fraud-risk-assessment

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Fraud risk assessment engine following the COSO Fraud Risk Management Guide. Builds fraud risk universes, maps anti-fraud controls, identifies red flags, designs data analytics detection programs, and evaluates anti-fraud program maturity. USE THIS SKILL when the user mentions fraud risk, anti-fraud controls, fraud detection, red flags, whistleblower program, fraud investigation, Benford's law, fraud triangle, fraud schemes, asset misappropriation, financial statement fraud, corruption, cyber fraud, or anti-fraud program assessment. Covers the full anti-fraud lifecycle from prevention through investigation readiness.

Kaakati By Kaakati schedule Updated 3/1/2026

name: fraud-risk-assessment description: > Fraud risk assessment engine following the COSO Fraud Risk Management Guide. Builds fraud risk universes, maps anti-fraud controls, identifies red flags, designs data analytics detection programs, and evaluates anti-fraud program maturity. USE THIS SKILL when the user mentions fraud risk, anti-fraud controls, fraud detection, red flags, whistleblower program, fraud investigation, Benford's law, fraud triangle, fraud schemes, asset misappropriation, financial statement fraud, corruption, cyber fraud, or anti-fraud program assessment. Covers the full anti-fraud lifecycle from prevention through investigation readiness.

Fraud Risk Assessment

Required Inputs

  • Organization: Company name, industry, size (revenue, employees), and organizational structure.
  • Business Processes: Key revenue, procurement, payroll, treasury, and financial reporting processes.
  • Control Environment: Existing internal controls, segregation of duties, approval authorities.
  • Prior Fraud History: Known fraud incidents, investigation outcomes, losses incurred.
  • Regulatory Context: Industry-specific anti-fraud requirements (SOX, FCPA, UK Bribery Act, etc.).
  • Whistleblower Program: Current hotline/reporting mechanism details.
  • Data Availability: Access to transactional data for analytics (ERP, accounting, procurement, HR systems).

Execution Steps

1. Fraud Risk Universe

Define the complete taxonomy of fraud schemes relevant to the organization.

Fraud Scheme Taxonomy (ACFE Classification)

Category Scheme Description Typical Perpetrator Avg. Loss Range
Asset Misappropriation
Cash Theft — Skimming Removing cash before recording Cashiers, front-line employees $10K-$100K
Cash Theft — Larceny Removing cash after recording Accounts receivable, cash handlers $25K-$250K
Billing Schemes Fictitious vendor, personal purchases, inflated invoices Procurement, AP staff $50K-$500K
Payroll Fraud Ghost employees, falsified hours, commission manipulation HR, payroll, managers $25K-$250K
Expense Reimbursement Fictitious expenses, inflated amounts, duplicate claims All employees, executives $10K-$100K
Check/Payment Tampering Forged checks, altered payee, unauthorized disbursements AP staff, signers, treasury $50K-$500K
Inventory/Asset Theft Theft or misuse of inventory, equipment, supplies Warehouse, operations staff $25K-$500K
Financial Statement Fraud
Revenue Recognition Premature recognition, fictitious revenue, channel stuffing Senior management, sales $1M-$100M+
Expense/Liability Manipulation Understating expenses, hiding liabilities, improper capitalization Senior management, accounting $1M-$100M+
Asset Overstatement Inflating asset values, improper impairment avoidance Senior management, accounting $500K-$50M+
Improper Disclosures Omitting material information, misleading footnotes Senior management, legal, accounting $1M-$50M+
Corruption
Bribery Payments to influence decisions (commercial or government) Sales, executives, agents $50K-$10M+
Conflicts of Interest Undisclosed relationships benefiting decision-maker Procurement, management, board $50K-$5M
Illegal Gratuities Payments for favorable past decisions Sales, management $10K-$500K
Economic Extortion Demanding payments under threat Vendors, partners (external) $25K-$1M
Bid Rigging Colluding to predetermine contract award Procurement, contractors $100K-$10M+
Cyber Fraud
Business Email Compromise (BEC) Impersonating executive/vendor to redirect payments External actors (targeting finance) $50K-$5M
Account Takeover Compromising credentials to authorize fraudulent transactions External actors (targeting any) $25K-$1M
Invoice Fraud (cyber-enabled) Compromised vendor emails requesting payment changes External actors (targeting AP) $50K-$2M
Data Theft for Fraud Stealing PII/credentials for identity fraud Internal or external actors $100K-$10M+
Cryptocurrency/Payment Fraud Manipulating digital payment systems Technical insiders, external actors $25K-$5M

2. Fraud Triangle / Pentagon Analysis

Assess organizational exposure through the lens of fraud motivation theory.

Fraud Triangle Factors

Factor Definition Assessment Questions Risk Level
Pressure / Motivation Financial or personal pressure to commit fraud
Financial pressure on employees Are employees under financial stress? Aggressive incentive targets? [High/Med/Low]
Organizational pressure Are there unrealistic financial targets? "Make the numbers" culture? [High/Med/Low]
External pressure Industry downturns? Competitive pressure? Covenant compliance? [High/Med/Low]
Opportunity Ability to commit and conceal fraud
Weak internal controls Are there gaps in segregation of duties, approvals, reconciliations? [High/Med/Low]
Override capability Can management override controls without detection? [High/Med/Low]
Inadequate monitoring Is there limited oversight of transactions, access, behavior? [High/Med/Low]
Complex transactions/structures Are there complex related-party transactions, off-book entities? [High/Med/Low]
Rationalization Ability to justify fraudulent behavior
Tone at the top Do leaders model ethical behavior? Is there a "rules don't apply to me" attitude? [High/Med/Low]
Organizational justice Do employees perceive fair treatment, compensation, recognition? [High/Med/Low]
Ethical culture Is there a strong code of conduct? Is it enforced consistently? [High/Med/Low]

Extended Pentagon Factors (Beyond the Triangle)

Factor Definition Assessment Questions Risk Level
Capability Skills and position to execute fraud
Technical knowledge Does the individual understand systems well enough to exploit them? [High/Med/Low]
Authority level Does the position carry sufficient authority to override or conceal? [High/Med/Low]
Coercion ability Can the individual pressure others to assist or remain silent? [High/Med/Low]
Arrogance Belief that rules do not apply
Entitlement Does the culture tolerate "star performers" who bend rules? [High/Med/Low]
Ego / overconfidence Do key individuals believe they are too smart to be caught? [High/Med/Low]

3. COSO Fraud Risk Management Guide Application

Apply the 5 COSO principles for fraud risk management.

COSO Fraud Risk Management Principles Assessment

Principle Description Current Maturity (1-5) Evidence Gap
Principle 1: Fraud Risk Governance Organization establishes and communicates a fraud risk management program that demonstrates expectations of the governing body and senior management and their commitment to high integrity and ethical values. [1-5] [Evidence] [Gap]
Principle 2: Fraud Risk Assessment Organization performs comprehensive fraud risk assessments to identify specific fraud schemes and risks, assess their likelihood and significance, evaluate existing fraud risk management activities, and implement actions to mitigate residual fraud risks. [1-5] [Evidence] [Gap]
Principle 3: Control Activities Organization selects, develops, and deploys preventive and detective fraud control activities to mitigate the risk of fraud events occurring or not being detected in a timely manner. [1-5] [Evidence] [Gap]
Principle 4: Investigation and Corrective Action Organization establishes a communication process to obtain information about potential fraud and deploys a coordinated approach to investigation and corrective action to address fraud appropriately and in a timely manner. [1-5] [Evidence] [Gap]
Principle 5: Fraud Risk Management Monitoring Organization selects, develops, and performs ongoing evaluations to ascertain whether each of the five principles of fraud risk management is present and functioning and communicates fraud risk management program deficiencies in a timely manner to parties responsible for taking corrective action, including senior management. [1-5] [Evidence] [Gap]

Maturity Scale for COSO Principles

Level Definition
1 - Initial No formal program. Fraud risk addressed reactively.
2 - Developing Some elements exist but not comprehensive. Limited documentation.
3 - Defined Formal program with policies, procedures, and assigned responsibilities.
4 - Managed Program actively monitored with metrics. Regular assessments conducted.
5 - Optimized Continuous improvement. Advanced analytics. Industry-leading practices.

4. Fraud Risk Assessment Matrix

Map each fraud scheme to business processes, assess likelihood and impact.

Fraud Risk Assessment Matrix

Scheme ID Fraud Scheme Business Process Likelihood Impact Inherent Risk Existing Controls Control Effectiveness Residual Risk
FR-001 Billing — Fictitious vendor Procurement / AP [1-5] [1-5] [1-25] [Control descriptions] [Strong/Moderate/Weak] [1-25]
FR-002 Payroll — Ghost employees HR / Payroll [1-5] [1-5] [1-25]
FR-003 Revenue recognition — Channel stuffing Sales / Revenue [1-5] [1-5] [1-25]
FR-004 BEC — Payment redirection Treasury / AP [1-5] [1-5] [1-25]
FR-005 Bribery — Government official Sales / Government relations [1-5] [1-5] [1-25]

Risk Scoring

Inherent Risk = Likelihood (1-5) x Impact (1-5)
    Range: 1-25

Residual Risk = Inherent Risk x (1 - Control Effectiveness %)
    Control Effectiveness: Strong = 80%, Moderate = 50%, Weak = 20%

Risk Classification:
    Critical (20-25): Immediate action required
    High (13-19):     Remediation within 30 days
    Medium (7-12):    Remediation within 90 days
    Low (1-6):        Accept or monitor

5. Anti-Fraud Control Mapping

Map preventive, detective, and corrective controls to each fraud scheme.

Control Mapping Matrix

Fraud Scheme Preventive Controls Detective Controls Corrective Controls
Billing — Fictitious vendor Vendor master approval workflow (dual approval); Vendor verification (TIN validation, address verification, bank account confirmation); Segregation of duties (requester ≠ approver ≠ payer) Three-way match (PO-receipt-invoice); Vendor master analytics (duplicate addresses, P.O. boxes, employee address matches); Invoice analytics (round amounts, sequence gaps) Vendor termination procedure; Loss recovery process; Disciplinary action per policy
Payroll — Ghost employees New hire approval workflow with HR verification; Segregation of duties (hire ≠ approve pay); Annual headcount reconciliation Payroll-to-HR master data reconciliation (monthly); Duplicate SSN/bank account detection; Terminated employee payroll audit Overpayment recovery; System access termination; Law enforcement referral
Expense reimbursement Written expense policy with limits; Pre-approval for expenses > threshold; Receipt requirements Duplicate expense detection; Benford's law analysis on amounts; Supervisor review of all claims; Analytics for round numbers, weekend dates, split transactions Reimbursement clawback; Policy violation consequences; Enhanced monitoring
Revenue — Premature recognition Revenue recognition policy aligned with ASC 606/IFRS 15; Deal desk approval for non-standard terms; Contract review process Revenue trend analysis (quarter-end spikes); Credit memo analysis post-quarter; Contract-to-revenue reconciliation; Side agreement audit Revenue restatement process; Disclosure to audit committee; Regulatory notification if material
BEC / Payment fraud Callback verification for payment changes (using independently sourced number); Email authentication (DMARC, SPF, DKIM); Wire transfer dual approval Payment change audit trail review; Domain monitoring (lookalike domains); Unusual payment pattern detection Immediate bank notification and recall; Law enforcement (FBI IC3); Insurance claim
Bribery / Corruption FCPA/anti-bribery policy; Third-party due diligence; Gift and entertainment policy with pre-approval; Compliance training Third-party payment analytics (round amounts, unusual destinations); Gift and entertainment log review; Whistleblower reports; Travel expense anomaly detection Investigation protocol; Self-disclosure analysis (DOJ/SEC); Remediation and enhanced controls
Conflicts of interest Annual COI disclosure requirement; Vendor relationship disclosure; Board member independence certification COI disclosure vs. transaction analysis (undisclosed relationships); Related-party transaction review; Procurement award pattern analysis Disclosure remediation; Recusal procedures; Contract renegotiation or termination

6. Red Flag Indicators by Fraud Type

Behavioral Red Flags (Applicable Across All Fraud Types)

Red Flag Possible Indication Follow-Up Action
Living beyond apparent means Employee may be supplementing income through fraud Discreet observation; if pattern persists, analytics on their transactions
Refusal to take vacation or share duties Concealment risk — fraud may be discovered in their absence Mandatory vacation enforcement; cross-training with job rotation
Unusually close relationship with vendor/customer Potential conflict of interest or kickback scheme COI disclosure review; transaction analysis
Excessive overtime without clear business reason Time theft or concealment activity requiring extra hours Workload review; access log analysis
Resentment or complaints about perceived unfairness Rationalization factor; may justify fraudulent behavior Management attention; engagement assessment
Defensiveness when questioned about work May indicate concealment Supervisory review of work products
Known financial difficulties (garnishments, bankruptcy) Pressure factor in fraud triangle Heightened transaction monitoring

Transactional Red Flags

Fraud Type Red Flag Detection Method
Billing fraud Vendor with P.O. box only; same address as employee; round-dollar invoices; sequential invoice numbers from different vendors; invoices just below approval thresholds Vendor master analytics, invoice analytics
Payroll fraud Employees with same bank account; employees with no tax withholding changes; overtime outliers; commission rate anomalies Payroll analytics, HR-payroll reconciliation
Expense fraud Expenses on weekends/holidays; round amounts; sequential receipt numbers; duplicate submissions; meals exceeding headcount Expense report analytics, duplicate detection
Revenue fraud Quarter-end revenue spikes > 40% of quarterly total; unusual credit memo volume post-quarter; large revenue reversals; channel inventory buildup Revenue pattern analytics, credit memo analysis
Corruption Payments to high-risk jurisdictions (CPI < 40); unusual commission structures; large cash payments; consultant payments without clear deliverables Third-party payment analytics, due diligence
Cyber fraud Email domain misspellings; payment instruction changes via email; unusual login locations; large transfers to new beneficiaries Email security, payment verification, access analytics

Analytical Red Flags

Technique What It Detects Application
Benford's Law deviation Fabricated numbers (natural datasets follow expected digit distribution) Expense reports, vendor invoices, journal entries
Duplicate detection Duplicate payments, invoices, or reimbursements AP transactions, expense reports, payroll
Round number analysis Fabricated amounts (fraudsters tend to use round numbers) All financial transactions
Threshold analysis Transactions structured just below approval limits Purchase orders, expense claims, wire transfers
Gap/sequence analysis Missing transactions, altered sequence numbers Check numbers, invoice numbers, receipt numbers
Trend analysis Unusual patterns over time Revenue, expenses, vendor payments, payroll
Outlier detection Statistical anomalies (Z-score > 3) Any high-volume transaction dataset
Network analysis Hidden relationships between entities Vendor-employee, vendor-vendor, customer-vendor

7. Whistleblower Program Assessment

Program Effectiveness Scorecard

Element Best Practice Current State (1-5) Gap
Reporting Channels Multiple channels: phone hotline (24/7, multilingual), web portal, email, in-person, anonymous options [1-5] [Gap]
Independence Managed by independent third party; reports to audit committee, not management [1-5]
Anonymity Anonymous reporting available and assured; no caller ID, no IP tracking [1-5]
Non-Retaliation Policy Written anti-retaliation policy; active enforcement; consequences for retaliation [1-5]
Awareness Regular promotion (posters, training, intranet, onboarding); all employees know how to report [1-5]
Accessibility Available to employees, contractors, vendors, customers; multilingual if applicable [1-5]
Triage Process Documented triage criteria; timely acknowledgment; clear escalation paths [1-5]
Investigation Protocol All reports investigated; qualified investigators; documented procedures [1-5]
Feedback Loop Reporters receive status updates (while maintaining investigation integrity) [1-5]
Metrics and Reporting Report volume, types, resolution time, substantiation rate tracked and reported to audit committee [1-5]
Benchmarking Reports per 100 employees benchmarked against industry (ACFE median: 1.4 per 100) [1-5]

Whistleblower Program Maturity Score: Total / 55 = [X]%

Score Range Maturity Level Action
85-100% Leading Maintain; benchmark externally
70-84% Effective Address specific gaps
50-69% Developing Significant enhancement needed
< 50% Inadequate Program redesign required

8. Data Analytics for Fraud Detection

Analytics Program Design

Analytics Type Frequency Data Source Fraud Schemes Detected
Continuous (automated, real-time) Daily/weekly ERP, payment systems Duplicate payments, threshold splitting, unauthorized payments
Periodic (scheduled analysis) Monthly/quarterly ERP, HR, expense systems Ghost employees, vendor anomalies, expense fraud, payroll anomalies
Ad Hoc (investigation support) As needed All available data Specific allegation testing, relationship mapping

Core Analytics Tests

Test Method Target Data Expected Output
Benford's Law Compare first-digit frequency distribution against expected Benford distribution; chi-square test for significance Expense reports, vendor invoices, journal entries Digit frequency chart with conformity score; p-value < 0.05 flags non-conformity
Duplicate Detection Match on amount + date, amount + vendor, invoice number across vendors, employee bank account matches AP transactions, expense reports, payroll List of potential duplicates with match criteria
Round Number Analysis Flag transactions where amount ends in 00, 000, 0000; compare % round numbers to expected baseline (< 5%) All disbursements Percentage of round amounts; list of round-number transactions above threshold
Threshold Analysis Identify transactions at 90-99% of approval thresholds; cluster analysis for split transactions Purchase orders, expense claims, wire transfers Transactions near thresholds; related transactions suggesting splitting
Vendor Master Analytics Match vendor addresses/phone/bank accounts to employee records; identify P.O. box-only vendors; dormant vendor activity Vendor master, HR master, AP transactions Potential shell vendors, conflict of interest matches
Ghost Employee Detection Compare active payroll to HR master; identify employees with no benefit elections, no tax changes, duplicate SSN/bank accounts Payroll, HR, benefits data Potential ghost employees for investigation
Journal Entry Testing Identify manual entries posted on weekends/holidays, round amounts, by unusual users, to unusual accounts, near period-end General ledger Suspicious journal entries ranked by risk indicators
Payment Pattern Analysis Identify new payees receiving large first payments, payments to high-risk jurisdictions, payments without PO/contract AP disbursements Anomalous payment patterns for review
Anomaly Detection (Statistical) Z-score analysis on transaction amounts by vendor/employee/account; isolation forest for multivariate anomalies Any high-volume transaction set Transactions with Z-score > 3 or anomaly score above threshold
Network Analysis Map relationships between vendors, employees, bank accounts, addresses, phone numbers to detect hidden connections Vendor, employee, payment master data Relationship graph; clusters of connected entities

9. Investigation Readiness Framework

Investigation Readiness Checklist

Element Required Status Gap
Written investigation policy and procedures Yes [In place/Partial/Missing] [Gap]
Qualified investigators (internal or retained external) Yes [Status]
Forensic accounting firm on retainer Recommended [Status]
Digital forensics capability (in-house or retained) Yes [Status]
Outside counsel with investigation experience Yes [Status]
Evidence preservation protocol (legal hold process) Yes [Status]
Interview protocol (rights, documentation, witnesses) Yes [Status]
Chain of custody procedures Yes [Status]
Investigation reporting template Yes [Status]
Board/audit committee investigation reporting protocol Yes [Status]
Law enforcement referral criteria and procedures Yes [Status]
Recovery and restitution procedures Yes [Status]
Post-investigation control enhancement process Yes [Status]

Investigation Decision Tree

Allegation Received
  |
  +--> Is it credible? (Initial assessment within 48 hours)
  |     NO  --> Document assessment rationale; close with audit committee notification
  |     YES --> Proceed
  |
  +--> Does it involve senior management?
  |     YES --> Audit committee directs; outside counsel leads; do NOT notify subject
  |     NO  --> Internal investigation team or outsource based on complexity
  |
  +--> Preserve evidence immediately
  |     +--> Implement litigation hold
  |     +--> Preserve electronic data (do NOT alert subject)
  |     +--> Secure physical evidence
  |
  +--> Scope the investigation
  |     +--> Who: Subjects, witnesses, affected parties
  |     +--> What: Transactions, time period, systems
  |     +--> Where: Locations, jurisdictions
  |
  +--> Execute investigation
  |     +--> Document review and data analytics
  |     +--> Witness interviews (peripheral witnesses first, subject last)
  |     +--> Expert analysis if needed (forensic accounting, digital forensics)
  |
  +--> Determine outcome
        +--> Substantiated --> Disciplinary action, recovery, control enhancement, law enforcement referral
        +--> Unsubstantiated --> Document findings, communicate to reporter, close
        +--> Inconclusive --> Enhanced monitoring, periodic reassessment

10. Fraud Loss Quantification

Loss Quantification Framework

Loss Category Calculation Method Example
Direct Loss Sum of misappropriated funds/assets $X in fraudulent payments identified
Investigation Cost Internal hours + external fees (forensic, legal, consulting) 500 hours x $150/hr + $200K external
Recovery Cost Legal fees for recovery, insurance deductible, asset tracing $X in legal fees; $X insurance deductible
System Remediation Control enhancements, system changes, additional staff $X in new controls, systems, and personnel
Regulatory Fines Penalties from regulators for control failures $X in SEC, DOJ, or other fines
Reputational Damage Customer churn, revenue impact, recruiting difficulty Estimated $X based on churn analysis
Opportunity Cost Management time diverted, delayed projects $X in estimated opportunity cost
Total Fraud Cost Sum of all categories $X total organizational impact

Loss Multiple Analysis

Total Fraud Cost is typically 2x-5x the direct loss amount

Industry benchmarks (ACFE Report to the Nations):
  Median loss per fraud case: $117,000
  Mean loss per fraud case: $1,783,000
  Median duration before detection: 12 months
  Estimated total fraud loss: 5% of annual revenue (ACFE estimate)

11. Industry-Specific Fraud Schemes

Financial Services

Scheme Description Key Controls
Rogue trading Unauthorized trading positions exceeding limits Position limits, independent P&L valuation, trade surveillance
Loan fraud Fictitious borrowers, inflated collateral values Independent appraisals, borrower verification, credit committee
AML failures Structuring, layering, insufficient KYC Transaction monitoring, CTR/SAR filing, enhanced due diligence
Insurance fraud Fictitious claims, inflated losses, staged events Claims investigation unit, analytics, SIU referrals

Healthcare

Scheme Description Key Controls
Upcoding Billing for more expensive services than rendered Claims data analytics, coding audits, compliance reviews
Phantom billing Billing for services never provided Patient verification, visit documentation, hotline
Kickbacks (Stark/Anti-Kickback) Referral payments for patient volume Fair market value assessments, compliance program, OIG exclusion checks
Diversion Drug diversion by healthcare workers Controlled substance tracking, discrepancy investigation

Government / Public Sector

Scheme Description Key Controls
Contract fraud Bid rigging, change order abuse, cost mischarging Competitive bidding, change order review, cost audit
Grant fraud Misuse of grant funds, false progress reporting Grant expenditure monitoring, progress verification
Time and attendance Falsified time records, no-show employees Biometric timekeeping, supervisor verification
Procurement fraud Favoritism, split purchases to avoid bidding Vendor rotation analysis, threshold monitoring

Retail

Scheme Description Key Controls
POS fraud Fictitious returns, void abuse, discount abuse POS analytics, void/return review, exception reporting
Inventory shrinkage Theft by employees or organized retail crime Inventory counts, CCTV, loss prevention team
Gift card fraud Fraudulent activation, balance draining Gift card reconciliation, activation monitoring
Vendor allowance fraud Fictitious deductions, unauthorized markdowns Vendor allowance reconciliation, deduction analytics

12. Anti-Fraud Program Maturity Model

Maturity Assessment

Domain Level 1: Reactive Level 2: Basic Level 3: Proactive Level 4: Managed Level 5: Optimized
Governance No anti-fraud policy Basic policy exists Comprehensive policy; board oversight Regular board reporting; fraud risk in ERM Continuous program evaluation; industry leadership
Risk Assessment No fraud risk assessment Ad hoc assessment Annual formal assessment per COSO guide Assessment tied to business changes; scenario-based Continuous reassessment; predictive risk modeling
Prevention Minimal controls Basic SOD and approvals Comprehensive preventive controls mapped to schemes Controls tested regularly; design kept current Adaptive controls; AI-based prevention
Detection Discovered by accident Basic whistleblower hotline Hotline + periodic data analytics Continuous monitoring + advanced analytics Real-time detection; machine learning models; full population testing
Investigation Ad hoc, untrained investigators Basic investigation process Formal protocol; trained investigators; outside counsel retained Structured program with metrics; lessons learned integration Best-in-class capability; proactive intelligence
Response Inconsistent consequences Documented disciplinary process Consistent enforcement; recovery pursued; law enforcement referral criteria Root cause analysis; control enhancement post-incident Comprehensive remediation; industry sharing; regulatory cooperation
Monitoring No program monitoring Annual review by management Regular KPIs; audit committee reporting Benchmarking against peers; program effectiveness metrics Independent program assessment; continuous improvement cycle

Maturity Score Calculation

Domain Score = Assessed Level (1-5)
Overall Maturity = Average of 7 Domain Scores

Target Maturity by Organization Profile:
  Public company (SEC registrant): Level 4 minimum
  Large private company: Level 3 minimum
  Mid-market company: Level 3 target
  Small/startup: Level 2 minimum, Level 3 target within 2 years
  Government / regulated entity: Level 4 minimum

Output Template

## Fraud Risk Assessment: [Organization]

### Assessment Parameters
| Field | Detail |
|---|---|
| Organization | [Name] |
| Industry | [Industry] |
| Revenue / Size | [$X / # employees] |
| Assessment Date | [Date] |
| Methodology | COSO Fraud Risk Management Guide |
| Assessor | [Name/team] |

### Executive Summary
[Overall fraud risk profile, critical findings, top fraud risk scenarios,
anti-fraud program maturity score, priority recommendations]

### Fraud Triangle / Pentagon Assessment
| Factor | Risk Level | Key Drivers |
|---|---|---|
| Pressure | [High/Med/Low] | [Key drivers] |
| Opportunity | [High/Med/Low] | [Key drivers] |
| Rationalization | [High/Med/Low] | [Key drivers] |
| Capability | [High/Med/Low] | [Key drivers] |
| Arrogance | [High/Med/Low] | [Key drivers] |

### COSO Fraud Risk Management Maturity
| Principle | Score (1-5) | Key Gap |
|---|---|---|
| Principle 1: Governance | [1-5] | [Gap] |
| Principle 2: Risk Assessment | [1-5] | [Gap] |
| Principle 3: Control Activities | [1-5] | [Gap] |
| Principle 4: Investigation & Corrective Action | [1-5] | [Gap] |
| Principle 5: Monitoring | [1-5] | [Gap] |

### Fraud Risk Heat Map
| Risk Zone | Fraud Schemes | Residual Risk Score |
|---|---|---|
| Critical (20-25) | [Schemes] | [Scores] |
| High (13-19) | [Schemes] | [Scores] |
| Medium (7-12) | [Schemes] | [Scores] |
| Low (1-6) | [Schemes] | [Scores] |

### Anti-Fraud Control Gap Analysis
[Control mapping with identified gaps and remediation recommendations]

### Red Flag Monitoring Program
[Key red flags to monitor with detection methods and responsible parties]

### Data Analytics Program Design
[Recommended analytics tests with data requirements and implementation priority]

### Whistleblower Program Assessment
[Effectiveness scorecard with improvement recommendations]

### Investigation Readiness
[Readiness assessment with gaps and remediation plan]

### Anti-Fraud Program Maturity Scorecard
| Domain | Current Level | Target Level | Gap |
|---|---|---|---|
| Governance | [1-5] | [Target] | [Gap] |
| Risk Assessment | [1-5] | [Target] | [Gap] |
| Prevention | [1-5] | [Target] | [Gap] |
| Detection | [1-5] | [Target] | [Gap] |
| Investigation | [1-5] | [Target] | [Gap] |
| Response | [1-5] | [Target] | [Gap] |
| Monitoring | [1-5] | [Target] | [Gap] |
| **Overall** | [Avg] | [Target] | [Gap] |

### Remediation Roadmap
| Priority | Action | Owner | Timeline | Est. Cost |
|---|---|---|---|---|
| Immediate | [Action] | [Role] | 0-30 days | [$X] |
| Near-term | [Action] | [Role] | 30-90 days | [$X] |
| Medium-term | [Action] | [Role] | 90-180 days | [$X] |
| Long-term | [Action] | [Role] | 180-365 days | [$X] |

### Disclaimers
> This fraud risk assessment provides a framework for identifying and
> mitigating fraud risk. It does not guarantee the detection or prevention
> of all fraud. No system of internal controls can provide absolute
> assurance against fraud. This assessment should be updated annually or
> when significant organizational changes occur.

Quality Checks

  • Fraud risk universe covers all 4 major categories (asset misappropriation, financial statement fraud, corruption, cyber fraud) with specific schemes relevant to the organization's industry.
  • Fraud triangle/pentagon analysis assesses pressure, opportunity, AND rationalization (plus capability and arrogance for pentagon) with specific organizational evidence.
  • COSO Fraud Risk Management Guide principles (all 5) are assessed with specific maturity scores and evidence.
  • Fraud risk assessment matrix maps specific schemes to specific business processes with scored likelihood and impact.
  • Anti-fraud controls are mapped as preventive, detective, AND corrective for each significant fraud scheme.
  • Red flag indicators include behavioral, transactional, AND analytical categories with specific detection methods.
  • Whistleblower program assessment covers all key elements (channels, independence, anonymity, non-retaliation, awareness, triage, investigation, feedback, metrics).
  • Data analytics program includes specific tests (Benford's law, duplicate detection, anomaly detection) with data requirements, not just general descriptions.
  • Investigation readiness framework includes both the readiness checklist and decision tree for investigation management.
  • Fraud loss quantification covers direct losses AND indirect costs (investigation, remediation, regulatory, reputational).
  • Industry-specific fraud schemes are included for the organization's industry.
  • Anti-fraud program maturity model scores all 7 domains on a 5-level scale with defined level descriptions.
Install via CLI
npx skills add https://github.com/Kaakati/managing-director --skill fraud-risk-assessment
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