Banks, asset managers, and fintech providers are deploying AI-driven workflow automation at an accelerating pace across trade lifecycles, risk reporting, and private markets operations. Efficiency demands and stringent regulatory requirements-including the EU's Digital Operational Resilience Act (DORA) and the EU AI Act-are driving adoption. The shift marks a transition from isolated pilots to enterprise-wide compliance infrastructure as institutions contend with escalating enforcement costs and increasingly complex data governance obligations.
Background
The regulatory backdrop has sharpened the urgency for automation. DORA became fully enforceable on January 17, 2025, requiring strict ICT risk management, incident reporting, digital resilience testing, and third-party risk oversight for all regulated financial entities across the European Union. Simultaneously, the EU AI Act's first phase of obligations came into effect in February 2025, with phased requirements for general-purpose AI transparency. Compliance teams are responding with model inventories, provenance controls, and AI governance workflows tailored to the Act's risk tiers, according to Future Market Insights.
The financial cost of non-compliance is also accelerating adoption. Banks in the United States and Canada now spend USD 61 billion annually on compliance, with 99% reporting rising costs, according to Mordor Intelligence. Regulators levied USD 263 million in AML penalties in the first half of 2024 alone, a 31% surge year-on-year, with Asia-Pacific fines jumping 266%. These pressures are pushing institutions from retroactive remediation toward predictive, always-on compliance models.
The regtech market reflects the scale of this response. The global regtech market was valued at approximately USD 24.34 billion in 2025 and is projected to reach USD 112.10 billion by 2033, growing at a CAGR of 21.1%, according to Grand View Research.
Details
AI adoption across trade and compliance workflows is advancing at the largest institutions. Approximately 45% of banks were deploying AI or machine learning in live client trade finance transactions as of 2025, up from around one-third the previous year, according to the Investment Banking Council. According to IOSCO, AI applications now span the full trading lifecycle-including pre-trade analysis, trade routing optimization, pricing, execution, and post-trade analysis.
Major institutions are embedding AI natively rather than as a bolt-on tool. According to BizTech Magazine, financial institutions are moving to embed AI "directly into the fabric of their operations," making it native to surveillance systems and KYC processes. Deutsche Bank, through its Google Cloud partnership, is developing internal AI assistants to streamline document analysis and automate regulatory reporting. JPMorgan Chase reports that over 200,000 employees are using its LLM Suite daily, with AML monitoring, contract review, and KYC checks as core use cases.
Data governance and auditability have emerged as critical technical prerequisites for regulatory acceptance. According to McKinsey's 2025 regtech analysis, a US-based bank's legacy system met just 75% of compliance requirements before adopting an automated RegTech solution, which raised compliance to above 95%. Regulators require not just demonstrated compliance outcomes but documented reasoning: according to BizTech Magazine, "regulators don't just want to know that a model works, they also want to understand why it reached a particular conclusion." AI-driven decisions must maintain traceable decision paths, version histories, and routing logs to satisfy auditors, according to Automation Anywhere.
Despite measurable efficiency gains-Intelligent Document Processing is capable of reducing manual document handling times by up to 72%, according to Fenergo-significant barriers to scale remain. Only 27% of financial institutions have fully integrated AI governance frameworks, according to the Financial Stability Board, leaving most compliance teams exposed to regulatory challenges. Interoperability challenges affect 40% of RegTech users, who cite the need for more seamless integrations across legacy systems and modern platforms, according to CoinLaw. Legacy system integration causes delays in RegTech adoption for over 30% of companies. The talent gap compounds these issues: the shortage of skilled professionals to manage and deploy RegTech solutions is expected to create a talent gap of approximately 15% by 2025.
Jurisdictional fragmentation further complicates scaling. Multinational firms face an average of 234 regulatory events per day in 2025, according to Mordor Intelligence, with divergent rules across MiCA, US frameworks, GDPR, and MiFID II requiring parallel compliance workflows in multiple regions.
Outlook
The industry is moving toward Digital Regulatory Reporting (DRR) architectures built on standardized models such as the Common Domain Model (CDM). Industry participants expect these architectures to reduce fragmentation and enable proactive compliance assurance rather than reactive remediation, according to discussions at the 2026 RegTech Conference. DORA enforcement is projected to generate USD 3-4 billion in incremental RegTech spending across EU-regulated institutions between 2025 and 2028, according to Future Market Insights. Institutions that cannot demonstrate explainability, data lineage, and audit-ready evidence trails face growing supervisory scrutiny-regulators have signaled they will move beyond policy audits toward log-level and dashboard-level inspection of AI systems in production.
