What is adversarial due diligence?
Adversarial due diligence is an analytical methodology that treats every claim in a deal submission as a hypothesis to be tested, not a fact to be accepted. Where conventional due diligence builds on the information provided by sponsors, adversarial due diligence cross-references each claim against independent data sources, flags discrepancies by materiality, and produces an evidence-graded assessment of the deal's actual risk profile.
How adversarial due diligence differs from conventional analysis
<p>Conventional due diligence typically accepts the sponsor's data room as the starting point. Analysts build financial models from the numbers provided, verify that calculations are internally consistent, and flag obvious gaps. The assumption is that the information provided is substantially accurate.</p> <p>Adversarial due diligence inverts this assumption. Every revenue projection, market size claim, director qualification, and regulatory compliance statement is treated as a claim requiring independent verification. The analysis starts from the question: what evidence exists outside the sponsor's own materials that supports or contradicts this claim?</p> <p>This distinction is structural, not cosmetic. It changes what the analyst looks for, what tools are required, and what the output tells the decision-maker.</p>Why the adversarial approach matters for AI-assisted analysis
<p>AI systems trained to be helpful are structurally incentivised to confirm the information they are given. Research has shown that reinforcement learning from human feedback — the standard training method for commercial AI — rewards agreement over accuracy. In a due diligence context, this means a conventional AI tool is more likely to find supporting evidence for a sponsor's claim than contradicting evidence.</p> <p>An adversarial system is designed to do the opposite: actively seek contradictions, inconsistencies, and gaps. It scores claims by the weight of independent evidence, not by how well the sponsor's materials read.</p>96% of AI benchmarks allow high scores through memorisation rather than genuine reasoning capability. McIntosh et al. (2024), arXiv:2402.09880