Real-time check fraud prevention: The next evolution in proactive, pre-posting decisioning

Most of us make the majority of our day-to-day payments through digital channels, rarely writing a check. Still, checks are deeply embedded in the daily operations of businesses and government services, and consumer activity hasn’t completely gone away. This means checks remain a viable and prolific channel for fraud. According to the 2025 AFP Payments Fraud and Control Survey, nearly 8 out of 10 organizations experienced payments fraud in 2024, and check fraud was the #1 method - impacting 63% of the financial professionals surveyed. The survey also revealed that the median dollar loss from check fraud had increased significantly year-over-year, with coordinated fraud campaigns resulting in losses in the millions for some institutions. 

The simplest way to stop check fraud would, of course, be to eliminate the use of checks in favor of payment methods that cannot be so easily tampered with. But when asked if checks would ever be eliminated, 75% of organizations polled indicated they had no plans to eliminate checks within the next two years. Thus, checks remain a stubborn exposure surface for financial institutions. Neither they nor the risk associated with them is going away - necessitating the adoption of sophisticated capabilities, like real-time check fraud prevention, that can keep pace with modern check fraud tactics. 

Real-world example: when delayed check fraud detection leads to loss 

Earlier this year, a mid-size regional bank was the target of a coordinated, multi-channel check fraud scheme. Fraudsters stole checks from the mail, chemically washed the payees and amounts (known as “check washing”), and deposited the altered items using mobile and ATM channels. 

The bank’s fraud controls relied on checks being reviewed after posting – meaning they only verified the checks were legitimate and were drawn against available funds after the check had already been posted to the depositor’s account. Because of this, their analysts didn’t identify the emerging fraud pattern until almost 48 hours had passed. Unfortunately, by then, more than $250,000 had already been siphoned from the institution using mule accounts, making fund recovery nearly impossible. With real-time detection, this exposure window could have been significantly reduced. 

Fraud rings have become more organized and nimbler, adopting automated methods, and can target multiple institutions or branches of institutions on multiple channels in a narrow window of time. Their sophisticated operations will coordinate attacks across geographic regions and time their deposits to exploit processing windows, thus maximizing the window before detection. For example, when activity occurs during holiday or weekend periods and manual review teams are not available, it can be even easier for fraudsters to exploit delays between deposit and review. This is why proactive, real-time check fraud detection is now essential. 

What is real-time, pre-posting decisioning—and why it matters 

Real-time, pre-posting decisioning gives banks and credit unions the ability to assess risk before a check is posted to an account. Often, this check fraud prevention technology can render a decision within milliseconds. 

Unlike traditional after-posting reviews that allow funds availability timelines to advance before fraud analysts can review an item and take action, pre-posting decisioning evaluates risk in session, while the deposit is made. Traditional batch processing systems will often create a 24-to-72-hour gap between deposit and review, and fraudsters have learned how to exploit this window. By the time a fraud analyst reviews a suspicious item, the funds may already be withdrawn, transferred, or spread across multiple mule accounts, making recovery a challenge.

Real-time check fraud detection technology is especially powerful for the detection of increasingly prevalent threats like: 

• Washed or otherwise altered checks where fraudsters have modified the payee, signature, and/or amount 
• Duplicate presentments (whether intentional or unintentional) across mobile, ATM, and branch channels 
• Forged signatures or mismatched metadata, identified using artificial intelligence (AI), machine learning, other forensic tools, or contextual insights 
• Checks from high-risk, previously compromised, or newly opened accounts, which might signal mule activity 

Pre-posting decisioning makes it possible for institutions to stop fraud before losses occur - rather than only uncovering it once the damage is done. 

Key benefits of real-time, pre-posting decisioning 

Shifting to a real-time, pre-posting system unlocks numerous advantages for financial institutions and provides a stronger and more scalable fraud defense strategy. Here is a look at several of the key benefits. 

Speed and accuracy 

Modern AI check fraud prevention models and risk-based decision engines are capable of analyzing dozens of attributes in milliseconds. This allows them to discover anomalies that human review alone often misses, especially when evaluating documents at scale. These systems are capable of simultaneously analyzing check characteristics that include magnetic ink character recognition (MICR) line integrity, signature patterns, endorsement authenticity, and historical account behavior, all while the customer is still at the ATM or conducting a mobile deposit. Institutions gain faster and more accurate assessments without any impact on customer experience. 

Operational efficiency 

When decision systems filter high-risk items automatically, institutions see a reduction in their manual review queues and lower false positives. This allows their fraud detection teams to spend more time dedicating their expertise to complex and higher-value cases. The reduction in items requiring manual review once pre-posting decisioning is implemented also translates to significant cost savings and reduces customer friction by minimizing unnecessary holds on legitimate deposits. Overall, review cycles are accelerated while the overall cost to detect is reduced. 

Cross-channel visibility 

Pre-posting decisioning delivers unified risk assessment across all channels, like mobile, ATM, tellers, and remote deposit capture (RDC) workflows, so there are no blind spots like there are in siloed systems. This holistic view makes it possible for institutions to identify patterns such as the same check being presented on multiple channels simultaneously or other unusual deposit behaviors that span digital and physical touchpoints. Ultimately, this means fraud detected in one channel won’t slip through somewhere else. 

Scalability and adaptability 

AI and machine learning-powered check fraud prevention systems are sophisticated and will continuously learn from evolving fraud patterns and incorporate intelligence from across the institution as well as from consortiums that share intelligence. This way, institutions can keep pace with fraudsters’ tactics even as they become more sophisticated. Even when deposit volumes fluctuate, whether that’s during seasonal peaks as seen with some government checks or due to an institution’s long-term growth, these systems will scale seamlessly. 

The future of real-time check fraud prevention 

Check fraud remains an ever-present threat for financial institutions. As long as checks remain in circulation - and they don’t appear to be going away any time soon - fraudsters will look for ways to exploit them. However, advanced check fraud detection tools can bring true, real-time intelligence to the moment of deposit, rendering decisions immediately rather than post-posting.  

Institutions that adopt proactive fraud detection and pre-posting decisioning will be the best positioned to reduce their fraud exposure and strengthen their customer protections. The more quickly a financial institution puts modern solutions to work, the better they will be able to keep losses from check fraud at bay. 

Whether you’re ready for a full technology overhaul or are always looking for ways to optimize your financial institution’s existing fraud strategy and technology stack, this is the ideal time to rethink when and how you detect check fraud.