Question 1

What is the best deepfake detection for banks and financial institutions?

Accepted Answer

The best deepfake detection for a bank is one built for financial workflows rather than generic media screening: real-time voice analysis for call centers, image forensics for KYC documents, video verification for remote authorization, plus the audit trail regulators expect. FalsiFind was designed around exactly these requirements, with signed evidence bundles for examinations, tenant-specific detection thresholds, SAML integration, and a privacy-by-design architecture that never stores customer media.

Question 2

Does FalsiFind offer a deepfake detection API?

Accepted Answer

Yes. FalsiFind is API-first: a low-latency REST API scores voice, image, and video media and returns a confidence score with an evidence payload, and webhooks push detection events into your case-management or fraud-orchestration stack. A typical integration takes one to two days, with no on-premise hardware required.

Question 3

How do you detect deepfakes in KYC and video onboarding?

Accepted Answer

Deepfakes reach KYC in two ways: manipulated identity documents and synthetic faces in selfie or video checks. FalsiFind analyzes submitted images for manipulation indicators such as EXIF metadata inconsistencies, edge transition anomalies, and frequency-domain artifacts, and screens video verification streams for face swaps and re-enactment. Suspicious applications are flagged with a confidence score so they can be auto-rejected or routed to enhanced review without slowing down legitimate onboarding.

Question 4

What is voice deepfake detection software and how does it work?

Accepted Answer

Voice deepfake detection software analyzes audio for the acoustic artifacts left by speech synthesis and voice conversion models, rather than comparing a caller to an enrolled voiceprint. That distinction matters: a good clone can defeat voice biometrics, but it still carries generation artifacts. FalsiFind analyzes live call audio in real time and flags synthetic speech within about 700 milliseconds, before a fraudster can complete an account change.

Question 5

Can deepfake detection run in real time on live calls?

Accepted Answer

Yes. FalsiFind's streaming analysis scores call audio continuously during the conversation, not after it ends. The first useful risk signal arrives in roughly 700 milliseconds, which lets call-center systems escalate, challenge, or terminate a suspicious call while the caller is still on the line.

Question 6

How does deepfake detection fit into an existing fraud stack?

Accepted Answer

Detection works as a scoring step inside the workflows you already run. Your ingestion layer calls the FalsiFind API at the moment of risk — account opening, a support call, a payment authorization — and routes the returned confidence score into your existing rules engine or case-management queue. Webhooks can automatically freeze withdrawals, require step-up verification, or open a review case.

Question 7

Is FalsiFind suitable for regulated, bank-grade environments?

Accepted Answer

FalsiFind was built for regulated financial institutions: SOC 2 Type 1 readiness and ISO 27001 alignment are in progress, SAML SSO integrates with enterprise identity providers, and every detection generates a cryptographically signed evidence bundle that documents your verification process for examiners. Media is processed in memory and never stored, supporting GDPR and GLBA data-minimization obligations.

Question 8

What does a detection confidence score mean, and how should we act on it?

Accepted Answer

A confidence score expresses how strongly the analyzed media exhibits signs of synthetic generation. Rather than a binary real/fake verdict, it lets you set thresholds per workflow: a high-value wire authorization can trigger review at a lower score than a routine balance inquiry. FalsiFind supports tenant-specific thresholds so each institution tunes the trade-off between fraud catch rate and customer friction.

Deepfake Detection FAQ

Frequently Asked Questions

Still evaluating deepfake detection?

Your privacy matters