Account creation
Review bot-driven signups, fake identities, device reuse, disposable credentials, and account-creation velocity before fraudulent accounts enter your ecosystem.
Where could you reduce fraud by 1%?
A 1% reduction might not look dramatic on a dashboard. Across year-end volume, it can mean fewer fraudulent transactions, fake accounts, chargebacks, manual reviews, and unnecessary challenges for legitimate customers.
Small improvements can have a meaningful business impact.
Fraud rarely appears as one major event. It often accumulates through smaller losses across high-volume customer flows, especially when seasonal traffic, promotions, and transaction volume increase.
A lower fraud rate can affect more than direct loss. It can reduce chargebacks, protect promotional spend, lower manual-review volume, and help fraud teams spend less time investigating activity that should have been stopped earlier.
The goal is not to add more friction everywhere. The goal is to apply the right level of scrutiny when signals indicate a user, device, transaction, or connection deserves closer attention.
A demo with IPQS is an opportunity to review the flows where your organization sees the most pressure and explore how real-time risk signals can support better decisions.
Start with the customer flows that carry the most risk.
Year-end pressure does not show up in only one place. Higher traffic and new offers can expose gaps across the customer journey, from signup through payment and account recovery.
Login and recovery
Look for credential stuffing, abnormal login patterns, unfamiliar devices, high-risk network traffic, and recovery attempts that could indicate account takeover.
Promotions and loyalty
Identify multi-accounting, referral manipulation, reward abuse, and linked activity that can drain incentives intended for real customers.
Transactions and payments
Add context from device, connection, identity, and behavioral signals before approval decisions turn into fraud loss or a chargeback.
Marketing and affiliate traffic
Filter invalid clicks, automated traffic, proxies, and abuse patterns before they consume acquisition budgets or distort performance data.
Applications and onboarding
Evaluate the digital footprint behind new customers, applicants, leads, and users before a risky identity moves deeper into your business.
Better fraud decisions depend on more than one signal.
Fraudsters can change IP addresses, emails, phone numbers, browsers, and payment details. Stronger decisioning looks at the context around the activity rather than treating one signal as a final answer.
Assess the connection
Identify risky IP addresses, proxies, VPNs, Tor nodes, hosting infrastructure, residential proxies, and other signals that can obscure a user’s origin.
Understand the device
Use device intelligence to detect repeat activity, automation, virtual machines, emulators, spoofing attempts, and patterns that persist across changing credentials.
Validate the identity data
Review email and phone reputation, disposable credentials, temporary services, and identity attributes that may be linked to previous abuse.
Apply the right response
Allow lower-risk activity to continue while routing higher-risk traffic to additional verification, review, challenge, or a block decision.
Reduce fraud without turning every user into a suspect.
The tradeoff is not simply fraud prevention versus customer experience. Risk-based controls can help teams focus additional scrutiny where it is needed and reduce unnecessary friction for users who show low-risk signals.
A single-signal approach
- Can miss connected fraud activity across devices, networks, and credentials
- May rely on stale reputation data or broad blocklists
- Can create false positives when rules are too blunt
- Often provides limited context for operational decisions
A layered risk approach
- Connects IP, device, email, phone, and behavioral signals
- Uses current intelligence to identify emerging abuse patterns
- Supports tailored responses based on risk level
- Gives fraud teams more context for automated and manual decisions
Results come from identifying the right gap in the right flow.
Every organization has different fraud patterns, volumes, and operational constraints. The value of a demo is understanding where IPQS intelligence can support a more accurate decision without adding avoidable friction.
Customer result
93%Reduction in fake accounts within 30 days
A major ISP used IPQS Enterprise Device Fingerprinting to address fraudulent account creation. The deployment handled peak enterprise traffic and reported no customer complaints during the rollout.
Enterprise result
74%Increase in bot detection
Greater visibility into virtual environments, emulators, and automated abuse patterns.
Customer experience
27%Reduction in unnecessary friction
Fewer verification steps and challenges for legitimate users in applicable enterprise deployments.
Find the place where a small fraud improvement could make a bigger difference.
Bring your highest-risk customer flow to an IPQS demo. We can walk through the signals available across IP, device, email, and phone intelligence, then discuss ways to apply them to your existing fraud decisions.
See where IPQS can strengthen your fraud decisions.
Schedule time with an IPQS fraud expert to review your use case, discuss the flows creating the most risk, and see relevant real-time risk signals in action.