use case

Check Fraud Affidavit & Claims Processing

Retail & Business Banking

Customer Service, Fraud Operations, Risk & Compliance

Customer Fraud Claims, Compliance & Documentation Automation

Business Challenge

Check fraud remains a major operational burden for banks: 63% of organizations report being impacted by check fraud, and physical checks are the most targeted payment method1.

When customers identify fraudulent check activity, they must initiate a fraud claim process which requires banks to collect and validate:

  • A signed customer affidavit
  • A notarized sworn statement
  • Transaction details for internal review
  • Supporting documents (e.g., voided check images, statements, ID, correspondence)

These submissions are unstructured, vary by case, and often include handwritten and scanned content. Strict reporting rules apply making accuracy and processing speed critical to avoid financial loss and denied claims.

Historically, analysts manually reviewed each file, validated signatures and notarization, compared claimant identity to account records, checked submission completeness, and keyed data into internal case systems.

This resulted in:

  • High staffing load for fraud ops teams
  • Delays in claims resolution and customer reimbursement
  • Potential compliance gaps and missed SLAs
  • Inconsistent documentation and validation quality
  • Overall dissatisfied customers

Solution: BizAI for Invoice Processing & Compliance

Fisent BizAI automates the ingestion, review, and processing of all caregiver invoices.

Using its Applied GenAI Process Automation framework, BizAI is able to apply the client’s reimbursement policies to all forms of billing templates to match and process the invoices while validating compliance standards — ensuring fast, accurate, and fully governed processing with zero data retention.

Representative BizAI Actions

Identify and categorize inbound submissions (e.g., service invoices, supporting care documentation, timesheets, caregiver notes, receipts).

Separate invoice bundles into individual chargeable line items, attachments, and supporting forms.

Automatically extract, structure, and validate all invoice data—including provider and patient details, authorizations, service codes, charges, payment terms, and caregiver documentation—to ensure accurate, compliant billing.

Cross-check extracted data against rate schedules, authorization guidelines, and contractual fee schedules.

Apply policy and compliance rules to determine reimbursable vs. non-reimbursable charges, flagging exceptions for audit review and potential fraud detection.

Integration & Workflow

System Integration

Structured outputs flow to AP, claims management, and compliance systems for payment decisioning.

Exception Routing

Non-compliant, duplicate, or unsupported invoices are routed directly to the compliance team with highlighted discrepancies.

Governance

BizAI is able to apply internal audit standards and payer compliance rules, ensuring policy and program adherence.

Auditability

Every extracted field and compliance decision is fully traceable back to the source invoice and governing policy clause.

Standardization Benefit

By digitizing and automating invoice intake and validation, BizAI replaces manual reviews with a standardized, rule-driven adjudication process. This ensures consistent application of reimbursement policies across all caregiver types and service categories — reducing variation, rework, and fraud exposure.

Business Impacts

80–90% reduction in manual invoice review time.

Consistent enforcement of reimbursement policies across all care programs.

Improved compliance visibility through audit-ready documentation.

Faster reimbursement cycles, enhancing caregiver satisfaction.

Reduced fraud and payment leakage through automated detection of invalid or duplicate claims.

Key Takeaway

Fisent BizAI transforms healthcare invoice processing from a manual, error-prone workflow into an automated, transparent and compliant process, ensuring that every charge is validated, reimbursed, and recorded accurately — protecting both the payer and the patient.

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