AI in Fintech Market Size

Statistics for the 2023 & 2024 AI in Fintech market size, created by Mordor Intelligence™ Industry Reports. AI in Fintech size report includes a market forecast to 2029 and historical overview. Get a sample of this industry size analysis as a free report PDF download.

Market Size of AI in Fintech Industry

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AI in Fintech Market Summary
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Study Period 2019 - 2029
Market Size (2024) USD 44.08 Billion
Market Size (2029) USD 50.87 Billion
CAGR (2024 - 2029) 2.91 %
Fastest Growing Market Asia-Pacific
Largest Market North America

Major Players

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*Disclaimer: Major Players sorted in no particular order

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AI in Fintech Market Analysis

The AI in Fintech Market size is estimated at USD 44.08 billion in 2024, and is expected to reach USD 50.87 billion by 2029, growing at a CAGR of 2.91% during the forecast period (2024-2029).

The COVID-19 pandemic outbreak has been accelerating the change in the way how people interact with financial services. Payment- and wealth-focused fintech companies have focused on bolstering their existing infrastructure by investing in new resources or expanding capacity to withstand the stress to their systems from higher transaction volumes. Though it seemed challenging for fintech companies, such actions have provided a significant need for AI solutions as these companies depend on transaction volumes for revenue. Such factors are expected to spearhead the demand for AI solutions in the fintech market.

  • Financial firms have been the early adopters of the mainframe computer and relational database. They eagerly waited for the next level of computational power. Artificial Intelligence (AI) improves results by applying methods derived from the aspects of human intelligence at a broader scale. The computational arms race for past years has revolutionized fintech companies. Technologies, such as machine learning, AI, neural networks, Big Data Analytics, evolutionary algorithms, and much more, have allowed computers to crunch huge, varied, diverse, and deep datasets than ever before.
  • Moreover, AI and machine learning have benefited banks and fintech as they can process vast amounts of information about customers. This data and information are then compared to obtain results about timely services/products that customers want, which has aided, essentially, in developing customer relations.
  • Additionally, machine learning is being adopted at unprecedented rates, specifically to create propensity models. Banks and insurance companies are introducing machine learning-based solutions for web and mobile applications. This has further enhanced the real-time target marketing by predicting the product propensity of the customers based on behavioral data in real-time.
  • Several market incumbents are establishing a niche by explicitly offering solutions, like AI Chatbots for banking. For instance, in June 2021, Talisma and Active.Ai has partnered to enable improved customer experience in BFSI using conversation AI enabled Chatbot.
  • Moreover, several credit card companies implement predictive analytics into their existing fraud detection workflows to reduce false positives. The studied market further gains traction with several players offering AI-based Anti-money Laundering (AML) and Fraud detection solutions for credit card companies and other financial institutions.
  • For instance, in June 2022, Lucinity, a developer of AI-driven anti-money laundering (AML) software has partnered with fraud management company SEON to include real time fraud prevention capabilities in AML compliance software. SEON's fraud prevention solution will be available through Lucinity's platform, providing customers with compliance risk services from transaction monitoring to real-time fraud detection and prevention.
  • Further, AI-ready infrastructure should be capable of efficient data management, have enough processing power, be agile, flexible, and scalable, and have the capacity to accommodate different volumes of data. Therefore, it would be more challenging for fintech small businesses to assemble the necessary hardware and software elements to support AI. Moreover, as the democratization of AI and deep learning applications expands, not only for tech giants but is now viable for small and medium-sized businesses. The demand for AI professionals to do the work has ballooned as well, and the scarcity of trained resources is the major challenge for AI in fintech.

AI in Fintech Market Size & Share Analysis - Growth Trends & Forecasts (2024 - 2029)