TLDR: A new report from McKinsey & Company highlights Agentic AI as a critical solution to the banking sector’s escalating financial crime challenges. Despite significant investments, financial institutions currently detect only a fraction of global financial crime. Agentic AI, an advanced form of artificial intelligence, promises to enhance efficiency, automate complex processes, and improve the effectiveness of anti-money laundering (AML) and know-your-customer (KYC) operations by enabling autonomous decision-making and intelligent workflow execution.
Financial institutions are grappling with an escalating tide of financial crime, pouring substantial resources into combating illicit activities with limited success. A recent article from McKinsey & Company, published on August 7, 2025, underscores this paradox, revealing that despite increasing investments by up to 10 percent annually in some advanced markets between 2015 and 2022, the financial industry detects only approximately 2 percent of global financial crime flows, according to Interpol. This inefficiency is largely attributed to fragmented data, unstandardized datasets, and operating models that necessitate extensive manual intervention, with banks often dedicating 10 to 15 percent of their full-time equivalents (FTEs) solely to Know Your Customer (KYC) and Anti-Money Laundering (AML) activities.
The McKinsey article, authored by Alexander Verhagen, Angela Luget, Olivia Conjeaud, and Vasiliki Stergiou, with contributions from Debanjan Banerjee, proposes Agentic AI as a transformative solution. This advanced evolution of analytical AI technology is designed to provide automation and enhance productivity across the entire client life cycle, serving as a potent ‘antidote to KYC/AML headwinds.’
Agentic AI distinguishes itself from previous AI iterations by its capacity for autonomous decision-making based on complex data inputs, often without continuous human oversight. It incorporates sophisticated ‘chain-of-thought’ reasoning, enabling it to break down intricate problems into logical steps and articulate the rationale behind its decisions. This capability allows Agentic Process Automation (APA) to execute complex business processes, significantly reducing the burden of manual tasks that currently consume considerable time for financial crime teams.
Industry reports corroborate the pressing need for such innovation. The Nasdaq + BCG Complexity Report indicates that global banks spend a staggering $250 billion on Risk & Compliance functions, yet many still contend with internal challenges like manual processes, siloed data, and legacy technology. Agentic AI’s ability to act as an intelligent agent, executing entire workflows from reviewing low-risk alerts to handling routine Enhanced Due Diligence (EDD) reviews, promises to revolutionize efficiency in financial crime investigations. By automating these tasks, analysts can redirect their focus to higher-risk, high-impact cases.
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Furthermore, Agentic AI’s goal-driven nature and ability to work across disparate systems make it an invaluable asset. It can learn from past tasks, utilize planning tools to determine optimal steps, and seamlessly integrate with various digital platforms. This not only reduces the risk of human error but also facilitates faster reactions to dynamic market changes. The Nasdaq Verafin’s Global Financial Crime Report projects a significant shift, with 70% of financial institutions expecting to increase their investment in AI and machine learning within the next two years, and the use of AI tools in anti-fraud programs anticipated to triple by 2026. This signals a clear industry recognition of Agentic AI’s potential to usher in a new era of efficiency and effectiveness in the ongoing battle against financial crime.
