Defending Against AI Fraud — Without Letting 

Customer Data Leave Your Network

Generative AI has made deepfakes cheap, fast, and dangerously convincing. With open-source tools and large AI models, a high-quality voice clone or a real-time face-swap can now be produced in minutes, at almost no cost. For banks and insurers, this has opened a new front in financial crime — one that traditional liveness checks and manual review can no longer hold on their own.

EmbedWay delivers a financial-grade, fully on-premise deepfake detection solution that lets institutions fight AI-driven fraud while keeping every piece of sensitive customer data inside their own network.

The Dual Challenge Facing Finance

Financial institutions today are caught between two opposing pressures:

• Surging AI fraud. Deepfake-enabled attacks are rising sharply in both frequency and sophistication. Synthetic faces and cloned voices can defeat conventional eKYC liveness checks (blink, nod, turn), and increasingly support real-time, interactive deception.

• Strict data-protection obligations. At the same time, institutions are bound by demanding data-residency and personal-data protection requirements. Customers' biometric data — their faces and voices — cannot simply be uploaded to a third-party cloud for analysis.

This creates a genuine paradox: institutions need powerful AI to detect forgery, yet they cannot send the very data that detection requires outside their controlled environment.

Why Existing Tools Fall Short

Single-modality detection is no longer enough. Looking at an image alone, or analyzing audio alone, is readily defeated by today's multimodal AI attacks.

Public-cloud SaaS is a compliance dead end. Many deepfake detection tools operate as public-cloud services, requiring institutions to transmit high-resolution customer video and images off-network for analysis. This introduces high latency, creates a serious data-leakage risk, and — critically — cannot pass the compliance review of a bank or insurer.

The result is a gap that conventional solutions cannot close: effective detection that is also fully compliant.

Two Critical Battlegrounds

Banking — Identity Forgery

Deepfakes are used to bypass an app's eKYC liveness checks, creating "ghost accounts" during remote onboarding. The attack chain extends well beyond account opening into high-risk scenarios such as large-value transfers, dormant-account reactivation, and password resets, enabling precise, targeted theft.

The EmbedWayadvantage:

• Protect core assets. Intercepting even a fraction of deepfake attacks can prevent enormous financial losses and reputational damage.

• Augment your existing systems invisibly. There is no need to replace your current face-recognition provider. EmbedWaydeploys as an "invisible anti-forgery shield" layered on top of what you already run — preserving a smooth experience for genuine users (conversion stays high) while sharply reducing fraud.

Insurance — Evidence Forgery

In auto and property insurance, fraud rings use AI image tools to fabricate realistic collision or flood photos and to alter loss-assessment videos. In health and medical insurance, AI is used to manipulate electronic 
invoices, diagnostic reports, and even patient injury photos — pixel-level tampering that human reviewers cannot reliably detect by eye.

The EmbedWay advantage:

• Directly improve your Combined Operating Ratio (COR). By accurately identifying AI-generated claims materials, EmbedWay plugs the payout leakage caused by fake evidence — strengthening underwriting profitability.

• Enable confident automated claims. Machine-speed authenticity checks give insurers the confidence to expand straight-through claims processing, reducing manual-review costs while improving efficiency.

The EmbedWay Solution: A Financial-Grade, Localized Authenticity Defense

EmbedWay is built to resolve the core dilemma — strong protection and no data leaving your network — through three core strengths.

1. Privacy-First On-Premise Deployment

The models and system are deployed entirely within the institution's own network. All sensitive audio, video, and image data stays fully on-premise across the entire processing chain, aligning with stringent datesecurity and data-residency requirements. The solution also supports localized server and compute-chip environments for institutions with domestic infrastructure mandates.

2. Multimodal Detection Model 

A purpose-built large model fuses spatial pixel-level analysis, frequency-domain signal features, voiceprint liveness, and temporal consistency to comprehensively detect face-swaps, voice clones, and AI-generated (AIGC) imagery — closing the gaps that single-mode tools leave open.

3. High Concurrency, Ultra-Low Latency

Built for real-world peaks — major banking campaigns and seasonal claims surges — the on-premise cluster delivers millisecond-level response, ensuring a seamless experience for end users even under heavy load.

Easy Deployment, Stay Competitive

Lightweight integration. EmbedWay provides an SDK/API integration model, enabling internal integration with your existing app, mini-program, or business systems — typically within weeks.

Continuous defense. Even with a fully on-premise deployment, EmbedWay delivers regular offline update packages for feature libraries and model parameters, ensuring your defenses stay ahead of the newest open-source deepfake algorithms.

Don't Trade Data Security for Fraud Protection

Defending against AI forgery should never come at the cost of customer data security. With EmbedWay, financial institutions get both: an uncompromising security perimeter and zero compliance risk.

Does your current defense meet the latest data-residency requirements?

Contact the EmbedWay expert team to schedule an On-Premise Deepfake Attack-and-Defense Demo and receive a tailored financial anti-fraud architecture assessment.