@ModusAudit

AI Native Accounting firm. Backed by @lightspeedvp

 NYC
modusalliance.com
Joined February 2026
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FinancialAuditBench is built from differentially private statistics from real audits to generate synthetic companies and their documents. A computational graph combines these priors with accounting rules and auditor expertise, keeping financial records consistent across files.
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Finding #4: More reasoning improves audit performance, but increases both time and cost. For GPT-6 Astra, low → max reasoning raises strict pass from 23.61% to 71.11%, while mean runtime increases from 3.08 to 24.94 minutes and model cost from $1.32 to $8.27 per attempt.
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We are excited to see how FinancialAuditBench can help improve audit agents and benchmark construction in privacy-sensitive domains! 🔗 Paper: arxiv.org/abs/2609.32835 🔗 Homepage: financialauditbench.com 🔗 Dataset: huggingface.co/datasets/modu… 🔗 Code: github.com/modus-audit/finan…

FinancialAuditBench: Benchmark Construction under Differential...

As AI agents are becoming widely adopted in the financial services industry, careful measurement is essential to understand where they can be reliably deployed and where oversight and professional...

arxiv.org
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AI agents are being adopted into financial audit workflows, but how reliably can they complete the work? In FinancialAuditBench, we evaluate agents on realistic audit tasks, and reveal where professional review remains necessary. 🔗 Paper: arxiv.org/abs/2609.32835 Thread 👇
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1/ Frontier models keep getting better. We wanted to know what that actually means for real audit work, so we built Financial Audit Bench (FAB). 90 audit tasks. 11 frontier models. Graded against rubrics written by licensed CPAs. Here's what we found:
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5/ Results vary a lot by area. Journal-entry completeness averaged a 94.5% pass rate across models. Accounts receivable averaged 4.2%. One failure we saw: testing receivables against the client's own cash-receipts report instead of the bank statement.
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6/ Agents can already do a lot of staff-level audit work. They still need professional review. FAB is how we measure where that line is, and how it moves as models improve. Built by @PranavAPillai @actuallyjerryh @AlexWang1025. Paper, tasks, and code: financialauditbench.com/

FinancialAuditBench · Modus Labs

A benchmark for AI agents on financial statement audits. Compare models and explore their work.

financialauditbench.com
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Every model update shifts the spectrum of what is possible
Arush Jain
@Arushj01Sep 2
Replying to @AnthropicAI
@AnthropicAI released its latest frontier model Fable 5.1 this afternoon. It's the clearest example of a frontier model doing large chunks of Audit work accurately, which was not possible even two months ago.
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Three college best friends, @Arushj01, @PranavAPillai, and @vinaykasat_, set out to rebuild systems that felt stuck. Years of collaboration turned into conviction, and from that conviction came @ModusAudit. We’re excited to lead Modus’ $85M Seed & Series A. Modus is rebuilding audit from the inside out. They invest in and partner with audit firms, deploy AI that improves audit quality, create a high-quality customer experience, and translate automation into new business. By rethinking audit at its core, they’re redefining what scale and quality look like in one of the most trust-critical industries. We’re proud to continue backing them on this journey. CC: Lightspeed partners Isaac Kim, Amish Desai, Alexa Boghosian, @jmover
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