We propose FinDRA, a multi-agent framework for financial question answering under asymmetric information access. FinDRA partitions a financial report into agent-specific evidence regions, allows agents to exchange only their answers, concise reasoning, and confidence estimates, and coordinates their revisions through full-document verifier feedback and authority-framed debate. Experiments on MultiHiertt show that the asymmetric verifier condition obtains the highest overall point estimates among the compared settings, with an EM score of 0.284 and a mean LLM-as-a-Judge score of 0.753 on a 0–2 scale. Importantly, the benefit of asymmetric access depends on evidence structure: it is strongest when question-relevant evidence remains within an agent-accessible region, whereas cross-partition questions expose a trade-off between semantic adequacy and exact numerical agreement. Agent-level analyses further show revision patterns consistent with the assigned authority framing, without attributing these differences to authority alone. Cross-dataset experiments on FinQA and TAT-QA similarly show that asymmetric access is not universally beneficial. These findings suggest that effective multi-agent financial reasoning depends not simply on providing more information, but on how evidence is partitioned, communicated, and verified.