGR) of 23.9%. The expected expansion during this forecast period is linked to the increasing automation of banking procedures, a rising demand for fraud detection solutions, the proliferation of digital banking, the necessity for greater operational efficiency, and an intensified focus on enriching the customer experience. Major trends profiled for this outlook period encompass chatbots powered by AI, risk management leveraging AI, customized financial services, AI-driven investment instruments, and the infusion of AI into mobile banking applications.
What Key Elements Are Boosting Growth in the Generative Artificial Intelligence (AI) In Banking Market?
The growth of generative artificial intelligence (AI) in the banking sector is set to be fueled by an increasing demand for fraud detection and prevention. Fraud detection and prevention encompass the methods and technologies utilized to spot, prevent, and manage fraudulent activities. The increasing sophistication of embezzlement tactics and the rise in the volume of financial transactions are factors contributing to the demand for fraud detection and prevention. Generative AI in banking aids in reducing fraud and improving detection by examining large amounts of data patterns to detect irregular transactions and halt fraudulent activities as they happen in real time. For example, the Australian Bureau of Statistics, a government organization based in Australia, reported that about 8.7% or 1.8 million individuals experienced card fraud in 2022-23, a rise from the 8.1% recorded in 2021-22. Thus, it is clear that the growing demand for fraud detection and prevention is supporting the expansion of the generative artificial intelligence (AI) in banking market.
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Who Are the Major Industry Players Fueling Generative Artificial Intelligence (AI) In Banking Market Expansion?
Major companies operating in the generative artificial intelligence (AI) in banking market are Google LLC, Microsoft Corporation, Amazon Web Services (AWS) Inc., accenture* plc, International Business Machines Corporation (IBM), Oracle Corporation, SAP SE, Tata Consultancy Services (TCS) Ltd., Nvidia Corporation, Salesforce Inc., Capgemini SE, Cognizant Technology Solutions Corporation, Infosys Limited, Finastra Group Holdings Limited, Pegasystems Inc., Temenos AG, C3.ai Inc., Clari Inc, DataRobot Inc., Aisera, Kasisto Inc.
How Is the Generative Artificial Intelligence (AI) In Banking Market Evolving?
Leaders in the generative artificial intelligence (AI) banking segment, are inventing new strategies like responsible generative AI. This technology aims for an ethical, transparent, and safe financial operation, whilst improving fraud detection and client services. Responsible generative AI implies deploying generative AI systems that uphold ethical norms, transparency, fairness, and accountability. Take for example, in May 2024, a significant advancement in the AI amalgamation into the financial services industry was witnessed when Temenos AG, a software establishment based in Switzerland, introduced Responsible Generative AI solutions for their core banking operations. These innovations form part of the AI-fused banking platform of Temenos API, which is engineered to enhance banks’ data management, hence driving productivity and profitability, while ensuring adherence to regulations and secure operations. Through the use of natural language inquiries, users can engage with the system, producing distinctive insights and reports swiftly, which lessens the time required by business stakeholders to obtain crucial data. This includes the capability to identify the most profitable customer divisions considering their demographic characteristics.
How Is the Segmentation of the Generative Artificial Intelligence (AI) In Banking Market Defined?
The generative artificial intelligence (AI) in banking market covered in this report is segmented –
1) By Technology: Natural Language Processing; Deep Learning; Reinforcement Learning; Generative Adversarial Networks; Computer Vision; Predictive Analytics
2) By Deployment Model: Cloud Deployment; On-Premises Deployment; Hybrid Deployment
3) By End-User: Retail Banking Customers; Small And Medium Enterprises; Investment Professionals; Compliance And Risk Management Teams; Operations And Process Optimization; Executives And Decision Makers
Subsegments:
1) By Natural Language Processing (NLP): Chatbots And Virtual Assistants; Sentiment Analysis For Financial Markets; Document And Contract Analysis; Speech Recognition For Customer Service
2) By Deep Learning: Fraud Detection And Prevention; Credit Scoring And Risk Assessment; Predictive Analytics For Investment; Customer Behavior Analysis
3) By Reinforcement Learning: Algorithmic Trading; Portfolio Management And Optimization; Dynamic Pricing Models; Personalized Financial Services
4) By Generative Adversarial Networks (GANs): Synthetic Data Generation For Training Models; Fraud Detection And Risk Management; Customer Data Augmentation For Personalization; Market Simulation And Analysis
5) By Computer Vision: Document Verification And Processing; ATM Surveillance And Security; Image-Based Fraud Detection; Visual Data Extraction For Financial Analysis
6) By Predictive Analytics: Risk Assessment And Management; Credit Scoring And Loan Default Prediction; Customer Churn Prediction; Market Trend Forecasting
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What Is the Leading Region in the Generative Artificial Intelligence (AI) In Banking Market?
North America was the largest region in the generative artificial intelligence (AI) in banking market in 2024. The regions covered in the generative artificial intelligence (AI) in banking market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What Is Covered In The Generative Artificial Intelligence (AI) In Banking Global Market Report?
– Market Size Analysis: Analyze the generative artificial intelligence (ai) in banking Market size by key regions, countries, product types, and applications.
– Market Segmentation Analysis: Identify various subsegments within the generative artificial intelligence (ai) in banking Market for effective categorization.
– Key Player Focus: Focus on key players to define their market value, share, and competitive landscape.
– Growth Trends Analysis: Examine individual growth trends and prospects in the market.
– Market Contribution: Evaluate contributions of different segments to the overall generative artificial intelligence (ai) in banking market growth.
– Growth Drivers: Detail key factors influencing market growth, including opportunities and drivers.
– Industry Challenges: Analyze challenges and risks affecting the generative artificial intelligence (ai) in banking market.
– Competitive Developments: Analyze competitive developments, such as expansions, agreements, and new product launches in the market.
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