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The best fraud detection software and companies in 2024

Fraud Knowledge & Training

If you’ve found this article, the chances are you’re looking for:

  • A fraud detection tool that’s powerful, efficient, and scalable.
  • A way to quickly tell what differentiates leading solutions.
  • How respected third parties assess top fraud and AML vendors’ capabilities.

Fraud detection software: 4 features to look for

When evaluating fraud detection vendors, there are several features fraud and compliance teams should look for:

  1. Artificial intelligence capabilities: As important as AI is, simply adding an ‘AI sticker’ to a solution doesn’t tell you much about its capabilities. Specific areas firms should explore include:
    • The use of advanced behavioral analytics via unsupervised machine learning and tailored rules to detect anomalies from an individual or peer group.
    • The use of identity clustering to detect fraud patterns across multiple accounts.
    • The use of alert prioritization to make remediation more efficient. 
  2. Fraud scenario coverage: Coverage of fraud scenarios across key touchpoints in the lifecycle of a transaction and all payment types is also critical — specifically, firms should consider:
    • Payment-agnostic fraud scenarios including account takeover, synthetic identity, and relationship fraud. In total, ComplyAdvantage has logged more than 50 of these.
    • Data types – emerging payment types with rich, structured data like ISO20022 offer huge potential to improve fraud detection.
    • Non-transaction events such as fraud detection for real-time payment methods, including FedNow and the Faster Payments network. Detecting fraud here requires pre-transaction screening via events like log-ins and profile changes. 
    • Establishment payment rails like ACH, SWIFT MT, SEPA, and Faster Payments should be included.
  3. Sector knowledge: The firm providing your solution should have relevant experience with similar customers. This will enable them to offer better recommendations on achieving your fraud detection requirements while minimizing the impact on the customer experience.
  4. Integration of fraud and AML capabilities: There are many benefits to working with vendors that offer fraud and AML products. This can help to overcome internal siloes but also improve efficiency and save money.

Top fraud detection software companies

1. ComplyAdvantage

The G2 GridⓇ for Anti-Money Laundering is a helpful way of measuring financial crime risk management vendors based on customer reviews. The G2 GridⓇ lists ComplyAdvantage as a leader in anti-money laundering.


Fraud Detection from ComplyAdvantage is an AI-based solution that enables firms to detect and prevent payment fraud efficiently. Our machine learning models have won hackathons organized by ACAMS and PwC and, in relation to fraud detection, have four key capabilities:

  1. Explainability: An “ensemble model” considers various fraud scenarios, explaining why each alert was created.
  2. Dynamic Thresholds: Calibrated to maximize precision and minimize false positives.
  3. Identity Clustering: Uses behavioral and personal characteristics to link accounts that a single individual or organization behind key fraud scenarios, such as synthetic identity fraud or money muling fraud, may control.
  4. Graph Network Detection: Uses graph network analyses to track fraudulent money within your system after the fraud has been committed.

Top ComplyAdvantage features

Fraud Detection by ComplyAdvantage is well suited to digital and regional/mid-market banks, international money transfer and foreign exchange firms, PropTech, and many payment companies. To help these firms detect fraud effectively, our solution includes the following capabilities:

  • Advanced machine learning (ML) detections – Capture unknown fraud risks rules alone can’t see, using ML models, identity clustering, and graph analytics.
  • Anomaly detection – See the unseen with peer group and individual anomaly detection using unsupervised machine learning algorithms.
  • Dynamic tuning – Fraud detection models continuously learn from analyst feedback.
  • Fine-tuned, real-time risk approach – Apply different rules and thresholds for different customer tiers.
  • Smart Alerts – Identify and prioritize alert risk factors, increasing team efficiency.
  • Flexible rules engine – Leverage fraud and industry-specific rules and scenarios, or work with industry experts to set your own.
  • 50+ fraud scenarios – Leverage our wide array of payment-agnostic fraud scenarios, including Account Take Over (ATO) Fraud, Synthetic Identity Fraud, Relationship Fraud, Email Compromise Fraud, Authorized Push Payment (APP) Fraud, and many more.
  • Coverage for all payment rails – Rest easy with comprehensive payment coverage, including ACH, Swift MT, SEPA, Direct Debit, FedNow, Faster Payments, and SEPA ICT.
  • Coverage for non-transaction events – Take advantage of holistic insights on customer behavior events like logins and profile changes.
  • Integrated case management – Open an investigative case directly from an alert, automate repetitive tasks, and reduce human error.
  • Custom workflows – Move transactions through the various states for reporting and escalation.
  • Flexible data format – Use as much of the data you have as possible in your format and build your compliance program around it.
  • Ongoing configuration – Independently perform ongoing rule and scenario configuration.
  • Behavioral analytics – Take advantage of identity clustering fuelled by customer behavior and identity data to link accounts controlled by a single hidden entity.
  • Neural network models – The wider ComplyAdvantage platform uses neural network models and algorithms to identify factors such as anomalies in transaction behavior. This includes, for example, discrepancies between reference text and transaction values to help identify fraud where the reference text may be used to mask the source or purpose of transferring funds.

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2. Featurespace

According to Crunchbase, Featurespace “provides an adaptive behavioral analytics technology and automated deep behavioral networks for risk management.” The company was founded in 2008, and its investors include Merian Chrysalis. 

3. Feedzai

Crunchbase describes Feedzai as a developer of “risk management tools to prevent fraud and money laundering in transactions.” The company was founded in 2011 and currently has more than 600 employees. Its investors include KKR, Sapphire Ventures, and Citi Ventures.

4. Sardine

Crunchbase describes Sardine as a “fraud prevention and compliance software company for the digital economy.” The firm was founded in 2020, and its investors include Andreessen Horowitz, XYZ, Nyca Partners, Sound Ventures, and Eric Schmidt. 

5. Hawk:AI

Crunchbase states Hawk AI is a “money-laundering detection & investigation platform.” Investors, including Sands Capital, DN Capital, and BlackFin Capital Partners, fund Hawk AI. It was founded in 2018 and has its headquarters in Germany.

6. Onfido

London-based Onfido was founded in 2012 and is described by Crunchbase as “a provider of automated digital identity verification.” The firm has several investors, including TPG Growth, SBI, and Salesforce. 

7. Abrigo

Abrigo is described by Crunchbase as a provider of “market-leading compliance, credit risk, and lending solutions to enable its customers to think bigger.” The Texas-based firm has investors, including Carlyle and Accel-KKR. 

8. SymphonyAI

SymphonyAI acquired financial crime detection firm NetReveal in October 2022. Crunchbase calls the firm “an enterprise AI company focused on delivering AI solutions for vertical sectors.” The firm was started with an injection of capital from its founder in 2017.

How to measure success

While every firm will have different objectives and challenges with their fraud detection software, our experts recommend three core objectives:

  • Protect the firm and its customers’ reputation. Detecting fraud before it hits the headlines is key to operating a sustainable, profitable business. It’s also important to keep customers informed if a transaction is stopped.
  • Minimize fraud losses. Fraudsters are creative and will keep evolving tactics until they breach security and steal customers’ money. Avoid heavy regulatory penalties by deploying insights-driven machine learning solutions that adapt quickly.
  • Improve analyst efficiency. Trying to grow the compliance team to manage a scaling organization isn’t realistic or cost-effective. Automation has to play a role, which means finding ways to help fraud analysts prioritize their workloads and focus on the greatest risks.

Next steps: Explore Fraud Detection from ComplyAdvantage

Discover why leading firms choose ComplyAdvantage for Fraud Detection, and book a demo to see the solution for yourself. 

All information is sourced from publicly available websites and is correct as of March 2024. If you’d like to request a correction, please e-mail [email protected] and we’d be happy to review this with you.

Originally published 14 June 2023, updated 20 March 2024

Disclaimer: This is for general information only. The information presented does not constitute legal advice. ComplyAdvantage accepts no responsibility for any information contained herein and disclaims and excludes any liability in respect of the contents or for action taken based on this information.

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