Fraud Pattern Detection & Scheme Analysis
Identify fraud schemes and quantify exposure through transaction pattern analysis
What You Can Do
You can analyze large volumes of transaction data to identify telltale fraud patterns that perpetrators use to obscure illegal activity—including threshold splitting, timing manipulations, circular routing, and gradual escalation tactics. Claude processes multiple detection lenses simultaneously (temporal anomalies, network patterns, statistical outliers, behavioral shifts) and synthesizes findings into coherent fraud narratives with quantified exposure estimates and litigation-ready evidence chains.
Features
Identifies statistical outliers, threshold-splitting tactics, and behavioral shifts that deviate from normal transaction patterns
Maps suspicious timing around period ends, payment clustering, and escalation sequences that suggest intentional obfuscation
Traces circular routing, intermediary chains, and vendor relationships to expose collusion and ghost vendor schemes
Segregates transactions by risk profile (high-risk, medium-risk, legitimate) with specific rationale for each classification
Builds documented linkages between transactions, actors, and outcomes to support forensic narratives in litigation or regulatory proceedings
Calculates financial impact ranges with confidence levels based on detected patterns and extrapolated risk indicators
Proposes specific fraud scenarios (embezzlement, kickbacks, round-tripping) with supporting transaction evidence for each theory
Example Output
Input: 6 months of vendor payment data (187 transactions, $2.3M total) for investigation of suspected kickback scheme.
Output:
Anomaly Summary:
- 12 payments to vendor XYZ Corp ($847K, 45% of payments to this vendor) show 4 red flags: (1) 89% paid via ACH post-close, (2) invoice amounts clustered at $68-72K (just below $75K approval threshold), (3) 8 invoices lack supporting POs, (4) invoice dates lag payment dates by avg 23 days
Evidence Chain Example:
- June 2: Procurement Manager A approves Vendor XYZ invoice for $71,500 (no PO)
- June 3: Finance processes payment; same-day internal email from A to Vendor XYZ contact
- June 8: $15,000 transfer from Vendor XYZ account to personal account linked to Manager A
- Pattern repeats: 7 similar cycles identified over 6 months
Exposure Calculation:
- Confirmed high-risk: $412K (invoices without POs, threshold splitting detected)
- Probable exposure: $285K-$420K (timing and routing anomalies suggest 60-70% involvement)
- Estimated total exposure: $412K-$710K
Recommended Actions:
- Immediate source document review for 12 flagged XYZ transactions
- Bank statement analysis for Manager A's personal accounts (June-Dec)
- Interview vendor XYZ regarding invoice generation process
What's Included
- SKILL.md: Complete fraud detection framework with detection methodologies
- Transaction Analysis Template: Structured worksheet for categorizing transactions by anomaly type
- Evidence Chain Checklist: Step-by-step guide for documenting transaction linkages and causality
- Fraud Scheme Profiles: Reference guide for embezzlement, kickbacks, ghost vendors, collusion, and round-tripping detection markers
- Data Preparation Worksheet: Instructions for organizing vendor payments, expense reports, and intercompany transactions for analysis
- Exposure Quantification Framework: Methodology for calculating confirmed, probable, and speculative exposure ranges with confidence levels
Who It's For
- Forensic Accountants — Investigating financial statement fraud and embezzlement schemes
- Internal Audit Managers — Identifying control gaps and high-risk transaction patterns during fraud investigations
- Compliance Officers — Analyzing vendor payment anomalies and third-party relationships for collusion detection
- Law Enforcement/Regulatory Investigators — Building evidence packages for fraud prosecutions and regulatory enforcement
- CFO/Controller Teams — Responding to suspected fraud allegations with rapid pattern-based triage and exposure quantification
Best For
- Vendor Payment Fraud — Ghost vendors, duplicate invoicing, threshold splitting, and kickback schemes
- Embezzlement Investigation — Identifying personal expense misclassification, unauthorized disbursements, and timing manipulation patterns
- Payroll Fraud — Ghost employees, unauthorized rate increases, and timing anomalies in compensation payments
- Expense Report Auditing — Detecting recurring patterns, threshold avoidance, and reimbursement manipulation across large employee populations
- Intercompany Transaction Analysis — Exposing circular routing, related-party manipulation, and collusion in affiliated entity transactions
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