# FAQ

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<details>

<summary>How Accurate Are the Analyses?</summary>

The accuracy of our analyses is >99%, confirmed by [NIST iBeta and NIST FRVT](/oz-knowledge/general/readme.md).

**APCER (FAR)**: 0%.

**BPCER (FRR)** (please note: the numbers below are for the portrait orientation, as the majority of the media we analyze are taken this way):

MSDK – depending on the gesture, 2.75% on iOS and 3.57% on Android for on-device analysis; 0.1-0.15% for server-based and hybrid analyses on both platforms.

Web SDK – 0.5-0.6%, depending on the gesture. &#x20;

</details>

<details>

<summary>I Use the On-Device Analyses. Why Should I Switch to Hybrid?</summary>

The hybrid analysis type is a combination of on-device and server-based types, that provides both their benefits while not having their drawbacks. If you switch to the hybrid analysis from the on-device one, the main benefit you’ll have is the **increase of accuracy**.<br>

Occasionally, the outcome of the analysis conducted on the device may be uncertain. By employing the hybrid approach, the system will merely forward the corresponding media to the server for an additional check. Should a definite result be determined on the device, no data is transmitted (configurable within the `Analysis` structure). Consequently, there will be a negligible increase in computational capacity and bandwidth usage, while simultaneously yielding more accurate results.

[To enable the hybrid mode on Android](/oz-knowledge/guides/developer-guide/sdk/oz-mobile-sdk/android/checking-liveness-and-face-biometry.md), when you launch the analysis, set `Mode` to `HYBRID`. [To do the same on iOS](/oz-knowledge/guides/developer-guide/sdk/oz-mobile-sdk/ios/checking-liveness-and-face-biometry.md), you need to set `mode` to `hybrid`. Please note: you’ll require server access. If you already have the access, the credentials remain the same.

</details>

<details>

<summary>I Use the Server-Based Analyses. Why Should I Switch to Hybrid?</summary>

The hybrid analysis type is a combination of on-device and server-based types, that provides both their benefits while not having their drawbacks. If you switch to the hybrid analysis from the on-device one, the main benefits you’ll have are:

* **reduced computational capacity**,
* **quicker analyses**,
* **decreased data transmission**.

In most cases, the on-device models can furnish you with a conclusive analysis result, so you can significantly decrease analysis time and resource usage. At the same time, the accuracy level will be similar to the server-based analysis one: whenever there's uncertainty, the system forwards the corresponding media to the server for an additional check. As for definite on-device outcomes, you have the option to configure what gets transmitted and stored on the server, ranging from the original media to nothing, based on the settings within the `Analysis` structure. Here are some figures derived from our experience:

* The customer journey is decreased by 30%.
* The necessary disk space is reduced by 2.5 times.
* The CPU usage is reduced by 2.5 to 3 times.

[To enable the hybrid mode on Android](/oz-knowledge/guides/developer-guide/sdk/oz-mobile-sdk/android/checking-liveness-and-face-biometry.md), when you launch the analysis, set `Mode` to `HYBRID`. [To do the same on iOS](/oz-knowledge/guides/developer-guide/sdk/oz-mobile-sdk/ios/checking-liveness-and-face-biometry.md), you need to set `mode` to `hybrid`. Your server access credentials remain the same.

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