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Buyside AI Reviews·Jan 1, 2026

Hudson Labs - Review #1

"HL's main value proposition is handling high-precision finance tasks where hallucination and accuracy errors can be very costly." "For context, as of December 23, 2025, GPT-5.2, GPT-5.1, and Opus 4.5 score in the ~53–57% range on finance-specific accuracy tasks, according to the Vals AI benchmark. That level of error remains a major obstacle for institutional investment research—reinforcing the importance of finance-specific retrieval and verification." "I found the accuracy of data and information retrieval to be high. Checking accuracy versus underlying documents was made easier with well-designed citation features." "It's easy to see the efficiency gains here—rather than locating a specific sentence in 20 different press releases and manually compiling a table, I can pull all of these data points in a few seconds."

By Buyside AI Reviews

Bloomberg Tax·Sep 22, 2025

KPMG’s Work for Silicon Valley Bank Exposes Audit Limits

The PCAOB pressed bank auditors on their response to shifting market conditions and found that some didn’t reconsider risk evaluations or going concerning assessments, the regulator said in its own a review following the bank failures. The report released in September 2024 didn’t specify which firms were included in the review. In the case of Silicon Valley Bank, the institution detailed its risks in its annual filing with regulators, said Kris Bennatti, CEO of investment research platform Hudson Labs. The role of auditors is to ensure that corporate accounting is reliable, she said, pointing to the requirements that auditors ensure reports detailing revenue and assets are free of significant misstatements because of an error or fraud.

By Amanda Iacone

Forbes·Aug 30, 2024

AI Spotted Super Micro Risks Two Years Before Filing Fiasco

Super Micro Computer (SMCI) shares nosedived 20% Wednesday on news of its missed 10-K filing and a scathing report by short firm Hindenburg Research alleging related-party accounting manipulation. The real story is that AI detected escalating financial reporting risk signals again by 2022 — all of which were permitted to ‘hide in plain view.’ One of the many valuable routine screens identifies related party disclosures placed SMCI in the top 100 companies with highest risk. Hudson Labs found ‘related party risk isn’t the only red flag at SMCI.’ Super Micro’s forensic risk score has been elevated since 2019. Hudson Labs showed existing AI advancements can readily accelerate financial risk signal detection.

By Noah Barsky