Today, regulators expect not only compliance but proactive prevention. Modern AML solutions combine real-time analytics, automation, and collaboration to help institutions identify illicit activities before they escalate into systemic risk.
What modern AML solutions do
Effective AML systems perform three critical functions: detection, investigation, and reporting. These functions rely on advanced technologies that turn vast amounts of transactional data into actionable intelligence.
Typical AML solutions include:
- Transaction monitoring systems (TMS): detect suspicious activity across payment channels.
- Customer due diligence (CDD) tools: assess customer risk during onboarding and throughout the relationship.
- Screening engines: check against sanctions, watchlists, and politically exposed person (PEP) databases.
- Case management and reporting systems: streamline investigations and SAR (Suspicious Activity Report) submissions to FIUs.
Each layer builds a defensive barrier against criminal infiltration, but their effectiveness depends on how well they integrate and interpret data.
The growing pressure of global regulation
According to the
Financial Action Task Force (FATF), money laundering accounts for an estimated 2–5% of global GDP annually — up to USD 2 trillion. Regulators across the EU, UK, and US are tightening requirements to address this.
The
EU’s Sixth Anti-Money Laundering Directive (AMLD6) now mandates stricter corporate accountability, enhanced customer verification, and increased information sharing among financial institutions.
Similarly, the
Financial Crimes Enforcement Network (FinCEN) in the United States is expanding the scope of its beneficial ownership reporting requirements under the
Corporate Transparency Act.The message from regulators is consistent: compliance is not static. Institutions must demonstrate ongoing, data-led vigilance and the ability to adapt to new typologies of crime.
Core challenges financial institutions face
Despite heavy investment, most institutions struggle to achieve both compliance efficiency and accuracy.
- High false positives: Legacy systems flag too many legitimate transactions, creating investigation backlogs.
- Data silos: Fragmented customer information limits visibility across departments or jurisdictions.
- Evolving typologies: Criminals constantly innovate — from trade-based laundering to crypto mixers.
- Operational costs: The global AML compliance burden exceeds USD 200 billion annually, according to LexisNexis Risk Solutions.
These inefficiencies create risk blind spots and expose institutions to enforcement penalties and reputational damage.
Technology at the center of AML innovation
Next-generation AML platforms use automation and machine learning to transform how data is analyzed.
- AI-driven detection: Models learn from historical behavior to identify new suspicious patterns.
- Behavioral analytics: Detects anomalies across customer networks and transaction types.
- Federated learning and privacy-preserving computation: Enables multiple institutions to train risk models collaboratively without sharing raw data.
- Explainable AI: Allows regulators and auditors to verify why a transaction was flagged, improving trust in automated systems.
These capabilities help compliance teams focus on true risk rather than noise.
How a new approach to financial crime could stop
fraud in its tracks
The proof-of-concept 2019 changed the frame: instead of judging each payment on its own, it followed how money travels across accounts and institutions. That shift revealed patterns single-transaction systems miss.
The scale is staggering. Financial institutions together spend an estimated $200 billion a year on compliance and AML, and yet fraud losses remain stubbornly high-costing banks and customers tens of billions annually.
What's inside?
-
Seeing the whole network
- A shared defense with measurable impact
and more...
Integration with CTF and fraud detection systems
Anti money laundering solutions work best when integrated with Counter-Terrorist Financing (CTF) and fraud detection frameworks. Criminal and terrorist networks often overlap, using similar methods to move funds covertly.
- Integrating AML, CTF, and fraud systems creates a unified intelligence layer that:
- Shares risk scores across multiple monitoring systems.
- Identifies coordinated activity between unrelated entities.
- Improves regulatory reporting accuracy.
- Enhances real-time detection across digital payment ecosystems.
This convergence is now supported by EU legislation under DORA, which requires resilience and interoperability across financial compliance technologies.
“The next generation of AML solutions is not about more rules — it’s about better data collaboration. Institutions that can analyze risk together, without exposing customer information, will set the new standard for compliance.”
– William Morris, Lead Enterprise Account Executive - UK
This reflects the direction regulators and industry leaders are taking: shared intelligence, powered by privacy-safe analytics.
AML and data protection: an unavoidable balance
AML systems handle highly sensitive customer information — identity data, transaction history, and behavioral patterns. While compliance requires data sharing, laws such as GDPR impose strict controls on how that data can be processed.
The challenge is to exchange intelligence without breaching confidentiality or exposing personally identifiable information. Traditional data-sharing models can’t solve this. Privacy-preserving computation technologies are now becoming essential for secure, compliant collaboration.
Partisia’s perspective
True AML effectiveness depends on secure data collaboration between banks, regulators, and technology partners. Partisia’s privacy-preserving data collaboration platform makes this possible using Multi-Party Computation (MPC).
With MPC, institutions can analyze and compare financial transaction data jointly — identifying patterns, risk correlations, or common exposure — without revealing underlying customer information. This means cross-bank AML collaboration can finally happen in a legally compliant, privacy-safe way.
By combining secure computation with advanced analytics, Partisia enables a new generation of AML solutions that are smarter, faster, and compliant by design — meeting the expectations of FATF, EBA, and DORA for transparency and operational resilience.