The New Frontiers of Check Fraud: In Conversation with Mitek
Check fraud hasn't diminished with time, but its characteristics have changed. What was once a slow-moving, paper-based crime has become a fast, organized, and increasingly AI-enabled threat. As financial institutions race to keep up, the gap between legacy detection systems and modern fraud tactics continues to widen.
That's why we recently partnered with Mitek to deliver a cutting-edge, AI-powered solution that helps financial institutions proactively pinpoint and block altered, forged, or counterfeit checks to mitigate fraud losses.
Our VP of Product, Fraud, Hrishi Talwar, sat down with Derek Abbott, Senior Business Intelligence & Strategy Manager at Mitek, to explore what's changing in the check fraud landscape, where current prevention technologies are falling short, and what's coming next in terms of technology. From AI-assisted fraud to real-time fraud networks, here's what institutions need to know to stay ahead.
Hrishi: Check fraud looks nothing like it did even a few years ago - what are the biggest shifts you're seeing?
Derek: Today's check fraud is moving faster and operating at far greater scale than ever before.
We're seeing a surge in high-quality counterfeit and altered items, often created using inexpensive image-manipulation tools that make forgeries nearly indistinguishable to the human eye. Rapidly migrating fraud rings are exploiting the fact that most institutions still operate in silos. When an item is flagged at one bank, that same check can be redeposited elsewhere within hours.
Mail theft and stolen check reselling have become industrialized, with fraudsters sharing or selling compromised checks in online criminal marketplaces. And then there's channel hopping, where fraudsters move between mobile, ATM, and in-branch deposits depending on where institutions have the weakest defenses.
These shifts are accelerating losses and overwhelming back-office teams, making proactive, real-time detection essential.
We’re taking a closer look at how AI is reshaping the game together on March 5th.
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Hrishi: Where are current check fraud prevention systems falling short?
Derek: Most fraud tools were built for a world where checks cleared overnight, fraud was largely on-us, and visual alterations were low-tech. That world doesn't exist anymore.
The gaps we see most often start with limited image-based analysis that fails to inspect deeper visual elements like handwriting style, signature geometry, check stock integrity, or layout anomalies. Then there's siloed data and limited consortium intelligence, leaving institutions unable to recognize checks, accounts, or behaviors already flagged as suspicious at other banks or across the ecosystem.
Batch-oriented and delayed processing means fraud is often detected after funds are made available which shrinks recovery windows and increases losses. High false-positive rates, driven by rigid, rules-based detection that relies on exact matches and static thresholds, create unnecessary holds and customer friction.
These approaches fail to account for normal business variability — such as payee name changes, formatting differences, transaction timing, or legitimate outliers — resulting in heavy manual review burdens.
There's also a fundamental lack of cross-channel visibility. Check deposits are evaluated in isolation rather than in the context of broader account behavior. Many systems can’t correlate check activity with real-time signals from mobile, ATM, teller, ACH, wire, or account lifecycle events. Without that broader view, institutions miss early indicators that only surface when activity is seen as a whole.
And critically, most systems can't detect emerging and synthetic fraud patterns, such as stolen checks deposited into newly formed shell businesses that appear legitimate in single-institution views, but reveal coordinated risk when analyzed across institutions and channels.
Traditional positive pay controls remain valuable, but they're insufficient on their own. What's missing is real-time intelligence applied earlier in the commercial check lifecycle, before funds are disbursed, risk escalates, and operational costs compound. These gaps create blind spots that sophisticated fraudsters readily exploit.
Hrishi: What check fraud techniques should institutions be watching for?
Derek: Three major areas are emerging, and they're all accelerating.
- AI-assisted counterfeit checks. Fraudsters are beginning to use generative tools to recreate checks with perfect typography, signatures, and backgrounds. The level of precision is startling.
- Synthetic entity and check pairing. Fraudsters open synthetic business accounts that match the stolen check's payee name, enabling deposits that slip past Positive Pay and traditional payee matching. It's a coordinated attack that exploits the seams between different validation layers.
- High-velocity deposit attacks. Coordinated teams deposit the same stolen check across multiple institutions within hours, attempting to beat slower fraud systems to the punch. It's a race, and institutions without real-time capabilities are losing.
As technology advances, the line between real and manipulated check images will only blur further, making automation and advanced image forensics indispensable.
Hrishi: What can AI do today that wasn't possible two years ago?
Derek: A lot has changed. Modern AI can now analyze a number of visual attributes of a check in seconds, far beyond account metadata alone. As an example, Mitek's check fraud solution analyzes 20+ attributes.
It can detect subtle manipulations, from mismatched handwriting to tampered MICR lines to micro-distortions invisible to human reviewers. It can tap into shared consortium data to identify items previously linked to fraud, even if they've never touched the institution reviewing them.
Critically, AI can now score fraud risk in near real time at the moment of capture, enabling instant decisioning and dramatically reducing losses. And it can combine image forensics with behavioral and transactional signals, giving institutions multi-dimensional fraud intelligence.
This level of precision simply wasn't possible a few years ago.
Hrishi: What will check fraud prevention look like in three to five years?
Derek: We're moving toward fully connected, real-time, AI-powered fraud ecosystems. In three to five years, check fraud prevention will feel less like "detection" and more like anticipatory defense. We expect to see...
- Automated decisioning with human-in-the-loop review that shrinks review times without eliminating oversight
- Always-on fraud intelligence networks where institutions share signals continuously, not hours or days later. When a suspicious check is identified at one institution, that intelligence can be surfaced across the network almost immediately.
- Deeper integration of compromised-data intelligence, surfacing whether a check or account appears on criminal forums before a deposit is even made.
These capabilities will be underpinned by explainable AI that provides transparent overlays and reasons behind alerts, reducing investigation time and cross-rail intelligence, linking check data to ACH, wire, and payment scams to uncover broader fraud campaigns.
Hrishi: Where should fraud leaders focus their check fraud technology investments right now?
Derek: Three areas deliver the highest ROI...
First, automation that reduces manual review. Modern image analysis dramatically cuts back-office workload while improving accuracy. The days of relying purely on human eyes to catch altered checks are over — the volume and sophistication have made that approach unsustainable.
Second, real-time fraud decisioning across channels. Fraud today moves fast and follows the path of least resistance. If you're only catching it in batch processing or after funds clear, you're already behind. Real-time detection at the moment of capture — whether mobile, ATM, or teller — is no longer optional.
Third, consortium-driven detection. Fraudsters collaborate; banks must too. Shared intelligence means a check flagged at one institution can be immediately recognized at another, closing the window for redeposit schemes and cross-institution attacks. Without consortium data, you're fighting fraud with one hand tied behind your back.
Hrishi: How is Mitek's approach to check fraud prevention different?
Derek: Mitek combines patented imaging science, consortium intelligence, and real-time AI to deliver exceptionally precise detection with minimal customer friction. But what really sets the approach apart is the depth and breadth of the consortium itself.
Mitek's cloud-hosted consortium includes DDAs from 8,300+ U.S. financial institutions and climbing. It spans all deposit channels—mobile, ATM, in-branch, RDC—so there's no gap for fraudsters to exploit by switching channels. And critically, it stores verified customer check profiles, enabling comparisons to known non-fraudulent checks.
That last point matters more than people realize. Traditional consortiums often share metadata: routing number, account status, and the likes. But they don't share high-fidelity visual attributes. Mitek's approach goes deeper, analyzing the actual image forensics and visual characteristics that reveal manipulation.
The consortium covers both "on-us" and "in-transit" fraud, eliminating blind spots that arise when institutions only monitor their own accounts. And it powers real-time decisioning, so suspect items are flagged before funds are released, not after.
The result is a defense system that's connected, proactive, and built for the speed and coordination of modern fraud.
Hrishi: Where is Mitek's technology headed in the next year or two?
Derek: Mitek is focused on three major priorities.
- First, expanding real-time detection to cover all channels
- Second, expanding consortium data to deliver even stronger cross-institution insights and pattern detection
- And third, advancing image forensics and AI models to stay ahead of synthetic checks and increasingly sophisticated visual forgery techniques
The result will be dramatically faster, more accurate decisions and fewer customer disruptions.
Bringing It Together: Mitek and Hawk
As we've learned from this conversation, the profile of a fraudster has fundamentally changed. Today's fraud operations use automation, anonymous collaboration channels, and AI. Many schemes are run like businesses which makes fraud faster, harder to detect, and more difficult to disrupt using traditional controls.
That means fraud leaders need to match that sophistication with their own investments in check fraud prevention.
That's exactly what the Mitek and Hawk partnership is built to deliver.
Mitek's best-in-class AI image forensics and consortium intelligence combined with Hawk's flexible, AI-powered precision and self-serve rule management creates a defense system that's both powerful and practical.
Through AI anomaly detection and advanced image forensics, the solution identifies subtle manipulations and behavioral patterns the human eye can't see, giving institutions an additional layer of defense against check fraud schemes. And critically, Hawk enables banks and credit unions to unify fraud monitoring across payment rails and channels, simplifying integration and eliminating the need for multiple tools.
Check fraud doesn't operate in isolation. This unified approach allows financial institutions to detect both check deposit fraud and suspicious movement of funds after clearing, stopping losses before they happen.
Learn more about how Mitek and Hawk are helping institutions stay ahead of modern check fraud here.