How to calculate the total cost of compliance for AML?

The 4 key factors in managing TCO for AML

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Regulators around the world are expanding anti money-laundering (AML) and counter terrorist financing (CTF) compliance coverage to include a range of sectors, such as manufacturing, corporates, exporters, property firms and more. Fines are issued for AML and CTF failures, but the weight of the total cost of ownership (TCO) is primarily felt by banks who have invested heavily over the years in systems and teams. In the UK, approximately 900 financial institutions bear the burden of sanctions controls, with much of this burden borne by traditional organisations such as banks.

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Countries with the highest AML compliance costs

This year’s Napier AI / AML Index found a few factors that influence high TCO for financial institutions by region.

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1. Proximity to sanctioned nations

As a close geographical neighbour to Russia but with European Union standards to uphold, Poland continues to report extremely high cost of compliance. Its efforts in AML effectiveness are being outshone by low efficiency right now, but should improve over time.

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2. Financial services hubs

‍Founding members of the new Anti Money-Laundering Authority (AMLA) in Europe, France and Germany both continue to spend whatever it takes to secure their market and lead by example. As major financial services economies, they will likely continue to experience the challenges of high attempted money-laundering and the need for increased defences, but with the right AI applications they could reduce TCO.

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Countries leading the adoption of AI in AML regulation

The Napier AI / AML Index also identified jurisdictions where regulatory provision for artificial intelligence (AI) in AML was felt to be most effective by the regulated entities operating there. The AI/AML Regulation Score within the Index seeks to predict which markets might top the rankings for both efficiency and effectiveness of AML efforts, driving down TCO through the safe, controlled, and accurate implementation of automation in AML transaction monitoring and sanctions screening.

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3. AI regulatory leadership

Singapore, United Kingdom, and Italy continue to be top performers in AI/AML Regulation scores, showing consistency in the national approach to AI regulation and the potential for initiatives like sandboxes and national registries to begin driving significant benefit TCO and AML effectiveness soon. France, Germany and Poland also all ranked well here, and showed year-on-year improvements, boding well for future reductions in TCO.

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The balance of cost vs compliance for AML

Where historically it has been viewed as just a cost centre, robust anti financial crime is quickly becoming a competitive advantage for financial institutions. But it is not as simple as just investing in AI tools.

To turn compliance from a cost-centre to key capability, it requires balancing innovation with the right governance and oversight.

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Within the Napier AI / AML Index, the ‘ideal’ ratio of compliance spend to money laundered is assumed to fall between 1.36% and 3.36%, based on a weighted average of the compliance spending for the higher-performing markets in terms of money laundering losses and effectiveness of AML.  

This range has been updated from 3-6% from last year, to reflect the improving performance of the top rated countries in this year’s Index. The art of the possible has been shown to be better than previously thought, and spending either within- or close to- this range provides good money laundering mitigation outcomes, while also maintaining operational efficiency of compliance departments. 

Read the Index to see if your country has a good ratio of compliance spend compared to money laundered.

Countries that sit in the ideal range include Canada, Spain and Switzerland. They exhibit a good balance of strong understanding of underlying risk, robust regulation and enforcement, and effective adoption of AI.

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4. Ideal AI & AML compliance spend

‍Countries that currently sit within the ideal range include Canada, Spain, UAE and Switzerland. Conversely, some of the countries in this range have worse overall Index scores than others outside of it, but the ideal definition is a good indication of which nations might have an effective AML regime that doesn’t place undue burden onto financial institutions.

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Spain is a good example: it appears to balancing efficiency and effectiveness, and sits amongst the top performers in this year’s Index thanks to top ranking in TCO score (even though its growth rate of cost of compliance was among the highest), and in the top half of the Index for both positive AML Attitude and AI/AML Regulation. Spain’s investment in AML appears to stay proportional to the value of money laundering losses, representing a pragmatic approach.

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Read Spain’s country page in the Napier AI / AML Index to learn more

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The future cost of AML compliance

Markets may be identified as overspenders currently, but also be known to have mature AML regimes (such as France, Germany, Singapore). These geographies represent the greatest opportunity to drive efficiencies through AI, as they seek to automate effective regimes. TCO should begin to fall in these markets as they see a return on their investments and the benefit of institutional knowledge and well tuned systems.  

Those that are marked as underspenders (e.g. India, Russia, Belarus, and Ukraine), need to invest in foundational national AML-regimes and embedding best practice in terms of a risk-based approach, before they will see true benefits from AI. Implementing AI for AML ahead of the maturity curve risks embedding poor screening and monitoring approaches and exacerbating inaccuracy and operational inefficiencies. These markets should expect to be overspenders before they achieve the ideal cost to compliance ratio.  

Read the Napier AI / AML Index 2025 – 2026 for more insights