Closing the Coverage Gap: Predictive Intelligence Makes Validation a No-Brainer

How we turned 95% unknowns into 80% verified accounts

When a large portion of your accounts, especially regional bank and credit union accounts, keep coming back as “no information found,” you’re not just missing coverage… you’re paying for zero value.

That’s exactly what an S&P 500 leader in business payments and expense management discovered: their incumbent solution returned “no information found” on a segment of their accounts, offering no verification, no authentication, and no insight.

So they tested a segment of their “no hit” or “no information found” accounts with ValidiFI, and every verified match became pure upside they’d never been getting before.

By layering consortium network data, proprietary signals, and machine learning (ML)-driven pattern matching, we turned dead ends into wins: ~80% verified accounts and on top of that, 43–51% of verified accounts, were able to be authenticated, confirming whether the account owner matched or failed ownership. All additive value on top of their existing performance—without chasing bank statements, checks, or adding in manual reviews.

CHALLENGE:
Many organizations see coverage gaps when validating accounts from credit unions and small regional banks:

• • Smaller institutions often don’t participate in large data-sharing networks, resulting in fewer signals to confirm account status or ownership.
  • Thousands of credit unions and regional banks rely on fragmented legacy systems, making real-time validation difficult.
  • These challenges are amplified by evolving compliance requirements, including Nacha’s changing rules for fraud monitoring and account validation.
  • Staying ahead of these changes is critical for payment providers.

The client’s situation:

• • In this case, this industry leader was increasingly dissatisfied with the verification performance of its incumbent solution; the ‘No Hits’ were leading to manual verification and chasing bank letters or statements.

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SOLUTION:

The company performed a data study analysis of ValidiFI’s vAccount+ Verify with AOA (Account Owner Authentication), designed to deliver deeper insights across the customer lifecycle.

ValidiFI implemented a two-step account intelligence framework, supported by a layered data strategy and ML-driven pattern matching.

• • Step 1—Verification (bank account and routing number assessment): Determines if account status is open, valid, closed, or indeterminate.
  • Step 2—Authentication (ownership): Confirms name-to-account ownership—does the person or business actually own the account or have authorized access?

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“Most solutions simply stop when they reach an unknown,” said John Gordon, CEO of ValidiFI. “What sets this approach apart is our ability to generate meaningful intelligence from accounts that others overlook. By combining layered data, network signals, and predictive pattern matching, organizations can finally break through long‑standing coverage gaps. The result is stronger verification, higher authentication rates, and smarter decisions across the entire customer lifecycle.”

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The Data Advantage
The strength of ValidiFI starts with its proprietary network, an unmatched data with deep coverage across subprime and non‑prime consumers, as well as credit unions and small regional banks. ValidiFI delivers visibility into accounts that other solutions routinely miss. When combined with authoritative partner networks that provide access to mainstream and large financial institutions, the result is broader, more accurate real‑time account validation and authentication that reduces risk.

By combining ValidiFI’s extensive bank data networks, fraud and risk signals, with predictive analytics and pattern matching, clients dramatically improve verification and authentication rates. This is where the 100% upside happens—converting previously “unknown” accounts into verified and authenticated outcomes, turning blind spots into confident decisions and measurable revenue impact.

What Makes this Approach Different and Dependable?

• • Consortium Partner Data Network: Access to large-scale payments data signals to enhance coverage.
  • ValidiFI Data Network (VDN): Aggregated and growing proprietary network, adding ~1.4M new records on an ongoing cadence to continuously improve match rates.
  • ML Pattern Matching: When an account is unseen (NDS), ValidiFI applies incremental pattern matching using routing patterns, ABA conformance checks, and historical payment behavior across similar accounts to assign high/medium/low confidence tiers—yielding actionable guidance even without a hard match.
  • Real-Time API: Instead of stopping and chasing documents, the client can verify via API calls during onboarding or payment setup.

This approach not only improves coverage but also supports compliance with Nacha’s fraud monitoring and account validation rule—helping organizations meet industry standards while reducing friction.

RESULTS:

• • Coverage Breakthrough:
    • Verified ~80% of the population (up from 5% verified with incumbent)—delivering 16X more verified accounts compared to their prior performance
    • Authenticated ~43% (business accounts) & 51% (consumer accounts)
      

      
      Tested No-Hit Data Sample

Metric	Incumbent	ValidiFI
No-Hit Rate	>95%	Reduced to ~20%
Verified Accounts	Minimal	~80%
Authenticated Ownership	N/A	~43% (business accounts) ~51% (consumer accounts)

• • Friction Reduction: ValidiFI data powers smarter decisions that can eliminate the need for manual bank letters/statements in most cases by providing confident validation paths in real time.

  • Business Impact: Higher coverage, fewer exceptions, and better fraud prevention—all without sacrificing compliance.

START POWERING SMARTER DECISIONS

Validating hard-to-find accounts is no longer a headache—ValidiFI it.

Talk to our team to see how ValidiFI closes the coverage gap.

 

📊 Read more about our industry impact: Data Study Impact Brief:
How Predictive Intelligence Transforms Account Verification for a Leading Consumer Finance Firm