AML Fraud Detection: Staying Ahead of an Evolving Threat

by Julie.JLee@experian.com 4 min read March 27, 2024

Financial institutions have long relied on anti-money laundering (AML) and anti-fraud systems to protect themselves and their customers. These departments and systems have historically operated in siloes, but that’s no longer best practice.

Now, a new framework that integrates fraud and AML, or FRAML, is taking hold as financial institutions see the value of sharing resources to fight fraud and other financial crimes.

You don’t need to keep them separated

For fraudsters, fraud and money laundering go hand-in-hand. By definition, someone opening an account and laundering money is committing a crime. The laundered funds are also often from illegal activity — otherwise, they wouldn’t need to be laundered.

For financial institutions, different departments have historically owned AML and anti-fraud programs. In part, because AML and fraud prevention have different goals:

  • AML is about staying compliant: AML is often owned by an organization’s compliance department, which ensures the proper processes and reporting are in place to comply with relevant regulations.
  • Fraud is about avoiding losses: The fraud department identifies and stops fraudulent activity to help protect the organization from reputational harm and fraud losses.

As fraudsters’ operations become more complex, the traditional separation of the two departments may be doing more harm than good.

Common areas of focus

There has always been some overlap in AML and fraud prevention. After all, an AML program can stop criminals from opening or using accounts that could lead to fraud losses. And fraud departments might stop suspicious activity that’s a criminal placing or layering funds.

While AML and fraud both involve ongoing account monitoring, let’s take a closer look at similarities during the account creation:

  • Verifying identities: Financial institutions’ AML programs must include know your customer (KYC) procedures and a Customer Identification Program (CIP). Being able to verify the identity of a new customer can be important for tracing transactions back to an individual or entity later. Similarly, fraud departments want to be sure there aren’t any red flags when opening a new account, such as a connection between the person or entity and previous fraudulent activity.
  • Preventing synthetic identity fraud: Criminals may try to use synthetic identities to avoid triggering AML or fraud checks. Synthetic identity fraud has been a growing problem, but the latest solutions and tools can help financial institutions stop synthetic identity fraud across the customer lifecycle.
  • Detecting money mules: Some criminals recruit money mules rather than using their own identity or creating a synthetic identity. The mules are paid to use their legitimate bank account to accept and transfer funds on behalf of the criminal. In some cases, the mule is an unwitting victim of a scam and an accomplice in money laundering. 

Although the exact requirements, tools, processes, and reports for AML and fraud differ, there’s certainly one commonality — identify and stop bad actors.

Interactive infographic: Building a multilayered fraud and identity strategy

The win-win of the FRAML approach

Aligning AML and fraud could lead to cost savings and benefits for the organization and its customers in many ways.

  • Save on IT costs: Fraud and AML teams may benefit from similar types of advanced analytics for detecting suspicious activity. In 2023, around 60 percent of businesses were using or trying to use machine learning (ML) in their fraud strategies, but a quarter said cost was impeding implementation.1 If fraud and AML can share IT resources and assets, they might be able to better afford the latest ML and AI solutions.
  • Avoid duplicate work: Cost savings can also happen if you can avoid having separate AML and fraud investigations into the same case. The diverse backgrounds and approaches to investigations may also lead to more efficient and successful outcomes.
  • Get a holistic view of customers: Sharing information about customers and accounts also might help you more accurately assess risk and identify fraud groups.
  • Improve your customer experience: Shared data can also reduce customer outreach for identity or transaction verifications. Creating a single view of each account or customer can also improve customer onboarding and account monitoring, leading to fewer false positives and a better customer experience.

Some financial institutions have implemented collaboration with the creation of a new team, sometimes called the financial crimes unit (FCU). Others may keep the departments separate but develop systems for sharing data and resources.

Watch the webinar: Fraud and identity challenges for Fintechs

How Experian can help

Creating new systems and changing company culture doesn’t happen overnight, but the shift toward collaboration may be one of the big trends in AML and fraud for 2024. As a leader in identity verification and fraud prevention, Experian can offer the tools and strategies that organizations need to update their AML and fraud processes across the entire customer lifecycle. 

CrossCore® is our integrated digital identity and fraud risk platform which enables organizations to connect, access, and orchestrate decisions that leverage multiple data sources and services. CrossCore cloud platform combines risk-based authentication, identity proofing and fraud detection, which enables organizations to streamline processes and quickly respond to an ever-changing environment. In its 2023 Fraud Reduction Intelligence Platforms (FRIP), Kuppinger Cole wrote, “Once again, Experian is a Leader in Fraud Reduction Intelligence Platforms. Any organizations looking for a full-featured FRIP service with global support should consider Experian CrossCore.” 

Learn more about Experian’s AML and fraud solutions

1. Experian (2023). Experian’s 2023 Identity and Fraud Report

Related Posts

Used EV Growth Signals a New Phase of Consumer Purchasing Behavior

The electric vehicle (EV) revolution isn’t slowing down, it’s changing lanes. While recent conversations have seemingly focused on softening demand for new EVs, the used segment has been gaining momentum. According to Experian Automotive’s 2025 EV Year in Review Report, new retail individual EV registrations fell 35.9% year-over-year. Meanwhile, the used retail individual EV registrations grew 25.4% from a year ago. As affordability and growing model availability reshapes consumer behavior, buyers are increasingly turning to pre-owned EVs, which has shown an interesting market divergence that is redefining how consumers are adopting this segment and what it can mean for automakers, dealers, and the overall industry. Key players behind rising used EV demand Notably, Tesla accounted for over half (60.5%) of used retail individual EV registrations in 2025, followed by Chevrolet at 6.4% and Nissan (5.5%). Diving a bit deeper, Tesla made up the top three models of the used individual registrations last year, with the Model 3 coming in at 27.2%, Model Y at 21.7%, and Model S (6.6%). The Chevrolet Bolt EV followed at 4.8% and the Nissan Leaf was at 4%. Tesla’s position as the leading make in the used EV market is a natural extension of its long-standing dominance in new EV sales. The brand’s leadership over the years created a large fleet of vehicles that are now entering the pre-owned market. What the used EV boom means for automotive professionals The growing demand for used EVs can present more opportunities for automotive professionals. Dealers that provide a healthy supply of pre-owned EVs can increase accessibility and play a role in adoption for consumers who are actively looking to purchase, while marketers can emphasize value and ownership benefits. As the market continues to evolve, automotive professionals who understand and respond to these changing dynamics will be best positioned to capitalize on the expanding pool of used EV shoppers. To learn more about EV insights, visit Experian Automotive’s EV Resource Center.

Published: June 30, 2026 by Kirsten Von Busch
How Terrace Finance Uses NeuroID to Respond to Fraud Faster and Smarter

Learn how Terrace Finance used NeuroID behavioral analytics to detect fraud faster, respond to attacks, and strengthen risk management.

Published: June 29, 2026 by Scarlet.Nickel@experian.com
Ask the Expert: A Closer Look at Modern Lending with Jeff Hops and Erin Haselkorn

In this first episode of Ask the Expert, Experian's Jeff Hops, Senior Director of Data Platform and Product, and Erin Haselkorn, Senior Director of Analyst Relations, explore how broader data and new signals can help lenders better understand today’s consumers, while maintaining responsible decisioning. Lending is changing  Interest rates, regulation, embedded finance and AI are reshaping the lending landscape. Consumer behavior is evolving just as quickly. But the core job hasn’t changed. Lenders are still making decisions about people they don’t fully know, and that makes data more important than ever. "There are periods where nothing changes, and periods where it seems like everything changes. We’re in the latter … but the core premise hasn’t changed. You’re still trying to lend to somebody you don’t know."Jeff Hops, Senior Director of Data Platform and Product To make those decisions with confidence, lenders need a strong foundation of identity, history and reliable signals. In a period of rapid change, the quality and completeness of that data become even more critical. A more complex view of today’s consumer What has changed is the consumer. Traditional credit data is foundational but can be further enhanced with visibility on how people earn, manage and move money. Income may come from multiple sources, and financial activity often spans bank accounts, applications (apps) and digital channels. Cash flow data, for example, can provide a clearer view of what’s actually coming into a consumer’s account, beyond what traditional records may show.These additional signals can help lenders better understand: Income variability across multiple earning sources Current financial behavior through cash flow activity Digital and identity-linked activity across channels These signals don’t replace traditional data; they expand it. The result is a more complete and current view of the consumer. From exploration to real-world application The conversation around broader data signals has moved beyond theory. Lenders are no longer just asking whether these signals are useful. They’re asking where, how and under what governance they can be applied across the lending lifecycle. Lenders are actively researching, testing and implementing new data sources across the lending lifecycle. What was once experimental is now operational. Institutions are progressing through a clear path: Research Understanding available signals and use cases Testing Evaluating performance in controlled environments Implementation Applying insights in production Today, alternative data is being used in areas like analytics, channel scoring and decisioning, often within governed environments that allow for safe testing and validation. AI may accelerate this shift by helping institutions identify patterns at scale, but its value depends on the strength of the underlying data: quality, governance, context and clear business use cases. More signal, more responsibility As data availability expands, lenders have access to more granular insights than ever before. That creates opportunity, but also responsibility. The institutions that lead won’t be the ones that use the most data. They’ll be the ones that know which signals to use, how to validate them and how to apply them in ways that are fair, explainable and aligned to consumer outcomes. “Institutions can unlock more granular and powerful decisions, but they have to do it responsibly.”Erin Haselkorn, Senior Director, Analyst Relations The future of lending will be shaped not just by how much data is available, but by how thoughtfully it’s applied. Keeping the consumer at the center of decisioning is essential to building trust and long-term success. Explore alternative data with us A more complete understanding of today’s consumers starts with better data. We help lenders responsibly incorporate broader data signals and advanced analytics into decisioning strategies, enhancing visibility into today’s consumers while strengthening risk assessment and expanding access to credit. Let’s work together to build more confident, more responsible lending decisions. Learn more Contact us About our experts Jeff Hops Senior Director, Data Platform and Product, Experian Jeff Hops is a Senior Director in Experian’s Financial Services and Data business with over eight years of experience driving innovation in credit and data solutions. He has led product development for Experian’s Credit Report and played a key role in launching Ascend Identity Platform™, a leading identity resolution platform. Erin Haselkorn Senior Director, Analyst Relations, Experian Erin Haselkorn is responsible for analyst relations for Experian. She has developed an understanding of key marketing trends across a broad range of verticals. Her market research around data strategy, AI, fraud, identity and data management, paired with her broad Experian product knowledge, gives her a unique understanding of business automation and data trends. Erin is a frequent spokesperson and guest blogger.

Published: June 22, 2026 by Julie.JLee@experian.com