Intelligent Anomaly Detection for Financial Control

ScanWise does more than digitize invoices. It continuously analyzes invoice data, supplier behavior, and financial patterns to detect irregularities before they turn into costly mistakes.

Why Anomaly Detection Matters

Manual invoice review cannot reliably identify hidden financial risks.

structured monitoring, companies often miss:

ScanWise transforms invoice processing into proactive financial oversight.

Comprehensive Risk Monitoring

ScanWise monitors multiple dimensions of invoice and supplier behavior.

Below are the core anomaly categories built into the system.

Duplicate & Structural Anomalies

Detects structural inconsistencies to prevent double payments.

Exact Duplicate Invoice

Same supplier + invoice number + amount + date.

Same supplier + invoice number + amount + date.

Potential Duplicate (Soft Match)

Similar invoice number or similar amount from the same supplier.

Detects possible human-entry variations.

Reused Invoice Number

Supplier reuses an invoice number with different financial values.


Flags unusual numbering behavior.

Shared Bank Account Across Suppliers

Identifies cases where multiple suppliers use the same bank account.

Adds fraud risk awareness.

Supplier Behavior Anomalies

Monitors vendor activity for unusual patterns.

Invoice Frequency Spike

Supplier invoices significantly more often than historical average.

Same supplier + invoice number + amount + date.

Sudden Supplier Inactivity

Regular supplier stops invoicing unexpectedly.

Detects possible human-entry variations.

New Supplier Detection

Flags first-time supplier entries.

Adds additional review layer for new vendors.

Shared Bank Account Across Suppliers

Identifies cases where multiple suppliers use the same bank account.

Helps detect inconsistencies.

Financial Amount Anomalies

Analyzes monetary values for deviations.

Amount Deviation from Historical Average

Invoice exceeds supplier’s typical average by configurable percentage.

Early warning for price irregularities.

VAT Percentage Inconsistency

VAT rate differs from supplier’s historical VAT pattern.

Reduces tax reporting risk.

Total Calculation Mismatch

Net amount + VAT does not equal total amount.

Prevents accounting errors.

Unusual Cost Center Assignment

Invoice assigned to unexpected department or expense category.

Improves internal cost control.

Data Integrity & AI Reliability Monitoring

Ensures data quality and extraction accuracy.

Low OCR Confidence

Critical field confidence below configured threshold (e.g., 80%).

Prevents blind trust in automation.

Missing Critical Fields

Important fields not extracted (VAT, Bank, etc).

Triggers manual review.

Suspicious Invoice Date

Supplier reuses an invoice number with different financial values.


Adds additional oversight layer.


Low Confidence Detection

Unlike basic OCR tools, ScanWise identifies when extraction may be unreliable. ScanWise converts them into structured, validated data in seconds.

Critical fields can be defined, such as:

Access is restricted to authorized users only.

Real-Time Status Visibility

Detected anomalies are clearly displayed inside the system:

Designed for Prevention — Not Investigation

Instead of discovering problems after payment, ScanWise helps you:

Detect duplicate invoices before transfer

Identify supplier irregularities early

Monitor cost 
deviations

Strengthen internal financial control

Improve audit
 readiness

Built for Baltic Accounting Systems

Anomaly detection works seamlessly with:

Business Impact

Companies using structured anomaly monitoring achieve:

Reduced duplicate payment risk
Better supplier cost oversight
Stronger financial transparency
Improved compliance control
Increased confidence in automation