ClearStaq

Parse & Extract

Bank Statement Parsing

900+ formats. <5s processing. 99.5% accuracy.

Tax Return Parsing

1040s, K-1s, 1120s — structured data in seconds.

Financial Analysis

P&L, cash flow, balance trends, and scorecards.

Protect & Verify

Fraud Detection

27 AI signals. Two detection layers. Zero tolerance.

Income Verification

AI-powered categorization of every deposit source.

API & Webhooks

REST API, SDKs, real-time notifications.

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By Industry

For MCA Brokers

Process more deals. Catch fraud. Close faster.

For Lenders

Automated underwriting with fraud protection.

For CPAs & Accountants

Extract and categorize client financial data instantly.

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FRAUD DETECTION

Catch fraud before you fund.

27 fraud signals. Two detection layers. Every document scanned automatically.

Risk Assessment

DOC-2025-0847
0/100
Low Risk

PDF creation tool mismatch

Adobe vs. Chrome PDF

Font inconsistency detected

2 mismatched fonts

Unusual weekend activity

3 transactions on Sunday

0
Fraud signals
0%
Detection rate
<0s
Analysis time
<0%
False positive rate

Fraudulent statements cost the industry billions

Manual review catches roughly 50% of fake statements. The rest? They slip through, get funded, and become your problem.

Average cost of one bad deal
$0K – $0K

Funded on a fake statement you didn't catch

27 signals. Every document. Every time.

Five categories of analysis working together to catch what humans miss.

PDF Metadata

6 signals
Creation tool analysis
Modification history
Producer mismatch
Creation timestamp
Embedded fonts
File structure

Font & Text

5 signals
Font consistency
Character spacing
Text rendering
Baseline alignment
Font substitution

Transaction Patterns

8 signals
Round number frequency
Running balance validation
Timing patterns
Duplicate detection
Weekend activity
Amount distribution
Sequence gaps
Balance jumps

Visual & Layout

5 signals
Logo verification
Header/footer consistency
Template matching
Compression artifacts
Watermark verification

Cross-Document

3 signals
Statement continuity
Format consistency
Historical comparison
All 27 signals checked in under 25 seconds

Two layers. Because one isn't enough.

Each layer catches what the other might miss.

LAYER 1

Structural Analysis

Examines the digital DNA of the document — metadata, fonts, mathematical validation.

PDF metadata inspection
Font consistency check
Balance calculation validation
Timestamp analysis
LAYER 2

AI Visual Inspection

Analyzes the document as an image — catching pixel-level edits humans can't see.

Logo authenticity check
Pixel manipulation detection
Template matching
Compression artifact analysis
Combined Score
0.00 – 1.00
Both layers contribute to a unified risk score with detailed explanations

The math is simple

What fraud costs you
Manual review time30-45 min/doc
Detection rate~50%
Cost per bad deal$50K-$200K
Reputation damageIncalculable
What ClearStaq saves you
Analysis time25 seconds
Detection rate95%+
False positive rate<3%
Peace of mindPriceless

"If ClearStaq catches one fraudulent deal per quarter, it pays for itself for a decade."

Fits your workflow

Three modes for different risk tolerances.

Auto-Flag Mode

Scores above your threshold get flagged for human review. Perfect for high-volume operations.

Set custom thresholds
Email alerts
Dashboard queue

Gate Mode

Hard stop on high-risk documents. Zero chance of accidentally funding a fraudulent deal.

Automatic blocking
Mandatory review
Audit trail

Audit Mode

Retroactive analysis on historical submissions. Find fraud you may have missed.

Batch processing
Historical reports
Pattern detection

Stop funding fraudulent deals.

Let AI catch what humans miss.

50 free documents. No credit card. No sales call required.

Start free — no credit card required

Take back your time and automate loan underwriting

Join 500+ lending teams using ClearStaq to parse statements, catch fraud, and verify income — all in under 5 seconds.

No credit card required. 50 free parses/month. Upgrade anytime.

ClearStaq

AI-powered bank statement parsing, fraud detection, and income verification for lending teams.

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