Explainable AI in Banking Market Report 2026

The explainable artificial intelligence (AI) in banking market size has grown exponentially in recent years. It will grow from $1.3 billion in 2025 to $1.61 billion in 2026 at a compound annual growth rate (CAGR) of 23.8%. The growth in the historic period can be attributed to rise of ai adoption in banking, increasing regulatory scrutiny on ai models, need for transparency in credit and risk decisions, early implementation of ai governance frameworks, demand for fraud detection solutions.

The explainable artificial intelligence (AI) in banking market size is expected to see exponential growth in the next few years. It will grow to $3.8 billion in 2030 at a compound annual growth rate (CAGR) of 24%. The growth in the forecast period can be attributed to growing requirement for explainable ai in compliance, expansion of ai-driven risk and credit solutions, increased integration of ai with banking analytics platforms, adoption of cloud-based explainability tools, rising demand for model interpretability and audit dashboards. Major trends in the forecast period include explainable risk and credit decision analysis, ai model validation and testing, integration with core banking systems, monitoring and reporting of ai decisions, bias detection and fairness assessment.

The increasing incidence and sophistication of fraud and financial crime are expected to support the growth of explainable artificial intelligence (AI) in the banking market going forward. The rise in fraud and financial crime is largely attributed to the rapid adoption of digital banking and online payment channels, which broaden the attack surface and create more opportunities for criminals to exploit system vulnerabilities at scale. The growing incidence and sophistication of fraud and financial crime make explainable artificial intelligence in banking essential, as banks must not only accurately identify complex fraudulent patterns but also transparently explain and justify automated risk decisions to regulators, auditors, and customers to maintain trust and ensure regulatory compliance. For example, in November 2025, according to the Federal Reserve Bank of Kansas City, a US-based central banking system, fraud-related losses in the United States totaled $12.5 billion in 2024, representing a significant 25% increase compared to 2023. Therefore, the increasing incidence and sophistication of fraud and financial crime are contributing to the growth of explainable artificial intelligence (AI) in the banking market.

Leading companies in the explainable artificial intelligence in the banking market are developing transparent transaction analysis solutions to strengthen regulatory trust and deliver more personalized banking services. A transparent transaction solution is an AI-powered system that clearly illustrates how transactions are interpreted, categorized, and analyzed from raw data, enabling banks to trace and justify every AI-driven decision for compliance and accountability. For example, in September 2023, Temenos, a Switzerland-based banking software provider, launched its Secure Generative AI Transaction Classification Solution. The platform delivers explainable classification of customer transactions from free-text narratives across multiple languages while supporting traceable and auditable risk and credit evaluations. It embeds explainability, scenario-based analysis, and audit capabilities into core banking processes, helping financial institutions validate AI insights to regulators, customers, and internal teams while promoting responsible AI adoption.

In April 2024, Aurionpro Solutions Limited, an India-based fintech and enterprise software company, acquired Arya.ai for approximately $16.5 million. Through this acquisition, Aurionpro strengthened its capabilities in transparent and explainable artificial intelligence by incorporating Arya.ai’s governance-ready and auditable AI models into its financial technology portfolio, improving regulatory compliance, decision clarity, and customer confidence in banking operations. Arya.ai is an India-based artificial intelligence platform focused on delivering explainable AI solutions for the banking sector.

Major companies operating in the explainable artificial intelligence (ai) in banking market are Alphabet Inc., Microsoft Corporation, Accenture plc, International Business Machines Corporation, Oracle Corporation, SAP SE, Cognizant Technology Solutions Corporation, Moodys Analytics Inc., SAS Institute Incorporated, Teradata Corporation, Fair Isaac Corporation, Tredence Inc., AlphaSense Inc., C3.ai Inc., H2O.ai Inc., Zest Artificial Intelligence Inc., Squirro AG, aiXplain Inc., Seldon Technologies Limited, Symphony Ayasdi AI Inc., MindBridge Ai Inc., and Arthur AI Inc.

Tariffs have influenced the explainable AI in banking market by increasing costs for imported servers, data processing units, and software tools critical for model interpretability and governance. The impact is significant on hardware-dependent and large enterprise segments, particularly in regions such as Europe and Asia-Pacific with reliance on foreign technology providers. Positive impacts include accelerated adoption of local hardware and software solutions and greater investment in domestic AI infrastructure, encouraging innovation and self-reliance in banking AI systems.

Explainable artificial intelligence (AI) in Banking refers to AI systems designed to make their decisions, predictions, and recommendations transparent and understandable to humans, including bankers, regulators, and customers. It enables clear insight into how models assess credit risk, detect fraud, or approve loans. It helps to ensure regulatory compliance, build trust, and support accountable decision-making.

The primary components of explainable artificial intelligence (AI) in banking include software, services, and hardware. Software refers to solutions that deliver transparency and interpretability into artificial intelligence models used within banking, allowing institutions to understand model outcomes, build trust, and meet regulatory requirements while enabling data-driven decision-making. These solutions can be deployed through on-premises or cloud-based modes. Adoption extends across organizations of varying sizes, including small and medium enterprises and large enterprises. The major applications include risk management, fraud detection, customer service, compliance, credit scoring, and other applications, and they are utilized by multiple end users such as banks and financial institutions, fintech companies, payment service providers, and insurance and investment firms.

The explainable artificial intelligence (AI) in banking market consists of revenues earned by entities by providing services such as explainable risk and credit decision analysis, AI model validation and testing, integration of explainability tools with core banking and analytics systems, and monitoring and reporting of AI decision outcomes. The market value includes the value of related goods sold by the service provider or included within the service offering. The explainable artificial intelligence (AI) in banking market includes sales of model interpretability and visualization tools, bias detection and fairness assessment products, AI governance and compliance management solutions, model monitoring and audit dashboards, risk and credit decision explanation modules, and data lineage and documentation tools. 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.

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

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