Recent security incidents show that even NIST-defined “phishing-resistant” authentication methods fail when users choose weaker backup options under manipulation. Authentication verifies identity but cannot detect when legitimate users act under duress.
The financial impact escalates yearly. Despite record spending on authentication technology, authorized push payment fraud—where victims willingly transfer money under manipulation—now represents the largest portion of fraud losses globally. Banks invest billions in identity verification while criminals perfect psychological manipulation tactics.
These attacks succeed because criminals no longer need to bypass authentication. Instead, they manipulate users into choosing less secure options. Using authority bias, urgency tactics, and cognitive overload, attackers make users bypass their own security measures. The cybersecurity industry invests billions annually strengthening authentication technology while ignoring a critical question: is the user acting under their own free will? Multi-factor authentication creates false security confidence because while it verifies identity, it cannot detect duress and manipulation.
Behavioral intelligence tools close this gap by detecting anomalies that distinguish typical behaviors from manipulation-driven sessions. Combined with continuous authentication, organizations can deliver adaptive security based on identity and behavioral signals. This dual-layer approach maintains security without compromising user experience—behavioral monitoring operates invisibly while users navigate familiar authentication flows.
Consider a recent attack pattern affecting employees: criminals pose as bank fraud prevention teams, warning of suspicious international transactions. While keeping victims on the phone, attackers guide them through banking apps to “verify” identity. Every authentication method works perfectly. Fingerprints, face scans, hardware tokens all validate. Yet behavioral intelligence can detect what authentication misses: little deviation in the user’s behavior such as session durations including signs of hesitation, suspicious transactions to low-reputation payees, or the presence of an active voice call during sensitive operations.
The technology establishes behavioral baselines unique to each user. When deviations occur—particularly multiple simultaneous anomalies—the system triggers graduated responses. Minor variations prompt additional verification, major deviations freeze transactions pending review, and critical alerts trigger intervention. Some institutions have implemented subtle protocols enabling customers to signal when they’re under duress.
Organizations implementing behavioral intelligence report significant reductions in successful attacks. Financial institutions deploying behavioral tools into their intelligence stack alongside rigorous authentication methods have detected the vast majority of social engineering attempts that bypassed traditional multi-factor authentication. These systems have prevented millions in potential losses from attacks that would have succeeded because legitimate users were authenticating under duress.
Successful deployment requires organizational transformation beyond technology adoption. Institutions must shift from perimeter defense to continuous validation, integrating behavioral signals across all digital channels. Fraud teams need training to interpret behavioral indicators alongside traditional risk signals. Most critically, organizations should remain transparent about how behavioral intelligence strengthens customer protection.
Financial regulators in multiple jurisdictions are exploring behavioral analytics as a complement to strong customer authentication. Forward-thinking institutions aren’t waiting for mandates. They’re implementing behavioral intelligence now, recognizing that protecting customers from manipulation strengthens both security and business outcomes.
As generative AI makes social engineering attacks more sophisticated, security must evolve from building supposedly unbreakable barriers to protecting human decision-making through real-time intervention. The industry’s wake-up call has arrived: protecting people requires understanding behavior, not just verifying identity. As downgrade attacks prove that perfect authentication can be circumvented through psychological manipulation, the future belongs to solutions that detect not just who users are, but whether they’re acting autonomously.
About the Author
Michal Tresner is the co-founder and CEO of ThreatMark, a company transforming how banks protect their customers from fraud. What started as a bold idea to understand how people behave online, rather than rely on static controls, has grown into a platform trusted by banks worldwide. Under Michal’s leadership, ThreatMark has built technology that helps financial institutions stop scams in real time while keeping digital banking effortless for genuine users. Michal is passionate about turning complex fraud challenges into smart, human-centered solutions that restore trust in the digital world.
Michal can be reached on LinkedIn at https://www.linkedin.com/in/michal-tresner/ and at our company website www.threatmark.com
