New account fraud was the only major fraud typology to grow in both victim count (+31%) and dollar losses (+13%) last year. Fraudsters increasingly use generative AI tools to alter ID documents in ways that are hard to spot by eye, or by an analyst working a review queue.
That's why we've shipped a number of Plaid Identity Verification (IDV) updates that strengthen every stage of the verification lifecycle: document verification, PII verification, and case management. Here's what's new and how it solves real-world problems.
Document verification: spot AI-manipulated images behind new account fraud
Detect manipulated images of ID documents
IDV’s integrity check inspects the metadata to flag tampered images from virtual camera software and signs of digital editing or AI generation. This feature is designed to counteract fraudulent ID documents that are especially prevalent at the point of account opening. This feature flagged 50+ virtual camera attempts in one month alone.
But hey, fraudsters don’t always go high-tech. They can show paper copies or photos of stolen IDs instead during online account opening processes as well. In those scenarios, Plaid also detects screens or printed copies as another layer of protection against document fraud.
Require both sides of an ID document
Requiring both sides of the ID to be uploaded creates a more confident assessment. If only the front of a driver's license is uploaded, users are sent back to the document type selection step with clear feedback. This closes a loophole that fraudsters exploit and helps organizations who have stricter compliance rules, such as financial institutions, to reduce manual outreach to chase down what’s missing.
Data source verification: recognize trusted emails and rescue typos for genuine customers
Perform additional email risk checks
Plaid IDV uses a LLM that cross-checks a user's name and date of birth against their email address to identify mismatches. This doesn't fail users outright, but flags suspicious patterns as a high-quality signal. In its first two weeks, it caught 100% of fraudsters in a live attack on a major customer. Applicable to the dashboard and the API.
Detect typos and offer retries
When a user enters an incorrect DOB, SSN, or name accidentally during the account opening process, they'll have the option to correct the typo rather than failing the session outright. This improves pass rates to capture sessions that would have otherwise failed based on typos.
Case management: more intel and better labels in one place
These product updates are about giving investigators the full picture faster, without asking them to trade thoroughness for speed.
Visualize anomalies on a map
In the IDV dashboard, you’ll see a session's location signals plotted on a customer location map — Document Address, Submitted Address, IP Address, and IP Address (VPN) — showing the distance between them and an associated risk level. An IP address from an unexpected country, or a large gap between a submitted address and an actual connection point, becomes immediately visible instead of buried across separate fields.
Submit more granular fraud labels
When you mark a session as “fraud” in the IDV dashboard, you’ll see expanded fraud report labels. This helps with faster categorization, cleaner investigation trails, and better training data going forward. The expanded fraud labels include:
User account and identity
User account takeover
Stolen identity
Synthetic identity
Multiple user accounts
Scam victim
Bank account or payment method
Bank account takeover
Bank connection revoked
Card testing
Transaction
Unauthorized transaction
Card chargeback
ACH return
Dispute
Behavior
1st party fraud
Missed payment
Loan stacking
Money Laundering
A configurable risk strategy for end-to-end coverage
These Plaid IDV enhancements strengthen each stage of the fraud prevention journey – from onboarding to case management to risk configuration. The beauty is that these are self-serviceable, don’t require any additional integration work, and are live today.
As you’re optimizing your risk strategy, ensure that you adopt a defense-in-depth strategy. Use a combination of data source verification, document verification, liveness checks, behavioral analytics, device fingerprinting, and network intelligence as trip wires to detect fraud, while fitting your risk appetite.
Want to see these updates in the dashboard or discuss how they fit your risk strategy?