How will AI impact payment technologies and the larger fintech landscape? Shai Gabay, CEO at Trustmi weighs in with a few perspectives:
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Hi Shai, tell us about Trustmi’s latest AI enhancement and how it enables end users?
Recently, Trustmi introduced the AI Investigation Agent, an investigation engine for payment-centric digital forensics. It reconstructs a suspected fraud incident in minutes, not days. The AI Investigation Agent works automatically: it collects the evidence, runs forensic analysis across every artifact, correlates the anomalies, and explains the risk, with the evidence attached, so an analyst doesn’t have to piece it together by hand. It works inside the tools teams already use, from their security platforms to Slack, so findings show up where people are already working instead of in yet another window.
A finance approver who gets a vendor bank-change request that feels off can query the Agent directly and see the findings, in plain language, with the manipulated fields shown, instead of escalating and waiting for a technical translation. That’s the shift the Agent is built around: it reduces the need for finance teams to translate business context for technical investigators, and for security teams to reconstruct payment activity without finance expertise. Both reach a shared, evidence-backed understanding faster, and can act before fraud results in financial loss.
What are some of the top concerns regarding fraud and fraud detection across the compliance and fintech market today?
There are three challenges that the compliance and fintech industries are facing today when it comes to fraud detection: authorized fraud and social engineering, synthetic and mule accounts, and the balance of protection and client experience.
Traditional fraud controls are only designed to detect unauthorized activity but today’s modern fraud campaigns can be authorized with legitimate bank accounts or a legitimate customer and vendor account. This creates a difficult detection problem because transactions can look completely legitimate based on traditional signals. In fact, Trustmi’s research found that 92% of incidents began with impersonation of a trusted finance authority, vendors, or executives. For CFOs and CISOs, the implication is clear: modern fraud is no longer engineered simply to fool people. It is designed to pass through security and payment workflows without being stopped. Every payment must be validated across identities, documents, and workflows continuously and in context, from initiation through execution.
Beyond impersonation, fraudsters can create synthetic and mule accounts to slip in undetected. This is done by using synthetic identities and stolen credentials to establish accounts and build credibility. They are also increasingly moving funds through mule networks that are coordinated channels of bank accounts that are used to move money by cyber criminals. This means that client onboarding and point-in-time KYC is becoming less effective on its own. Fintechs increasingly need continuous identity and behavioral monitoring to detect when a legitimate-looking account begins exhibiting characteristics associated with fraud. Lastly, fintechs need to balance fraud prevention with customer experience. Aggressive fraud controls can introduce more friction in customer workflows and processes. This means that there needs to be more real-time risk decisions that can determine genuinely suspicious behavior from legitimate but unusual customer activity.
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Since AI is used both to cause and prevent fraud, financial institutions must be a lot more cautious and focus on developing the right AI expertise within their organizations to build better AI protocols for tackling rising fraud. What are the best steps to take?
It is imperative for today’s finance professionals to expand their knowledge of generative AI technologies to keep pace with developments in the market. There are different uses of AI, for both bad and good use of AI, and finance teams can leverage AI tools in the B2B payment process to protect their bottom line.
AI leaders in fintech should understand how AI, fraud, compliance, and cybersecurity blend together and that AI fraud prevention is not Soley a technology challenge. These leaders should be well versed in how fraudsters are using AI, how detection tools need to be modernized to keep pace, and where these models and tools can create blind spots and vulnerabilities. These systems and processes need to be well aligned with evolving regulations and governance requirements.
These teams should not assume that an AI model that works well today will be successful next week. Defenders need to mimic how fraudsters are adopting advanced technologies and adopting sophisticated techniques. Therefore, AI leaders need to continuously test models for accuracy, false positives, bias, explainability, model drift, and adversarial attacks. There also needs to be clear processes for making the necessary changes to the model.
Lastly, AI leaders make sure that their AI models have strong data and context backing it up. Models should be connected to identity, device, behavioral, and transactional signs in order to give LLMs the full picture. The Federal Reserve’s 2026 discussions specifically highlighted greater fraud-data sharing, public-private partnerships, and standardized due diligence and validation of AI technology providers as potential ways to improve defenses against AI-enabled fraud.
What payment technologies (PayTech) are making waves across the global fintech market today?
There are a handful of payment technologies that are making waves across the global fintech market: real-time payments, A2A infrastructure, embedded payments, and fraud prevention. Companies are transitioning from fragmented, manual processes and toward automated, integrated platforms that enable faster and safer payments and allow for greater visibility and more efficient cross-channel transactions.
At the same time, the fintech market is being majorly overhauled by fraud prevention. Business email compromise, social engineering, and vendor impersonation are the driving tactics modern fraud attackers are using to layer their playbooks. These tactics are forcing enterprises to implement AI-powered behavioral analytics and real-time risk scoring. The leading organizations are actually embedding these capabilities directly into payment workflows in order to identify and respond to fraud campaigns before money moves.
Together, these developments are pushing enterprise PayTech toward a more intelligent, integrated, real-time, and secure payment ecosystem, where fraud prevention is built into the infrastructure rather than treated as a separate layer.
AI and fintech and payments: what will redefine the future scope of this landscape?
The next phase of fintech will be defined by the convergence of AI, payments, and real-time risk intelligence. As payments become faster and embedded in automated workflows, that speed can create a vulnerability, traditional rules-based fraud identification is not designed for an environment where transactions happen instantly, and fraudsters can pivot quickly. Security and finance leaders will need to start understanding behaviors and patterns and not just simply checking transactions against rules.
Behavioral AI will become a critical layer of payment infrastructure. AI can instantly flag when there are anomalies in communications, documents, and transactions. A subtle deviation that today’s fraud prevention systems may allow to slip under the radar would be immediately identified and flagged by AI. These deviations could include an unusual payment pattern, a compromised account, or a sophisticated social-engineering attack. AI can not only react to known fraud signals but also predict and prevent emerging attacker strategies as they evolve.
AI will redefine fintech by making trust as intelligent and dynamic as the payments themselves. The leading companies will be able to deliver frictionless experiences while also ensuring these payment safety guardrails are a strategic component of their solutions, building the next generation of financial infrastructure.
What final thoughts would you leave everyone in fintech with before we wrap up?
If there’s one thing I’d leave everyone with, it’s that the future of fintech isn’t just about making payments faster and smarter, it’s about building the intelligence and trust to make them safer, too.
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By stopping fraudulent payments before funds are transferred, Trustmi helps businesses safeguard their revenue and build trust in every transaction.
Shai Gabay, is CEO at Trustmi
