AI Power to Combat Fraud

Online fraud is always changing, so should your prevention strategies!

Veri-id harnesses advanced AI models to evaluate fraud risk and intelligently adapt to the specific and evolving threat landscapes of your business.

Insightful User Devices

Veri-id goes beyond standard user data, analyzing device information to uncover suspicious behaviors that may indicate fraud, whether from individual attackers or coordinated fraud rings.

Customizable Risk Rules

Empower your business to make precise risk decisions by setting customizable rules and thresholds, giving you full control to tailor fraud prevention to your unique risk profile.

Unveil Fraud From Device Fingerprints

Capturing up to 100 device attributes, the Fraud Detection System creates distinctive fingerprints to detect abnormal browsing from untrusted devices.
Device Type
Mobile
Location
Asia/Singapore
Webdriver
Not Detected
OS
iOS 18.5
AI Risk Level
0.85-Normal
Emulator
Not Detected
IP Address
119.8.184.250
VPN/Proxy
Detected
Tor lP/Browser
Not Detected

Detecting Suspicious Access

Not only detecting account access, the System also assesses how suspicious is the traffic behavior behind every account.
Single Device-Abnormal
Number of Visits
Single IP Address-Abnormal
Number of Visits
Single device acting as multiple & switching IPs

Adaptive Rule Settings for Risk Control

Combining AI-powered risk scoring and contextual rules to enable smarter, safer, and more responsive fraud prevention.
Low Risk Scenario
  • Al Score > 0
  • +
  • Within 30 minutes
  • Same device, Same account
  • > 1 sucessful authentication
  • Transaction amount < 3,000
Automated Approval
High Risk Scenario
  • AI score < -0.5
  • VPN in use
  • +
  • Within 20 Minutes
  • Same device, Different account
  • > 5 failed transactions
Decline/ Review

Unmasking Abnormal Device Relationship

In this scenario, the Fraud Detection System looks into the relationship between one single device accessing different accounts through changing IP Adresses.

Unmasking Abnormal Device Relationship

Once a device is confirmed as fraud, an entire fraud ring may be revealed through devices,
IP addresses, and account mapping.

Fraud Analysis

Step 1: Confirmed Fraud Detected
Device 1 identified as fraudulent.
Step 2: IP Traced
Found links from Device 1 to IP 1 and IP 2.
Step 3: Account Correlation
Accounts accessed via Device 1 or traced IPs are identified.
Step 4: Suspicious Connections
Devices sharing IPs or accounts flagged.
Further Review Required
Devices 1, 2, 3 are marked for deeper investigation.

Fraud Analysis

Step 1: Confirmed Fraud Detected
Device 1 identified as fraudulent.
Step 2: IP Traced
Found links from Device 1 to IP 1 and IP 2.
Step 3: Account Correlation
Accounts accessed via Device 1 or traced IPs are identified.
Step 4: Suspicious Connections
Devices sharing IPs or accounts flagged.
Further Review Required
Devices 1, 2, 3 are marked for deeper investigation.

Fraud Analysis

Device-Account Links
Devices 1-6 are simultaneously accessing Accounts 1-2.
IP Patterns
All devices are using IP 1, IP 2, IP 3,noting that they are located within close proximity.
Fraud Insight
When many devices share the same IPs and cross-access the same accounts, it's a potential sign of coordinated fraud.

Fraud Analysis

Device-Account Links
Devices 1-6 are simultaneously accessing Accounts 1-2.
IP Patterns
All devices are using IP 1, IP 2, IP 3,noting that they are located within close proximity.
Fraud Insight
When many devices share the same IPs and cross-access the same accounts, it's a potential sign of coordinated fraud.

Fraud Prevention for Online Business

With Veri-id, institutions know the risks behind each user through their browser or app activities.
This data allows instant detection of suspicious behavior or untrusted devices without user experience interruption.

Whether the cardholder is making transactions through a browser, mobile application,
or merchant site checkout, fraudulent behaviors can be spotted in real-time.

Whether the cardholder is making transactions through a browser, mobile application,or merchant site checkout, fraudulent behaviors can be spotted in real-time.

Effectively detecting

Account takeover

Bot attacks

BIN attacks

Chargeback fraud

Card testing

Phishing attacks

Quickly identify and mitigate fraud risks in online credit card transactions and merchant back-end portal account logins.

Effectively detecting

Account takeover

Bot scripts, crawling

Account data theft

Device spoofing

Card testing

Phishing attacks

Online merchants often require consumers to log in for purchases or membership management,
let Veri-id safeguard your user accounts from unauthorized access and beyond.

Online merchants often require consumers to log in for purchases or membership management,let Veri-id safeguard your user accounts from unauthorized access and beyond.

Effectively detecting

Credential stuffing

Account takeover

Promo abuse

Device spoofing

Account testing

Phishing attacks

If your business operates an online platform with member accounts, your login systems are always at risk of fraud attack,
especially if you also process payments or store card information.

If your business operates an online platform with member accounts, your login systems are always at risk of fraud attack,especially if you also process payments or store card information.

Effectively detecting

Credential stuffing

Account takeover

Brute force

Device spoofing

Transfer fraud

Phishing attacks

Interactive Risk Intelligence Portal

Empower your team with actionable risk insights at a glance.

Daily Authentication Results

Total Transaction Volume

4,522,391

Distinct Payment Cards Used

1,860,132

Transactions with Device Fingerprint

251,911

Number of Distinct Devices

150,880

Customer Geographic Coverage

183

Number of Distinct Merchants

173

Daily Authentication Results

Authentication Outcome Breakdown

Transaction Status Volume Percentage
Y 3,402,302 67.60%
N 736,877 16.37%
Nan 496,584 11.03%
A 68,326 1.52%
R 68,315 1.45%
C 54,689 1.22%
U 36,250 0.81%
Total 4,500,343
Explore more