Fin-RATE: How LLMs Fail at Cross-Period and Cross-Entity Financial Analysis
Fin-RATE shows LLM accuracy collapses 18.60% on longitudinal tracking, with the retrieval pipeline, not the model, as the binding bottleneck.
#machine-learning
Machine Learning
Machine learning techniques for financial data analysis and automation
FinDER: Real Analyst Queries Expose a 74% Recall Gap in Financial RAG
FinDER's 5,703 real analyst queries show top RAG recalls only 25.95% of 10-K evidence. Normalize abbreviations first, before swapping embeddings.
Lost in the Middle: Position Bias in LLMs and Its Impact on Finance AI
LLMs score up to 20 points worse when the answer sits mid-context, so finance RAG pipelines should place the best passages first or last.
AD-LLM Benchmark: GPT-4o Hits 0.93+ AUROC Zero-Shot for Text Anomaly Detection
AD-LLM finds GPT-4o hits 0.93–0.99 AUROC zero-shot for text anomaly detection, but LLM model selection stays unreliable for financial audit AI.
CausalTAD: Causal Column Ordering for LLM Tabular Anomaly Detection
CausalTAD reorders table columns by causal dependency before LLM serialization, raising average AUC-ROC from 0.803 to 0.834 over AnoLLM.
AnoLLM: Fine-Tuning LLMs for Tabular Anomaly Detection in Financial Data
AnoLLM beats classical baselines on mixed-type fraud data by scoring rows with LLM negative log-likelihood, but adds no edge on purely numerical tables.
LLMs Score 2.3% on Beancount DSL Generation: The LLMFinLiteracy Benchmark
LLMFinLiteracy finds five ~7B models write correct Beancount transactions just 2.3% of the time, failing on accounting reasoning rather than syntax.
TableMaster: Adaptive Reasoning for Table Understanding with LLMs
TableMaster hits 78.13% on WikiTQ with GPT-4o-mini, 13 points over Chain-of-Table, via table-of-focus plus adaptive reasoning for agents over Beancount ledgers.
Zero-Shot Anomaly Detection with LLMs: How GPT-4 Performs on Tabular Data
GPT-4 reaches 74.1 mean AUROC on ODDS zero-shot, near the 75.5 ECOD baseline, but fails on high-variance data. Ledger auditing is not solved yet.
DocFinQA: Long-Context Financial Reasoning on Full SEC Filings
DocFinQA swaps FinQA's 700-word passages for full SEC filings, a 175× longer context that nearly halves GPT-4 accuracy on long documents.
TheAgentCompany: Benchmarking LLM Agents on Real-World Enterprise Tasks
TheAgentCompany benchmarks 175 enterprise tasks in a simulated intranet, and the best model, Gemini-2.5-Pro, finishes only 30% at $4 each.
τ²-bench: Measuring the Cost of Dual-Control in Conversational AI Agents
τ²-bench finds active users with their own tools cut conversational agent success by 18–25 points. Beancount agents sharing write access lose the same way.