Smaller financial institutions face mounting pressure to meet anti-money laundering (AML) compliance standards as regulators increasingly target firms previously considered low-priority, according to analysis from compliance technology provider Consilient.

Community banks, neobanks, money services businesses and crypto platforms now face the same AML obligations as major institutions despite having fewer resources and less sophisticated technology systems, the company said in a recent analysis.

Smaller institutions face specific structural disadvantages that make AML compliance disproportionately difficult, according to the analysis. These include operating with tighter profit margins where AML compliance represents a growing cost rather than revenue-generating activity, unlike larger institutions that can spread compliance costs across broader portfolios.

Access to advanced AML technologies such as real-time risk scoring engines and AI-enhanced screening tools often remains beyond smaller institutions' budgets. This forces reliance on manual processes, outdated systems or lower-capability vendors, increasing operational risk and the likelihood of control breakdowns.

Resource constraints compound the problem as smaller firms must manage cybersecurity, liquidity, data privacy and regulatory reporting with limited headcount. While larger institutions operate specialised compliance teams, smaller entities often rely on staff handling multiple roles or outsourced services.

Recruiting experienced compliance professionals presents another challenge, with larger banks better positioned to attract seasoned AML officers. Smaller firms, particularly in regional areas, struggle to compete for talent, resulting in insufficient internal expertise for risk assessments and customer due diligence.

The analysis also identifies difficulties establishing compliance culture in smaller organisations where commercial pressures and growth targets can overshadow regulatory obligations.

Technology solutions target compliance gaps

Consilient claims its federated learning technology can help address compliance gaps by allowing institutions to collaborate on training advanced risk models without sharing sensitive data. The company asserts its AML models deliver "up to 4x greater detection effectiveness and a 75% improvement in efficiency" compared to traditional systems.

The technology allows smaller institutions to benefit from machine learning models trained across multiple organisations while keeping their data private, according to Consilient.

In Australia and New Zealand, similar challenges exist for smaller financial institutions subject to AUSTRAC and Reserve Bank of New Zealand AML requirements.

The compliance pressure is set to intensify significantly in Australia as AUSTRAC prepares to expand AML/CTF regulations to new sectors from March 2026. Real estate agents, property developers, dealers in precious metals, lawyers, conveyancers, accountants and trust service providers will come under regulation for the first time from July 2026.

Additional virtual asset services will be captured from March 2026. Many of these newly regulated entities are likely to be smaller businesses facing the same resource constraints identified in the Consilient analysis.

The compliance burden includes customer due diligence, transaction monitoring, and suspicious activity reporting - functions that larger institutions can spread across specialised teams but smaller firms must often handle with limited staff.