The fastest, most accurate bank statement parsing engine in the industry. Built on a decade of machine learning innovation with native PDF intelligence — no OCR errors, no compromises.
Core Capabilities
From bank statements to tax returns, our AI reads, extracts, and validates financial documents with precision no other platform can match.
Industry-leading extraction of transactions, balances, account details, and cash flow metrics from any bank statement format — PDF, scanned, or digital.
Continuous machine learning models trained on millions of documents detect tampering, fabrication, and inconsistencies invisible to manual review.
Our systems automatically identify document types and learn new formats. Upload any financial document and our AI figures out how to extract it.
We read PDF data at the structural level — bypassing OCR entirely. This eliminates the errors and fraud vulnerabilities inherent in image-based extraction.
Expert reviewers handle edge cases where documents are incomplete, damaged, or flagged for potential fraud — ensuring nothing falls through the cracks.
Process hundreds of thousands of documents per hour. Our distributed architecture scales elastically to handle your peak volumes without degradation.
Bank Statement Extraction
Every transaction. Every balance. Every detail. Our extraction engine processes bank statements from thousands of institutions with 99.7% accuracy — and it's getting smarter every day.
Fraud Detection
Our AI-driven fraud detection goes far beyond surface-level checks. We analyze document structure, metadata signatures, transactional patterns, and cross-reference anomalies that manual review and OCR-based competitors simply miss.
Identifies altered PDFs, modified transaction amounts, inserted or deleted entries, and font inconsistencies at the binary level.
Machine learning models continuously trained on millions of statements identify statistical anomalies in transaction patterns and balances.
Our models evolve with every document processed. As new fraud techniques emerge, our system automatically adapts its detection capabilities.
Transaction on line 47 uses Helvetica 9pt while document standard is Arial 8.5pt. Potential manual insertion detected.
Running balance diverges from calculated sum by $2,340.00 between pages 3-4. Flagged for human review.
Route to human-in-the-loop review. Confidence: 89% probability of document manipulation.
How It Works
A streamlined pipeline that turns raw financial documents into structured, validated, actionable data.
Submit documents via API, SFTP, or web upload. Any format — PDF, scanned images, or direct bank feeds.
Our AI reads the native PDF structure and extracts every transaction, balance, and data point with 99.7% accuracy.
Multi-layer fraud detection analyzes document integrity, transaction patterns, and cross-references for anomalies.
Structured JSON output with extracted data, cash flow metrics, fraud scores, and confidence levels — ready for your systems.
Our Technology
Built on proprietary technology developed since 2012, our platform combines native PDF intelligence with continuously evolving machine learning models.
While competitors rely on OCR to convert documents to images and then attempt to read them, we parse the actual PDF data structures. This means we access text, tables, and formatting information directly — with zero optical recognition errors.
This architectural decision, made in our earliest days, gives us a fundamental accuracy advantage that OCR-based approaches cannot replicate.
Our ML models don't just classify documents — they learn how to read new ones. When a new bank statement format appears, our system auto-detects the layout, maps data fields, and begins extraction without human intervention.
Over a decade of training data from millions of documents gives our models an understanding of financial document structures that no new entrant can match.
Built by founders with deep financial services security backgrounds. Bank-grade encryption at rest and in transit, SOC 2 compliance, and strict data isolation ensure your borrower data is protected at every layer.
Documents are processed in isolated environments and purged according to your retention policies. We never use customer data to train models without explicit consent.
Our distributed processing architecture scales horizontally to handle peak volumes without latency degradation. Process hundreds of thousands of statements per hour with consistent sub-3-second turnaround times.
Whether you're processing 100 or 100,000 documents in a batch, our infrastructure automatically allocates resources to meet your SLAs.
Beyond Bank Statements
Our platform extends across the complete landscape of financial documents. The same AI that leads in bank statement extraction powers intelligent processing for every document type in the underwriting workflow.
1040, 1065, 1120, K-1 forms
Income verification
Asset verification
Bills, statements, invoices
About MoneyStream
Founded in 2012 by Silicon Valley veterans with deep roots in financial services and security, MoneyStream set out to solve a fundamental problem: extracting reliable, structured data from the messy reality of financial documents.
Over the past decade, we've built proprietary AI and machine learning systems that can read, understand, and validate virtually any financial document — from digital PDFs to scanned paper mail. Our technology doesn't just parse documents; it understands them.
Today, our platform processes hundreds of thousands of documents per hour with industry-leading accuracy, serving lenders, fintechs, and financial institutions who demand the highest standards of precision, security, and speed.
Silicon Valley roots, financial services DNA
Proprietary models trained on millions of documents
Native PDF parsing eliminates OCR errors entirely
Expert review available for every edge case
Get in Touch
Schedule a demo to see how our bank statement extraction and fraud detection can accelerate your underwriting decisions. Our team will walk you through the platform and show you results on your own documents.
We've received your inquiry and will be in touch shortly.
We use cookies to improve your experience and analyze site traffic. By continuing to use this site, you agree to our use of cookies.