Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Dregs offers fraud detection solutions specifically designed for SaaS applications. By utilizing a lightweight JavaScript tracking script, it fingerprints devices and records user interactions, scoring each identity based on four key dimensions: Humanity (detection of bots and automation), Authenticity (identification of fake profiles and temporary email addresses), Uniqueness (detection of duplicate accounts linked via shared devices, IP addresses, and sessions), and Behavior (comparison of user activity against expected behaviors).
The scoring system is transparent, derived from individual observations by the analyzers that can be reviewed and adjusted, rather than relying on a vague risk score. Alerts can be configured to notify teams via a dashboard, email, Slack, or webhooks, and the implementation process is structured in four stages — Scoring, Alerts, Escalation, and Autonomy — ultimately allowing for automated responses such as rate limiting and account quarantining.
Dregs effectively addresses issues such as free-trial exploitation, fraudulent promotions and referrals, duplicate account creation, stolen credit card testing, SMS pumping, credential stuffing, and data scraping. Additionally, the setup process is user-friendly, featuring a self-serve model that includes a free trial and clearly outlined pricing options, making it accessible for teams to integrate into their operations. This comprehensive approach ensures that businesses can protect themselves against various forms of fraud effectively.
Description
In the modern era, enterprises that leverage digital transformation primarily conduct their operations online and in real-time, minimizing the need for human involvement. While this strategy significantly lowers expenses and enhances customer satisfaction, it simultaneously opens the door to substantial risks of fraud perpetrated by savvy individuals who exploit the online environment's inherent anonymity and ease of access. For instance, in the realm of e-commerce, fraudulent transactions can arise from hacked accounts and pilfered payment information. Additionally, various forms of deception may include account takeovers, misuse of complimentary trials, fake reviews for products, warranty abuses, refund scams, reseller fraud, and exploitation of discount programs. These fraudulent actions can severely impact both the bottom line and the brand reputation of the business. Unlike in the early days of the internet, today's fraudulent schemes are often executed by organized, well-funded groups of professionals who are adept at navigating online systems. The evolving landscape of cyber threats necessitates a proactive approach to safeguard against these sophisticated fraud tactics.
API Access
Has API
API Access
Has API
Pricing Details
$17/month
Free Trial
Free Version
Pricing Details
No price information available.
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
Dregs LLC
Founded
2025
Country
United States
Website
dregs.com
Vendor Details
Company Name
Microsoft
Founded
1985
Country
United States
Website
learn.microsoft.com/en-us/dynamics365/fraud-protection/
Product Features
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
Product Features
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