Corruption and fraud investigations usually start with:
- Complaints or reports
- The discovery of a red flag, or
- “Proactive,” automated fraud detection tests
Complaints or reports
See information on how to respond to a complaint.
Discovery of a red flag
If the case begins with the discovery of a red flag:
Match the red flag to the potential scheme or schemes and then look for other indicators of the suspected scheme(s).
For example, the continued acceptance of high priced, low quality work, without complaint, could indicate kickbacks. If these red flags are detected, look for other indicators of kickbacks, such as improper selection of the suspected contractor or sudden unexplained wealth by the approving project officials. There is a list of indicators for each scheme in the most common schemes and steps of proof link on the main menu.
As stated above, don’t obsess over any one indicator – look for a number or pattern of indicators of the suspected scheme.
See more information on detecting corruption and fraud through red flags.
“Proactive,” automated fraud tests
Basic steps:
- Identify high risk areas for fraud, corruption, bid rigging or collusion, such as where offenses previously had been detected or controls are weak
- Identify the potential schemes that are most likely to occur in the high risk areas by reviewing prior complaints, audits and investigative reports
- Identify the red flags of the potential schemes that can be detected electronically, for example unusual bidding patterns
- Create and search electronic databases for the targeted red flags
- Match the initial red flags that are detected to other indicators of the potential scheme(s), look for patterns of indicators
- Identify the parties (firms and individuals) involved in the indicated transactions and schemes
- Conduct due diligence background checks on the suspect parties to identify other evidence of corruption or fraud
- Conduct further traditional detection and investigation steps (document reviews, interviews, etc.) for each scheme
See examples of automated tests to detect collusive bidding and the data required to conduct them.