July 21, 2025
Plaid Protect in action: Key moments to fight fraud in real-time
Fraud doesn’t follow a fixed playbook—neither should your defenses. Plaid Protect is designed to flex around your specific customer journey, delivering real-time fraud risk scoring wherever you need it most. While every business is different, there are three moments where companies often choose to integrate Protect: at sign-up, during ID verification, and when linking a bank account. Protect is also designed to complement your existing systems—working alongside your current risk models to enrich them with deeper, network-level insights and signals you won’t find anywhere else
At the heart of Protect is the Trust Index, Plaid’s adaptive fraud model that combines diverse intelligence into a single score. What makes the Trust Index so powerful is the breadth and uniqueness of the information it uses and the patterns between them that it connects:
Network intelligence: Data from a billion interactions, showing how users and devices behave across the financial ecosystem.
Advanced ID intelligence: Identity insights including data consistency, financial history, voter registration activity, legal records, and ID verification behaviors.
Bank account insight: Signals from linked accounts, such as account age, changes in contact info, or high-velocity usage patterns.
Consortium feedback: Fraud reports shared across Plaid’s customer network, allowing risk signals to travel in real-time.
As a user progresses through onboarding, Protect can tap into more insights and update the user’s Trust Index score accordingly, helping you apply the right amount of scrutiny at the right time.
Here’s how Protect fits into three key points in the customer journey.
1. At sign-up: early insight to spot fraud before it costs you
Why it's useful here: The sign-up page is your first, and sometimes only, chance to identify a risky user before they sink deeper into your funnel. By loading the frontend Protect SDK, you can instantly assess device and network-level risk the moment they begin engaging with your sign up page.
But this goes far beyond traditional device fingerprinting. Protect maps the device to fraud patterns we’ve seen before—across thousands of platforms. If that same phone, emulator, or IP has been used in account takeovers, high-velocity bank linking, or synthetic identity behavior, you’ll know instantly.
This allows you to spot known fraud patterns before they burn support hours, trigger costly verification flows, or worse—complete a fraudulent transaction.
Information collected:
Device
IP address
Integration lift:
Frontend: Load the Protect SDK
Backend: 1 API call
Timeline: ~1–2 weeks of engineering work
Ideal for:
Top-of-funnel bot and fraud screening
Preventing resource waste on fraudulent actor
Determining whether to apply friction and gather additional data
2. During identity verification: optimizing the experience based on risk
Why it's useful here: When users begin entering personal information, like their name, DOB, SSN, or address, Protect immediately becomes more powerful. As each input is added, Protect refines the user’s Trust Index score, giving you a dynamic, up-to-date read on potential fraud risk.
This isn’t just about detecting fraud, it’s about making smarter decisions at scale and creating better experiences for trusted users. With Protect, you can use Trust Index scores to build custom, automated workflows:
High-risk users can be escalated to deeper verification steps, like ID document checks or liveness detection.
Low-risk users with high Trust Index scores can be fast-tracked through onboarding, improving conversion and reducing unnecessary friction.
These rules are fully configurable in the Protect dashboard, so you can create intelligent, automated pathways tailored to your risk tolerance and user base.
Information collected:
Name
DOB
Address
SSN
Phone
Email
ID document (optional)
Liveness (optional)
Integration lift:
1 backend API call
Choose from API-only or full IDV flow
Timeline: ~1 day to 1 week of engineering work
Ideal for:
Dynamic step-ups
Screening synthetic identities
Minimizing user friction for low-risk profiles
3. At bank account linking: end-of-funnel defense
Why it's useful here: Right before money moves is one of the most critical moments in the user journey, and one of the most vulnerable from a fraud risk perspective. At this stage, you’re often dealing with sophisticated fraudsters who’ve made it through initial checks. It’s your last chance to screen before funds are transferred, cards are issued, or accounts are fully activated.
That’s where Protect shines. By analyzing the linked bank account, Protect taps into the full spectrum of information—network signals, bank account-level risk, and consortium feedback. This depth of insight is essential to catch the toughest types of fraud, including account takeovers, synthetic identities, and first-party fraud.
Protect doesn’t just check if the account exists—it looks for indicators like newly opened accounts, sudden changes to account holder info, and links to past fraudulent behavior. It flags high-risk users before they can transact, and it does so with the speed and precision required at this high-stakes moment.
Information collected:
Linked bank account
Integration lift:
1 backend API call
Timeline: ~1–3 days of engineering work
Ideal for:
Transaction risk assessment
Blocking compromised or suspicious accounts
Protecting against first-party fraud and stolen identities
Built to Adapt to You
Plaid Protect isn’t limited to these three stages, it’s where many customers choose to start. Whether you want a frictionless top-of-funnel screen, tailored verification paths, or a safety net before money moves, Protect offers flexible workflows that meet your specific needs.
And because Protect keeps monitoring risk signals after onboarding, you’re covered even when fraud evolves.
Ready to explore where Protect fits into your user flow? Sign up for the waitlist.