The Problem Nobody Talks About
FinTech has come a long way, real-time payments, AI-driven underwriting, and mobile-first banking are the norm. But ask anyone working inside a bank or finance team and they’ll tell you the same thing: checks and invoices are still a pain.
They’re slow to process, expensive to handle, and full of errors when humans have to key in the details. Basic OCR helped for a while, but it was never built for the messiness of real documents: handwritten notes on checks, invoices with dozens of line items, fraudsters pushing screenshots instead of originals.
This is where multimodal data extraction changes the game. At Veryfi, we built models that don’t just “scan text.” They combine visual layout, language, and metadata signals to actually understand financial documents, the way a human would, but in seconds.
Why It’s a Big Deal
Checks: Still Alive & Costly
- Despite the rise of digital payments, checks remain a core instrument in many corporate and institutional workflows.
- Their analog nature means they require manual scanning, character recognition, and verification before reconciliation can occur.
Invoices: Scaling the Pain
Manual invoice processing is one of the most persistent bottlenecks in finance. Error rates average around 1–2% per invoice, and costs can reach $15–$16 each when you factor in labor, rework, and overhead. At scale, those mistakes translate into lost time, delayed payments, and unnecessary spend.
Automation changes the equation. By extracting vendor details, line items, taxes, and due dates with accuracy above 95%, institutions can reduce error rates dramatically while freeing teams from repetitive tasks. What once slowed entire AP teams can now be handled in seconds.
In short: mistakes scale, cost scales, and the hidden drag on operations is enormous.
Moreover, one interesting industry example: Brillio recently publicized a use case in which they used GPT-4 (or generative AI techniques) to modernize check processing workflows for a financial client. In effect, they’re validating the industry trend that intelligent document understanding is now non-optional.
How Veryfi Helps
With Veryfi’s API, financial institutions and startups get a system built for today’s reality, not 1990s OCR.
- Checks, in seconds: Pull out payer, payee, routing and account numbers, amounts instantly.
- Invoices, line by line: Capture vendor details, taxes, due dates, even line-items with accuracy north of 95%.
- Fraud signals baked in: Catch screenshots, duplicates, or tampered docs with metadata and device fingerprints.
- Compliance by default: Every extraction comes with an audit trail that stands up to SOC2, HIPAA, and GDPR.
What used to take minutes of manual effort, or endless error-prone OCR tuning, is reduced to an API call that returns clean, structured JSON in under five seconds.
The Bigger Picture: FinTech + AI
Financial services are under pressure to do more with less. Customers expect instant everything, regulators expect bulletproof compliance, and margins are thin. AI isn’t a “nice-to-have” anymore, it’s the only way to keep up.
Embedding a multimodal extraction engine like Veryfi into payment rails or accounting platforms means:
- Cash moves faster.
- Teams scale without headcount bloat.
- Fraud gets caught before it becomes a liability.
- Customers get the smooth experience they expect.
And unlike buzzword-driven experiments, this isn’t a lab demo. It’s production-grade infrastructure that FinTech companies can (and already do) deploy today.
Closing Thoughts
Checks and invoices aren’t glamorous, but they’re the plumbing of finance. If they’re slow, everything downstream slows too. Veryfi takes that bottleneck away.
By replacing manual entry and brittle OCR with multimodal AI, FinTechs can finally process documents at the speed of their customers, instant, accurate, and secure.
👉 Curious to see how it works? Explore the API or reach out for a demo.
