Deepfake fraud in financial services is no longer just a theoretical risk. It is happening during live calls, in real time. The targets include treasury teams, bank managers, and finance staff. These individuals often struggle to distinguish a synthetic voice from a real one. Deloitte projects that AI-driven fraud losses in the United States will reach $40 billion annually by 2027. To address this challenge, a new detection platform called Diopter AI has emerged. It fills the gaps that traditional identity controls cannot cover.
Introducing Diopter AI
Diopter AI is a detection platform designed for small and mid-sized businesses (SMBs) and mid-market teams. It identifies synthetic voices, deepfake videos, and live conversation manipulation during video and voice calls. The platform evaluates every interaction in real time. It delivers a verdict before any financial decision, like a wire transfer or approval, is made. Unlike identity verification tools that focus on who is on the call, Diopter AI assesses what is happening in the conversation. It determines if the conversation is being manipulated towards an irreversible financial request.
The Growing Threat
The threat of deepfake fraud has increased significantly in the past 18 months. In 2025, deepfake-related fraud losses in the United States reached $1.1 billion. This was a significant increase from $360 million the previous year. Vishing attacks surged by 442% during the same period. In one case, a cloned executive voice call resulted in a $35 million loss for a mid-market bank. This happened after a manager authorized an unscheduled wire transfer. In another 2024 incident, a finance employee authorized 15 wire transfers totaling $25.6 million. This occurred after joining a video conference where all participants, including the CFO, were deepfakes.
Challenges with Existing Defenses
These incidents are not just failures of individual judgment. They highlight structural failures in controls designed for a world where voice impersonation required physical access. Existing defenses, such as voice biometrics and identity checks, verify who someone is at a single point in time. They do not evaluate whether a conversation is being manipulated towards an irreversible financial decision. A synthetic voice that passes these checks can still succeed in fraudulent activities.
How Diopter AI Works
Diopter AI was created to address these gaps. It monitors voice and video signals during every call in a financial team’s workflow. This includes platforms like Microsoft Teams, Zoom, Google Meet, Webex, and VoIP systems such as RingCentral, 8×8, and Dialpad. The platform evaluates the conversation as it unfolds. It scores each stage for indicators like authority framing, urgency, isolation, and escalation towards an irreversible request. When both the voice signal and the conversation arc indicate an attack, Diopter AI delivers a verdict before any financial transaction is processed.
Target Audience and Deployment
Diopter AI is specifically designed for SMBs and mid-market teams. These groups are most vulnerable to this type of fraud and have historically lacked access to enterprise-grade detection tools. For managed service providers, the platform supports multi-tenant deployment. This allows one operator to manage multiple clients from a single console.
The Future of AI-Generated Fraud
With AI-generated fraud expected to grow at a compound annual rate of 32% through 2027, financial teams using standard video and voice channels face a detection gap that identity controls alone cannot close. Diopter AI addresses this gap at the call level. It ensures that potential fraud is detected before any financial transfer is approved.
