Amanda Wilson

Profile

Multi-domain investigation grounded in evidence, not assumption.

My practice covers the full fraud lifecycle across multiple domains: detecting anomalies in claims, transactions, and onboarding data; tracing funds through ACH records, bank and card statements, and accounting systems; conducting interviews; and translating financial complexity into clear, defensible written findings. My experience spans healthcare fraud, waste, and abuse, financial-crime and forensic accounting, payments and card fraud, identity and synthetic-identity schemes, and vendor and benefits fraud.

That breadth is deliberate. I have uncovered a multi-six-figure fraud scheme, assembled litigation-grade evidence packages addressing fraudulent tax reporting and worker misclassification, surfaced systemic billing and enrollment discrepancies across major carriers, and designed detection logic for first-party, third-party, and synthetic-identity patterns. Every engagement is conducted independently, objectively, and in full compliance with the law, toward a single objective: to establish what actually occurred.

PatternTraces

A fraud-investigation platform, built from the casework.

PatternTraces is the fraud-investigation platform I developed from my own investigative practice. It reached more than 300 company seats within its first two months.

The platform

PatternTraces — home of the FraudLens Workbench — operationalizes the methods behind my investigations: transaction and identity detection, fund-flow tracing, case management, and audit-ready reporting. Its rapid adoption reflects a system designed by a practicing investigator for the realities of investigative work.

Detection across financial-pattern and identity/behavioral signals
Case intake, triage, evidence handling, and defensible reporting
300+ company seats in the first two months

The training

Detection tools deliver results only in capable hands. I train fraud analysts in compliance and sound investigative methodology — scoping an allegation, working evidence objectively, guarding against over-calling fraud, and documenting findings that withstand scrutiny.

Investigation methodology, from intake to defensible report
Compliance-first, objectivity-driven case handling
Hands-on graded scenarios drawn from real referrals

Expertise

Core competencies across fraud types

A single investigative discipline applied across fraud types — methodology and analytics that transfer between domains, not a narrow specialty.

Financial Crime & Forensic Accounting

Reconstruction of fund flows across ACH, wire, and card rails through intermediary and pass-through accounts
Quantification of diversion via double-counting, ACH-reversal, and round-tripping analysis
General-ledger reconstruction reconciled against source-of-funds to expose concealment
Exposure of inflated 1099 / tax reporting and breach-of-contract loss

Healthcare Fraud, Waste & Abuse

Claims-pattern analytics across CPT/HCPCS and DRG coding to surface upcoding, unbundling, and phantom billing
Provider and member network analysis for collusion and kickback indicators
Medicare Advantage risk-adjustment (HCC/RAF) and effectuation integrity
Reconciliation against CMS and MARx enrollment and payment data

Identity & Synthetic Fraud

Synthetic-identity detection via tradeline velocity, SSN issuance anomalies, and fabricated credit profiles
Device-fingerprint, IP /24, and locale/timezone clustering across sessions
Account-takeover signal correlation and onboarding-abuse modeling
Application-ring and mule-account graph analysis

Payments, Card & Chargeback Fraud

Card-testing and BIN-attack detection via authorization velocity and approval-rate inversion
First-party (friendly) fraud and CNP refund-cycling analysis
Chargeback representment and compelling-evidence packaging under network rules
MCC and merchant-pattern profiling for concentration risk

Benefits & Eligibility Fraud

FSA / HRA / HSA substantiation against IRS §213(d) eligibility and plan-year timing rules
Dependent-eligibility, orthodontia, and recurring-claim scheme detection
Provider-collusion and inflated- or fabricated-receipt analysis
Vendor substantiation-failure and exception-rate review

Compliance, AML & Investigations

Structuring and layering detection against CTR/SAR thresholds and FinCEN typologies
Enhanced due diligence and beneficial-ownership review
Self-directed investigative scoping and adversarial hypothesis testing
FRE-aware evidence packaging built to withstand opposing scrutiny

Casework

Selected investigations

Forensic Accounting · Concealment Scheme

$750K concealment scheme reconstructed across four systems

$750,000 in concealed activity quantified; ~$387K inflated 1099 disproven

Built a forensic reconciliation model spanning QuickBooks, Ramp, PayPal, and bank records to normalize and de-duplicate transactions across all four ledgers against a single source-of-funds timeline. The model isolated the inflation mechanics — double-counted entries, ACH reversals booked as revenue, and pass-through payments improperly attributed to the payee — proving a ~$387K Form 1099-NEC was overstated. Output was a tie-out package mapping every disputed dollar to source documents, structured to survive opposing expert review in active litigation.

Multi-Ledger ReconciliationRound-Tripping / Reversal Analysis1099 InflationSource-Document Tie-OutLitigation-Grade

Healthcare · Federal Program Integrity

HRSA COVID-19 claims fraud surfaced via eligibility logic

$100,000+ in false claims identified; referred to DOJ under the False Claims Act

Designed claim-level detection logic against the HRSA COVID-19 Uninsured Program, testing each submission for eligibility integrity — coverage status at date of service, duplicate and resubmitted claims, and service patterns inconsistent with the billed encounter. The ruleset flagged a systemic pattern of ineligible and duplicated claims exceeding $100K, which I quantified and packaged into a documented referral submitted to the Department of Justice under the False Claims Act.

Eligibility Detection LogicDuplicate-Claim AnalysisFWAFalse Claims ActDOJ Referral

Insurance · Data Integrity & Reconciliation

Carrier reconciliation engine exposing false chargebacks

$20K+ in false chargebacks recovered; platform data-integrity failures proven

Stood up a reconciliation engine matching carrier commission and effectuation records (UHC, Humana, Aetna, Wellcare, Heartland) against book-of-business and payment data across an ~700–800 client portfolio. By reconciling statement-level activity against enrollment status and chargeback events, the model exposed systemic data-integrity failures in the prior platform — including over $20K in chargebacks issued against active, valid policies — and produced reporting that held up under carrier and upline challenge.

Reconciliation EngineChargeback ValidationEffectuation / BOBCMS / MARxData Integrity

Method

How an investigation runs

01 — INTAKE

Triage & scope

Assess the allegation, define scope, and identify the material facts to prove or disprove.

02 — GATHER

Collect & trace

Authenticate records — claims, transactions, statements, ledgers — and interview subjects and witnesses.

03 — ANALYZE

Test the facts

Reconcile the money, surface anomalies and patterns, and test every hypothesis against the evidence objectively.

04 — REPORT

Decide & document

Deliver an accurate, defensible account, coordinate with leadership, and recommend a sound, compliant action.

Credentials

Education & certification

B.S., Criminal Justice Management

Union Institute & University — Cincinnati, OH

Conferred 2022

Certificate, Forensic Accounting & Fraud Analysis

West Virginia University

Completed 2023

Skills & Systems

Healthcare FWAForensic AccountingIdentity & Synthetic Fraud Card & Chargeback FraudFSA / HRA / HSAAML / Structuring InterviewingReport WritingACH / Fund Tracing Medicare AdvantageCMSMARxCarrier Portals QuickBooksExcelCompliance AuditingVendor Due Diligence Evidence PackagingData ReconciliationInvestigator Training