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Description
Bynn is an innovative platform focused on identity verification and fraud prevention, employing artificial intelligence to enhance compliance processes such as KYC, KYB, and AML by seamlessly validating individuals and organizations worldwide with real-time assessments of risk. The platform is capable of recognizing and extracting information from a vast array of over 14,000 types of identity documents from more than 200 nations, integrating live document capture, accurate face matching, and liveness detection techniques to counteract deepfakes effectively. Furthermore, it utilizes AI-driven forensic methods to uncover any signs of manipulation, forgery, or synthetic identities. The automation extends to business verification as well, simplifying the onboarding of entities through intelligent document ingestion, ownership verification, and automated compliance decision-making, while also providing the option for human oversight when necessary. Bynn ensures continuous AML screening, identifies proxy and anonymous IPs, verifies ages and utility bills, and implements a sophisticated customer risk profiling mechanism to thwart evolving fraudulent activities, all while enhancing conversion rates by minimizing unnecessary drop-offs during the verification process. This comprehensive approach allows businesses to remain agile in the face of changing compliance demands and emerging threats.
Description
An accessible platform that incorporates cutting-edge methods for detecting deepfakes is available for use. Users can upload a single video file from their computer at a time. Deepfakes, which are AI-generated fabricated media, can create misleading representations of individuals and their actions, posing significant risks when misused. The DeepFake-o-meter, created by the UB Media Forensics Lab, is an open-source tool designed to identify deepfake technologies created by third parties. It offers a user-friendly service that allows for the analysis of deepfake content using various advanced detection techniques, ensuring that results are delivered securely and privately. Additionally, it features an API framework that enables developers to integrate their deepfake detection algorithms and execute them on a remote server. Furthermore, it serves as a valuable resource for researchers in digital media forensics, providing a platform for assessing and benchmarking the effectiveness of different detection algorithms against one another. This multifaceted approach ultimately enhances the fight against the misuse of deepfake technology.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Bynn
Founded
2003
Country
United States
Website
www.bynn.com
Vendor Details
Company Name
UB Media Forensics Lab
Founded
2020
Country
United States
Website
zinc.cse.buffalo.edu/ubmdfl/deep-o-meter/
Product Features
Address Verification
Address Validation
Autocomplete
Automatic Formatting
Data Cleansing
Data Discovery
Data Quality Control
Data Verification
Geographic Maps
Geolocation
Metadata Management
Reporting / Analytics
Search / Filter
AML
Behavioral Analytics
Case Management
Compliance Reporting
Identity Verification
Investigation Management
PEP Screening
Risk Assessment
SARs
Transaction Monitoring
Watch List
Fraud Detection
Access Security Management
Check Fraud Monitoring
Custom Fraud Parameters
For Banking
For Crypto
For Insurance Industry
For eCommerce
Internal Fraud Monitoring
Investigator Notes
Pattern Recognition
Transaction Approval