Protecting customers from SMS fraud beyond the security perimeter
CheckTxt provides security, fraud, and trust teams with shared visibility into customer-targeted attacks.
Ways to Deploy CheckTxt
CheckTxt operates beyond your current security stack
CheckTxt operates beyond internal systems, extending enterprise security into customer-facing messaging—where SMS fraud actually occurs.
Customer-facing SMS fraud protection as a managed service.
Deliver SMS fraud protection to clients without adding operational complexity. MSSPs can deploy quickly across environments, provide visibility into customer-targeted attacks, and offer immediate value with minimal support overhead.
Embedded SMS fraud detection
Integrate real-time SMS fraud detection into existing platforms and workflows. Our API enables programmatic analysis and automated response wherever SMS is sent or received, without changing user behavior.
Customer risk is owned by many teams.
Messaging-based fraud crosses all of them.
Early signals provide clarity so security, fraud, and trust teams act earlier
Customer-facing fraud doesn’t arrive neatly categorized by team. It spreads across messaging channels before any alert, transaction, or case is created. CheckTrust helps teams get ahead of that spread by providing earlier signal and shared visibility into messaging-based attacks.
1. Earlier visibility into customer-facing attacks
Suspicious messages are analyzed as customers encounter them — not after damage has already occurred. This gives teams insight into fraud attempts that would otherwise surface later through chargebacks, account takeovers, or support tickets.
2. Reduced downstream impact
By surfacing risk before transactions occur, teams can reduce fraud losses, customer confusion, and operational burden — rather than reacting after the fact.
3. Shared signal across teams
Messaging-based fraud rarely belongs to a single function. CheckTrust provides a common signal layer that security, fraud, and trust teams can all reference, reducing handoff delays and fragmented response.
4. Handles growing attack volume without increasing operational load
As AI-driven fraud and richer formats like RCS grow, teams face more noise with the same resources. CheckTrust eases this by highlighting clearer signals early, allowing teams to prioritize real risks over downstream issues.
5. Faster identification of emerging campaigns
As similar messages appear, patterns emerge quickly. Teams can identify coordinated attacks earlier, understand how they’re evolving, and take action before fraud scales across customers.
6. Clearer signal to guide action
Early signal only matters if teams know what to do with it. CheckTrust helps security, fraud, and trust teams move from uncertainty to action by providing clearer context around suspicious messages. This makes it easier to decide when to warn customers, escalate internally, or monitor emerging activity before it turns into a larger incident.
“I received a text impersonating my bank about a $2,400 withdrawal. CheckTxt analyzed it in seconds and confirmed it was a scam. It showed how messaging-based fraud reaches customers before any transaction occurs.”
How CheckTxt Stops SMS Fraud and Scams Before They Escalate
Fraud is intercepted at the customer edge in a text, email, or voice message. Suspicious messages are analyzed as they reach customers, enabling earlier detection than transaction- or complaint-based signals.
Campaigns are identified before they spread. Patterns emerge quickly as similar messages appear, allowing coordinated fraud and scam attacks to be contained before they scale.
Threat intelligence is built in real time. Every analyzed message contributes to a shared intelligence layer across channels, revealing evolving tactics and impersonation patterns.
Teams act earlier with clearer signal. Security, fraud, and trust teams gain higher-quality insight sooner, reducing losses, chargebacks, and operational burden.
As fraud scales through AI-driven operations, automated workflows, and richer messaging formats like RCS, the platform is designed to adapt, using intelligence gathered across channels to detect new patterns early.