Document Processing

Stop Wasting Hours on Manual Document Processing

Custom AI solutions built for financial services: faster, more accurate, and audit-ready.

Industry Context

Financial services firms process high volumes of documents daily—loan applications, compliance forms, transaction records—and regulators demand detailed, accurate records. Manual handling is slow and error-prone, creating compliance risk and operational bottlenecks. An aging workforce and rising labor costs mean automation isn't optional anymore. It's how you stay competitive and avoid penalties.

By the Numbers

75%

of financial data trapped in unstructured documents

Accenture Banking, 2024

15 min

average manual processing per loan application

McKinsey Lending, 2025

88%

extraction accuracy with AI document processing

Gartner AI Applications, 2024

The Problem

What you're dealing with

Manual data entry from scanned loan applications causing typos and delays in approval cycles

Compliance teams spending hours cross-referencing client documents against changing regulatory lists

Invoice and statement processing requiring multiple rounds of human validation, slowing accounts payable

Non-standard forms or handwritten fields that can't be extracted automatically, requiring full rework

Missing or incomplete audit trails because manual processes are fragmented across departments

The Solution

How it works

We start by mapping your actual document workflows—how your team really handles documents, not how it's written up. Through AI-driven interviews, we find bottlenecks, variations, and exceptions. Then we build a system that fits your tools, data sources, and compliance requirements. Our internal tooling accelerates the build without locking you into a generic product. You get a system that extracts, validates, and routes documents based on your business rules, with built-in audit trails and continuous learning from your data. It works within your existing tech stack, needs minimal training, and scales as volume grows.

POI

Maps real-world document handling patterns through process discovery and workflow analysis

Arc

Trains and deploys custom AI models for document classification and data extraction

In Practice

Before and after

Before

Loan officers manually re-type data from PDF applications into the CRM. Compliance checks happen separately via email and spreadsheets.

After

Applications are automatically classified, data is extracted and checked against internal rules, and exceptions are flagged for review. The system updates the CRM and notifies compliance in real-time.

1 Document upload triggers automated classification and data extraction
2 Extracted data is validated against business rules and external databases
3 Exceptions are routed to the appropriate team with context and suggested actions
4 Approved data flows directly into downstream systems like CRM or ERP
5 Full audit trail is generated for compliance and reporting

6 weeks

Average delivery time

From discovery to deployed system for financial document processing

FAQ

Common questions

How do you handle data security and compliance?

We build within your existing security protocols and compliance framework. Data is processed in your environment or in secure cloud instances you control. All models are trained on your data, not shared across clients.

What if our documents are non-standard or change frequently?

The system learns from corrections and adapts to new formats over time. It includes tools for your team to train the model on new document types without our help.

How long does it take to build and deploy?

Most systems ship in 4-8 weeks, depending on complexity. Our internal tooling lets us iterate quickly based on your feedback.

Do we need to replace our current systems?

No. We plug into your existing software—CRMs, ERPs, compliance tools—so the AI works within your current setup.

What happens if the system makes a mistake?

Low-confidence extractions get routed to a human for review. The system learns from those corrections and gets more accurate over time.