> For the complete documentation index, see [llms.txt](https://docs.vida.id/identity-stack/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.vida.id/identity-stack/online-fraud-detection/overview.md).

# Overview

**Identity fraud** during onboarding is a significant global issue, leading to substantial financial losses each year. The challenges posed by fake identities, altered documents, and unauthorized account usage are considerable. Implementing a robust system for fraud assessment is crucial to ensure compliance, enhance security, and maintain customer trust.

As a certified PSrE in Indonesia to issue digital identities to end users, we utilize our expertise in artificial intelligence and apply our proprietary algorithms and machine learning technologies to offer a comprehensive suite of features designed to mitigate risks and protect your customer identities.

VIDA offers a comprehensive fraud detection suite that combines **Deepfake Protection**, **Biometric Data Mitigation**, and **Data Control** to safeguard digital transactions and identity verification processes. By integrating our fraud assessment technology into your workflows, you can enhance security measures, minimise risks, and protect your organisation's interests.

Within this documentation, you will find details about the product offering, which includes

### **Deepfake Protection** 

VIDA’s liveness detection solution is positioned as a defense against deepfake threats. It ensures that only real, live individuals can successfully pass identity verification processes. This solution comes in two forms:

1. **Deepfake Shield (SDK-Based)**
   * **Deepfake Shield** is an SDK-based solution that integrates into mobile apps (Android and iOS). It leverages both **Active** and **Passive Liveness Detection** methods to authenticate users.
     * **Active Liveness**: Requires users to perform specific actions like blinking, smiling and head shaking. ensuring real-time presence and deterring spoofing attempts.
     * **Passive Liveness**: Analyzes user selfies in the background without requiring any interaction, offering a seamless and frictionless experience for users.
   * **Anti-Spoofing Mechanisms**: Protects against various spoofing attempts, including mask, screen, and injection attacks.
2. **Deepfake Defender (API-Based)**
   * **Deepfake Defender** is an API-based solution designed to integrate with web or backend systems. It performs real-time liveness detection during user verification processes.
     * **Efficient Liveness Detection**: Assigns a liveness score to each selfie, ensuring authenticity and flagging any potential fraud.
     * **Spoof Detection**: Identifies attempts to use photos, videos, or other manipulated media to bypass verification processes.

### **Biometric Data Mitigation**

VIDA’s fraud detection technology goes beyond deepfake prevention by analyzing and validating biometric data. This ensures that any face, fingerprint, or other biometric identifiers are genuine and belong to the actual person being verified.

### **Data Control**

VIDA’s **Data Control** ensures that user demographic information is verified in real-time. It enhances security by cross-referencing identity data with official records and evaluating biometric data for accuracy, ensuring a secure and trustworthy identity verification process.

### **How it works**

* **Simple Integration:** Our fraud assessment solution seamlessly integrates into your existing workflows, with easy-to-use APIs and SDKs.
* **Efficient Verification:** Streamline identity verification processes with rapid and accurate assessment results, ensuring a frictionless user experience.
* **Customisable Configurations:** Tailor the fraud assessment solution to meet your organisation's specific needs with customisable parameters and thresholds.