Artificial Intelligence (AI) in Trade Finance Market Report 2024

This Artificial Intelligence (AI) In Trade Finance market 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 artificial intelligence (AI) in trade finance market size has grown rapidly in recent years. It will grow from $9.67 billion in 2023 to $11.46 billion in 2024 at a compound annual growth rate (CAGR) of 18.5%. The growth during the historic period can be attributed to the increasing need for improved risk management, a higher demand for process automation, a shift towards digitalization, growing complexity in global trade, a greater emphasis on regulatory compliance, and a rising threat of fraud in financial transactions.

The artificial intelligence (AI) in trade finance market size is expected to see rapid growth in the next few years. It will grow to $22.72 billion in 2028 at a compound annual growth rate (CAGR) of 18.7%. The growth during the forecast period can be attributed to the rising demand for automation, enhanced risk management capabilities, increased adoption of digital platforms, a growing focus on regulatory compliance, heightened need for fraud detection, and greater investment in high-performance computing infrastructure. Major trends expected include the integration of AI with blockchain technology, the adoption of AI-driven predictive analytics, expansion of AI-powered automation, enhanced utilization of machine learning models, and the development of AI-enhanced customer service platforms.

The growth of artificial intelligence (AI) in trade finance is projected to accelerate due to increasing volumes of international trade. International trade involves the exchange of goods and services across national borders, and its expansion is driven by reduced trade barriers and growing economic interdependence among countries. AI tools in trade finance streamline tasks such as document generation, processing, and verification, which reduces manual errors and speeds up transaction times. For example, the Bureau of Economic Analysis reported in February 2023 that the U.S. goods and services deficit reached $948.1 billion in 2022, up by $103 billion from the $845 billion deficit in 2021. Exports increased to $3.0 trillion, a $453.1 billion rise from 2021, while imports also grew to $3.95 trillion, an increase of $556.1 billion from 2021. Consequently, the expanding international trade volume is driving the growth of AI in trade finance.

Leading companies in the AI trade finance market are developing automated platforms to enhance operational efficiency and shorten processing times. These digital solutions leverage advanced technologies to automate and simplify trade finance tasks, improving transaction handling, documentation, and compliance. For instance, HSBC Holdings plc introduced HSBC Trade Solutions (HTS) in October 2022. This sophisticated digital platform enables clients to manage all trade finance activities online, enhancing speed, security, and efficiency. The HTS platform features a modular, API-based design, supports HSBC’s trade services, and offers a user-friendly, self-service interface with automation and advanced risk management features such as anti-money laundering and fraud controls.

In December 2022, Tradesun Inc., a U.S.-based IT and services firm, acquired Coriolis Technologies Pvt. Ltd. for an undisclosed amount. This acquisition strengthens Tradesun's network by integrating Coriolis' ESG platform, which provides tools for assessing and verifying sustainability in supply chains. This move supports TradeSun's commitment to promoting transparent and eco-friendly trade practices. Coriolis Technologies Pvt. Ltd., based in India, specializes in analytics for trade and trade finance, utilizing AI to extract insights from large data sets.

Major companies operating in the artificial intelligence (AI) in trade finance market are HSBC Holdings plc, Accenture plc, International Business Machines Corporation, BNP Paribas SA, Oracle Corporation, SAP SE, Infosys Limited, Genpact LLC, Asseco Poland SA, Finastra Group Holdings Limited, Pegasystems Inc., Temenos AG, Appian Corporation, Tungsten Automation Corporation, ABBYY Solutions Ltd., Tradeshift Holdings Inc., Nucleus Software Exports Limited, Demica, Rossum, Cleareye.ai, Tradeteq Limited, Previse Ltd, Newgen Software Technologies Limited, Traydstream, TradeSun Inc.

North America was the largest region in the artificial intelligence (AI) in trade finance market in 2023. The regions covered in the artificial intelligence (AI) in trade finance market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the artificial intelligence (AI) in trade finance market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Artificial Intelligence (AI) in trade finance involves using advanced algorithms and machine learning to enhance and automate the financial processes that support international trade. AI applications in trade finance include fraud detection, document processing automation, risk assessment, trend prediction, compliance simplification, supply chain optimization, customer service improvement, routine task automation, and market insight provision.

The primary components in the AI in trade finance market are software and services. AI software refers to programs and applications designed to use artificial intelligence to streamline and enhance various trade finance functions. Technologies employed include machine learning, natural language processing (NLP), robotic process automation (RPA), predictive analytics, and blockchain. Deployment options are available in both cloud and on-premises settings, covering areas such as trade documentation and validation, fraud detection and risk management, supply chain finance, trade credit insurance, trade compliance and monitoring, and others. The end-users of these solutions include banks, financial institutions, insurance companies, and other related entities.

The artificial intelligence (AI) in trade finance market research report is one of a series of new reports that provides artificial intelligence (AI) in trade finance market statistics, including the artificial intelligence (AI) in trade finance industry global market size, regional shares, competitors with artificial intelligence (AI) in trade finance market share, detailed artificial intelligence (AI) in trade finance market segments, market trends, and opportunities, and any further data you may need to thrive in the artificial intelligence (AI) in trade finance industry. These artificial intelligence (AI) in trade finance market research reports deliver a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The artificial intelligence (AI) in trade finance market includes revenues earned by providing services such as automated document processing, risk assessment and management, fraud detection and prevention, and supply chain optimization. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI) in trade finance market also includes sales of hardware security modules (HSMs) and encryption devices. 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.

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