Developer's AI Agent Hallucinated a Fake Fund, Then Found Real Data Conflicts in Finance

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A software developer building an AI agent to compare FANG+-linked investment trusts in Japan discovered the tool confidently recommended a non-existent product, 'eMAXIS Slim FANG+', which it had apparently fabricated by combining two familiar brand names. When the developer cross-checked a legitimate fund, iFreeNEXT FANG+, across multiple sources, he found conflicting information about its NISA eligibility between the asset manager's official site and a distributor's website. The asset manager's site listed the fund as eligible, while the distributor's site indicated otherwise, highlighting how secondary sources can carry outdated or inaccurate data. The incident led the developer to identify a clear information hierarchy — primary sources such as asset managers, secondary sources like distributors, and AI-generated content — which his agent had been treating as equally reliable. He concluded that AI research agents must include active verification mechanisms rather than treating all sourced data as equally trustworthy.

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