Stop Fraud

STOP FRAUD

Fraud prevention in the credit and financial sector, insurance and logistics based on a face recognition system

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Fraud prevention

Incident investigation

Indemnification

Preventing recurrence of fraud

Capabilities

EVENTS ARCHIVE

Large anonymized event archive

SEARCH AND COMPARISON

Convenient search and event filtering

MATCH IDENTIFICATION

Quick search for similar faces in the current database

BEST TECHNOLOGIES

Ability to recognize faces and text even on low-quality photos

UPDATING

Real-time information updates

INCIDENT MODEL

Information on accomplices based on identified incidents

Applications

FINANCIAL AND CREDIT

LOGISTICS

INDUSTRY

How does it work?

Stages of identity verification

The solution ensures exceptional accuracy and reliability through 3 stages of identity verification:

DATA ENTRY

IMAGE COMPARISON

SOURCE SEARCH

Results

AUTOMATION AND TRANSPARENCY OF PROCESSES

REDUCTION OF LOSSES FROM UNFRIENDLY PRACTICES

PREDICTABLE EFFECT

SECURITY

Stop-Fraud

The Information and Analytical System "Stop-Frod" is a tool that reduces the risks of interacting with unreliable counterparties by comparing their data with an accumulated database of fraudsters and related incidents. This solution optimizes the tasks of screening job candidates and customers before providing services due to its high data processing speed.

Technologies

The IAS operates based on a combination of the following methods:

Search for information using both application data (full name, passport, phone) and photographs. The system cross-references information from all available sources to obtain accurate results.

The system consolidates all instances of fraudulent activity associated with a specific person into a single profile. This allows you to see the complete threat picture, rather than isolated facts.

Verification of document photos for signs of tampering, erasures, or image replacement, preventing fraud with fake IDs.

The system allows cross-comparison of multiple photographs even when image quality varies.

Real-time photo and video analysis to recognize a live person and distinguish them from a mask, photograph, or video. Approximate age is also estimated, serving as an additional verification factor.

Ability for operational interaction between system users for rapid response to a new incident.

Application area of IAS "Stop-Frod"

The system is in high demand in finance, logistics, and other business sectors where companies are interested in ensuring security when hiring trustworthy employees and working with reliable customers and contractors.

IAS "Stop-Frod" easily integrates with any IT systems and information databases, allowing comprehensive cross-verification to be performed automatically in a short time. The solution features an advanced API that enables integration with any corporate systems and services, automating the processing of incoming requests. Its distributed architecture ensures operation under high-load conditions with a large number of requests. The extensive use of neural networks for both text query processing and image analysis takes request processing, text recognition, and document examination for signs of graphical manipulation to a new level.

The system fully complies with the legislation of the Russian Federation in the field of information security.

Financial and credit

Logistics

Industry

Popular questions

The "Stop-Frod" system uses multi-factor analysis to prevent fraud:

Search and verification against application data.
Use of advanced algorithms for image similarity assessment (face matching).
Liveness check (confirming that a live person is in front of the camera, not a photo or mask) in real time.
Cross-referencing against internal and shared incident databases to identify matches with known fraudsters.
Automatic monitoring that notifies when new negative events related to the verification subject appear.

Yes, the system is equipped with an AI-based document recognition module. When a photo or scan of a document is uploaded, the AI conducts an in-depth analysis: checks the integrity of security elements, identifies signs of retouching, photo replacement, or font inconsistencies, and then outputs the percentage probability of document authenticity.

Yes. Due to the high level of neural network training on specific datasets, the "Stop-Frod" system demonstrates high recognition accuracy even when working with low-resolution images, poor lighting, or digital noise.

Financial sector: Banks, MFOs (microfinance organizations) and MCCs (microcredit companies) – preventing credit fraud.
Logistics and transport: screening drivers and forwarders to prevent cargo theft.
HR security: in-depth screening of candidates for critically important positions regarding possible involvement in fraudulent schemes in the past.

Currently, the information perimeter of the "Stop-Frod" system includes several tens of millions of records, ensuring high representativeness when searching for connections and identifying patterns of fraudulent behavior.

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