What is anti-money laundering (AML) software?
AML software helps to prevent an organization from being used as a vehicle for criminals to access the financial system, so they can make their illicit funds appear to be from legitimate business dealings. This software supports an organization’s entire AML program and is typically made up of several components:
Model risk governance
Regulatory reporting
Payment screening
Customer screening
List of AML software & tools
What technology is used in an AML program?
AML programs use technology called transaction monitoring. This is the process of monitoring transactions that occur through institutions for suspicious patterns of activity that are indicative of money laundering or other financial crimes. These institutions typically include banks, casinos, insurers, and other money service organizations. Activities that are monitored include money transfers, customer withdrawals, and deposits made to personal and non-personal bank accounts.
The 10+ best AML software & tools
Let’s drill into the best AML software and tools and lay out the important details. Here, we will provide a comprehensive overview of the software and a list of capabilities.
Disclaimer: Everything you’ll read in this article was gathered from online research, including user reviews. Note that we have not manually tested every tool that we are referencing. This guide was last updated in January 2025. If any information is factually incorrect and needs to be updated, please get in touch here.
Quantexa
Unlike traditional systems, Quantexa’s AML software offers a holistic view of risk. It visualizes hidden connections and identifies hidden risks through additional context.
Threats are identified in batches and alerted based on the client monitoring thresholds. There are fewer alerts because risk is detected at a network level, rather than isolated red flags at a transactional level.
Context gaps, which in traditional systems lead to ineffective fincrime control, are filled by stitching data sets together across internal silos and are enriched with external data sets, helped by the investments financial institutions have made in third-party data. This allows organizations to identify and deal with high-risk cases and false positives quickly.
Quantexa uses innovative strategy to detect complex financial crime risks via typology-based scorecards, enabling a targeted approach to risk detection.
The Entity Lab provides full transparency via a UI into how entities are resolved and which enables users to adjust resolution of entities, when appropriate, for advanced investigations.
The system provides audit transparency via detailed tracking logs and the ability to snapshot an investigation. This enables auditors and regulators to review investigations from a specific point in time with the data available then, rather than an evolving dataset.
The software is available for industries such as banking, the public sector and beyond.
SAS
This end-to-end AML compliance solution monitors the whole customer lifecycle.
Unknown relationships are identified using a combination of scenarios and data.
It uses automated monitoring powered by AI and machine learning, but also explains why the models made the decisions it did, so AML teams can understand, learn from it, and explain it to other stakeholders and regulatory figures.
The system administration can be low code or no code depending on what suits the organization, while a drag-and-drop interface makes it easy to use.
It includes KYC capabilities and integrated CDD/EDD to monitor client risk ratings dynamically.
The system is built on cloud-native architecture.
Nice Actimize
This entity-centric platform combines advanced technology with user-friendly features, and provides full compliance coverage and auditability.
It uses AI and machine learning to adapt and evolve to detect anomalies and potential risks in real time.
Customer information is consolidated into one view. Organizations can use the customizable dashboards and reports.
The software optimizes transaction monitoring and suspicious activity monitoring.
Symphony AI
This software conducts CDD while enhancing both KYC and AML efforts, with everything (including sanctions screening and payment fraud management) integrated into one central hub.
It’s scalable, adaptable, and integrates with existing systems, so you can adjust according to the needs of your organization.
The software connects, analyzes and summarizes data from various sources, reducing false positives and comparing customer behavior against predefined risk indicators.
Available for organizations in banking, insurance, financial markets, private banking and wealth management.
Oracle
Oracle’s AML software is powered by AI and machine learning technologies.
Using graph and advanced analytics, it supports transaction monitoring as well as including pre-configured scenarios to detect unusual behavior and money movement.
Feedzai
Built into a single platform, Feedzai's four key offerings cover the essentials of AML:
KYC/CDD
Customer screening with automated watchlist updates
Payment screening with alerts
AMl transaction monitoring
Alerts are prioritized based on your organization's risk policies.
It shows visual links between entities, accounts, and companies.
Includes in-depth analytics and profiling tools.
ComplyAdvantage
ComplyAdvantage’s transaction monitoring system is designed to enhance AML compliance. Powered by AI, it continuously learns from data to reduce false positives and accurately prioritize alerts based on potential risk levels.
Users can add notes and attachments to alerts and cases, supporting the investigation process.
The no-code rules builder allows organizations to tailor the monitoring scenarios to their needs, including the ability to segment customers and customize thresholds.
The dashboard provides real-time analytics and insights.
Organizations can test and adapt rules before deployment.
SEON
SEON enables continuous monitoring, with organizations able to customize the automated monitoring rules to fit their needs.
Organizations can screen against PEPs (politically exposed persons), sanctions, relatives, close associates, crime lists and financial watchlists from one centralized platform. All searches and logs are centralized too.
The software uses intelligence from government lists and machine learning to reduce false positives.
Cross-checked information adds context, helping organizations to decide whether an alert should be resolved and closed or escalated.
ThetaRay
ThetaRay’s AML software uses AI technology to analyze the entire transaction process in real time, detecting and flagging any suspicious behavior.
The AI learns from datasets to become more effective over time, and identifies previously unknown patterns to detect new risks.
The software ensures compliance with regulatory requirements and offers fast implementation.
Hawk.AI
The Hawk tool includes AML transaction monitoring, payment screening and KYC in one place.
The AML transaction monitoring software has predefined rules but also uses AI to identify suspicious activity traditional rules don’t pick up on, increasing the efficiency of alerts and reducing false positives. Users can also create custom rules.
The interface doesn’t require any coding, making it more accessible to analysts across an organization.
Featurespace
Featurespace’s system looks at fraud and anti-money laundering (FrAML) in one place.
The idea is to bring fraud and financial crime teams together to share intelligence and bolster their investigations.
The system investigates the alert and the customer. It uses machine learning models, with automation deployed when necessary.
It also includes case management tools, reporting, and anomaly detection.
Intelligence-led Investigations
Comparison of AML software providers at a glance
| AML software | Free trial or demo | Key features |
|---|---|---|
| Quantexa | Can request a demo |
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| SAS | 14-day free trial |
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| Nice Actimize | Can request a demo |
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| Symphony AI | Not mentioned, but you can fill in a contact form |
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| Oracle | Can request a demo |
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| Feedzai | Can request a demo |
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| ComplyAdvantage | Can request a demo |
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| SEON | Not mentioned, but you can schedule a meeting with one of their experts |
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| ThetaRay | Can request a demo |
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| Hawk.AI | Can request a demo |
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| Featurespace | Can request a demo |
|
Features of AML software
When evaluating AML software, organizations should focus on features that comply with both AML regulations, as well as industry-specific standards.
Here we breakdown the key components of AML software:
Entity resolution
A critical component of AML software, entity resolution is designed to enhance the detection and prevention of illicit financial activities. It involves the process of identifying and linking multiple records that refer to the same entity — such as a customer or transaction — across various internal and external datasets. It also helps in accurately identifying suspicious activities by revealing hidden connections. This technology not only safeguards the bank and ensures robust adherence to regulatory requirements.
Note: Entity resolution isn’t used by all AML monitoring platforms. It is used by Quantexa instead of a purely rules-based system.
Entity-level alerting
Entity-level alerting plays a pivotal role in enhancing the efficiency and effectiveness of monitoring financial activities. Unlike traditional systems that focus on individual accounts or isolated transactions, entity-level alerting consolidates alerts against a single entity, which may be across accounts, products, lines of business, or even non-bank counterparts. This approach allows organizations to view a comprehensive snapshot of a customer's behavior across multiple accounts and transactions, providing deeper insights into potential suspicious activities. By rolling up alerts at the entity level, you can better identify patterns indicative of money laundering, reduce false positives, and streamline their compliance processes.
Network generation
This refers to the process of creating and visualizing connections between entities, such as individuals, accounts, or transactions, to detect suspicious patterns and illicit activities. By leveraging advanced algorithms and data analytics, AML software can map out these relationships, providing a comprehensive view of potential risks. This capability not only enhances a business's ability to identify and prevent money laundering activities but also streamlines compliance with regulatory requirements.
Unlike static network builds, which rely on predefined, unchanging connections, dynamic network generation continuously updates and adapts as new data emerges, offering a more flexible and comprehensive approach to financial crime detection.
Note: Network generation isn’t used by all AML monitoring platforms. It is used by Quantexa instead of a purely rules-based system.
AI/ML
A rules/scores library is a crucial component of AML software that enhances the effectiveness of detecting suspicious activities.
A rules library comprises a collection of pre-defined red flags and detection scenarios that help identify potential money laundering behaviors. These rules are based on regulatory guidelines and industry best practices, allowing businesses to automatically flag transactions or activities that deviate from the norm.
Scoring assesses transaction and associated customer, counterpart and network risk to identify certain risky behaviors, effectively prioritizing alerts for further investigation.
Together, these libraries form the backbone of AML detection models.
Prioritization/Hibernation
Prioritization and hibernation are pivotal features that enable auto-dispositioning of alerts based on known customer behavior or clear anomalous activity.
Prioritization refers to the intelligent ranking of alerts using machine learning algorithms, which evaluate various risk factors and historical data to assign prioritization levels of alerts. This process ensures that compliance teams focus on the most critical alerts first, enhancing efficiency and reducing the likelihood of missing significant red flags.
Re-alerting
Re-alerting enhances an organization’s ability to monitor suspicious financial activities effectively. It’s designed to suppress alerts of previously identified behaviors, thus reducing unnecessary noise and allowing you to focus on genuinely new and potentially fraudulent activity.
Reporting
Effective AML software offers comprehensive reporting capabilities that allow organizations to monitor and analyze KPIs and metrics through intuitive dashboards. These dashboards provide real-time insights into FinCrime process activities, enabling businesses to quickly identify suspicious behavior and emerging threats and typologies. By leveraging these reporting features, businesses can stay informed, make data-driven decisions, and ensure they remain compliant with regulatory requirements, staying ahead of the ever-changing threat environment.
Configurability/Dynamic UI
Configurability ensures that the software can be tailored to align with specific business processes, allowing organizations to adapt their anti-money laundering protocols without extensive overhauls. Meanwhile, a dynamic UI enhances user experience by providing an intuitive and responsive interface that adjusts to changes in workflow seamlessly.
Case management
Case management acts as a centralized repository for documentation and workflow processes. AML software with robust case management functionality enables organizations to efficiently organize, track, and resolve potential financial crimes. By integrating case management, businesses can streamline their investigative workflows, ensuring that every suspicious activity alert is systematically evaluated and documented.
Regulatory reporting/Validation
Regulatory reporting is designed to help organizations automate the process of submitting Suspicious Activity Reports and other required regulatory reports, based on jurisdictional requirements. This reduces the risk of human error and ensures timely compliance. The auto or batch filing capability of AML software allows businesses to efficiently manage and submit large volumes of regulatory reports simultaneously, saving both time and resources.
Tuning/champion-challenger
Tuning and champion-challenger strategies play pivotal roles in optimizing the effectiveness of AML efforts.
Tuning involves adjusting the parameters and thresholds within AML software to enhance its ability to accurately detect suspicious activities while minimizing false positives. Advanced analytics and machine learning techniques enable statistically driven tuning, based on behavioral aspects and prior customer activities, reducing the likelihood of overlooking critical alerts.
The champion-challenger approach allows organizations to test different rules and score configurations simultaneously, identifying which set performs best under real-world conditions. This method provides a dynamic framework for continual improvement, as you can directly compare the outcomes of existing (champion) and proposed (challenger) settings.
What should you look for in an AML software provider?
AML solutions should enable you to effectively detect known and emerging financial crime threats.
AML solutions that you choose should provide your bank with the means to know who a customer is, what is expected of the customer, and how to effectively monitor the anticipated behavior, while alerting on activity that is considered to be consistent with criminal activity, or outside of normal behavior. In doing so, banks can help protect innocent people from falling victim to scams or being taken advantage of by criminal rings (such as those involved with mules or trafficking).
Additionally, having a strong AML program built on innovative solutions helps to safeguard the overall health of the global financial system and stop abuse.
AML solutions for banks should enable them to make more informed, self-sufficient and confident decisions about onboarding, offboarding and ongoing monitoring.
Shifting to an automated AML end-to-end solution provides:
The ability to transform a risk policy into a digital AML workflow
Access to the data needed for customer due diligence
Dynamic risk profiling (i.e. creating a picture of risk associated with customers)
Collaboration and communication methods, both for cross-team work and work with customers
Analytics and reporting tools to gauge efficiency and track audit history
What are the benefits of AML software?
Improve risk coverage
Advance outcomes and human impacts through a complete understanding of complex criminal networks.
Accurately detect
Drive proactive and accurate detection of targets and natural persons risk by combining flags across cash indicators, geographical data and absence of typical account activity.
Identity complex typologies
Combine indicators, including payment flows, references, cash activity and specific merchant types.
Pinpoint real risk
Focus detection on real risk through a multi-scorecard approach and utilize a proven library of successful model features (including mitigating and escalating factors).
Reduce false positives
Alert when multiple personas are interacting.
Uplift efficiencies
Improve investigator efficiency and effectiveness through automation.
Make trusted decisions
Provide investigators with clear context to facilitate confident decisions.
Transform approach
Move away from technical compliance toward more risk-led tactics.
Maximize operations
Employ a single platform for multiple use cases organization wide.
How does an AML system work?
Traditionally, an AML system focuses on transactional data and looks for outliers in activity according to the existing rules library. This identifies activities that appear to be risky, but not specific criminal activity. The enrichment of third-party data takes place after an alert is made.
Modern AML systems take a different approach. Consolidated profiles of entities are used to create networks, with the goal of looking for internal and external risks associated with the customer. This gives organizations a better picture of their behavior, further enhanced by enriching the stitched-together customer profile with external data to understand more context around both your customer and their counterparties’ footprint.
AML software FAQs
Who needs AML software?
AML software is essential for organizations in:
Banking
Broker-dealing
Registered investment advising
Accounting
Credit providing
Insurance
Cryptocurrency
Casinos
Gaming
Art dealing
Real estate
Law
Many of these, such as insurance, cryptocurrency, casinos, gaming and art dealing, are completely geography dependent.
Financial institutions must follow strict laws and regulations, but high-risk industries outside of finance will often be required to follow regulations as well. Specific regulations vary depending on where the organization operates.
Why do financial institutions need AML software?
In today's rapidly evolving financial landscape, banks face the critical challenge of preventing money laundering and related illicit activities. This is where AML software becomes an indispensable tool. By employing advanced algorithms and real-time data analysis, it enables banks to detect suspicious activities, monitor transactions, and ensure compliance with stringent regulatory standards. Implementing this software not only helps banks mitigate risks but also fosters trust among customers and regulatory bodies alike, making it an essential component of modern banking operations.
Why do casinos and gaming need AML software?
The casino and gaming industries are fast paced and considered to be high risk, and money laundering schemes are becoming increasingly sophisticated. Ensuring AML compliance is vital for keeping up with regulatory requirements and maintaining trust with customers. By integrating AML software, businesses can effectively monitor transactions and identify suspicious behavior, preventing illicit activities that can tarnish reputations and lead to significant financial penalties. In 2023, the industry incurred £366 million in fines.
What is a financial crime risk management solution and why use it?
A financial crime risk management solution is software designed to help businesses combat the complex challenges of financial crime. It streamlines and automates the process of detecting, preventing, and reporting suspicious activity that could be related to money laundering and other financial crimes. AML tools often include features such as transaction monitoring, risk assessment, customer due diligence, and compliance reporting. Implementing AML software not only fortifies an organization's defense against financial crime but also builds trust with clients and regulators alike.
Useful links
We’ve discussed a lot regarding AML software in this guide. However, there could be more you want to know about the impact it can have on your AML program. Browse the following articles for further reading.