Bid rigging and fake competition
Shared bank accounts, addresses, tax identifiers, or contact details across bidders; rotating award patterns; bid amounts clustered too closely to be independent.
RISK COVERAGE
Procurement & Vendor Risk Analytics
Test whether competition was real, whether suppliers are independent, and whether the price you awarded is the price you paid.
Procurement risk rarely appears in a single transaction. It appears in patterns: the same three bidders rotating wins, a supplier that shares a bank account with its competitor, a contract awarded at one value and settled at nearly double after change orders.
foretale.ai builds a relationship view across your vendor master, sourcing events, contracts, and purchase orders, then tests that network for the collusion and leakage patterns below. Because it evaluates connections rather than single records, it finds relationships that rule-based checks on individual fields cannot see.
WHAT WE DETECT
Risks tested in this domain
Vendor collusion networks
Suppliers with no shared attributes that nonetheless always bid together, share directors, or transact with each other — detected as a graph rather than a rule.
Post-award change order abuse
Contract value that grows materially after a competitive award, change orders just below re-tender thresholds, and scope added without documented approval.
Vendor due diligence gaps
Suppliers missing required onboarding evidence, sanctioned or politically exposed parties, and vendors created and paid within unusually short windows.
Purchase order abuse
Orders split below approval thresholds, retrospective purchase orders raised after invoice receipt, and repeated single-source awards without justification.
Third-party and conflict-of-interest risk
Overlap between vendor and employee master data — shared addresses, bank accounts, or phone numbers — indicating undisclosed interests.
HOW IT RUNS
Understand → Plan → Execute → Explain
foretale.ai maps your data and relationships, plans the analytics for this domain, tests the full population, and returns findings with evidence attached. Your team keeps every judgement.
DATA USED
What we need from your systems
- Vendor master and onboarding records
- Sourcing events, bids, and award decisions
- Contracts and amendments
- Purchase orders and change orders
- Employee master data for conflict testing
- Sanctions and watchlist reference data
Related reading
Frequently asked questions
How can analytics detect bid rigging?
Bid rigging detection works by testing whether supposedly independent bidders are actually connected. The strongest indicators are shared bank accounts, tax identifiers, addresses, phone numbers, or directors across bidders, combined with behavioural patterns such as rotating wins, consistent bid spreads, and repeated joint participation. Together these show that competition was structural rather than real.
What is vendor relationship network analysis?
Vendor relationship network analysis models suppliers, employees, bank accounts, and addresses as a connected graph instead of testing each field in isolation. This finds indirect relationships — two vendors linked through a third party, or through a shared intermediary — that pairwise rule-based matching misses entirely.
Can we detect collusion when vendors share no obvious attributes?
Yes, and this is the common case. When suppliers deliberately avoid sharing bank accounts or tax identifiers, behavioural analytics take over: joint bidding frequency, win rotation, pricing correlation, and timing patterns. Graph analysis then tests whether they connect through any intermediate entity.
Which procurement data is required?
At minimum the vendor master, purchase orders, and award or sourcing records. Adding contracts, change orders, and employee master data materially improves coverage, because it enables post-award cost testing and conflict-of-interest detection.
NEXT STEP
See it on your data.
Request a focused walkthrough—usually within one business day.