Develop an evidence-based fraud-risk screening checklist covering behavioral, transactional, control, vendor, customer, and reporting red flags.
This prompt has variables that can be replaced with your own information. Copy and use it with your preferred LLM, or try it out in the LearnerBox Prompt Playground.
Act as a senior fraud-risk and forensic-accounting professional.
Develop a fraud-risk behavioral red-flag screening checklist using the information provided below.
Organization or process:
{{organization_process}}
Fraud-risk context:
{{fraud_context}}
Transactions and data:
{{transaction_data}}
Controls and access information:
{{controls_access}}
Known incidents, allegations, or concerns:
{{known_concerns}}
Policy and investigation protocol:
{{policy_protocol}}
Analysis requirements:
1. Identify relevant fraud-risk categories, including:
- asset misappropriation;
- procurement fraud;
- payroll fraud;
- expense fraud;
- revenue manipulation;
- financial-statement fraud;
- bribery and corruption;
- conflicts of interest;
- vendor collusion;
- customer collusion;
- cyber-enabled fraud;
- identity fraud; and
- management override.
2. Develop red flags across:
- behavior;
- transactions;
- master data;
- access rights;
- journals;
- vendors;
- customers;
- payroll;
- expenses;
- cash;
- inventory;
- revenue;
- related parties;
- approvals; and
- reporting.
3. For every red flag, document:
- indicator;
- rationale;
- data source;
- threshold or rule;
- false-positive risk;
- severity;
- owner;
- review action; and
- escalation path.
4. Distinguish:
- anomaly;
- control failure;
- policy breach;
- conflict of interest;
- suspicious pattern;
- allegation; and
- substantiated finding.
5. Identify combinations of red flags that may be more significant than isolated indicators.
6. Include behavioral warning signs only as contextual indicators, never as proof.
7. Develop triage levels:
- routine review;
- enhanced review;
- urgent escalation; and
- formal investigation referral.
8. Define evidence-preservation, confidentiality, independence, and legal-consultation requirements.
9. Do not identify a person as fraudulent or criminal based solely on indicators.
10. Do not invent allegations, motives, evidence, personal attributes, or findings.
11. Avoid collecting or exposing unnecessary sensitive personal information.
12. Require authorized investigators to determine next steps.
Present the result as:
{{output_format}}
Include:
- fraud-risk taxonomy;
- behavioral red flags;
- transactional red flags;
- control and access red flags;
- vendor and customer indicators;
- financial-reporting indicators;
- scoring or triage logic;
- false-positive controls;
- escalation workflow;
- evidence-handling checklist;
- confidentiality safeguards; and
- investigation-referral criteria.Replace each variable shown in double curly brackets with accurate information from your own professional context.
{{organization_process}}
Example: Example: Procurement and accounts payable
Identify the business process, entity, or function being screened.
{{fraud_context}}
Example: Describe products, transactions, locations, incentives, vulnerabilities, and known fraud risks.
Use the organization’s approved fraud-risk assessment where available.
{{transaction_data}}
Example: Describe available journal, vendor, customer, payroll, expense, cash, inventory, and access data.
List data fields and quality limitations without exposing unnecessary personal data.
{{controls_access}}
Example: Provide approval limits, segregation of duties, system access, override rights, and monitoring controls.
Control context helps distinguish anomalies from control failures.
{{known_concerns}}
Example: Summarize verified concerns, prior incidents, hotline themes, and unresolved anomalies.
Use neutral language and avoid unnecessary identifying details.
{{policy_protocol}}
Example: Provide escalation thresholds, investigation authority, confidentiality rules, and evidence procedures.
The checklist should align with approved legal and investigation procedures.
{{output_format}}
Choose the format required for monitoring, audit, compliance, or investigation triage.
A responsible fraud-risk screening framework containing behavioral and transactional indicators, thresholds, false-positive controls, triage, escalation, evidence handling, confidentiality, and investigation-referral criteria.
These characteristics describe the type of thinking, customization, and output structure involved in using this prompt effectively.
This breakdown explains how the prompt’s major components work together to guide the AI toward a useful, reliable, and well-structured response.
Positions the AI as a fraud-risk and forensic-accounting specialist.
Defines fraud risks, transactions, controls, access, concerns, policies, and investigation protocols.
Requires a red-flag screening, scoring, triage, and escalation framework.
Prevents accusations, invented evidence, motives, findings, and unnecessary personal-data exposure.
Requires taxonomies, indicators, thresholds, false positives, triage, evidence, and referral criteria.
Organization, fraud context, transaction data, controls, concerns, policy, and output format.
AI-generated responses can contain errors, omissions, unsupported assumptions, outdated information, or recommendations that do not reflect your jurisdiction or professional context.
Verify calculations, evidence, regulations, standards, policies, and professional recommendations before relying on the result. The qualified professional remains responsible for the final decision.
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