Serial Fraud Monitor
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70% of serious fraud cases slip through regular identity verification checks
Powered by advanced neural networks, AU10TIX’s award-winning Serial Fraud Monitor has identity intelligence designed to combat coordinated traffic-level attacks, helping you to stay ahead of the game and ensure the safety of your business.
Monitor subtle fraud patterns and behaviors, moment-by-moment at a live-traffic level
Saving organizations an average of $5 billion annually
Identity intelligent systems save money by automating verification, reducing fraud, and cutting operational costs. Faster, more accurate detection prevents costly breaches, ensures compliance, and streamlines onboarding for efficient scaling.
Advanced Neural Network Technology
Highly accurate fraud detection, leveraging machine learning and AI mechanisms to recognize even the most sophisticated synthetic fraud.
Deepfake Detection
Detect deepfakes by analyzing behavioral patterns, anomalies, repetitions and conflicts.
Traffic-Level Fraud Analysis
Real-time fast reaction and insights that detect fraudulent activity based on incoming and historical traffic patterns.
Consortium Validation
Reputation scoring and data cross-checking in a consortium, utilizing millions of data points.
Comprehensive Data Tracking
Tracks over 20 visual, data, and non-data vectors, such as background and geolocation, providing robust validation.
On-Demand Fraud Detection
Check existing data blocks to identify fraudulent accounts and prevent existing threats.
Experience the unmatched strength of AU10TIX’s Serial Fraud Monitor
Synthetic
Fraud
Detection using
advanced neural
network technology
Predictive Modeling
and Decision-Making
Based on pattern
recognition and
repetition analysis
24/7
Protection
Continuous
monitoring with a
feedback loop
Consortium
Validation
Reputation scoring
and data crosschecking
Related resources
Streamlined customer onboarding for a leading financial Institution
Partnering with Au10tix, the financial institution revolutionized their customer onboarding process. With streamlined workflows and cutting-edge technology, they achieved faster verifications, improved customer satisfaction, and ensured compliance with regulatory requirements.
Take It From Our Customers!
Fiverr found AU10TIX’s support impeccable. Their regular communication about technical changes, deployments, and any potential downtime ensured a seamless partnership. Working closely with the Customer Success Managers and their proactive availability, even in the same country, made the experience smoother.
Liat Shefer Cohen, Director of Trust and Safety
Fiverr
We are excited for AU10TIX to take our company’s technology vision to the next level, enabling business growth for merchants and a secure shopping experience for millions of ShopBack Pay and PayLater users, whether it be in-store or online.
Hamish Moline, Managing Director of Financial Services
ShopBack Pay
AU10TIX was the obvious choice for us to partner with thanks to their demonstration of unmatched speed and fully automated ability to detect complex fraud attempts that were unexpected by other verification providers. We are excited for them to take our verification capabilities to the next level.
Manette Domingo, General Manager
AllEasy
Microsoft plans to include the Reusable ID technology in its third-party onboarding flow to streamline repeated validation of user identity verification at critical steps while preventing fraudulent activity and ensuring regulatory compliance.
Deepak Marda, Senior Product Manager
Microsoft
Aspire Global has enjoyed strong collaboration with AU10TIX for years, so we felt the logical next step was to expand the service to our full portfolio of companies.
Rinat Belfer, COO
NeoGames
AU10TIX is the go-to identity verification solution for the hospitality industry, with a client base that includes the biggest names in the sector.
Ben Sand, VP of Global Operations
Guesty
AU10TIX’s strategic collaboration with Microsoft in the decentralized identity space and their impressive track record of client satisfaction underscores their ability to deliver impactful solutions.
Deepali Sathe, Senior Industry Analyst, Cybersecurity
Frost & Sullivan
Collaborating with AU10TIX empowers businesses to verify information at scale while ensuring users have greater control over their personal information.
Sue Bohn, Partner Director Program Management
Microsoft
Last year, we partnered with identity verification company AU10TIX, to integrate its facial recognition technology to verify the identities of customers and new merchants. Deploying such technology has enabled us to counter the growing threat of fake identification documents that criminals are using to scam merchants and payment platforms.
Nadav Naaman, Chief Product Officer
PayU
Integration made simple
Quickly integrate AU10TIX solutions with your existing systems using our flexible, low-code tools. From API and SDKs to WebApp integration, we offer multiple options to suit any business need and use case.
4-click
integration tool
Reduce integration time to from days to hours
Pre-built
user interface
Ready-to-use web and mobile interfaces for enhanced UX
Simplified
JSON
Easy-to-read JSON with data grouping for clearer representation
Real-time
support
24/7 assistance to ensure smooth implementation
FAQs
What is identity intelligence and how does it improve fraud prevention?
Identity intelligence uses advanced algorithms and data analytics to verify identities in real-time, detecting anomalies and fraudulent patterns, helping businesses prevent identity fraud before it occur
How does deepfake detection technology work in protecting businesses?
Deepfake detection leverages AI to analyze visual and audio data for signs of manipulation, such as inconsistencies in facial movements or audio mismatches, ensuring that only genuine identities are verified.
What is synthetic fraud, and how can identity intelligence systems detect it?
Synthetic fraud occurs when fake identities are created using a mix of real and fabricated information. Identity intelligence systems detect these by analyzing behavioral patterns, cross-referencing data, and identifying unusual inconsistencies.