According to a research report "AI in Finance Market by Product (Algorithmic Trading, Virtual Assistants, Robo-Advisors, GRC, IDP, Underwriting Tools), Technology, Application (Fraud Detection, Risk Management, Trend Analysis, Financial Planning, Forecasting) - Global Forecast to 2030" published by MarketsandMarkets, the AI in Finance market is expected to reach USD 190.33 billion by 2030 from USD 38.36 billion in 2024, at a CAGR of 30.6% during 2024–2030.
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AI-driven chatbots and virtual assistants are significant growth drivers in the AI in finance market, enhancing customer service by delivering 24/7 support and personalized user interactions. AI-enabled technologies streamline routine tasks like account management or transaction tracking, freeing up human advisors for complex cases. By enabling users to make financial decisions, this accessibility broadens the services offered to end clients. Machine learning models enhance strategic planning and investment decisions by delivering accurate forecasts based on vast, real-time data analysis. Its capacity to change and improve over time guarantees consistently improved tactics, increasing decision-making. These models identify trends, predict market movements, and assess risks, enabling financial institutions to optimize portfolios and allocate resources effectively.
“AI automates tasks, reducing operational costs, boosting efficiency, and enabling financial institutions to pursue strategic innovations.”
The AI in Finance market is projected to grow from USD 38.36 billion in 2024 to USD 190.33 billion by 2030, at a compound annual growth rate (CAGR) of 30.6% during the forecast period. AI is transforming the finance industry by automating repetitive tasks, boosting productivity, and lowering operating expenses. By handling processes like data entry and invoice processing, AI enables financial institutions to redirect human resources toward strategic innovations. This shift streamlines operations and improves accuracy and decision-making, allowing firms to respond more effectively to market dynamics and customer needs, driving growth and competitive advantage in the industry.
“By Product type, the chatbots and virtual assistants segment will contribute the highest market share during the forecast period.”
Chatbots and virtual assistants are in demand in the AI-driven finance market due to their ability to automate customer service, enhance user experience, and reduce operational costs. Companies like Fiserv, HighRadius, and Envestnet Yodlee leverage these technologies to streamline tasks such as account management, payment processing, and financial planning. Chatbots respond instantly to common queries, while virtual assistants offer personalized financial insights, making services more accessible. These tools improve efficiency by reducing the number of human agents needed for more complex tasks, which leads to higher customer satisfaction and retention.
"Finance as business operation: “By Application, fraud detection and prevention segment will contribute to have highest market share during the forecast period.”
Financial institutions are investing in AI solutions capable of real-time anomaly detection and transaction pattern analysis, essential for identifying and preventing fraudulent activities. Traditional security measures often fall short against evolving threats, making AI an indispensable tool for enhancing security protocols. By leveraging advanced algorithms and machine learning, these institutions can proactively address potential fraud before it leads to significant losses, thereby prioritizing customer trust and safety in their operations. The integration of AI improves the effectiveness of fraud detection and streamlines overall risk management processes within the financial sector.
"Finance as business function: “By end user, retail & ecommerce will register the highest market share during the forecast period.”
Due to several key factors, retail and e-commerce are poised to hold the largest market share in the AI in finance market. Personalization is a major driver, with AI analyzing customer data to create tailored recommendations, boosting sales by 10-30% according to a NVDIA’s 2024 survey. Additionally, AI enhances operational efficiency by improving inventory accuracy by up to 30%, minimizing overstock and understock risks. Customer satisfaction also rises through AI-powered chatbots and virtual assistants, which provide 24/7 support, resulting in a 20-30% increase in satisfaction scores. Furthermore, AI automation leads to up to 30% operational cost reductions, allowing organizations to reallocate resources and invest in innovative solutions. These elements collectively position retail and e-commerce at the forefront of AI adoption for financial applications.
“By region, Asia Pacific to register the highest CAGR market during the forecast period.”
Rapid digital transformation across economies and the rise of fintech startups are driving AI solutions in Asia Pacific. Countries like China and India are investing heavily in AI technologies to enhance financial services and improve customer experiences. The region's vast consumer base presents major customized financial products and services opportunities. Regulatory bodies such as Monetary Authority of Singapore (MAS) and Cyberspace Administration of China (CAC) promote innovation and further boost market growth. The increasing focus on data-driven decision-making and the need for efficient risk management solutions also contribute to the rapid adoption of AI in finance, positioning Asia-Pacific as a leader in this sector.
Some major players in the AI in Finance Market include FIS (US), Fiserv (US), Google (US), Microsoft (US), Zoho (India), IBM (US), Socure (US), Workiva (US), Plaid (US), SAS (US), C3 AI (US), HighRadius (US), AWS (US), SAP (Germany), HPE (US), Oracle (US), Intel (US), NVIDIA (US), Salesforce (US), DataRobot (US), Enova International (US), AlphaSense (US), NetApp (US), Ocrolus (US), Vectra AI (US), Teradata (US), Pega (US), Vena Insights (US), Affirm (US), Symphony AI (US), Envestnet Yodlee (US), Addepto (Poland), Deeper Insights (UK), H2O.ai (US), App0 (US), Underwrite.ai (US), Deepgram (US), Emagia (US), InData Labs (US), Zest AI (US), Scienaptic AI (US), Gradient AI (US), Kasisto (US), Trumid (US), DataVisor (US), Kavout (US), WealthBlock (US).
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