Trustmi announced new Behavioral AI, anomaly detection, and risk-scoring capabilities to help enterprise customers combat social engineering attacks on their finance teams, payment systems, suppliers, and processes.
The new wave of sophisticated AI-driven social engineering attacks generates highly personalized and convincing messages, making it increasingly difficult for employees and traditional security measures—such as email security—to differentiate between legitimate and malicious communications.
These attacks have a singular focus: targeting finance teams and executives with access to funds to facilitate theft. According to the latest Verizon Data Breach Investigations Report, 95% of social engineering attacks were financially motivated.
The latest FBI IC3 report revealed that cybercrime losses exceeded $12.5 billion in 2023, with Business Email Compromise (BEC) alone accounting for $2.9 billion. But these attacks have evolved far beyond email, targeting the entire financial ecosystem.
Cybercriminals now use AI-generated trusted app scams, CXO deepfakes, and sophisticated impersonation techniques to manipulate finance teams, suppliers, and executives. By mimicking voices, writing styles, and even real-time video, attackers can convincingly pose as trusted individuals, bypassing traditional security controls and enabling large-scale financial fraud.
“Attackers are increasingly manipulating trusted individuals within organizations and among vendors using a new AI-powered toolkit. Coupled with massive, complex processes and siloed operations, businesses encounter a perfect storm of vulnerability,” said Shai Gabay, co-CEO of Trustmi. “Our emphasis on safeguarding payment processes has allowed us to observe this rapid evolution. By integrating continuous monitoring, anomaly detection, and automated risk scoring, Trustmi’s behavioral AI provides a powerful layer of protection that directly addresses the human and psychological factors at the core of social engineering attacks.”
Trustmi’s new capabilities empower enterprise customers by integrating a behavioral AI engine with three data layers—vendor, employee/user, and payment fingerprint—to produce a comprehensive, contextual risk score tailored to roles with access to funds, such as finance teams and executives. Instant risk scoring prioritizes high-risk cases for immediate review.
By integrating with various systems, Trustmi holistically evaluates threats, concentrating on bad actors’ primary goal of stealing money. It adapts to complex schemes and enhances detection using contextual data specific to financial transactions.
“What concerns me right now are elements outside my control, such as a compromised vendor. Our company, people, and systems may be secure, but someone else’s issue becomes my problem if a bad actor can access our systems via a compromised vendor. The complexity of threats has advanced dramatically over just a few years,” said Yuval Levinson, VP of Finance at AppsFlyer.