Check fraud is rarely just a check problem. It can be the opening move in a broader attack that shifts funds across payment channels.
While detecting an altered payee, counterfeit image, endorsement mismatch and suspicious deposit all matter in the detection of check fraud, viewed only under that single lens they reveal only the fraud entry point into a financial institution. Given the time discrepancy from when a fraudulent check is discovered versus when the funds become available to the fraudster, focusing only on check fraud lets a larger risk emerge as funds move from that check deposit into ACH, wire, peer-to-peer (P2P) payments or other channels. If institutions investigate only the item, they may miss both the broader attack and the point where the loss ultimately surfaces.
A central takeaway from a recent Consumer Bankers Association (CBA) webinar was that financial institutions must reconstruct the full fraud journey — not simply catch more bad checks. As fraud volumes rise, scams become more sophisticated and payments accelerate, connected defenses are essential to show how fraud moves and where its signals appear.
The Check Is the Trigger, Not the Whole Story
Fraud teams understand the pressure surrounding check fraud, but the most damaging schemes rarely remain within one channel. A stolen check may first be altered or counterfeited, then deposited into one or more accounts. Once the funds appear available, they can be pushed through faster, harder-to-recover payment rails.
That creates a measurement problem as much as an operational one. If an institution records the deposit as check fraud but the funds exit through P2P or wire channels, its reporting may fail to connect the entry point with the resulting loss. Over time, that gap can distort priorities by making one connected attack cycle look like a series of isolated events.
The question is not only, “Was this check fraudulent?” It is, “What happened before this deposit, what changed after it, and where is the money trying to go?”
The Most Useful Signals Are Often Outside the Check Image
Verifying image quality, checking for signs of alteration and other red flags will still prevent fraud losses. But fraudsters are getting better at making the item itself look legitimate. They have access to the same speed and technology the rest of us do, without the governance constraints institutions operate under.
That means financial institutions need to widen the aperture. Account-opening data may reveal whether an account was “born to be bad,” while account age and profile changes may show that a previously quiet account has suddenly become risky. Device and behavioral patterns can indicate whether a customer is acting normally, being coached or operating under remote access. Payment and beneficiary signals can reveal whether funds are headed to an unfamiliar destination, a party previously associated with risk or a beneficiary newly introduced to the institution.
Individually, these signals can be ambiguous. A new account, a suspicious deposit, a profile change, an unusual login session and a first-time outbound payment may each be explainable on its own. Together, they tell the story of a broader attack chain.
Silos Limit Visibility into the Fraud Attack Lifecycle
During the webinar, the discussion of cross-channel connections quickly turned to P2P because funds can move so rapidly. ACH and wire present different risk and recovery considerations. No single rail is always the problem — fraudsters are indifferent to channels and focused on cashing out.
Financial institutions, however, often organize defenses by channel: Deposit teams focus on incoming items, wire teams on outbound transfers and digital teams on device activity. When those views remain separate, each function sees only part of the attack. Analysts then lose critical time searching across systems to assemble the context required for a decision.
A consolidated profile matters because it gives analysts one decision flow instead of a scavenger hunt across systems. Bringing identity, account, device, transaction, payment, beneficiary, network and external intelligence together helps reveal relationships that remain hidden when each signal is reviewed separately. Layered defense is not simply a larger collection of tools; it is the ability to make those layers work together when risk is being evaluated.
Collaborate to Break the Chain
A single institution has a strong view of its own customers. It has a much weaker view of what happens beyond its walls. That means you’re missing pre-attack signals, such as when a beneficiary has appeared at another institution, when an account has been closed elsewhere for suspicious activity, or when stolen checks and compromised credentials are circulating before the institution ever sees the transaction.
Extending visibility beyond your institution’s own records with consortium intelligence provides those pre-attack signals that uncover risk:
- Internal data shows the fraud already touching the institution.
- Industry-scale data can expose related patterns across organizations.
- Dark-web intelligence can surface compromised information earlier in the timeline.
- Payment and counterparty insights can reveal risk around the destination before funds leave.
Together, these sources support a stronger question: not only “Is this transaction unusual?” but “What does the full path of risk tell us?”
The goal is not to create friction everywhere. Good customers need less friction. Risky moments need the right friction. That may mean a pause, a closer look, a cooling-off period or a better-informed analyst decision before money is gone.
Stop Fraud Before It Migrates Across Your Institution
Start by mapping the fraud journey from beginning to end. Look left of the check, then trace the exit — not just the entry. Bring deposit fraud and payments into the same conversation, identify signals that do not reach the people or systems that need them, and measure fraud across the lifecycle rather than by isolated channel. The work can feel complex, so approach it one step at a time.
AI will continue to increase the speed and sophistication of fraud, but it can also help fraud teams manage alert volume, assemble context and automate investigative triage. Analysts should retain responsibility for the decision — AI should reduce the manual work required to gather and connect the relevant signals.
For financial institutions rethinking check fraud defenses, the path forward is more connected: broader intelligence, stronger cross-channel visibility and a model that follows the money as quickly as fraudsters do. Nasdaq Verafin is built to support that approach by helping institutions see more of the fraud journey sooner, reduce false positive noise and act with greater confidence and speed before funds leave.
Listen to the full CBA webinar to learn more about the cross-channel signals, intelligence and defense strategies discussed in this article.
FAQs
Why is check fraud often more than a check problem?
A fraudulent check can be the entry point to a larger scheme in which funds move through P2P, ACH, wire or other channels. When deposit, payments, digital and fraud teams operate separately, each may see only one stage of that movement. Connecting customer, account, device and payment signals helps analysts reconstruct the full attack and identify where intervention is still possible.
What signals can help identify broader fraud risk?
Useful signals span three areas: account context, such as account age and recent profile changes; behavioral context, such as unusual device activity; and transaction context, such as deposit behavior, new beneficiaries and first-time outbound payments. External intelligence about the account or counterparty can add risk context beyond the institution’s own data.
How can financial institutions improve their response to check fraud?
Start by mapping the complete fraud journey from deposit through cash-out. Then connect deposit and payment data, identify signals trapped in separate systems, and measure losses across the lifecycle rather than assigning them only to the channel where they appear.
How does consortium intelligence support fraud detection?
Consortium intelligence helps institutions recognize risk that may be invisible within their own customer base. By revealing suspicious counterparties, repeated behaviors and patterns observed across organizations, it can help analysts identify a broader scheme earlier and make a better-informed decision before funds move.
About the Author
GREG WILLIAMSON
Head of Fraud Commercialization Strategy
Greg Williamson is Head of Fraud Commercialization Strategy at Nasdaq Verafin and a seasoned leader in financial crime prevention, with more than two decades of experience across fraud, identity and authentication. Specializing in fraud strategy and analytics, cyber fraud prevention and the development of enterprise-scale identity and authentication solutions, Greg has held senior leadership roles at PNC Bank, Prudential, JPMorgan Chase, and Mastercard. Prior to joining Nasdaq Verafin, Greg led fraud reduction initiatives at the Bank Policy Institute, collaborating with industry leaders to advance policies, operational practices, and best practices in combating financial crime. He holds both a bachelor’s degree in Economic Crime Investigation and a master’s degree in Economic Crime Management from Utica University, and has also contributed as an adjunct instructor in economic crime studies, bringing a strong academic foundation to his practical, industry-driven perspective.
