IDP vs OCR: Why Financial Services Firms Are Moving Beyond Traditional Document Scanning

Last week, we showed you the cost of manual document processing in UK financial services. But when firms do invest in automation, many start with the same tool their predecessors adopted in the 1990s: OCR. It captures text. It doesn’t understand it. Here’s why that distinction matters more than ever.

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What OCR Actually Does — And Where It Stops

Optical Character Recognition (OCR) converts images of text — scanned documents, PDFs, photographs — into machine-readable characters. That’s it. OCR doesn’t know what the text means. It doesn’t know that “£47,250” is an invoice total, not a postcode. It doesn’t know that “expiry date” on a KYC form requires a compliance check.

OCR technology matured in the 1990s and has been incrementally refined since. Modern OCR engines achieve high character-level accuracy on clean, structured documents. For a typed invoice from a known supplier, OCR performs well. For a handwritten claims form, a low-resolution scanned contract, or a document in an unexpected format, accuracy degrades significantly.

Why OCR Alone Fails in Modern Financial Services

UK financial services firms process an enormous variety of document types: loan applications, trade confirmations, SWIFT messages, KYC bundles, insurance claims, regulatory filings, broker notes. No two suppliers format their invoices the same way. No two customers complete a form identically.

OCR outputs raw text. Someone — or something — still has to map that text to structured data fields, validate it against business rules, check it for errors, and route it to the right system. In most OCR deployments, that “someone” is still a human. The OCR step saves keystrokes; it doesn’t eliminate the processing cost.

The result is a partial automation that often creates as many problems as it solves: OCR errors propagate downstream, exception queues fill up, and compliance teams spend time reconciling what the OCR thought it read versus what the document actually said.

What Intelligent Document Processing Adds

Intelligent Document Processing (IDP) uses OCR as one input among many. Where OCR reads pixels and returns characters, IDP reads documents and returns meaning. It uses machine learning models trained on document structure, natural language processing to interpret field semantics, and configurable business rules to validate extracted data.

The practical difference: an OCR system extracts “£47,250” from a document. An IDP system extracts “the invoice total is £47,250, which matches the purchase order within tolerance, the supplier is verified, and this document should route to accounts payable for payment within 30 days.”

IDP platforms handle document classification automatically — they identify what type of document they’ve received before attempting extraction. They manage variation in document layouts without requiring manual template configuration for each supplier or format. And they flag exceptions intelligently, only surfacing documents that genuinely require human review rather than every document that doesn’t match a rigid template.

The Compliance Dimension: Why IDP Is Better for FCA-Regulated Firms

For UK firms regulated by the FCA, document processing isn’t just an operational concern — it’s a compliance obligation. AML checks, KYC verification, trade reporting, and client suitability assessments all depend on accurate, timely document processing with complete audit trails.

OCR deployments typically lack audit trail functionality. They convert documents to text; they don’t record what was extracted, when, by which model, at what confidence level. When a compliance question arises — and in FCA-regulated environments, it always does — the OCR system has no answer.

IDP platforms log every processing decision immutably. Every document, every extracted field, every validation result, every routing action is recorded with timestamps and model confidence scores. For regulatory reporting and audit responses, this creates a defensible, complete record that OCR alone cannot provide.

What to Look for in an Enterprise IDP Solution

Not all IDP platforms are equal. When evaluating options for a financial services context, the critical differentiators are: accuracy on unstructured and handwritten documents (not just clean PDFs), native support for financial document types without extensive template configuration, configurable validation rules that business teams can maintain without IT involvement, and full audit trail logging that satisfies FCA requirements.

Integration is equally important. An IDP solution that can’t connect to your existing core banking system, CRM, or compliance platform creates a new manual step rather than eliminating one. Look for platforms with pre-built connectors for the systems your firm already uses, and a REST API for custom integrations.

Moving from Pilot to Production

The most effective IDP deployments in financial services start small and expand. Choose the document type with the highest volume and clearest ROI — often trade confirmations, loan application packs, or invoice processing — and deploy IDP against that single workflow first. Measure the results: processing time, error rate, exception volume, cost per document.

With a proven baseline, expansion to additional document types and workflows becomes a straightforward business decision rather than a leap of faith. Sentient Concepts’ ICE-Ai platform is designed for exactly this phased approach — fast time to first value, then systematic expansion as confidence and ROI data accumulate.

If your firm is still relying on OCR as its primary document automation strategy, the gap between where you are and where you could be is measurable — and closeable. The question is which document workflow you’ll start with.