On Oct. 18, 2021, Bart Verbeeck, former director of sales, and Robby Van Mele, former director of operations, admitted that they — along with co-conspirators at competing firms — colluded to allocate security services contracts and to fix the prices at which the firms had bid for contracts. In June, G4S NV, the security and logistics firm where they’d worked, pleaded guilty and agreed to pay a criminal fine of $15 million for its involvement in the conspiracy. The U.S. Department of Justice (DOJ) has also indicted several other members of the conspiracy. The companies allegedly rigged bids, fixed prices and allocated customers for defense-related security services, including a multimillion-dollar contract issued in 2020 to provide security services to the U.S. Department of Defense for military bases and installations in Belgium, and a NATO Communications and Information Agency contract.
This was the first international resolution obtained by the U.S. Procurement Collusion Strike Forces (PCSF), which the DOJ created in 2019 to combat antitrust crimes and related fraudulent schemes that impact government procurement, grant, and program funding at all levels of government — federal, state and local. Global investigative partners included the Department of Defense Office of Inspector General, Defense Criminal Investigative Service, the FBI’s International Corruption Unit and the U.S. Army Criminal Investigation Command. (See the DOJ releases, October 18, 2021, June 25, 2021, and June 30, 2021.)
Anti-competitive collusion, like the opening case, is a perennial hidden problem for most organizations. Reducing these crimes in public procurement could save taxpayers tens of billions of dollars per year, and — in the private sector — could significantly affect bottom lines. Based on an estimate by the Organisation for Economic Co-operation and Development (OECD), eliminating bid-rigging could help reduce public procurement costs by 20% or more. (See “Fighting Bid Rigging in Public Procurement,” OECD.)
Technological advances in procurement processing and systems pose unique challenges, but they also offer distinctive opportunities for law enforcement and fraud examiners to leverage data analysis to detect anti-competitive conduct. We’d like to help you understand what antitrust crimes are, provide you with indicators to help you detect antitrust collusion in procurement data, and discuss global efforts and successes through the PCSF.
What makes price-fixing, bid-rigging and market-allocation schemes illegal? In the U.S., it’s the Sherman Antitrust Act, under which “every contract, combination in the form of trust or otherwise, or conspiracy, in restraint of trade or commerce among the several States, or with foreign nations, is declared to be illegal.” In short, an antitrust crime occurs when competitors agree to fix prices, rig bids, or allocate markets or customers. (See “15 U.S. Code § 1 - Trusts, etc., in restraint of trade illegal; penalty,” Cornell Law School.)
Based on an estimate by the Organisation for Economic Co-operation and Development (OECD), eliminating bid-rigging could help reduce public procurement costs by 20% or more.
A common thread runs through all three crimes: They involve an agreement between two or more horizontal competitors (companies that provide, or have the capability to provide, competing goods or services). Let’s look at the basics of each.
In a price-fixing conspiracy, competitors agree to fix or otherwise determine the price at which their products or services are sold. Price fixing encompasses more than just agreements about the actual price charged to customers — it includes any agreement to affect price. Examples include agreements among competitors to:
In a bid-rigging conspiracy, competitors agree in advance who’ll win a bid. This allows the predetermined winner to bid a higher amount than it otherwise would have if it had to compete to win the contract. The contracting entity is then forced to pay a higher amount than it otherwise would have — had the bidders legitimately been competing with one another. Often, as part of these schemes, competitors will give the illusion of competition to the contracting entity when in fact there’s none. Bid-rigging has three basic variations:
In an allocation agreement, competitors agree to divide up a market. They could do this in several different ways, including division by geographic area, customer, product or labor workforce. (See “Antitrust Guidance for Human Resource Professionals,” DOJ Antitrust Division and Federal Trade Commission, October 2016.) In allocation agreements, competitors agree on who gets what “piece of the pie.” Competitors might use a bid-rigging scheme to ensure that each competitor gets its allocated piece.
Technological advances in procurement processing and systems pose unique challenges, but they also offer distinctive opportunities for law enforcement and fraud examiners to leverage data analysis to detect anti-competitive conduct.
Certain conditions can make customers or supply chains more vulnerable to antitrust crimes. These conditions don’t mean that an antitrust crime is definitely happening — only that you should pay attention to suspicious patterns and pattern aberrations. These can include:
The fewer the number of competitors, the easier it is for those competitors to put an antitrust conspiracy into place. It also makes it more difficult for conspiring competitors to try to “cheat” on a bid-rigging agreement.
This is especially relevant when competitors are made aware of details beforehand through a procurement official, a trade association or a public solicitation announcement. When competitors know roughly how much business is coming down the pipeline and how often, it’s easier for them to take advantage of that knowledge to enter into an agreement to divvy up future spoils equally with other competitors.
In the wake of a disaster or an international pandemic, contracting processes often move more quickly to get help to those in need as soon as possible. During these times, there’s often an increase in bad actors looking to take advantage of this faster pace to cut corners without detection. In 2009, for example, a federal grand jury convicted Durwanda Elizabeth Morgan Heinrich, a sand and gravel subcontractor, of conspiracy and bribery in connection with a $16 million protection project for the reconstruction of a New Orleans levee following the devastation caused by hurricane Katrina in 2005. Heinrich offered to pay former contract employees of the U.S. Army Corps of Engineers in exchange for their attempt to steer a dirt, sand and gravel on the levee project to her. Heinrich planned to use proceeds from the subcontract to pay the bribes. (See “Former Sand and Gravel Subcontractor Sentenced to 5 Years in Prison After Conspiracy and Bribery Conviction in Connection with a Levee Reconstruction Project,” DOJ, Aug. 26, 2009.)
To maximize the detection of anti-competitive criminal collusion, fraud examiners and investigators can use data analysis to bolster traditional detection techniques that rely on reactive case leads (i.e., whistleblower, consumer complaints, leniency applicants, U.S. Suspicious Activity Reports or U.S. Currency Transaction Reports) and manual review processes (i.e., comparing isolated groups of bid records).
Such techniques, though important, may not capture the entirety of an anti-competitive conspiracy. In the worst case, the use of traditional techniques may result in a failure to detect an existing conspiracy. Data analytics enables the proactive detection of collusion and the development of key circumstantial evidence. The right data is fundamental to successful analytics. For procurement-related analytics, this includes:
Company bids: The most comprehensive dataset includes each company’s bid records for a certain solicitation, especially records from the losing bidders. This bid information should include the identity of the company (and person and department within the company) placing the bid, the exact product or service being offered, the corresponding price to the smallest decimal point practicable, the quantity being offered, the exact time and date of the bid, and any details relating to how the bid was placed (IP address, email or physical mailing address, fax number). If a company uploads documents to complete the bid, a procurement system should store the original native file of the document to preserve the document’s metadata.
Company information: Procurement systems should include a mechanism in which company bidders can be identified to include company email addresses, mailing addresses, fax numbers, internet protocol (IP) addresses; names and contact information of responsible parties, principals and owners; and system passwords, if applicable.
Contract/solicitation information: Obtain information on the contract type, market or location of the contract, customer, service period of contract, product delivery locations and any solicitation-specific procedures.
Post-award data: Once a contract has been awarded, identify any bank account numbers a company used to receive contract payments, and company information and exact product or service the subcontractors are providing.
Once you’ve collected all this information in a centralized database, you can use several methods to determine whether collusion may be present in a procurement solicitation or in a series of solicitations, some of which are listed as follows. (Of course, no two conspiracies are the same, and the list here isn’t exhaustive.)
Analyzing bidders’ win/loss frequency can reveal suspicious patterns. For example, if bidding is competitive, it’s unlikely that one company either wins or loses all of its bids over a series of bidding rounds. Rather, one bidder repeatedly winning or losing could indicate a bid-rigging conspiracy where the conspirators are submitting the losing bids to create an illusion of competition. Similarly, winning frequency may reveal a pattern consistent with companies who appear to “take turns” winning bids, i.e., three companies routinely bid in the same solicitations, and each win 1/3 of the awards or 1/3 of the overall cost of all contracts awarded.
You can analyze markets at a granular level to assess bidding patterns. Check for extreme bidding patterns in markets and submarkets. You may notice that companies only submit bids in certain geographic areas, for certain types of products or customers, which all could indicate market-allocation conspiracies.
Data analytics enables the proactive detection of collusion and the development of key circumstantial evidence. The right data is fundamental to successful analytics.
Companies that frequently bid against each other in the same solicitations, and companies that submit bids for services or products that are outside of their core businesses, could suggest complementary-bid conspiracies. Conversely, companies that never bid against one another despite providing similar services or products — or being known competitors in the same market — could reveal bid-suppression conspiracies. Also, examining the exact timing of when competitor bids are submitted may reveal coordination.
Shifts in bidding patterns could be a sign of anti-competitive agreements, such as when companies bid against each other for a certain period of time in a way that’s consistent with competitive bidding, but then one or more companies withdraw from bidding entirely.
Another red flag is a solicitation for a specific product or service that normally generates multiple bids, and you see a sudden decrease in the number of bidders, particularly when the solicitation includes a minimum bidder requirement. One-off bids by a company that doesn’t typically submit bids, particularly a bid that’s disproportionally high or suspiciously close, may also suggest a complementary bid.
Examine company bid prices over a broad number of solicitations. A company’s prior bids for similar projects may reveal unexplained increases in prices. Or unexpectedly high prices can indicate that the company is submitting an intentionally losing bid. Similarly, drastic or sudden price increases for a product or service that can’t be explained by cost increases, particularly when bid pricing increases suddenly and identically across multiple companies, may indicate a collusive agreement. If prices suddenly or drastically decrease upon the entry of a new bidder, a closer examination is needed to determine whether the new bidder disrupted an anti-competitive cartel, particularly when the market participants’ bids were stagnant or the same prior to the new bidder’s entry.
Examining the overall spread between bid prices can reveal bid coordination. For example, an indicator of potential collusion among three bidders would be if the three are within 10% of each other and the fourth bid is half. Examining line-item pricing can similarly reveal coordination. If Bidder B’s line items are all exactly 10% higher than the same line items in Bidder A’s bid, this suggests that Bidder B had access to Bidder A’s bid prior to bidding and coordinated with Bidder A to submit an intentionally losing bid. Some studies have shown that the statistical measure of “relative distance” can be used to detect complementary bidding; the difference between the winning bid and second-best bid is high when collusion is present. (See “Detecting Bid-Rigging Cartels With Descriptive Statistics,” by David Imhof, Journal of Competition Law & Economics, Feb. 11, 2020.)
If bid pricing is typically based on granular calculations resulting in exact numbers, the presence of round numbers in a bid can indicate that a bidder didn’t put any effort into calculating its bid and may be submitting an intentionally losing bid. The same inference may be made if a bid or line item appears to bear no relationship to its expected price, or there are drastic differences in quantity estimates.
A winning bid that’s unusually high compared to internal cost estimates, published price lists or industry averages could be indicative of collusion among competitors, especially for contracts where the lowest bidder wins the award. While not necessarily an indicator of collusion, a bid that’s unusually close to internal cost estimates could indicate access to inside information. A bid that’s very low could suggest the winner may be padding change orders and invoices post award.
Detecting anti-competitive activity in public procurement is achievable with the right data, insights — and in the case of cross-border conspiracies — cooperation. Moreover, it’s a worthy cause given the vast sums of public money at stake.
Companies may be affiliated in some way with common identifiers such as physical addresses, phone or fax numbers, email or IP addresses. Affiliation could be indicative of potential opaque or shell company ownership, but it’s also a data point you can use to identify relationships among vendors. Another red flag is a company that won a solicitation but frequently subcontracts to a company that lost a solicitation.
You can use “natural language processing” to review proposals and bid packages submitted by competitors to detect common language, spelling or grammar errors, format, letterhead, calculations and other contextual nuances, which might suggest direct collusion among competitors. (See “Natural Language Processing - Machine Learning Methods in Forensic Accounting,” by Andre Castillo, CFE, CPA, The CPA Journal, August 2021.)
Globalization has pushed governments and companies to expand traditional fraud detection to include data analytics domestically and internationally. Many companies need to cooperate with foreign authorities. In fall 2020, the PCSF expanded its footprint with the launch of “PCSF: Global,” which is designed to deter, detect, investigate and prosecute collusive schemes that target government spending outside of the U.S.
The announcement of charges in PCSF’s first international investigation, detailed in the opening paragraphs, highlighted the benefits of a dedicated partnership focused on overseas U.S. government spending.
Many nations share our faith in the value of competition and the need to protect it. Indeed, approximately 130 jurisdictions have enacted antitrust laws to ensure open and free markets, promote consumer welfare and prevent conduct that impedes competition. PCSF: Global offers a model for leveraging international relationships to detect antitrust conspiracies in cross-border procurements.
Detecting anti-competitive activity in public procurement is achievable with the right data, insights — and in the case of cross-border conspiracies — cooperation. Moreover, it’s a worthy cause given the vast sums of public money at stake. To learn more about the U.S. approach to procurement collusion enforcement and for additional resources, please visit justice.gov/procurement-collusion-strike-force.
[See sidebar: “The U.S.'s infrastructure drive and the need to deter bid-rigging”.]
The authors’ views expressed in this article aren’t purported to reflect those of the U.S. Department of Justice, Department of Defense Office of Inspector General or Defense Criminal Investigative Service.
Casey Buffalini, CFE, is a special agent and program manager for public corruption and major theft, U.S. Department of Defense Office of Inspector General, Defense Criminal Investigative Service. Contact her at Casey.Buffalini@dodig.mil.
Helen Christodoulou, Esq., is a trial attorney, U.S. Department of Justice Antitrust Division. Contact her at Helen.Christodoulou@usdoj.gov.
Milosz Gudzowski, Esq., is a trial attorney, U.S. Department of Justice Antitrust Division. Contact him at Milosz.Gudzowski@usdoj.gov.
Sandra Talbott, Esq., is the assistant director, Procurement Collusion Strike Force, in the U.S. Department of Justice Antitrust Division. Contact her at Sandra.talbott@usdoj.gov.
In the U.S., concerns about bid-rigging and fraud related to infrastructure took on renewed significance in 2021 after lawmakers in November passed an over $1 trillion infrastructure bill. (See “Biden signs $1 trillion bipartisan infrastructure bill into law, unlocking funds for transportation, broadband, utilities,” by Jacob Pramuk, CNBC, Nov. 15, 2021.)
Like the billions of dollars in COVID-relief funds that came before it, government infrastructure spending is vulnerable to fraudulent activity given the significant amounts involved and the difficulties in verifying details about infrastructure projects. (See “Trillions in infrastructure spending could mean hundreds of billions in fraud,” by Jetson Leder-Luis, The Conversation, Sept. 28, 2021.)
According to the Director of the Procurement Collusion Strike Force Daniel Glad, for fiscal year 2019, the U.S. federal government spent $586 billion on contracts for goods and services. And that doesn’t include federal funds that flow to state and local levels for infrastructure or COVID-19 relief funding. (See “Daniel Glad Delivers Remarks at ABA Section of Public Contract Law’s Public Procurement Symposium,” DOJ, Oct. 13, 2021.)
“With the current levels of pandemic and disaster recovery spending, and, potentially, increased infrastructure spending, faith in the public procurement process is as essential as ever,” Glad said at the ABA Section of Public Contract Law’s Public Procurement Symposium in October.
“The increasing amounts of government spending that may be authorized to meet the needs of the country present an ample opportunity — an attractive target — for greed to override ethical conduct,” Glad added. “This risk demands focused deterrence and aggressive enforcement, which is why this is and continues to develop as an area of focus for the PCSF.”
The administration of President Joe Biden and the DOJ have emphasized vigorous anti-trust enforcement, promising to continue to crack down on bid-rigging and other forms of collusion. “If you fix prices, rig bids or divide markets, we will prosecute you whether your scheme cheats consumers or harms workers,” Associate Attorney General Vanita Gupta said in September 2021. (See “Vanita Gupta Delivers Remarks at Georgetown Law’s 15th Annual Global Antitrust Enforcement Symposium,” DOJ, Sept. 14, 2021.)
Recent DOJ prosecutions show that procurement collusion enforcement is picking up steam and building upon longstanding efforts. In September 2021, a Minnesota concrete contractor, Clarence Olson, pleaded guilty to rigging bids on public concrete repair and construction contracts and faces an up to 10-year prison sentence and a $1 million criminal fine. In June 2021, a North Carolina engineering firm, Contech Engineered Solutions LLC, was sentenced to pay $8.5 million in fines and restitution after pleading guilty to conspiring to rig bids and defraud the state’s department of transportation. (See “Concrete Contractor Pleads Guilty to Rigging Bids for Public Contracts in Minnesota,” DOJ, Sept. 28, 2021, and “Engineering Firm Pleads Guilty to Decade-Long Bid Rigging and Fraud Scheme,” DOJ, June 7, 2021.)
Paul Kilby is the former editor-in-chief of Fraud Magazine. Contact him at pkilby@acfe.com.
Unlock full access to Fraud Magazine and explore in-depth articles on the latest trends in fraud prevention and detection.
Read Time: 5 mins
Written By:
Roger Seifert, CPA, ABV, CFF
Jamal Ahmad, J.D., CFE, CPA/CFF
Read Time: 14 mins
Written By:
Tom Caulfield, CFE, CIG, CIGI
Sheryl Steckler, CIG, CICI
Read Time: 10 mins
Written By:
Tom Caulfield, CFE, CIG, CIGI
Sheryl Steckler, CIG, CICI
Read Time: 5 mins
Written By:
Roger Seifert, CPA, ABV, CFF
Jamal Ahmad, J.D., CFE, CPA/CFF
Read Time: 14 mins
Written By:
Tom Caulfield, CFE, CIG, CIGI
Sheryl Steckler, CIG, CICI
Read Time: 10 mins
Written By:
Tom Caulfield, CFE, CIG, CIGI
Sheryl Steckler, CIG, CICI
